INTERNATIONAL JOURNAL OF DISASTER RISK MANAGEMENT (IJDRM)
UDC: 614.8.069
ISSN (printed edition) 2620-2662
ISSN (electronic edition) 2620-2786
SCIENTIFIC-PROFESSIONAL SOCIETY FOR DISASTER RISK MANAGEMENT, BELGRADE, THE REPUBLIC OF SERBIA
INTERNATIONAL JOURNAL OF DISASTER RISK MANAGEMENT (IJDRM)
Vol. 2 • № 2
Belgrade, 2020
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TABLE OF CONTENS
Peter Olawuni, Oluwaseun Olowoporoku, Oluwole Daramola
DETERMINANTS OF RESIDENTS’ PARTICIPATION IN DISASTER RISK MANAGEMENT IN LAGOS METROPOLIS NIGERIA 1
Ahmed H. Al-ramlawi, Mohammed M. El-Mougher, Mohammad R. Al-Agha
THE ROLE OF AL-SHIFA MEDICAL COMPLEX ADMINISTRATION
IN EVACUATION & SHELTERING PLANNING 19
Uttam Kumar Chakma, Akhter Hossain, GN Tanjina Hasnat, Humayain Kabir WATER CRISIS AND ADAPTATION STRATEGIES BY TRIBAL COMMUNITY: A CASE STUDY IN BAGHAICHARI UPAZILA OF RANGAMATI DISTRICT
IN BANGLADESH 37
Dilip Kumar Jha, Rajib Kumar Bhattacharyya, Shariar Shyam, Udita Rohana Ratnayke INDICATOR BASED ASSESSMENT OF INTEGRATED FLOOD VULNERABILITY INDEX FOR BRUNEI DARUSSALAM 47
Vladimir M. Cvetkovic, Jovana Martinović
INNOVATIVE SOLUTIONS FOR FLOOD RISK MANAGEMENT 71
DOI: https://doi.org/10.18485/ijdrm.2020.2.2.1
UDC: 005.334:504.4(669.1)
351.862
Original Article
DETERMINANTS OF RESIDENTS’ PARTICIPATION IN DISASTER RISK MANAGEMENT IN LAGOS METROPOLIS, NIGERIA
Olawuni, P. O, *Olowoporoku O. A., Daramola, O. P.
Department of Urban and Regional Planning, Obafemi Awolowo University Ile-Ife Nigeria.
*Correspondence: oluwaseunayodele6@gmail.com
Received: 1 November 2020; Accepted: 6 December 2020; Published: 1 January 2021
Abstract: This study examined the determinants of residents’ participation in Disaster Risk Management in Lagos, Metropolis, Nigeria. The metropolis was stratified into two clusters (island and mainland areas). Two political wards were randomly selected in each of the six LGAs identified in the two clusters. A total of 5019 buildings were identified in the study area. Using systematic sampling tech- nique, every 10th residential building was sampled in the selected wards upon which questionnaire was administered. The study established a variation in so- cioeconomic attributes of residents as well as awareness of disaster types across the two clusters; it also found out that while majority of the residents were aware of DRM, very few proportions had DRM training. The result of the study also re- vealed that age, monthly income, length of residence and educational status can explain residents’ level of participation in DRM. Using regression analysis, the study found out that age, educational status and length of stay with Beta values (.130), (-0.112) and (-0.105) respectively were the determinants of peoples’ par- ticipation in DRM. It recommends that environmentally concerned stakeholders should invest in DRM in areas of awareness and training of residents, establish- ment, funding and equipment of DRM agencies.
Keywords: hazards, vulnerability, disaster, disaster risk management, residents, Lagos metropolis.
Introduction
Disasters are sudden occurrence that causes damage, ecological disruption, loss of hu- man life, or deterioration of health and health services on a scale sufficient to warrant an extraordinary response from outside the affected community or area (National Emergency
Mnanagement Authority; NEMA, 2013; Olowoporoku, 2017; Okunola, 2017; WHO, 2019). They are also defined as emergencies caused by natural hazards and/or human induced activ- ities that result into significant physical damage or destruction to the environment (Winser, Blaike, Canon & Davis, 2004; Robin & Marti, 2015; United Nations International Strategy for Disaster Reduction [UNISDR], 2017). Several criteria have been proposed to define disasters in terms of their consequences. The Center for Research on the Epidemiology of Disasters (CRED) (2003) requires that for a disaster to be entered into the database: at least one of the following criteria has to be fulfilled: ten or more people reported killed; 100 people reported affected; a call for international assistance; and declaration of a state of emergency.The extent of impacts of disasters, may depend fundamentally on how the social, political, economic, environmental and technological systems interact to manage emergencies in different socie- ties (Olowoporoku, 2018). Therefore, disasters emanates from a combination of hazards and the potential negative consequences of risks (Kihampa, 2010; Okunola, 2018).
The increased rate of the occurrences of disaster over the last two decades in various parts of the world has become alarming. The WHO (2019) noted that about 190 million are vic- tims of various forms disasters with significant impacts on their wellbeing across the world. The outbreaks of these disastsers either have global, national of local consequences. Among the disasters with devastating costs to human lives are drought, cyclones, tsunamis, traffic collisions and fires earthquakes etc. One of the possible causes of disasters is the increasing population of the world which has forced many people to live in disaster prone areas (Van Niekerk, 2015; Wahab, 2013). Cities in the developing countries are the worst hit by disasters because they are exposed to increasing dangers of disasters with limited management capac- ity (Jinadu & Sanni, 2008). The EM-DAT data collected in Africa between 2010 and 2015 revealed that about 80 million people were affected by large-scale natural disasters which re- sulted in 45,733 deaths (UNISDR, 2015; Otuseye, Johnson & Brown, 2017). The susceptibility of these African cities to disasters can be attributed to socio-economic stress, inadequate physical infrastructure, lack of awareness, among others (Daramola & Olowoporoku 2019).
Nigeria like other African countries is experiencing both natural and man-induced disas- ters of various kinds with grievous consequences on sustainable development (Adaku, 2020; Abin & Wahab, 2013). In the country, disasters such as flood, landslide, tidal wave, coastal erosion, sand-storm, dust-storm, locust/insect infestation, oil spillage, building collapse have claimed many lives in Nigeria and many homeless persons (National Emergency Manage- ment Agency [NEMA], 2019). Studies such as Okon (2018), National Disaster Management Framework [NDMF] (2010) and Adeoti and Akintunde (2014) opined that the significant loses from disaster occurrences in Nigeria can be attributed to the nation’s weak DRM insti- tutions. As such, acute community vulnerability to disasters has added to the growing num- ber of urban challenges confronting the country (Odunsi, 2019; National Planning Commis- sion, 2012), thus seriously threatening sustainable development.
Disaster Risk Management (DRM) is the process of lowering the effects of the occurrences and impacts of disasters. DRM is a uninterrupted, combined, multi-sectoral and multi-dis- ciplinary, activities of preparation and implementation of measures, aimed at anticipating, averting or reducing the risk of disasters, lessen its consequences, emergency preparedness, rapid and operative response to disaster and post-disaster recovery (Bhatti, 2003; National Disaster Management Framework (NMDF), 2010; Adeniran, 2013; UNISDR, 2015). It pro- vides a basis for addressing public and institutional systems, including organizational capac- ities, policy, legislations and actions (Okunlola, 2017). In most developing countries of the world like Nigeria, DRM is perceived as humanitarian relief supplies which involve costly expenses after emergencies (Aribisala, 2018; Ibem, 2011).
According to Aribisala (2018), the most common approaches to the management of dis- asters in Nigeria are the post occurrence of disasters. In this sense, contingency thinking and technique of management of disaster is neglected for the supply of relief materials after the occurrence of disaster. This has made residents living in disaster prone areas discouraged from participating in its management, thus, aggravating the incidences (Lamond, Adekola, Adelekan, Eze & Ujoh, 2019; Adebayo, 2014). Residents’ participation is crucial to the man- agement of disasters (UNCRD, 2003; 2004). It aids the design and implementation of activ- ities and can contribute to the implementation of disaster management programs tailored to the actual vulnerabilities and to the needs of the affected people (Lewis & Kelman, 2012; Baytiyeh & Naja, 2013; Lewis, 2013). These collective efforts can lessen the level of vulnera- bility to various types of disasters. With the increased rate of occurrences of disaster in Ni- geria, there is a need for a paradigm shift from the conventional emergency responses to the involvement of citizens in every phase of disaster management. In order words Nigeria must depart from that tradition that awaits disaster occurrence to a more responsive, pragmatic and proactively engaging approach of pre-empting disaster occurrence and set measures to either forestall or mitigate them.
Lagos is one of the cities in Nigeria ravaged by several types of disasters (NEMA, 2019; Olanrewaju et al, 2019; Odunsi, 2019; Aribisala, 2018; Okunola, 2017; Adenekan, 2016; Aderogba, 2012). Over the last decade, the occurrence of disasters in the metropolis has increased in frequency and intensity (Lagos State Government, 2020; NEMA, 2016). For in- stance in the last two years, Legos metropolis have witnessed many forms of disasters such as fire tragedy, flood, pipeline explosion, collapsed building among others in various districts which had resulted into loss of many lives, properties and displacement of people (Thisday, 2020; Nairametrics, 2020; Lagos State Government 2020; Business Day 2020; BBC News, 2020). Also in 2018 Lagos recorded the loss of over 84 lives and about USD 35 million to fire outbreaks in homes, markets and roads (Sahara Reporter, 2019; Vanguard, 2019). In fur- therance of these in 2011 flood events in the metropolis affected approximately 5 thousand people and resulted in about 25 deaths with direct economic losses totalled about USD 250 million (Adelekan 2015; Aderogba, 2012; IFRC, 2011; Oladunjoye, 2011). With the devastat- ing consequences of disasters in the metropolis, various management efforts have recorded minimal successes.
Issues related to management of disasters have been a subject of discourse among re- searchers in Nigeria. For instance, Adaku, (2020), Odunsi, (2019), NEMA (2019), Olow- oporoku (2017), Wand, Ayuba & Azika (2015), Kawuwa, Adamu & Umar (2015) and Chuk- wuma (2014) have examined disaster management activities of the government in Nigeria and studies laid emphasis on government activities in the aftermath of disaster. The studies of Iliyasu (2017), Amanchukwu, Amadi-Alli and Ololube (2015), Ojo (2013), Aderogba (2012), Adelekan (2013) examined issues pertaining to flood disasters in Nigeria. The studies ex- amined the impacts of flood disasters with less consideration on citizens’ involvement in its management. Furthermore, Olowoporoku (2017), Hossain (2013) Olorunfemi (2011) and examined residents’ knowledge of various types of disasters however; their involvement in its management was not considered. The impacts of disasters could be mitigated if DRM is institutionalised by stakeholders (Aribisala, 2018). Effective DRM, reduces disaster losses, lessen the pains and sufferings of people and also enhances sustainable development (Hos- sain, 2013). This study therefore examines residents’ participation in DRM activities in Lagos metropolis, Nigeria.
Study Area, Materials and Methods
Study Area
The study area is Lagos Metropolis which forms the most part of Lagos State, one of the states in Nigeria. It is located in the South-West geo-political zone and situated between 6° 230 and 6° 410North and 2° 420 and 3° 420 East. Lagos is the fastest urbanizing city in Nigeria and ranks as the 19th most populated urban agglomeration in the world (World Economic Forum, 2016). With more than 20 million inhabitants, Lagos metropolis accommodates more than 10% of Nigeria’s population. The average population density in the metropolis is over 20,000 persons per square km. The physical growth and development of Lagos are tied to its expanding economic and political roles, which is aided by its explosive population growth.
Lagos, which ceased to be Nigeria’s administrative capital in 1991 harbors over 50% of the total business and industrial establishments in the nation (Samuel, 2004). There is no doubt that the rising status of Lagos as an emerging megacity and a commercial nerve centre in sub-Saharan Africa has come with a number of challenges. High densities per land use, proliferation of slums and environmental degradation are considered as contributing factors to increasing vulnerability to environmental hazards in this city. In fact, perennial floods, ocean surge, transport accidents, fire incidence, building collapse, industrial and construc- tion related events are among the development-induced hazards and risks that have assumed an alarming proportion in this city (Simpson, 2006; Ana, Sridhar, Olakunle & Gregory 2007; Okunlola, 2017).
2.2. Methodology
Multi-stage sampling technique was utilized in selecting the eligible respondents for this study. The first stage involved the division of Lagos Metropolis into two clusters; island and mainland. There are two Local Government Areas (LGAs) in Lagos Island. These are Lagos island LGA and Eti-Osa LGA. The two LGAs are characterised with administrative, com- mercial and residential land uses. In the second cluster Lagos mainland, there are 14 LGAs. The two most prominent LGAs in Lagos mainland that are comparable with the LGs on the islands in terms of activities are Lagos Mainland and Ikeja LGAs. The LGAs are also admin- istrative, commercial and reliable centres like their counterparts on the island. Two political wards were randomly selected in each of the identified LGAs. A total of 8 wards were select- ed for questionnaire administration. Reconnaissance survey revealed that there were 5,019 residential buildings in the selected wards. Using systematic sampling technique, every 10th residential building was selected for sample. Thus, 501 buildings were sampled. The sample size was 501 residents from the selected 501buildings on which questionnaire were adminis- tered. Of the 501 questionnaire administered, 474 were retrieved.
Data collected through the questionnaire survey include socio-economic attributes of the residents, those pertaining disaster awareness and preparedness in the study area. The meth- od of analysis is similar to that of Zhang (1993) which was used in the assessment of environ- mental hazard and risk in China. Analysis of the data collected was carried out using Cross Tabulation, T-Test and Analysis of Variance (ANOVA). Bonferroni correction adjustment was used for multiple comparison analysis (confidence intervals were constructed) while the overall confidence coefficient was maintained. This is done to reduce the risk of making type I error.
Mean indexes was used to determine the level of awareness of disaster in the study area. The views of the residents with these variables were expressed using a five-point Likert scale. Residents were provided with a list of prevalent disasters in the last decade. The analysis of the responses evolved Disaster Awareness Indexes (DAIs) and mean Disaster Awareness Indexes (
). To obtain a DAI, a weighted value of 5,4,3,2 and 1 were respectively attached to rate each response (1= not at all aware, 2 = slightly aware, 3 = somewhat aware, 4 = mod- erately aware and 5 = extremely aware) on any of the disaster. The SWV for each item was obtained through the sum of the product of number of responses of each item and the respec- tive weighted value attached to each rating. This is expressed mathematically as:5
SWV = X i Yi
I 1
Where:
SWV = summation of weight value,
Xi = number of respondents to rating i;
Yi = the weight assigned a value (i = 1, 2, 3, 4, 5).
The DAI for each item on the scale was arrived at by dividing the Summation of Weighted Value (SWV) by the total number of respondents in each residential area, mathematically expressed as:
DAI=
The
later was computed by summing residents’ disaster awareness and dividing by the number of the functions (n = 15), mathematically expressed as:
=
Research Findings
This section discusses the profile of the respondents. It also contains discussions on the awareness of disaster and residents participation in disaster risk management activities and determinants of residents’ participation in DRM in the study area.
Socioeconomic attributes of residents
The study examined socioeconomic characteristics of residents that could influence their participation in disaster risk management in the study area. The variables considered in this regard are gender, age, educational status, income, household size and duration of residence. These variables among others have been established as factors that influences people’s aware- ness of environmental issues (Odunsi, 2019; Aribisala, 2018; Olowoporoku, 2017; Daramola, 2016; Muttarak & Lutz, 2014; UNISDR, 2009; Philip & Rayhan, 2004; Lindell & Perry 2000). As presented in Table 1, findings revealed that 52.6% of the respondent in the island areas were males while 47.4% were females. In the mainland areas, 63.4% of the respondents were males while 31.7% were females. In general, 60.8% of the respondents were male while 39.2% were female.
Age is considered a significant factor in assessing environmental awareness. Studies such as Grothmann and Reusswig (2006), Lindell and Hwang (2008) and Olowoporoku (2017b) have established that elderly persons are more environmentally conscious than their younger counterparts. The continuous raw data collected on age of the residents were categorized into four to aid better presentation. These are: teenagers (those less than 20 years); young adults (20 to 39 years); matured adults (40 to 59 years) and elders (above 60). Findings from the island area revealed that 19.8% of the respondents were teenagers, 26.2% younger adults, 18.5% were matured adults while 35.5% of the respondents were elders. Investigation from the mainland areas revealed that respondents within the age group of teenagers, young adults, matured adults and elders constituted 3.7%, 64.6%, 28.0% and 3.7% respectively. Further findings revealed that majority (88.6%) of the residents fell within the adult age group. The mean ages in the mainland and island areas were respectively 43 years and 35 years while the overall mean age in the study area was 34 years. The results of the T-test [T = (468) = 0.001
< 0.05] revealed that there exist a significant variation in difference in the age of residents across the two residential clusters.
The studies Odunsi (2019) and Muttarak and Lutz (2014) have identified educational at- tainment as an important factor in disaster management. Investigation into the education- al attainment of respondents in the study area revealed that 15.8% had primary education, 51.3% had secondary education while 32.9% had tertiary education. In order to determine the number of years respondents spent in school, the data collected was converted into the 6-3-3-4 (i.e. Primary- Junior secondary-Senior secondary -Tertiary) operational education system in the country. The mean number of years spent on educational attainment across the study area was 10 years. The T- test results [T (468) = 0.023 < 0.05)] indicated that there was a significant difference in the mean number of years spent in pursuit of education by residents in the study area.
As expressed by Olowoporoku (2017) and Yodmani (2001) improved source of livelihood influences participation in DRM. For easy analysis, the initial quantitative data on residents’ average monthly income was categorised into three (low income; middle income and high income). The low income group, constituted respondents that earned less than ₦51,000, me- dium income group constituted respondents that earned between ₦51,000 and ₦100,000 while respondents that earned above ₦100,000 were categorised as high income earners. In the island areas, 44.4% of the respondents were low income earners, 38.9% were middle income earners while 16.7% were high income earners. Findings from the mainland areas revealed that the proportion of respondents that comprised low, middle and high income earners were 11.8%, 42.6% and 45.6% respectively. The mean monthly incomes in the island and mainland areas were respectively ₦77,256 and ₦81,838. The result of T- test [T (414) =
0.009 < 0.05] revealed that there was a significant difference in monthly income of residents across the two residential clusters.
Household size was considered important in disaster issues. This is because household size helps in determination of the number of people exposed to disaster. Daramola and Olow- oporoku (2016) defined a household as a person or group of people with shared cooking and living arrangements. Household size was measured by the number of people living with these arrangement and households were placed into three categories. Household sizes with one to five members were categorised as small, those with six to ten members as medium while those with more than ten members are categorised as large. In the island area, respondents with small, medium and large household size constituted 41.4%, 25.3% and 33.3% respective- ly while on the mainland respondents with low, medium and high household sizes accounted for 67.1%, 25.3% and 7.6% respectively. In summary, majority (72.1%) of the respondents across the two clusters have a small household size.
Table 1. Socioeconomic Characteristics of Respondents
Attribute
Island
Mainland
Total
Frequency (%)
Frequency (%)
Frequency (%)
Gender
Male
120 (52.6)
168 (68.3)
288 (60.8)
Female
108 (47.4)
78 (31.7)
186 (39.2)
Total
228 (100.0)
246 (100.0)
474 (100.0)
Age
< 20
45 (19.8)
9 (3.7)
54 (11.4)
20-39
60 (26.2)
169 (64.6)
219 (46.2)
41-60
42 (18.5)
69 (28.0)
111 (23.4)
≥60
81 (35.5)
9 (3.7)
90 (19.0)
Total
228 (100.0)
246 (100.0)
474 (100.0)
Educational Status
Primary
18 (7.9)
57 (23.2)
75 (15.8)
Secondary
150 (65.8)
93(37.8)
243 (51.3)
Tertiary
60 (26.3)
96 (39.0)
156 (32.9)
Total
228 (100.0)
246 (100.0)
474 (100.0)
Income Status
≤₦31,000
96 (44.4)
24 (11.8)
120 (28.6)
₦31,000-
₦80,000
84 (38.9)
87 (42.6)
171 (40.7)
≥₦81,000
36 (16.7)
93 (45.6)
129 (30.7)
Total
*226 (100.0)
*204 (100.0)
*420 (100.0)
Household Size
≤5
93 (41.4)
159 (67.1)
252 (54.6)
6 – 10
47 (25.3)
60 (25.3)
117 (25.3)
>10
75 (33.3)
18 (7.6)
93 (20.1)
Total
*225 (100.0)
*227 (100.0)
*462 (100.0)
Length of Residence
≤10years
87 (38.2)
117 (50.0)
204 (44.2)
11 – 20years
72 (31.5)
66 (28.2)
138 (29.8)
≥21 years
69 (30.3)
51 (21.8)
120 (26.0)
Total
*228 (100.0)
*224 (100.0)
*462 (100.0)
* Responses were less than 156 because some respondents did not provide information on the variables
The length of stay of residents within the metropolis were categorised into three (≤ 10 years; 11-20 years; > 20 years). Findings revealed that respondents that have spent less than 10 years, between 11 to 20 years and above 20 years residence on the island were 38.2%, 31.5% and 30.3% respectively. Findings from the mainland areas revealed that the proportion of respondents that have spent less than 10 years, 11 to 20 years and above 20 years residence explained 50.0%, 28.2% and 21.8% respectively.
3.2 Residents’ Awareness of Disaster
Sequel to the discussion of socio-economic characteristics of the respondents across the metropolis, their level of awareness of disasters is presented in this section. The rating of the level of awareness was premised on the assumption that the highest rated disasters in terms of awareness were the most occurring disaster in the study area in the last decade.
Presented in Table 2 are the mean Disaster Awareness Index (
) for the different types of disaster experienced across the two cluster areas in the study area. The mean Disaster Aware- ness Indexes ( ) for the island and mainland areas were 3.12 and 3.26 respectively. In the island areas, findings revealed that road accident, smoke, flood and house collapse were the four most prominent disasters as they rated 4.49, 4.33, 4.24 and 4.15 respectively while the least rated disasters in the mainland area were earthquake, drought, landslide and industrial/ chemical accident which rated 1.26, 1.43, 2.01 and 2.29 respectively. In the mainland areas, the disaster occurrences that respondents took cognisance of mostly were flood, house col- lapse, electricity accidents, road accident and fire outbreak which rated 4.54, 4.12, 4.05,4.01 and 4.01 respectively while the least rated disasters in terms of awareness were ethno-reli- gious violence (1.49), earthquake (2.04), break out of disease (2.12) and drought (2.38).
Table 2. Disaster Awareness Indexes.
Disaster
Island
Mainland
DAI
DAI-
Rank
DAI
DAI-
Rank
Road accident
4.49
1.37
1
4.01
0.75
4
Smoke
4.33
1.21
2
3.91
0.65
6
Flood
4.24
1.12
3
4.54
1.28
1
Wind/Thunder/Rain storm
3.15
0.03
9
3.20
-0.08
7
Landslide (soil erosion)
2.01
-1.11
13
2.99
-0.29
10
Droughts
1.43
-1.69
14
2.38
-0.88
11
Fire outbreak
3.61
0.49
6
4.01
0.75
4
Earthquake
1.26
-1.86
15
2.04
-1.22
13
Pipeline/Oil tanker explosion
3.33
0.21
8
3.98
0.72
5
House collapse
4.15
1.03
4
4.12
0.86
2
Political crisis
2.93
-0.19
10
3.18
-0.08
8
Ethno-religious violence
3.46
0.34
7
1.49
-1.77
14
Break out of disease
2.49
-0.63
11
2.12
-1.14
12
Industrial/Chemical accident
2.29
-0.83
12
3.00
-0.26
9
Electricity accident
3.72
0.60
5
4.05
0.79
3
Total
46.89
3.12
49.02
3.26
Island areas = 3.12 Mainland areas = 3.26
4.3 Residents’ Participation in DRM
The study also examined the awareness and involvement of residents in DRM across the metropolis as presented in Table 4. One identifiable parameter in DRM is awareness and participation of residents. Awareness and involvement aid the population in preparing for, coping with and recovering from disasters. The findings revealed that the proportions of respondents who had knowledge of DRM in the island areas constituted 31.2% while re- spondents who did not possess knowledge of DRM accounted for 61.8%. On the mainland, respondents who indicated having knowledge of DRM constituted 72.0% while 28.0% admit- ted a lack of DRM awareness.
As for respondents’ who had previous trainings on DRM in the study area, 41.3% in the island areas affirmed training on DRM while 58.7% revealed they had never undergone DRM trainings. On the mainland, 64.4% of the respondents indicated receiving training in DRM while 35.6% had not. Across Lagos metropolis, respondents who had not received any type of training on DRM accounted for 68.4% of the respondents. Findings on the organisations which DRM training was received revealed that in the island areas 40.9% of the respondents were trained by government agencies, 13.6% were trained by private institutions while 45.5% were trained by NGOs. On the mainland areas, the proportion of respondents trained by government, private institutions and NGOs constituted 52.8%, 5.6% and 41.6% respectively.
On respondents’ involvements in DRM programs in the metropolis, findings revealed that 77.3% and 75.0% of the respondents on the island and mainland areas respectively, were trained in DRM and were involved in DRM related activities in their areas. On the other hand, 22.7% and 25.0% of respondents who had DRM trainings did not participate in DRM activities in their respective areas. Overall, the majority (75.9%) of the respondents indicated engaging in DRM activities after receiving DRM trainings.
As shown in Table 3 is respondents’ roles in DRM. On the island area 41.9% of the house- holds were engaged in raising the community’s awareness about disasters, 20.3% sourced for funds during disasters, 14.9% engaged in provision of relief materials and 23.0% played no role in DRM. In the mainland areas, respondents who participate in community awareness about disasters constituted 43.5%, those who participates in the disaster relief works were 15.2% and 13.0% source for funds during disaster. Respondents who are not involved in DRM accounted for 28.3%. Findings on the availability of DRM agencies in respondent’s area revealed that 80.3% of the respondents in the island areas indicated lack of DRM agencies. Similarly in the mainland areas, as a higher percentage of the respondents (76.8%) indicat- ed the absence of DRM agencies in their LGAs. From the study, absence DRM agencies in respondents’ LGAs could be responsible for the relatively low level of awareness, knowledge and participation in DRM in the study area.
Table 3. Residents’ Awareness and Participation in DRM
Options
Island
Mainland
Total
Count (%)
Count (%)
Count (%)
Awareness of DRM
Yes
87 (31.2)
177 (72.0)
264 (55.7)
No
141 (61.8)
69 (28.0)
210 (44.3)
Total
228 (100.0)
246 (100.0)
474 (100.0)
Training in DRM
Yes
36 (41.3)
114 (64.4)
150 (56.8)
No
51 (58.7)
63 (35.6)
114 (43.1)
Total
*87 (100.0)
*177 (100.0)
264 (100.0)
Sectors from which DRM Training was received
Government agencies
27 (40.9)
57 (52.8)
78 (42.3)
Private institutions
9 (13.6)
6 (5.6)
15 (8.6)
NGOs
30 (45.5)
45(41.6)
75 (43.1)
Total
*196 (100.0)
*108 (100.0)
*174 (100.0)
Respondents Involved in local DRM activities
Yes
51 (77.3)
81 (75.0)
132 (75.9)
No
15 (22.7)
27 (25.0)
42 (24.1)
Total
*66 (100.0)
*108 (100.0)
*174 (100.0)
Respondents’ Roles in DRM activities
Fund raising
45 (20.6)
36 (13.0)
81 (16.3)
Disaster relief work
33 (14.9)
42 (15.2)
75 (15.1)
Community awareness education
93 (41.9)
120 (43.5)
171 (42.8)
Not involved
51 (23.0)
78 (28.3)
129 (25.9)
Total
**222 (100.0)
**276 (100.0)
**498 (100.0)
Availability of DRM agencies in Respondents Metropolis
Yes
45 (19.7)
57 (23.2)
102(21.5)
No
183 (80.3)
189 (76.8)
372 (78.5)
Total
218 (100.0)
246 (100.0)
474 (100.0)
Preventive actions against disaster
Avoidance of disaster condition
81 (25.6)
73 (19.2)
154 (22.1)
Purchase of disaster kits
65 (20.6)
69 (18.2)
134 (19.3)
Report early warning signs
47 (14.9)
69 (18.2)
116 (16.7)
Participation in disaster prevention project
123 (38.9)
169 (44.4)
292 (41.9)
Total
**316 (100.0)
**380 (100.0)
**696 (100.0)
* This is lower than the total number of respondents because some respondents do not participate in DRM activities in the area
** The total is higher than the number of respondents because respondents selected multiple options of their roles in DRM
Findings were also made on the preventive actions carried out by respondents in the man- agement of disaster. On the island, 25.6% of the respondents claimed they avoid disaster conditions, 20.6% purchase disaster combat kits, 14.9% report early warning disaster signs while 38.9% participates in disaster prevention projects. On the mainland, 19.2% of the re- spondents claim they avoid disaster situations, 18.2% purchase disaster combat kits, 18.2% report disaster signs to the necessary agencies while 44.4% participates in disaster prevention projects. Overall, the majority (41.9%) of the respondents indicated participating in disaster prevention projects.
3.4 Difference in Involvement in DRM based on Socioeconomic Characteristics
The study also examined the statistical significant in involvement in DRM based on so- cioeconomic characteristics as it is suggested that socioeconomic attributes influence en- vironmental concerns (Philip & Rayhan, 2004; UNISDR, 2009; Muttarak & Lutz, 2014). In order to achieve this, tests of statistically significant difference in involvement in DRM by residential characteristics were conducted using Analysis of Variance (ANOVA). The results of these tests are presented in Table 4. The included factor variables in the tests are place of residence, gender, age, monthly income, household size, length of residence, and educational attainment. The individual scores of awareness of DRM, trainings on DRM, respondents’ involvements and roles in DRM were summed to create a sum-score for the participation of residents in DRM. The sum-scores were then added up to create the respective composite sums. A mean value of the variables was later computed to arrive at residents’ participation in DRM.
Table 4. Difference in Participation in DRM by Residential Characteristics
Sum of Squares
Df
Mean Square
F
Sig.
Place of residence
Between Groups
3231.390
2
1615.695
8.906
.002
Within Groups
65209.760
424
57.250
Total
68477.150
426
Gender
Between Groups
.722
2
.241
.957
.415
Within Groups
34.943
424
.251
Total
35.664
426
Age
Between Groups
2986.072
4
746.518
11.908
.000
Within Groups
23416.907
422
58.467
Total
26402.979
426
Monthly income
Between Groups
3525.616
3
1175.205
7.049
.001
Within Groups
270375.982
423
57.580
Total
273908.958
426
Household size
Between Groups
247.411
3
82.470
2.634
.052
Within Groups
4257.761
414
56.307
Total
4505.171
417
Length of residence
Between Groups
2292.790
3
764.263
9.013
.003
Within Groups
271615.810
423
58.960
Total
273908.598
426
Educational status
Between Groups
3599.976
4
899.994
7.192
.001
Within Groups
270308.622
401
58.476
Total
273908.598
405
The ANOVA tests results revealed that there were statistically significant differences in residents’ participation in DRM based on their place of residence, age, monthly income, length of residence and educational status in all the LGAs. The analyses were further subject- ed to post hoc tests for multiple comparison analysis for those with more than two categories using Bonferroni. Findings revealed that significant difference existed within and between the groups in residents’ participation in DRM. For instance, significant statistical differenc- es were found between each of the place of residences, and between categories of monthly income, length of residence and educational status in terms of participation in DRM of resi- dents across the LGAs in the two clusters in the study area. Nevertheless, there are no statis- tically significant differences in participation in DRM based on gender and household size in the study area. The implication of these findings is while socioeconomic characteristics such as age, monthly income, length of residence and educational status may be used to explain some level of participation in DRM in Lagos metropolis. Gender and household size may not be used likewise in the study area.
3.5. Determinants of Residents’ Participation in DRM in the Study Area
In this section, residents’ participation in DRM was the dependent variable while the in- dependent predictors were the identified socioeconomic characteristics of the respondents. The predictors comprised characteristics such as gender, age, education status, income status, household size and duration of residence. The categorical variables were transformed into interval data to make them suitable for parametric tests and binary categorical variable gen- der was coded as “0” and “1”. A multiple regression analysis was conducted. This was carried out in order to determine whether the identified socioeconomic characteristics can predict a
significant amount of the variance in participation in DRM among residents. The regression model summarizes these factors in relation to residents’ participation in DRM.
Table 5. Residents’ Participation in DRM Regressed on Socioeconomic Characteristics
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
(Constant)
18.550
.749
24.779
.000
Gender
-.006
.008
-.071
-.780
.437
Age
-2.873
.628
.130
-5.321
.000
Educational status
-1.356
.355
-.112
-5.715
.000
Monthly income
3.541E-006
.000
.089
.982
.328
Length of residence
-1.424
.511
-.105
-.4157
.003
Household size
-.048
.019
-.093
-2.516
.013
R = 0.291; R Square = 0.093
The combined effects and the relative contributions of each independent variable on par- ticipation in DRM are presented in Table 5. The composite correlation coefficient of the rela- tionship between socioeconomic characteristics and residents’ participation in DRM is 0.291. This value provides a good estimate of the overall fit of the regression model. The regression value (R2), which provides a good gauge of the substantive size of the relationship, is 0.093 for this model. This implies that 9.3% of the variance in participation in DRM is accounted for by the predictor variables. Furthermore, presented in the table is the relative contribution of each predictor variable to the variance in residents’ participation in DRM. Age has the high- est beta value (.130), followed by educational status (-0.112), length of residence (-0.105). However, the predictor variables of gender, monthly income and household size have no significant effect on residents’ participation in DRM.
These findings are consistent with the results of earlier studies by (Aribisala, 2018 and Olowoporoku 2017b; Olowoporoku, 2017; Muttarak & Lutz, 2014; Bourque et al. 2012; UN- ISDR, 2009; Lindell & Hwang 2008; Philip and Rayhan, 2004) have indicated that there is a significant statistical association between socioeconomic characteristics such as age, edu- cational status and length of residence and residents participation in disaster management. Thus, these variables serve as strong predictors of residents’ participation in DRM in the study area. The analyses also revealed results that do not reflect findings of studies like those of (Olowoporoku 2017; Daramola & Olowoporoku, 2016; Yodmani, 2001) that have iden- tified gender, income and household size as being strong predictors of environmental con- cerns. The basis for the difference may be due to the peculiarity of the study area.
Conclusion
This study assessed the determinants of residents’ participation in DRM in Lagos, Me- tropolis, Nigeria. Based on the findings of the study, it suggests that majority of the residents were unfamiliar with DRM and those who were aware of DRM did not engage in disaster preparedness and reduction activities. Also, the study identified inadequacy of available en- vironmental protection agencies and residents’ limited concerned for environmental threats as contributors to disaster. Furthermore, it suggests that socioeconomic characteristics such as age, educational status and length of residence can be used to explain variance in res- idents’ participation in DRM. These factors could inform residents’ involvement in DRM
activities in the study area and other Nigerian city with similar background. These results on residents’ participation in DRM would limit losses that emanates from disaster occurrences. These findings have policy implications for effective management of disasters both in Lagos, Nigeria and other area with similar urban settings. The study recommends the following;
The government should develop a strong awareness system among residents on DRM in the study area. Adequate awareness is essential in achieving success in en- vironmental issues. This can be achieved through introduction use of billboards, tel- evision and radio jingle and leaflets and also formation of environmental awareness groups who would engage residents on the need to embrace DRM. This will invoke a mind-set reorientation to make management of disaster not an after-thought idea in the planning process;
The government and all concerned stakeholders should invest in the training of residents especially landlords about DRM; and
Concerned stakeholders such as government and NGOs should establish, fund and equip environmental protection agencies in the study area.
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Original Article
DOI: https://doi.org/10.18485/ijdrm.2020.2.2.2
UDC: 005.521:[614.2:351.862.2(569.4)
005.742-057.162:005.334
616-083.98:355.469.2
THE ROLE OF AL-SHIFA MEDICAL COMPLEX ADMINISTRATION IN EVACUATION & SHELTERING PLANNING
Ahmed H. Al-ramlawi1, Mohammed M. El-Mougher2, Mohammad R. Al-Agha3 1 Emergency Management- MOH
2 Evacuation and Emergency Management- IUG
3 Sustainable Development- IUG
* Correspondence: a7meed.ps1989@gmail.com.
Received: 2 November 2020; Accepted: 3 December 2020; Published: 1 January 2021
Abstract: The study aimed to Highlight the role of Al-Shifa Medical Complex administration in evacuation and Sheltering Planning, due to the suffering of the Gaza Strip from repeated attacks by the Israeli occupation, and the escalation of such attacks over the past ten years. The researcher used the content analysis method and Descriptive approach to try to collect all the appropriate data for this topic. The researcher relied on several tools: observation (field visits), personal interviews with stakeholders, risk analysis of the Al-Shifa Medical Complex. The results showed that Quick response in implementing evacuation mechanisms is a critical element in the success of the plan and saving the lives, and showed that planning for evacuations and sheltering is among the priorities of Al-Shifa Complex Administration and the General Administration of Hospitals and that Al-Shifa Complex Administration had prepared a comprehensive evacuation plan and it is developed annually. However, the study found that no maneuver was conducted that simulate activation of the plan for all the working staff in the complex, due to several reasons, and also showed that risk analysis contributes to enhancing preparedness for crisis and disasters, and improving response level to any risk that may occur in future. The study recommends the necessity of form- ing an internal emergency committee specialized in crisis, disasters, and emer- gency management and activating it permanently to enhance preparedness level, implementing maneuvers that simulate the evacuation, sheltering, and isolation of major hospitals by standard and modern methods, Developing and strength- ening of working staff capabilities in emergency and evacuation management.
Keywords: evacuation, sheltering, planning, Al-Shifa Medical Complex, admin- istration, the Gaza strip, Palestine.
Introduction
The role of the health sector in most societies and countries revolves around providing health and medical services for patients and strengthening interventions to address risks and losses resulting from them and reduce their effects, as that health institutions rely on devel- oping their performance and enhancing their preparedness to face potential risks. The higher management of the national health system is interested in building preventive measures and activities and emergency response interventions, including management of evacuation and sheltering operations for hospitals and health centers, which requires knowledge of planning and organization methods, taking into account their proximity to reality for the success of the evacuation and shelter management plans. (Anis, Ali, 2015)
Due to the exposure of the Gaza Strip to repeated attacks by the Israeli occupation, and the escalation of these attacks on the Strip during the last ten years, which included Exposed many hospitals and government health centers for directly targeted, which led to several casualties and injuries. Therefore, we had to look and discuss at field evacuating and shelter- ing hospitals planning to develop the capabilities of the medical, technical and administrative staff for manage the evacuation and sheltering operations if a hospital is under some threat, and to contribute enhancing the resilience and preparedness of the health sector for any emergency event. (Palestinian National Information Center, 2012).
Research Problem
The study problem focused on the nature of the risks to which the Gaza Strip is exposed, and after conducting an initial risk analysis matrix, it was observed that emergency planning needs to reinforcement the risk analysis methodology, Especially after analyzing the content of the evacuation plan for the Shifa Medical Complex for the year 2019, there was also a spread of chaos regarding the spread of rumors related to the evacuation one of the complex buildings during the Israeli aggression in 2014.
Main Question:
What is the role of the Al-Shifa Medical Complex administration in planning for evacua- tion and sheltering if a complex is exposed to a risk that requires evacuation?
Sub-Questions:
What is the methodology for preparing an evacuation and sheltering plan for Al-Shifa Medical Complex if exposed to an emergency event?
What is the preparedness extent of the medical, technical, and administrative staff when implementing the evacuation and sheltering plan?
What are the main challenges that hinder the implementation of the evacuation and sheltering plan at Al-Shifa Complex for the year 2019?
Research Objectives
General objective:
Highlight the role of Al-Shifa Medical Complex administration in evacuation and Shel- tering Planning.
Sub objectives:
Analyzing the content of the evacuation plan of Al-Shifa Medical Complex.
Determine the preparedness of the medical, technical, and administrative staff if the evacuation and sheltering plan are activated.
Identify the mechanisms of evacuation and sheltering followed at Al-Shifa Medical Complex.
Research Justifications
Contributing to the development of Al-Shifa Complex preparedness to face crises and disasters.
Helping decision-makers in achieving the goal of maximizing the preparedness of health institutions by the political and security changes prevailing in the Gaza Strip.
The study simulates a vital topic that represents a top priority for governmental emer- gency committees and authorities charged with preparing emergency, evacuation, and shel- tering plans.
Research Methodology
Due to the importance that the study subject acquires, and to try to collect all the appro- priate data for this topic, it has been adopted the content analysis method appropriate to the phenomenon of the study, and the descriptive approach to display the current situation.
Data Collection Tools
Primary data: collecting primary data through observation (Field visits), and personal interviews with the relevant stakeholders.
Secondary data: Collecting secondary information and data from scientific books, ref- ereed research, and thesis related to the study field.
Previous Studies
Previous studies considered an important component of scientific studies, and no study can achieve its goals without reviewing it.
Study of (AL-Mughier, et al., 2019) entitled:
The Role of Evacuations and Shelters Process on the Internal Front in Gaza Strip
The study aimed at explaining the role of evacuations and shelters process on the internal front in the Gaza Strip. through the use of the analytical descriptive method using interviews with specialists and direct observation. The researchers reached several results, the most im- portant is that the evacuation and shelters based on planning contribute to the effectiveness of the protection of the internal front in the Gaza Strip. And the study recommended the
need to provide multiple plans and scenarios according to risk assessment of each crisis that has a high probability to occur in the Gaza Strip and work to organize evacuation and shelter operations to protect and fortify the home front.
Study of (Nero, Ortenwall, & Khorram-Manesh, 2013) entitled:
Hospital Evacuation: Planning, Assessment, Performance, and Evaluation – Gothenburg
This study focused on the factors that contribute to hospital evacuation and analyzed them to prepare appropriate plans, the objectives focused on: analyzing the risks and weaknesses (vulnerabilities) of the hospital evacuation plan, identifying the risks that lead to hospital evacuations, and proposing a model for evaluating evacuations. The study adopted of ana- lyzing risks and vulnerabilities methodology for a hospital evacuation plan, and researching the literature and previous studies related to the hospital evacuation field. The results of the study confirmed that all hospital evacuation plans are inadequate due to a lack of knowledge and appropriate tools for planning, implementing, and evaluating hospital evacuations pro- cedures, vulnerability, and risk analysis that can be used to identify key factors in the evacu- ation process. The study recommended: that Hospitals are in constant need of a detailed plan for evacuation procedures, and carry out risk and vulnerability analysis of the evacuation plan continuously to identify areas of weakness and use a general guide as a basis for evacu- ation planning.
c. Study of (Bagaria, Heggie, & Murray, 2012) entitled:
Evacuation and Sheltering of Hospitals in Emergencies: A Review of International Experience – London
The study aimed to define the scope of common hospital evacuations and to define hos- pital evacuation policies, and the processes and challenges involved in hospital evacuation globally, The methodology of the study was represented by its use of several methods: struc- tured search at the database (PubMed) and agencies concerned with disasters, and use of some relevant previous references, communication with WHO staff, analysis of literature and media reports. This study showed that hospitals are highly vulnerable to natural disasters and human disasters, and that hospital evacuations are taking place worldwide. The pub- lished policies in the hospital evacuation and sheltering management field were divided into three groups/ international policy: its primary goal is to establish safe and capable hospitals that can function during and after emergency events. National policy: Emphasize on meas- ures taken to evacuate patients with considering all potential risks, and provide appropriate plans for evacuations, sheltering safe transportation, and follow-up of patients. Local policy: It works to create plans in response to phased evacuations and complete evacuations. among the challenges faced by the study is the lack of scientific references and policies related to hospital evacuation, and recommended the importance of conducting similar studies.
Comment and Comparison
The current study differed from previous studies in choosing the place and community of the study which represent at Al-Shifa Medical Complex, it is the largest medical complex in the Gaza Strip, and most of them provide various medical services, and the evacuating process is very complicated due to several great challenges.
Previous studies did not shed light on the role of hospital administration in emergency planning, evacuation, and sheltering if exposed to a threat or risk.
Previous studies did not talk about the importance of the role of medical staff in man- aging crises and disasters, and strengthening the home front.
Most studies did not offer clear mechanisms for hospital evacuation and sheltering dur- ing complex emergencies.
Theoretical Framework
Introduction
Emergency events contribute negatively to exacerbating the general conditions of all vital sectors, especially the health sector, Due to the exposure of many direct and indirect attacks, The Gaza Strip is considered one of the unstable areas due to the multiplicity of dangers and threats facing the population, and deterioration of the Palestinian infrastructure and the re- sulting climate change and weather factors. (Governmental Emergency Committee, 2018)
Concept of Evacuation:
It is the deportation of persons or residents from areas exposed to the dangers of wars and disasters to safe areas and far from danger areas, and work to fully care and assist these peo- ple, whether humanitarian or health services. (Cambridge Dictionary, 2019)
Medical Evacuation:
It is an important part of the evacuation in general, but it is specific to a certain group of people affected by the disaster, Where the injured and deceased are evacuated from incident sites to the medical triage area while passing through the disinfection area in the event of poi- soning cases, then transferred to health facilities equipped to combat epidemics of poisoning or deal with the injured and wounded. (Ministry of Interior and National Security, 2017)
Motivations of Evacuation:
the motivation of evacuation is considered the primary pillar on which decision-makers rely on activating the evacuation plan in the threatened place or location.
Figure 1. shows the motivation and causes of Evacuation
(Bagaria, Heggie, & Murray, 2009, p.2)
Types of Evacuation
When an emergency occurs in the institution and that incident requires evacuation, it is necessary to immediately start activating the pre-prepared evacuation plan and determine the level and type of evacuation according to the size and severity of the emergency.
Figure No. (2): shows the levels and types of evacuation for buildings and hospitals (Wallack, Performing Emergency Evacuations, 2007)
Sections of Evacuation
Evacuation occurs optional or mandatory according to the emergency and according to variables in the area at risk. It also occurs completely, partially, temporary or permanent, the official sources and agencies differed in determining the types and sections of evacuation. (Qurani, 2007)
Table No. (1): shows all the details of hospital evacuation departments if they are exposed to a threat or danger.
Sections of evacuation
Definition & Other information
1.
Completely Evacuation
This evacuation takes place when a disaster oc- curs to an area as a result of a natural event such as (floods - rains - earthquakes - volcanoes - an epidemic) or an artificial event (sabotage - neglect
- a direct military threat). While the order is issued to the teams, the persons concerned, and the civil defense personnel, it is necessary to immediately start preparing the supplies for people sheltering, and that by preparing another site for them, as this place is equipped with all the requirements while ensuring the continuity of providing all basic and health services.
2.
Partially Evacuation
Th s type of eviction occurs on a certain part of the population, while the risk of occurrence is limited to a specifi place, Therefore, teams assigned to cri- sis management must move people from the danger area to a nearby safe area, or transfer people from the building at risk to another safe building near the emergency event, and it must also provide them with all their needs and requirements of health ser- vices and food aid until the emergency stabilizes.
3.
Temporary Evacuation
This evacuation is considered one of the easiest known evictions, as it does not exceed a few hours, such as evacuations resulting from false reports in institutions or agencies, which takes only a short period until emergency and crisis management teams make sure that the situation is safe and does not require evacuation.
4.
Permanent Evacuation (several years)
This type of evacuation is one of the most difficult types of evacuation and only occurs in war times, as the evacuation order/decision is issued by the highest authority in the state or region that the population and civilians must be evacuated from that area due to fear of entering it on the battlefield. the evacuated area is often occupied or destroyed, and thus it takes several years to rebuild it, there- fore this type was called (permanent evacuation).
(Source: University of Bahrain, Security and Safety Division, 2019)
Evacuation Tracks
It’s the tracks that predetermined for safe evacuation methods, and designated for trans- porting patients and working staff from inside the hospital to alternative health facilities in case of external evacuation, It shows specific information about the safe routes that must be taken by the participating transport means, and assist the competent authorities and security agencies in directing traffic and close unsafe roads to facilitate the external transport process. (Office of Emergency Management, 2020)
Evacuation Time
It is the time required to evacuate patients and working staff from inside hospital depart- ments to alternative medical sheltering sites or surrounding hospitals, there are several meth- ods of estimating it, including a comprehensive actual plan training or a simulated hospital evacuation. (Palestinian Ministry of Health, 2019)
The time element must also be taken importantly during the evacuation process, as the time required to evacuate the building is measured according to its seriousness and mate- rials involved in its construction and the extent of its resistance to the existing danger. The evacuation time depends on the rate of people exit from emergency exit per minute, and this varies according to the type of building, as well as the different type exit method, whether it is horizontal or vertical.
Hospitals Evacuation Stages
The decision to evacuate hospitals is a very difficult decision, and it is carried out with the participation of a group of managers and officials in the hospital or by the higher government authorities after conducting a careful assessment of the potential threats and exhausting all possible alternatives. The following figure shows a detailed diagram of the main stages in the hospital evacuation process (Harvard University, 2014):
Figure 2. shows the basic stages of hospital evacuation.
Figure (2) shows the basic stages of the entire hospital evacuation process from the issu- ance of evacuation orders to transferring of patients outside the hospital site, tracking them and informing their families of their locations (Harvard University, 2014).
Evacuation Orders / Decision
Governmental institutions rely on issuing evacuation orders based on information sourc- es or risk analysis carried out by the competent institutions, or based on reports issued by international organizations, or based on the decision of the Higher Governmental Emergen- cy Committee, the institutions take decisions to evacuate either optionally, especially in the case of natural hazards that could cause sinking and destroying the facilities and buildings and the infrastructure, or mandatory evacuation when the areas and Facilities, institutions are exposed to a direct threat.
Sheltering
Most of the international legislations and laws are agreed that civil protection is the top priority of the state towards its citizens in terms of protection and relief of people and prop- erty in all circumstances, and in war times and disorders and during calamities as well as preventing natural, industrial and war hazards, mitigating their consequences, uniting efforts to confront those dangers, and setting appropriate procedures and actions to protect lives. among the necessary measures taken by the state to save lives are the urgent evacuation and sheltering of the affected people until the end of the crisis or disaster (Al-qidwa, 2008).
Concept of Sheltering
It’s the process of providing basic services and protection for the internally displaced pop- ulation (IDP) to pre-determined shelters by government agencies, by international standards and in a manner that ensures community participation (UNHCR, 2018).
Concept of Shelter
The shelter is a vital survival mechanism in crisis times or displacement, it is also an essen- tial element to restore a personal security sense, enjoy self-sufficiency and dignity, where pro- tection and humanitarian aid and health care are provided to the displaced. (UNHCR, 2020)
Medical Sheltering (Medical Shelter)
It’s the shelter that seeks to meet the medical needs of people who have been displaced from their residence place as a result of a disaster or an emergency event, which requires a temporary place equipped with all medical equipment to ensure the continuity of providing medical services. (California Department of Public Health, 2011).
The Safe Healthy Shelters
are the shelters that specifically established for urgent sheltering, and provides basic and health services, necessary materials and equipment, additionally, the facilities and infrastruc- ture shall be habitable, suitably located, taking into account the privacy and requirements of persons with special needs, the elderly, children and their mothers.
Purpose of Healthy shelters
The following figure shows the purpose of the field of medical shelter during emergencies, in which health service is provided for people who need daily therapeutic and diagnostic monitoring and follow-up.
Figure 2. Clarifies the purpose of the field of medical shelter during emergencies. (Delaware Health and Social Services, 2009)
Alternative Places that can be used as Medical Shelter
Those places that could be used as temporary medical shelters for patients who are to be evacuated from the hospital at risk can be summarized, as shown below:
Basic elements that must be provided in the medical shelter (Delaware Health and Social Services, 2009):
Figure 3. Shows the basic elements that must be provided in the medical shelter
The health system in Gaza Strip
The Israeli occupation has contributed to complicating the Palestinian health system due to the succession of closures, chronic blockade, and geographical separation between the
North and South governorates. This posed a massive challenge for the Ministry of Health by facing difficulties in the availability of health care services and affected the harmony of the health care system in all Palestinian cities. (Palestinian Ministry of Health, 2017)
Dangers That Facing Gaza Strip
By looking at the natural or even industrial (human) hazards in Palestine, that most of these risks can have a short-term impact, and some of them have a long-term impact, below is an overview of these risks (Ministry of Interior and National Security, 2017):
Palestinian Ministry of Health (MOH)
The Palestinian Ministry of Health is responsible for citizens’ public health of the State of Palestine, and it’s the main provider of all health, medical, and treatment services in its vari- ous specialties, all hospitals, and treatment centers belonging to the public sector belong to it.
General Hospital Administration – MOH
It is considered a governmental institution affiliated to the Palestinian Ministry of Health that is concerned with news and activities of the hospital sector at the Ministry of Health and aims to continuously raise the level and technical quality and administrative performance in hospitals, to keep up with all global developments in the art of medical management to devote effort at planning, organizing, directing and controlling work.
Governmental hospitals
The governmental hospitals affiliated with the Ministry of Health provide treatment and diagnostic services in various specialties to the Gaza Strip population, whose number for the year 2019 was (1.99) million.
Table No. (2) reviews governmental hospitals in the Gaza Strip
Central hospitals
Al Shifa Medical Complex, Nasser Medical Complex, European Gaza Hospital.
General hospitals
Provides basic secondary services
Al-Aqsa Martyrs Hospital, Indonesian Hospital,
Mohammed Yousuf al-Najjar Hospital, Beit Hanoun Hospital.
Mono-specialty hospitals
Ophthalmic hospital
Emirates Crescent Obstetrics and Gynecology Hospital El Naser Children’s Hospital
Muhammad Al-Durra Children’s Hospital Abdel Aziz Al-Rantisi Children’s Hospital.
(Palestinian Ministry of Health, General Administration of Hospitals, 2018)
Methodology and Tools
Due to the importance that study subject acquired, which seeks to highlight the role of al-Shifa medical complex administration in the evacuation and sheltering planning, and be- cause the topic touches on the health system, it has been based on methods used in admin- istrative, engineering, and economic studies, Where the researcher relied on the descriptive and analytical approach.
Study Tools
Observation (Field Survey)
The researcher conducts several field visits to Al-Shifa Medical Complex buildings, where he used direct observation, to know the mechanisms of evacuation and sheltering if the com- plex is exposed to a threat or danger.
Personal Interviews
Several structured interviews were conducted with stakeholders in an evacuation, shelter- ing and emergency management (General managers, supervisors, administrators, heads of departments) at Al-Shifa Medical Complex, to obtain clear and accurate answers to some of the questions that need explanations, and to reach objective results.
Study Results
Risk Analysis Matrix Results
Looking at the matrix, we find that the Mentioned risks have taken several different risk levels, and those levels can be clarified and classified through the following figure:
(Al-Ramlawi, Ahmad, Hazard Analysis Matrix Results, 2020)
We conclude that (risk analysis matrix) contributes significantly to detecting and showing potential risks before they happen, and determine the priority of immediate intervention to deal with it, to prevent its occurrence or mitigate its consequences, it also contributes to enhancing preparedness for crises and disasters, and improving response level to any risk that may occur in future. This corresponds with the study of (Nero, Ortenwall, & Khor- ram-Manesh, 2013). where the study reached in its findings that the risk and vulnerability analysis contribute effectively to identifying the strengths, weaknesses, threats, and risk fac- tors of hospital evacuation plans, it also strengthens the basic factors in evacuations opera- tions and can be used in planning, implementation, and evaluation. This study recommend- ed that the risk and vulnerability analysis of the evacuation plan should be implemented continuously to identify areas of vulnerability, and use it as a general guide for planning and preparing evacuation and emergency plans.
Interviews & Field Visits Results
The Role of Al-Shifa Medical Complex Administration in Emergency, Evacuation, and Sheltering management Planning.
The medical director of Internal Medicine Hospital confirmed that planning for evacua- tion and sheltering is among the priorities of the complex administration, it also that emer- gency planning is done continuously and permanently with the participation of all parties concerned at evacuation and sheltering operations due to the nature of threats and potential risks that may occur at any moment in future. On the other hand, the previously Adminis- trative Director of Surgical Hospital stated that hospital administration participated in pre- paring the emergency and evacuation plan and had a basic role in the planning of evacuation and sheltering mechanisms for al-Shifa complex if exposed to an imminent threat or danger, and he also confirmed that the complex administration conducted a workshop to clarify evacuation and sheltering mechanisms, but not all administrators and working staff at Shifa Medical Complex were involved. On the other hand, the supervisor of nursing at Emergency Departments (Internal Medicine and Surgery) confirmed that the complex administration has prepared a complete and comprehensive evacuation plan that clarifies the mechanisms and procedures of evacuation and sheltering, it also updated and developed annually. This confirms that the al-Shifa Complex administration has a basic role in evacuation and shelter- ing operations planning to raise the level of preparedness for any emergency. This means that al-Shifa Medical Complex administration Give great attention to emergency planning and potential risks, and it’s also working to develop preparedness level to confront any potential risks or crises by preparing appropriate evacuation and emergency plans. However, it turned out that al-Shifa complex administration did not conduct any maneuvers, training, or work- shops for evacuation and emergency plan for all working staff at the complex, and this matter is considered a weak point and a clear threat for evacuation plan and needs to be addressed by the decision-makers in the complex.
Evacuation and sheltering mechanisms in case the complex is exposed to a military threat or some danger.
The Director of nursing at internal medicine Hospital talk about the measures that would be taken upon decision issuance to activate the evacuation plan, and explained as follows:
Firstly: The medical and nursing staff shall prepare and equip patients for the evacuation operation, in addition to collecting all the necessary medicines, files, and documents, and classifying patients according to their health conditions to ensure transported inappropriate ways.
Secondly: Continuous coordination with the civil defense to help implement evacuation and sheltering procedures and operations, in addition to coordinating with receiving parties of patients and informing them about the emergency.
Thirdly: Equipping ambulances, including Intensive care ambulances, also preparing portable medical equipment and devices that are used for patients during the transportation process to ensure continuity of providing health services.
Fourthly: begin the evacuation of patients gradually to Gathering point, in proportion with nature of their conditions and not to endanger their health at risk, then loaded them into ambulances to transfer them to alternative health places Pre-agreed upon in the emer- gency plan.
it’s also confirmed that quick implementation of these mentioned procedures is a crucial element in the success of the evacuation and sheltering plan and saving life. This corresponds with a guide (Harvard University, 2014), Where noted the importance of applying these men- tioned steps if a hospital evacuation decision is issued, and it must be applied within a specific frame time commensurate with the emergency event.
Main obstacles obstructing evacuation operations.
Most of the interviewees agreed on a set of obstacles and challenges hindering evacua- tions, the most important are:
The very large number of patients and staff working.
Lack number of nursing, medical, and technical staff participating in the evacuation and sheltering operations.
lack of necessary medical equipment, supplies, and tools during the evacuation pro- cess.
culture of community members and gathering of escorts and visitors within the walls of the al-Shifa medical complex.
Poor coordination and communication with concerned parties involved in hospital evacuations and sheltering.
lack of emergency exits and their narrow space poses a real threat during the evacua- tion of patients.
Inability to ensure continuity of providing medical services for hemodialysis patients if internal medicine building is evacuated, due to a large number of patients and a lack number of hemodialysis machines in other health institutions. Among proposed hospitals for referring hemodialysis patients (Al-Quds Hospital, Abdel Aziz al-Rantisi Hospital, Indonesian Hospital). This agreement with the study of (Agha, 2019), which recommended the necessity of interest by the Ministry of Health to fill all gaps and obstacles at health facilities by providing all the equipment and supplies needed to ensure service quality and its Sustainability during and after crises and disasters, and developing work environment.
Role of the civil defense in evacuation and sheltering management at Hospitals.
The Supervisor of Nursing at emergency departments (Internal Medicine and Surgery) confirmed that complex administration participates the civil defense in evacuation oper- ations and procedures, and has previously conducted (risk analysis) for internal risks and security and safety procedures of evacuation plan in partnership with civil defense, it’s also the involvement of Palestinian police and high Committee for ambulance and emergency in Evacuation and sheltering procedures management.
On the other hand, the Deputy Director-General of Civil Defense at Gaza Strip stated that civil defense is always well prepared to deal with emergencies of all levels, as the civil defense teams participated in managing the evacuation of some hospitals during the Israeli aggression on the Gaza Strip in 2014, and in case of similar emergency events that require evacuating a government hospital such as Al-Shifa Medical Complex in future; Our teams are ready to intervene and participate in several different roles at evacuation and sheltering management, it’s also noted that Planning and Development Department at Civil Defense participated in preparation and development of emergency and evacuation plan for Al-Shifa Medical Complex and recommended for evaluating and testing by conducting a live maneu- ver to evacuate one of the hospital sections or buildings. The researcher believes that civil defense has an important and primary role in emergency planning and hospital evacuation and sheltering, it also participates in (risks analyzing and monitoring) with hospital manag- ers and crisis and disasters management specialists to identify potential risks and predict the extent of their occurrence and risk level and priority of intervention to manage and deal with them as required.
Recommendations
Based on the results of the study, the researcher extracted several recommendations that he hopes will have an effective role in strengthening the role of evacuation and sheltering planning and raising levels of preparedness for crises and disasters and worst possibilities and variables surrounding the health facilities.
Interest the Ministry of Health to develop this study and fill all the gaps that have been mentioned, and complete this effort to include other hospitals and health facilities in Gaza Strip.
Forming an internal emergency committee specialized in managing crises, disasters, and emergencies, and activating it permanently to enhance preparedness.
Improve and develop evacuation and sheltering plans and set isolation mechanisms to make the plan able to confront all potential risks, especially epidemics and infectious diseases risk.
The necessity to implement maneuvers that simulate the evacuation, sheltering, and isolation of major hospitals by standard and modern methods, by the recommendations of the World Health Organization and agencies concerned with crisis and disaster management.
Update emergency and evacuation plans annually by specialists in crisis and disaster management and present them to consultants in emergency management.
Conducting several research studies specializing in an evacuation, sheltering, and iso- lation management of major hospitals if exposed to worst expected risks.
Developing and strengthening of working staff capabilities in emergency and evacua- tion management, and informing them about updated plans internationally.
Communicating all research study outputs to decision-makers and officials in the Ministry of Health and emergency committees, to enhance and raise knowledge level in evacuation and sheltering management of major hospitals.
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Dictionary of Cambridge. (2019). Evacuation & Shelter Definition, Dictionary Cam- bridge org. Retrieved from: https://dictionary.cambridge.org/dictionary/english/shelter
General Directorate of Palestinian Civil Defense. (2017). Crisis and Disaster Risk Reduc- tion National Framework. Gaza: Palestinian Ministry of Interior.
Governmental Emergency Committee. (2018). Governmental emergency plan for the winter season. Gaza, Palestine: General Secretariat of the Council of Ministers.
Harvard University. (2014). Hospital Evacuation Planning Guide. Harvard School of Public Health, Cambridge, USA.
Lindell, Michael. (2013). Evacuation planning, analysis, and management, University of Washington Seattle, Washington, USA.
Ministry of Interior and National Security. (2017). national framework for managing and Confronting crisis and disaster risks. Gaza: Palestinian Civil Defense.
Nero, C., Ortenwall, P., & Khorram-Manesh, A. (2013). Hospital evacuation: planning, assessment, performance, and evaluation. Journal of Emergency & Disaster Medicine, Gothenburg, Sweden.
Palestinian Ministry of Health, General Administration of Hospitals. (2018). Annual sta- tistical report for hospital performance. Gaza, Palestine: Palestinian Ministry of Health.
Palestinian Ministry of Health, General Administration of Hospitals. (2019). Evacuation plan for Al-Shifa Medical Complex. Gaza: Ministry of Health.
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UNHCR. (2018). Shelter solutions, Shelter management. Retrieved from The UN Refugee Agency: https://emergency.unhcr.org/entry/57186/shelter-solutions
8. Appendices
Appendix No. (1): Interview questions
S | Interview questions |
1. | What is your role in evacuation and sheltering operations planning, did you participate in workshops related to evacuation and sheltering? |
2. | What are the training maneuvers that being implemented for staff working at the al-Shifa complex about evacuation mechanisms? |
3. | How are evacuation and sheltering procedures applied if the complex is exposed to a threat or danger? |
4. | What are the coordination mechanisms with parties involved in evacuation and sheltering operations? |
5. | What are the main obstacles that hinder evacuation operations? |
6. | What are procedures that ensure continuity of providing services for patients during evacua- tion? |
7. | Is the civil defense involved in evacuation and sheltering operations? if the followed plan is activated |
Appendix No. (2): interviewees names
S | Name | Job title | Date of inter- view |
1. | Dr. Mohamed Zaqqout | Medical Director - Internal medicine Hospital | 27/04/2020 |
2. | Ahmed Ahmad | Nursing Director _ Internal medicine Hospital | 28/04/2020 |
3. | Mohammad Al-Khudary | Emergency Nursing Supervisor (Surgery - Internal Medicine) | 28/04/2020 |
4. | Mohammad Al-Ra’i | Administrative Director - Surgical Specialist Building | 27/04/2020 |
5. | Dr. Imad Al-Fayoumi | Emergency Manager - Internal medicine Hospital | 27/04/2020 |
6. | Dr. Muhammad Al-Attar | Deputy Director-General of Civil Defense - Gaza Strip | 30/06/2020 |
7. | Mahmoud El-Sayed | Specialist in Emergency Management - Al-Shifa Medical Complex | 20/04/2020 |
Original Article
DOI: https://doi.org/10.18485/ijdrm.2020.2.2.3
UDC: 005.334:628.112(549.3)
005.52:556.36
WATER CRISIS AND ADAPTATION STRATEGIES BY TRIBAL COMMUNITY: A CASE STUDY IN
BAGHAICHARI UPAZILA OF RANGAMATI DISTRICT IN BANGLADESH
Uttam Bikash Chakma1 , Md. Akhter Hossain2, Kamrul Islam3, G.N. Tanjina Hasnat4, Md. Humayain Kabir5*
3 Department of Systems Innovation, Graduate School of Engineering,
5 Wegener Center for Climate and Global Change, University of Graz, Austria, email: mhkabir@cu.ac.bd
* Correspondence: mhkabir@cu.ac.bd.
Received: 5 November 2020; Accepted: 1 December 2020; Published: 1 January 2021
Abstract: Water crisis under changing climate is one of the major environmental challenges in Bangladesh. Tribal communities of Chittagong Hill Tracts (CHTs) have been suffering from water scarcity since long. This study aimed to identify the available water sources, extent of water scarcity and traditional adaptation practices to cope with water scarcity in hilly area of Bangladesh. This study was conducted by face-to-face interview using a structured questionnaire in 6 vil- lages of three union of Bagaichari upazila which were selected through stratified random sampling method. The main sources of water for drinking, domestic use and irrigation were river, streams, dam over streams (Godha), very small stream (Thagalok), well dug on hill bottom (Shillaw hoo), springs, big dug well, tube- well, ring-well, river, and pond. In every year December-April is the dry and water crisis period. To overcome the severity, people built small dams (Godha) to raise water level and use in irrigation and domestic purposes. For drinking water maximum 42% people dependent on shilaw hoo. For domestic purposes 38% households dependent on streams and 65% dependent on Ghoda for irri- gation water. Tribal people of the study area have to walk a long hours to collect water from sources located about 1-2.5 kilometers away from the settlement with
earthen or plastic buckets sized 10 to 15 litters. Water crisis was found in severe condition since last 5-10 years. Before that water was available in hilly region. Maximum people (89%) reported deforestation as the main reason of water cri- sis. This study suggests both government and non-governmental professionals to foster local communities’ adaptation capacity against the water scarcity in Bagai- chari upazila. This study will play a vital role to take relevant adaptation policies both by the policy makers and practitioners.
Key words: Tribal, Chittagong Hill Tracts, water crisis, adaptation strategies, de- forestation.
Introduction
Water is an important element of environment. People need water for drinking, washing, cooking, planting and many other uses. About 97% of the earth’s water is in the ocean and unfit for human consumption because of its high salt content. Of the remaining 3%, 2% is locked in the polar icecaps and only 1% is available as fresh water in rivers, lakes, streams, reservoirs and ground water which is suitable for human consumption (De, 2003). Over 98% of available global fresh water is stored as ground-water in the saturated zones within pores and fractures in rocks (Hiscock, 1994).
Bangladesh is a developing country with rising population, increased crop production and economic growth. During dry period, it needs 147 BCM (billion cubic meters) water in the country but only 90 BCM is available. This 40% deficit leads to drought in some re- gions (Bangladesh, 2007).Chittagong Hill Tracts is the region where water scarcity is major problem (Kabir and Faisal, 1999). During water crisis period people of the hill tracts collect water and use without filter resulting various water borne diseases such as diarrhea, cholera, typhoid, boil etc. According to World Water Organization (2010), safe drinking water and freshwater are imperative for development and public health since 21 of the 37 primary dis- eases in developing countries are related to water and sanitation. Many children and women are died in every year in CHTs due to water borne diseases. They don’t get medical facilities for treatment because of unavailable of clinic and hospital otherwise communication facil- ities are very poor. However, during crisis period they adopt some adaptation measures to cope with the water crisis situation.
Bagaichari upazila is very remote area of Rangamati District near the Indian border. The communication systems are very poor here. Consequently the government and non-govern- ment agencies do not get proper information regarding water crisis. People of this upazila are suffered from acute water crisis every year. Increasing population day by day and de- forestation through various means including shifting cultivation caused reduction of water flow in the natural water sources and had created water scarcity. Every year the ground water level seems to be drowned deeper level due to indiscriminate loss of forest cover. The people mainly suffer from drinking water in dry season. Water is a vital factor for high yield. Since people started growing more crops in the hills and valleys round the year, they are facing se- vere water scarcity and farmers cannot produce their crops properly. As a result they depend on forest for their livelihood. People are facing a lot of problems collecting sufficient water due to less availability of tube well. In some areas, women need to carry water from a long distance from well, stream, tube well to their homes during the crisis period. As the ethnic groups of Bagaichari upazila of CHTs facing severe water scarcity, but information regarding the water crisis and relevant adaptation capacity of the local people is scarce, so, this study was undertaken to identify the available water sources, extent of water scarcity and tradition- al adaptation practices to cope with water scarcity in the study area.
Materials and methods
Background information of study area
The study area Bagaichari was selected purposively considering the water scarcity faced by the local peoples which was covered by several daily newspapers. Stratified Random Sam- pling method was followed. At first, three unions from Bagaichari upazila and two villages from each union were selected through random sampling (Table 1). For interview six indi- viduals from each village were selected randomly.
Bagaichari is the largest upazila of Rangamati district covering an area of 1931.28 sq. km. The upazila is bounded by Tripura and Mizoram on the north, Langadu upazila on the south, Mizoram on the east and Dighinala upazila on the west. Main rivers are Kachalang, Shijakh. The upazila was established in 1965. Now, it consists of 7 Union Parishads, 19 mouzas, 178 villages. 75% people of this upazila are tribal 93% of these tribal are Chakma,whereas Tri- pura, Pangkuya and others casts constitute 7%. This upazila has one river named Kasalong which is originated in Mizoram and most of the people here dependent on the River for water for household use and irrigation purposes. Pump machines are used to draw water for the irrigation of agricultural fields.
Data collection
A structured questionnaire was designed for collection of data through interviewing the inhabitants of the study area. It was designed based on questions relating to main water crisis, available water sources and their adaptation practices in dry season. At first reconnaissance survey was done to collect primary information in the study area. Preliminary information about the available water sources, water scarcity, communication networks and systems were collected from the unions and villages. Help was taken from a local field guide from each village. The questionnaire was tested at that time to check field applicability and necessary adjustments were made based on the field situation. Then the main interview was done in the same villages which were visited during reconnaissance survey.
Figure 2.1
Figure 1. Location and map of Bagaichari upazila showing study areas.
Secondary data and relevant literature were reviewed related to water scarcity, water harvesting practices, various water borne diseases etc. Data were collected from published research papers, websites and reports of various projects conducted by government and non-government organizations. Primary data were collected through personal interview us- ing the designed questionnaire. Data related to earthen size, daily water requirement, dis- tance of water sources, seasonal availability of water, adaptation practices, reasons and his- torical perspective of water scarcity from the interviewer were collected.
Table 1. Selected unions and villages from Bagaichari upazila for study.
Bagaichari Upazila
Union
Village
No. of Respondents/ households
Total
B. Block
6
36
Dulubannya
6
Boradam
6
Golachari
6
Sajek
Vei-bon Chara
6
Nandaram
6
For data collection, available sources of water for drinking, domestic or household uses and irrigation in the crop lands were found out. Daily requirements of water for drinking, domestic or household purposes were also explored. The distances of different water sources
i.e. well, stream, tube well, thagolok, shilaw hoo, pond, lake etc. from respondents’ houses in different seasons were also revealed through questioning of respondents. Information were also collected about seasonal availability of water, various water borne diseases suffered by different family members, frequency and duration of the water borne diseases, adopted treat- ment, and respective cost incurred for treatment of the diseases. Present study also focused on traditional or indigenous adaptation practices practiced by respondents of the study area in dry season. A historical perspective of water availability was tried to found out by taking data for previous 5 years, 10 years and 15 years along with present data. Finally a compari- son between previous and present data was made. The data obtained through questionnaires were compiled in Excel2013 for analyze and to get final result.
Results and discussion
Socioeconomic information about the respondents
The respondents were from different occupation. Among them maximum (56%) were farmer followed by job holder (22%), women (14%) and businessmen (8%). The respondents interviewed were adult and age ranges from 25 to 60 years. Family members of the house- holds ranges from 4 to 10 members containing nuclear and joint families (table/figure??).
Available sources of water
The available water sources found in the study area were tube-well, ring-well, spring, Chara(stream), Shilaw hoo(well dug on hill bottom), well, river, pond, Ghoda (dam over stream), Thagalok (very small stream) and rainfall. Almost all the households use rain wa- ter for both drinking and domestic use purposes. During rainfall no irrigation is needed in the crop lands.Maximum households (42%) depend on Shilaw hoofor drinking water fol- lowed by tube-well (27%) and Thagalok(18%). In case of domestic use i.e. bathing, washing
and cooking etc. water was collected from streams, tube-well and river by 38%, 17% and 17%households’ respectively. During dry period farmers collected water for irrigation from Ghoda (65%) and adjacent rivers (35%) (Figure 2).
Figure 2. Peoples’ dependency on various water sources for drinking, domestic and irrigation purpose.
Water availability period and main sources of drinking water
The availability of water was measured through scoring it from 1 to 5, where, 1 represents water scarcity, 2 for moderate-scarce water, 3 for moderate water availability, 4 for availa- ble-moderate water and 5 for available water. According to the respondents score following water availability chart it is found that during May to October water remain available due to monsoon rainfall. In the months from December to March the water became scarce for all purposes due to dry condition. The research revealed that during water scarcity period peo- ple collect drinking water from tube-well, Shilaw hoo and Thagalok. The study also indicated that, both in Sajek and Bangaltali union Shilaw hoo is the main source of drinking water during water crisis period where 50% people (respectively) collect water from it. In Rupakari, Tube-well is the main source of drinking water and 58% people dependent on it during dry period (Figure 3).
Figure 3. Seasonal water availability (left) and Main sources of drinking water (right) in Bagaichari upazila during water crisis period.
Water crisis faced in Bagaichari upazila
The study revealed that, in average 70% households living in the remote areas of Bagaich- ari are suffered from water crisis. It is due to drying out of the natural pure drinking water sources and insufficient number of tube-wells. Most of the families (92%) suffered from water crisis in Sajek union. In Bangaltali union 67% families faced water crisis in the dry season and in Rupakari union it was 50% (Figure 4). Water crisis found comparatively lower in Rupakari union. After analyzing data it was found that in this union number of service holders was comparatively higher than other two unions that enabled them to install tube-wells.
Figure 4. (a) Households (%) suffered from water crisis;
(b) people (%) walked different distances every day to fetch water
Adaptation techniques adopted by ethnic families during crisis period
The ethnic people face severe pure drinking water crisis in dry season especially from January to April. Most of the water sources become dried during December-April. Very few shilaw hoo and thagalok contain water at that time. The people of Bagaichari upazila have to fight with the pure drinking water in dry season. The tribal people maintain the forest cover near the well or stream to get the drinking and domestic water in dry season. They maintain the ghoda or dug well for irrigation purpose. They use it as a means of keeping the water cool.
In the study area, a remarkable number of people usually had to fetch drinking water from remote natural water sources. They exited early in the morning from house to fetch drinking water. The results of the study indicated that 38%people had to walk from 1.1 to 1.5 km for collecting water followed by 1.6 to 2 km (30%). There were some families (7%) found living in the remote hills who had to walk from 2.1 to 2.5 km daily to fetch water (Figure 4).Some people used to harvest rainwater and store in water reservoir for future use. Reduced use of water also found another strategy mentioned by some respondents.
Extra time spent for bringing water
It is clear from the results of the present study that, the tribal people specially women spend most of their time to bring water during dry period. In Sajek union,people have to walk an average of 1.3 km more path to fetch water during water scarce season than that of water available season. People of Rupakari union have to walk 0.5 km more in water crisis time and inBangaltali union it is 0.9 km more than that of non-crisis period. The result of the study revealed that people need at least 1 more hour in average to bring drinking water and ½ an
hour to collect water for domestic purposes. Among three unions, people have to walk more distance in Sajek, and hence spend more time in comparison to others unions (Figure 5).
Figure 5. Extra time (hr.) spend to fetch drinking and domestic water in dry season.
Historical perspective of water availability in dry season in the hilly areas
Peoples’ opinion about the water availability in the previous years was gathered through interviewing to get the idea about its historical perspective. The local people opined that the water status was very good at 15 years ago in this hilly area. Water from different natural sources was good in terms of availability as most of the respondents mentioned water was available or moderately available at that time (Table 2). There was no need of tube-wells at 15 years ago but now it is moderately needed and available in the study area. Total forest cover is destroyed due to increasing population and demanded decreased rotation of shifting culti- vation. As a result, the infiltration rate is declined and surface runoff water increased due to lack of forest cover. The tribal people said that all of the water sources are in bad condition except tube-well. From their opinion some of the water sources were in medium condition still before 10 years ago (Table 2).
Table 2. Percentage of historical availability of water in dry season at Bagaichari upazila.
Source of water
Present status
5 years back
10 years back
15 years back
Shilaw Hoo
Scarce (100%)
Scarce (100%)
Scarce (80%)
Moderate (20%)
Available (60%)
Moderate (40%)
Chara
Scarce (100%)
Scarce (100%)
Scarce (60%) Moder-
ate (40%)
Available (67%)
Moderate (33%)
Normal Hoo
Scarce (100%)
Scarce (100%)
Scarce (67%)
Moderate (33%)
Available(50%) Moderate (50%)
Thagolok
Scarce (100%)
Scarce (100%)
Scarce (63%)
Moderate (37%)
Available(63%) Moderate (37%)
Spring
Scarce(100%)
Scarce (100%)
Scarce (79%)
Moderate (21%)
Available(64%) Moderate (36%)
Tube-well
Moderate (100)
Moderate (100)
Scarce (100)
Scarce (100)
Reasons behind water crisis
Deforestation was found the common reason for water crisis in Bagaichari upazila. About 89% family reported about that. From the perception of 55.5% family, practice shifting cul- tivation indiscriminately is another reason of water crisis (Table 3). Actually it is an indirect reason of water crisis as it caused forest cover loss in the hilly terrain and induced deforest- ation.
Table 3. Peoples’ perceived reasons of water crisis in Bagaichari upazila.
Union
Village
De- fores-ta- tion (%)
Shifting cultivation (%)
Soil erosion (%)
Insufficient precipita- tion (%)
Insufficient tube-well (%)
Poverty (%)
Bangaltali
B. Block
83
67
33
67
55
67
Dulubanya
100
83
17
50
67
50
Rupakari
Boradam
100
50
17
83
50
50
Golachari
100
67
33
67
45
67
Sajek
Vei-bon
Chara
67
33
17
67
67
45
Nandaram
83
33
17
50
83
55
Average in Bagaichari upazila
89
55.5
22
64
61
56
Soil erosion is happening due to the loss of forest cover. It reduces the infiltration rate through the seepage. It is another cause of flood and flash flood. About 22% families think that, soil erosion is the reason of water scarcity. Insufficient tube wells were another impor- tant issue in Bagaichari upazila and 61% respondents thought that water crisis occurred due to insufficient tube wells. Poverty is one of the main issues as it provokes people to depend on forests for their livelihoods and 56% family agreed with it as the indirect issue to create water scarcity during dry period. Due to climate change the rain fall rate is also reduced in the hilly areas that create water crisis too.
Conclusion
This study ended with some important findings concerning the available sources for drinking, domestic and agriculture water, extent of water crisis and respective traditional adaptation practices. The result of the study revealed that water scarcity is increasing day by day and from peoples’ perception it is found that the mother cause of water scarcity is loss of forest cover. Moreover, deforestation induces other causes like shifting cultivation, reduced surface runoff, reduced water table, soil erosion etc. To cope with water crisis during dry sea- son people adapted some strategies by building dam on streams, digging wells or ponds. But with loss of forest cover the water table lifted down and causes minimum or no water flows in natural water sources. Increase of forest coverage through assisted natural regeneration, afforestation and reforestation could uplift the ground water table, slow down surface runoff and increase the water availability in the natural water courses, thus reduce water scarcity in the hilly region.
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DOI: https://doi.org/10.18485/ijdrm.2020.2.2.4
UDC: 005.334:627.51(592.6)
Original Article
INDICATOR BASED ASSESSMENT OF INTEGRATED FLOOD VULNERABILITY INDEX
FOR BRUNEI DARUSSALAM
Dilip Kumar1, Rajib Kumar Bhattacharyya2, Shariar Shyam3, Udita Rohana Ratnayke3
1 Civil engineering department, G B Pant Engineering college Ghurdauri, Uttarakhand,
2 Civil engineering department, IIT Guwahati, Assam India,rkbc@iitg.ac.in
3 Civil engineering programme area, universiti teknologi brunei, Jalan tungku link, gadong BE 1410, Brunei Darussalam, shams.shahriar@utb.edu.bn, uditha.ratnayake@utb.edu.bn.
* Correspondence: jhadilip27@gmail.com.
Received: 3 November 2020; Accepted: 7 December 2020; Published: 1 January 2021
Abstract: Since the beginning of human civilization, the flood is always con- nected with extensive destruction of properties and loss of lives. The intensity of flood-related disasters is increasing day by day due to the rapid increase in devel- opment activities, changes in land-use land-cover, population growth, unplanned urbanization, and above all, the driving force resulting from climate change and climate variability. Therefore, researchers are paying increased attention to floods with particular focus on flood vulnerability. The present study is a pioneer at- tempt on indicator-based flood vulnerability assessment for Brunei Darussalam. In this study, an integrated approach towards vulnerability assessment has been proposed, considering hydrological, environmental, social, and economic as- pects of different districts of Brunei Darussalam. Indicators are generated and incorporated to visualize the vulnerability map of the country. The findings of the study can be used to identify the vulnerability status of different regions in Brunei, used to reduce the vulnerability and also to minimize disaster risk by allocating more resources for vulnerable districts. The results of the study will also be helpful in deriving better disaster management strategies for the country.
Keywords: vulnerability; index; indicators; assessment; map.
Introduction
The management and mitigation of flood hazard is a multidimensional task (Ayala et al., 2020; Jaiswal et al., 2020). It requires knowledge and integration of various disciplines such as hydrology, meteorology, geology, sociology, economics, statistics, demographic studies, policy, and planning (Karmaoui et al., 2016; Prinos, 2008). The influences of different aspects of the livelihood of people like social, cultural, and economic affect the vulnerability of a region directly and indirectly (Munyai et al., 2019; Nasiri et al., 2019; Rehman et al., 2019; Žurovec et al., 2017). Moreover, the hilly and coastal areas are likely to be more vulnerable due to frequent and intensive flash floods under various climate change scenarios (Costa and Machado 2017; Guillard-Gonçalves and Zêzere 2018). As such, it is essential to study the im- pact of climate change on the vulnerability index of a country. The concept of vulnerability is, therefore, a multidimensional factor that has a strong correlation to climate change, among other factors. It includes risks, sensitivity, natural hazards, etc. In general, the vulnerability comprises of the following characteristics:
Multidimensional: consist of many factors like physical, economic, social, environmental, as shown in Figure 1 (Dottori et al., 2018; Lee et al., 2013).
Dynamic: change of vulnerability over time (Dottori et al., 2018; Science, 2018).
Scale-dependent: vulnerability can vary from household to community, community to districts and districts to a country (Kumar and Bhattacharjya 2020; Singh et al. 2014).
Site-specific: different for each country or state.
Fig.1: Multidimensional nature of Vulnerability (Balica et al., 2017)
Many researchers have extensively studied about flood hazards and their mitigation, including flood vulnerability assessment. A comprehensive and multidimensional vulner- ability is defined by Birkmann (2006). According to him, indicators and criteria used for vulnerability measurement should have physical, economic, and social relations within the area of interest (Kha et al., 2008; Villordon, 2015). Balica et al. (2012) explained the flood vulnerability with an indicator based method. This indicator-based method, which is used to calculate Flood Vulnerability Index (FVI), depends upon geomorphological characteristics such as shape, size, area of a river catchment, sub-catchment, slope and topography, drainage network, rural/urban area and coastal area (Fernandez, Mourato, Moreira, et al., 2016; Hajar Nasiri et al., 2016). Atkins et al. (1998) suggested a composite vulnerability index for devel-
oping/island countries. They computed the integrated vulnerability index for 110 developing countries. The results indicated that small countries are more likely to be vulnerable as com- pared to large countries (Fernandez, Mourato, Moreira, et al., 2016; Karmaoui et al., 2016). Monika Blistanova et al. (2016) assessed the flood vulnerability based on different criteria for the Bodva river basin in the eastern part of Slovakia. They used hydrological factors, such as discharge and inundation depth of the basin along with the geomorphological properties of the basin, like slope and soil type, etc. All these indicators are analyzed and incorporated in GIS to classify the study area in four classes – acceptable, moderate, undesirable, and un- acceptable vulnerability zone (Huang et al., 2005; Sadeghi-Pouya et al., 2017). Birhanua et al. (2016) evaluated the vulnerability of Addis Ababa due to rapid urbanization and climate change. They used the SWAT model to obtain the peak discharge and incorporated the peak discharge as one of the indicators. The future rainfall was predicted by using the General Circulation Models (GCM), and land cover data was generated from the Landsat images. The results showed that there is a considerable increase in discharge due to climate change, which eventually increases the vulnerability (Lee et al., 2013). Kaspersen et al. (2017) elabo- rated the multidimensional aspects of flood vulnerability, considering social, economic, and hydrological aspects. Their analysis was based on an integrated approach for all the factors of flood vulnerability, known as the Danish Integrated Assessment System (DIAS). This DIAS is capable of evaluation of risk due to flooding from severe precipitation, and the model is applied in the city of Odense, Denmark (Rimba et al., 2017).
Study on Flood vulnerability index for Brunei Darussalam
Ndah et al. (2017) proposed a theoretical aspect of vulnerability assessment in Brunei Darussalam based on the Pressure and Release (PAR) model. They found that Hazard-risk assessment for the country is crucial due to the topographic condition and also due to the im- pact of climate change. They also reported the absence of a vulnerability mapping system in the country (Banyouko et al., 2017; Ndah et al., 2016). The report published by disaster man- agement agency, reveals that floods remain the most prominent and economic loss in Brunei Darussalam, with an annual loss of about USD 37.31 million (Profile et al., n.d.). An official report based on disaster mitigation provides information on the general causes and effects of floods. It also explains the flood mitigation measures that are in place in Brunei Darussalam (Officials & Societies, 2015). Apart from these reports, there is hardly any study that has been carried out for the assessment of vulnerability in Brunei Darussalam. The growth of eco- nomic activities resulting from Methanol industry, Fertilizer plant in Sungai Liang and the Petrochemical industry in Pulau Muara Besar and potential growth for agricultural activities (Shams et al., 2015) requires an Integrated Water Resources Management (IWRM) approach (Shams and Nasrin, 2019) with development of flood vulnerability index for Brunei Darus- salam. The present study emphasized on estimating the integrated flood vulnerability index of Brunei Darussalam, considering social, economic, environmental, and hydrological fac- tors together. The limitation with the present study is the unavailability of data at the mukim (village) level. Therefore, this study focuses on developing an integrated flood vulnerability index at the district level.
The review of the literature shows that the assessment and evaluation of flood vulnerabil- ity with an integrated approach have not been carried out in many countries in the world, including the southeast ASEAN country. The vulnerability describes the extent to which a population, human settlement, community/society is exposed to hazards like flooding, land- slides, earthquake, etc. The coastal flood and flash floods are very common phenomena in Brunei Darussalam due to intensive short-duration rainfall. Generally, the flash flood is oc- curring due to cloud bursting, which is very common in South Asia such as Bangladesh, India, Sri Lanka, etc. However, in Brunei Darussalam, the flood is not only occurring due to
cloud bursting but also due to other factors such as backflow resulting from tidal surge. This has aggravated the situation further with obstructions in the drainage system. Since the vul- nerability is site-specific, it is especially important to note down the parameters that describe different components of vulnerability along with their measurement at the sub-basin level or basin level, national level, or regional level. It is also essential to know how to link them with hazard parameters for obtaining an integrated vulnerability assessment. Hence, all the factors of vulnerability, as discussed above, are further classified into three different categories: expo- sure, susceptibility, and resilience.
Exposure Index: (EI)
Exposer describes the condition of people, infrastructure, services, production places settled in hazard-prone or flood-prone areas (Feloni et al. 2020; Kumar and Bhattacharjya 2020). This can be due to the shift in climatic parameters or variation in climatic situations. For the present study, a total of twenty variables, including the hydrological factors, also called as indicators were taken into consideration to study the district-wise exposure to flood and their impacts. For generating the exposure index, we combined all the indicators related to floods and landslides.
Susceptibility Index (SI)
Susceptibility is defined as the elements present within the system that determine the chances of being harmed at the time of hazards (Khajehei et al., 2020; Pricope et al., 2019). For the present study, twenty-one variables, i.e., indicators, were taken into consideration to calculate the district-wise susceptibility to flooding. The indicators considered in this study are listed in Table 1, along with their relationship with the vulnerability.
Resilience Index (RI)
The capacity of a social system to counter and overcome any adverse event is defined as resilience (Ayala et al. 2020; Nasiri et al. 2019; Khalili et al., 2015). It includes the strength of the system to absorb impacts, coping with the event as well as post-event adaptive response. In general terms, it helps the system’s ability to rearrange, modify, and discover the hazard or any disaster. Resilience can also be understood as the coping capability of a system during flood and restoration ability after the flood. In the present study, thirteen indicators were tak- en to examine the district-wise resilience to flood and their impacts in terms of forest cover, communication penetration rate, awareness, and past experience, etc.
As vulnerability is a function of exposure (E), susceptibility (S) as well as resilience (R), an integrated approach has been applied to assemble all these factors into a single value (Kar- maoui et al., 2016; Kayulayula & Banda, 2015; Teng et al., 2017). The selection of indicators is the most critical task for generating a reliable vulnerability index. So, the selection of dif- ferent indicators is made based on past studies and expert judgment. The selected indicators amongst social factors (population density, elderly population, children population, literacy rate, disability, female-headed house, etc.), economic factors (unemployment, migration rate, electricity coverage, etc.), hydrological factors (rainfall pattern, distance from the riverside, flood frequency), environmental factors (land use, urbanization, forest cover), were taken into due consideration to accurately represent the vulnerability of the area.
Table 1: Indicators considered in this study, along with their relationship with vulnerability.
S.No
Indicators
Definition
How to affect the vulnerability
Indicator Sub-head
Source/ References
1
Inactivity Rate (%)
The proportion of the population that is not in the labour force
+
S
(Data-da- lam-penerbi- tan, n.d.)
2
Waste land of the total geographical area (%)
Total percentage of barren land of the total geo- graphical area
+
E
(Agency, 2015)
3
No of tourist visited (2010- 2018)
The tourist coming in the country and they don’t know the geographic condition of the visiting country
+
E
(Data-da- lam-penerbi- tan, n.d.)
4
Forest fire (total affected area, ha) up to 31/12/2018.
Forest fire results into burnt land/waste land unfit for any activities
+
E
(Morani, 2017)
5
Urbanized area of the total area (%)
More urbanized area means more runoff
+
E
(Ndah et al. 2016; Wagh- wala and Agnihotri, 2019)
6
No. of HEP(hydroelectric power), All types
If the hydropower plant is more that means more dam for water storage with high capacity
+
E
(Profile et al., n.d.)
7
Outward migration, share of the state population (%)
If more population is going outside the country, in case of disaster very less person can help others
+
E
(Data-da- lam-penerbi- tan, n.d.)
9
Area with altitude more than 3000 m (%)
More altitude, more chances of landslide
+
E
(Data-da- lam-penerbi- tan, n.d.)
10
Landslide zone area of the total area (%)
More landslide area, more affected at the time of disaster
+
E
(Data-da- lam-penerbi- tan, n.d.)
11
Unemployment (%)
Unemployment leads to peoples crowded at a single place for needs during any natural disasters and so recovery time is very slow in case of disaster
+
E
(Data-da- lam-penerbi- tan, n.d.)
12
Cultural heritage
No. of historic buildings, the museum in the state, at the time flood highly chance to get affected
+
E
(Morani, 2017)
13
Population close to the coastline
Percentage of the population living near to coast and mostly affected at time costal fl od
+
E
(Morani, 2017)
14
Growth of population in the last 10 years near the coastline (%)
If more growth (%) then more population density near cost line
+
E
(Data-da- lam-penerbi- tan, n.d.)
15
Low cost building (%)
Low cost buildings have higher chances to collapse at the time of disaster
+
E
(Data-da- lam-penerbi- tan, n.d.)
16
Population density
More population in an area, very tough to exca- vate the place at the time of disaster
+
S
(Data-da- lam-penerbi- tan, n.d.)
17
Disabled people
They are not able to move at a safe place at the time of disaster by themselves
+
S
(Data-da- lam-penerbi- tan, n.d.)
18
Elderly population
They are not able to keep themselves at a safe place at the time of disaster
+
S
(Data-da- lam-penerbi- tan, n.d.)
19
Children under 15
They are not able to move at a safe place at the time of disaster by themselves
+
S
(Data-da- lam-penerbi- tan, n.d.)
20
Agriculture workers
Generally, they are dependent on agriculture and mostly economic weak and highly targeted at the time of the flood
+
S
(Data-da- lam-penerbi- tan, n.d.)
21
Literacy rate
If the people are more literate, they can take pre- ventive measures during and after a disaster
-
S
(Data-da- lam-penerbi- tan, n.d.)
22
Large Household size
Large household size means living rooms more than two rooms and having more than one floor to accommodate more people and in case of failure more people will be affected
+
S
(Data-da- lam-penerbi- tan, n.d.)
23
Number of houses with poor material
The houses with poor building material are subjected to collapse/failure easily at the time of disaster
+
S
(Data-da- lam-penerbi- tan, n.d.)
24
Poverty Rate
Higher the poverty rate means more economical weak people and greatly affected during and after the flood
+
S
(Data-da- lam-penerbi- tan n.d.; Solin et al. 2019)
25
Decadal growth rate
More growth rate, more peoples are living at a place
+
(Assessment
& Issues, n.d.)
26
Female Population
Females are taking care of other family members and the time of disaster they firstly prevent other members of the house and less attention towards own safety
+
S
(Data-da- lam-penerbi- tan, n.d.)
27
Total no of the river in the state
More river means more chances of flood at the time of high rainfall
+
S
(Data-da- lam-penerbi- tan, n.d.)
28
Total no of industries unit in the state
If industrial units are more in a place that more peoples are living there and will be affected more at the time of disaster
+
S
(Data-da- lam-penerbi- tan, n.d.)
29
Human development index
More HDI means peoples are economically sound and reduces the impact of disaster
-
S
(Data-da- lam-penerbi- tan, n.d.)
30
% of Forest cover of total geographical area(ha)
More forest area can reduce the runoff and soil erosion
-
R
(Data-da- lam-penerbi- tan, n.d.)
31
Structural measure for flood protection
If the transportation facility is well, they can be used at the time of evacuation in case of disaster
-
R
(Ndah et al., 2016)
32
The total length of ap- proaching road linked with major district road(km)
If the transportation facility is well, they can be used at the time of evacuation in case of disaster
-
R
(Department of Statistics Malaysia, 2017)
33
Communication penetra- tion rate (%)
More communication facilities can spread the emergency condition amongst the people at the time of emergency
-
R
(Data-da- lam-penerbi- tan, n.d.)
34
The area having electricity (%)
If electricity is available, in case of emergency, the evacuation process can be smooth
-
R
(Data-da- lam-penerbi- tan, n.d.)
35
Village connected with pucca roads (%)
If the transportation facility is well, they can be used at the time of evacuation in case of disaster
-
R
(Data-da- lam-penerbi- tan, n.d.)
36
No. of transport vehicles (registered vehicle of all types/1000 km2)
If the transportation facility is well, they can be used at the time of evacuation in case of disaster
-
R
(Data-da- lam-penerbi- tan, n.d.)
37
No. of hospital / 0.1 million population
The hospital can be used in case of disaster to treat the people effectively
-
R
(Data-da- lam-penerbi- tan, n.d.)
38
No. of flood forecasting
/ warning system/ Flood hazard maps
The warning system can alert the people about coming hazard
-
R
(Data-da- lam-pener- bitan n.d.; Henriksen et al., 2018)
39
Awareness about Hazard
If the group of peoples knows about the hazard, they can prepare themselves in case of emergency
-
R
(Nottingham, 2014), SUR- VEY*
40
Past Experience about Hazard
If the peoples have experience about the hazard, in future they can tolerate and take preventive measures in case of emergency
-
R
(Tan et al., 2017), SUR- VEY*
41
The total length of canaliza- tion in the different part of the state
They can be used to move the extra water in case of flooding
-
R
(Assessment and Issues n.d.)
42
People having flood insur- ance (%)
The insurance company can fulfill the loss in case of flood
-
R
(Mahidin, 2017)
43
Open space land (%)
Can be used as grouping center or shelter at the time of hazard
-
R
(Mahidin, 2017)
44
Average Proximity to the river of different districts in a state (m)
If a place is near to river bank the place is highly affected in case of flood
+
HE
(Abdullah, 2013), Google earth
45
Average rainfall(mm) in Monsoon season in last 25 years
More rainfall can cause flood events frequently
+
HE
(Banyouko et al., 2017; Ratnayake, 2018)
46
Flood frequency in a flash flood (≥ 250 cumecs)
If the frequency is more than flood can come at very less time interval
+
HE
(Morani, 2017; Profile et al., n.d.)
47
Maximum rainfall (mm/ day)
More rainfall can cause flood events frequently
+
HE
(Morani, 2017; Profile et al., n.d.)
48
Avg. heavy rainfall days, (Rainfall is > 170mm)
More rainfall can cause flood events frequently
+
HE
(Morani, 2017; Profile et al., n.d.)
50
Coastline length
If the costal length is more, there is a high proba- bility to come flood near coastal areas
+
HE
(Morani, 2017; Profile et al., n.d.)
51
No. of cyclone in the last 15 years
More chances that the same disaster will happen again
+
HE
(Morani, 2017; Profile et al., n.d.)
52
Flood duration
If the duration of flood is more, the destruction due to this is more
+
HE
(Morani, 2017; Profile et al., n.d.)
(+ = higher %, higher vulnerability, - = higher %, lower vulnerability), (E= Exposure, S= Susceptibility, R= Resilience, HE = Exposure under hydrological factor)
(*Survey = a total of 10 families, consist of around 70 peoples in each district of Brunei)
1.2 Data collection approach for the survey
In the vulnerability assessment, a probability proportional to respective size (PPRS), as described by the (Alnaimat et al., 2017; Antwi et al., 2015) was applied to determine the size of sample in different district of Brunei.
Case study
Brunei Darussalam is located on the northwest coast of the island of Borneo in South East Asia between latitude 4°30’N and longitude 114°04’E. It has a total land area of 5,765 km2 and a coastline of 168 km bounded by the South China Sea on the north and the East Malaysian states of Sarawak and Sabah on the east and west, respectively. Brunei Darussalam being a tropical country, very rich in biodiversity and well known for its pristine rain forests, has its unique importance in the region, particularly in relation to eco-tourism. It has some historical places such as water villages (Kampong Ayer) located on Brunei River and Istana Nurul Iman Palace, the palace of the light of faith, which attract not only local visitors but also foreigners (Tiquio et al., 2017). Water villages have a history of more than one thousand years. Throughout the year, the average temperature can range from 28°C (82°F) to 32° (89°F) during the day. The population of Brunei in 2014 was 411,900, with an annual growth rate of 1.27%. Brunei Darussalam has an equatorial climate influenced by the monsoon systems known as northeast monsoon and southwest monsoon. The country generally experiences wet, humid and hot conditions throughout the year, with an average annual rainfall of 3,000 mm. Brunei Darussalam is experiencing a rapid change in climatic conditions, particularly in terms of temperature and the amount of rainfall received annually. The field survey revealed that the elders often complained about the rising temperature as compared to the temper- ature when they were young (Shams et al., 2015). This has been further validated by the observed climate change trends in Brunei Darussalam, which include an increase in the av-
erage temperature of 0.031°C and rainfall of 26.16 mm annually (Hassan et al., 2016). Brunei Darussalam is expected to experience more warming and less frequent precipitation events but with a possibility of intensified and drastically high rainfalls in the future (Hassan et al., 2017). The high-intensive rainfall will cause flash flood inundating low lying and coastal ar- eas. The study area, along with its four districts, is shown in Figure 2, and basic information like area of different districts, the river basin etc. are shown in Figure 3.
Fig.2. Location of Brunei Darussalm
a.
b.
c.
Fig. 3(a-c): Brunei-districts with their area and a major river
There are four major river basins in Brunei Darussalam. The length and their catchment area are shown in Fig. 3(b-c). These river basins are flowing directly to the South China Sea through their main channels. Out of four, two of the river basins are considered prone to regular flooding, especially the Tutong River basin (Assessment & Issues, n.d.; Ghani et al., 2012; Ndah et al., 2016; Pengairan & Saliran, 1987). Fig. 4 shows some photographs taken at the time of the flood in different parts of Brunei Darussalam.
Figure 4. The flooded area at Tutong and Brunei-Muara in Brunei Darussalam during the flood
Methods
The flow diagram indicating all the steps towards the development of an effective flood vulnerability index is shown in Fig.5. The different indicators of vulnerability relevant to the study area are selected, and the value of the indicator is normalized to prepare the exposure, susceptibility, and resilience index. All indexes are incorporated in ArcGIS10.4 to get the index map. As seen in literature, various methods are available to generate the vulnerabili- ty index value such as, based on pixel value using image analysis (Fernandez, Mourato, & Moreira, 2016; Frigerio et al., 2018), using Artificial Neural Network (ANN) and fuzzy logic (Antwi et al. 2015; Kumar et al. 2012; Lee et al. 2013; Prasad and Narayanan 2016; Science 2018; Cai et al. 2019) and quantitative method as used in the present study (Adger, 1998; Gebreyes & Theodory, 2018; Kissi et al., 2015; Wijaya & Hong, 2018).
Figure 5. Flow diagram for integrated flood vulnerability index.
Two types of operative association are possible between vulnerability and their indicators. Firstly, the vulnerability increases with the increase (or decrease) in the value of the indicator or vice versa. In this study, two formulas are used to normalize indicators, depending on their operative association with vulnerability. If the vulnerability increases with the factors, the normalization is done using the following equation.
X
ij
ij
MinX
Yij
ij
MaxX
ij
MinX
(1)
On the other hand, if the vulnerability decreases with the factors, the normalized score is calculated as:
ij
MaxX
ij
X
Yij
ij
MaxX
ij
MinX
(2)
Where,
is the value of 
th indicator 
in the 
th district 
and 
is the matrix corresponding to the normalized score. It has been already mentioned that the estimated value of 
lies between 0 and 1. The value 1 is corresponding to that district with maximum value, and 0 is corresponding to the district with the minimum value.After calculating the normalized scores, the composite index is formed by giving an un- equal weight to all indicators. In most of the previous work, several methods were used to give weight to indicators. These methods are either providing equal weights, i.e., a simple av- erage of the scores provided by Patnaik and Narain Methods (Rimba et al., 2017) or unequal weights, i.e., by expert judgment as used by Iyengar and Sudarshan (Kissi et al. 2015; Godfrey et al. 2015). The weight can also be provided by multivariate statistical techniques, i.e., by the principal components and cluster analysis method (Bahinipati, 1999; Balica et al., 2017; Bhadra et al., 2009; Chakraborty & Joshi, 2017; Marques et al., 2015).
In this study, we used the Iyengar and Sudarshan method (Adger, 1998; Kissi et al., 2015) to give weight to all indicators contributing to vulnerability. Iyengar and Sudarshan (1982) (Fernandez, Mourato, Moreira, et al., 2016; Kha et al., 2008) obtained an equal index from multidimensional data, and the index was used to rank the districts/states in terms of their financial enforcement. The proposed method is statistically reliable and equally satisfactory for the development of the proposed index. In Iyengar and Sudarshan method, the value of the indicators is hypothesized to change inversely with the variance. The weight of each factor
is determined by:
Wj
c
ij
VarX
12
(3)
Where c is a normalizing constant i.e.
c
1
ij
VarX
1
12
(4)
The composite indicator for flood vulnerability factors (exposure, susceptibility, and resil- ience) for the
th state was obtained as:Yi WjYij
(5)
Where Yi is the composite indicator of
th state, Wj is the weight for each indicator lies between 0 and 1, ∑Wj = 1, and Yij is the normalized scores of indicators.To ensure that the indices calculated for each vulnerability factor can be compared, the sum for each factor of exposure, susceptibility, and resilience are divided by their respective number of indicators that describe each vulnerability factor. The composite vulnerability in- dex for the exposure factor is given as:
W Y
Cl ex
.
j ij
n
(6)
Where
is the composite vulnerability index of exposure factor, Wj is the weight of an indicator, Yij is the normalized value of exposure indicator, n is the number of indicators. Similarly, we calculate susceptibility and resilience factors, i.e., 
, and 
. Finally, the integrated flood vulnerability index can be given as
(Feloni et al., 2020; Kumar & Kumar Bhattacharjya,2020a; Line, 1999; Hajar Nasiri et al., 2016) (7)
Where,
is the exposure index, is the susceptibility index, 
is the exposure index for hydrological factors and is the resilience index.Results and discussion
Exposure index:
As explained earlier, that exposer defines the condition of people, infrastructure, accom- modations, production capacities settled in hazard-prone or flood-prone areas. For the pres- ent study, a total of twenty variables (out of which 7 indicators are as hydrological exposure), also called indicators, were taken to examine the state-wise exposure to flood and their im- pacts. For generating the exposure index, we combined all the indicators related to floods and landslides. We have used the historical data obtained from different agencies (Table 1) to determine the weights of the individual exposure indices. Finally, we created a common exposure index by adding different exposure indices as per Iyengar and Sudarsan method (Coninx & Bachus, 2007; Villordon, 2015). Some indicators have a positive relationship with vulnerability, i.e., the vulnerability increases with the increase in the value of the indicators. On the other hand, some indicators have a negative association with vulnerability. The graph- ical representation of all the indicators considered under the exposer index is presented in Fig. 6 and Fig. 7.
Figure 6. Different indicators under exposure index
Along with these indicators, seven indicators under hydrological factors are also chosen to explore the exposure index, as shown in Fig. 8. The rainfall data is available only for the Bru- nei-Muara district and not for the other districts. For estimation of average monthly rainfall, we used Inverse Distance Weighting (IDW) method (Supharatid, 2015). Since this method can be used to estimate unknown spatial data from known data of sites that are adjacent to an unknown location, we considered a few neighboring areas of Malaysia and interpolated the average rainfall. The IDW method estimates the unknown cell values in the output surface by averaging the values of all input sample data points that lie within the specified search radius (Nyatuame et al., 2014). Daily, monthly or yearly rainfall data for a region with coordinates (Latitude and Longitudes) are the input of the model. The method involves the process of assigning values to unknown points by using values from a set of known locations. The esti- mated average rainfall pattern of different districts of Brunei Darussalam from 1991 to 2016 has been presented in Fig. 7 (a-d).
|
|
(a) | (b) |
|
|
(c) | (d) |
Fig. 7 (a-d): The monthly average rainfall pattern of a. Brunei-Muara
b. Belait c. Tutong d. Temburong
As per the graph shown in the Fig.7a-d, we can say that the variation of average rainfall is from 600-800 mm in the month of Jan, Feb, Nov, and Dec for all districts except Belait, where the variation is up to 1100 mm. Also, as per the literature review, the heavy rainfall days are considered as the day when rainfall is more than 170 mm(Assessment & Issues, n.d.; Banyou- ko et al., 2017; Ndah et al., 2016).
Figure 8. Hydrological factors under the exposure index.
|
|
a. | b. |
Figure 9. (a-b): Showing the exposure map of Brunei Darussalam
The analysis of the data (Fig. 8) shows that Brunei-Maura has more low-cost buildings, level of urbanization, coastline length, and more population living close to the coastal area in comparison with other districts. In Kuala Belait, the average rainfall and maximum rainfall are high in comparison to other districts of the country. The exposure map of different states of Brunei Darussalm is shown in Fig. 9(a-b). All the four districts of Brunei Darussalm have low exposure (5-10%) towards the vulnerability due to less rate of unemployment, outward migration, and landslide zonation. In the case of hydrological exposure, the Tutong district has high exposure, followed by Temburong, which has moderate hydrological exposure. In the Tutong district, the proximity to the riverside is very less and also, the district is facing the maximum number of rainfall days, along with maximum flood durations. The level of classification of vulnerability components is presented in Table 2 (Chakraborty & Joshi, 2017; Huang et al., 2005; Karmaoui et al., 2016; Kissi et al., 2015).
Table 2. Vulnerability level classification
Range of factors (in %) | Level of vulnerability or vulnerability components |
<1 | No |
1-5 | Less or low |
6-10 | Moderate |
11-15 | High |
>15 | Extreme or severe |
Susceptibility index:
For the present study, twenty-one variables (indicators) were taken into consideration to calculate the district wise susceptibility to flooding. The indicators considered in this study are listed in Table 1, along with their relationship with the susceptibility index. The graphical representation of all these factors is shown in Fig. 10 (a-c).
a.
b.
c.
Figure 10. (a-c): The different indicators of the Susceptibility index for Brunei districts.
Brunei-Muara has the highest population density as well as the most female population. Even then, none of the four districts of Brunei Darussalam have high susceptibility towards vulnerability. The main region behind this is that the country has a very good household income, high literacy rate, low annual growth rate, and high human development index, es- pecially in the Brunei-Muara. The susceptibility index is calculated based on these indicators and shown in Fig. 11. The figure shows no susceptibility in Kuala Belait and less susceptibility in the other three districts of the country.
Figure 11. Showing the susceptibility map of Brunei.
Resilience index
As explained earlier, the capacity of a social system to counter and overcome any adverse event is called resilience. In the present study, fourteen indicators were taken to examine the district-wise resilience to flood and their impacts in terms of forest cover, communication penetration rate, awareness, and past experience, etc. Fig. 12 (a-b) shows the graphical rep- resentation of different resilience factors used in the analysis.
a.
b.
Figure 12. (a-b): The different indicators of resilience index for Brunei.
The resilience or resistive factor towards vulnerability like length of road connecting dis- trict headquarters, transport vehicle availability, length of canals, and health facilities centers are best available in the Brunei-Muara. Even then, the Kuala Belait has most resilience to- wards the vulnerability, followed by the Tutong district since the Kuala Belait has maximum forest cover and canalization in comparison with others. In Tutong, the maximum number of the population has experience as well as knowledge about the flood and disaster.
Based on these indicators, the resilience index is calculated and shown in Fig. 13. A com- parative bar diagram showing the different indicators of vulnerability in different districts of Brunei Darussalm is presented in Fig. 14.
Figure 13. Showing the resilience map of Brunei.
Figure 14. Showing all indexes of the vulnerability of different districts
of Brunei Darussalam. The impact of different indicators over vulnerability indices: Correlation analysis
The correlation analysis of different indicators with their corresponding indices i.e. be- tween exposure index and the exposure indicators, between susceptibility index and suscep- tibility indicators and so on, are shown in table 3, 4, and 5, respectively. In case of exposure, the factors like proximity of district to the river, annual growth rate, percentage waste land, and the population distribution range are major factors which are contributing towards the vulnerability. In the case of susceptibility female populations, old age population, and pop- ulation density make a location more vulnerable. The factors like communication facilities
available, connectivity to district headquarters, availability of flood forecasting system, and the number of hospitals, are major resilience factors which reduce the vulnerability of an area.
Table 3. Relation between different exposure factors and exposure index and the Pearson correlation coefficient (r)
Factors | Pearson correla- tion coefficient ( r) |
CI_Exposure | 1.00 |
% of waste land of total geographical area | 0.47 |
No. of tourist visited | 0.36 |
Forest fire (Total affected area)(ha) | 0.41 |
Urbanized area(%) | 0.41 |
Unemployment(%) | 0.78 |
Proximity to ocean (m) | 0.71 |
Avg. Rainfall of last 50 years in JJA (mm/year) | 0.66 |
Flood frequency(≥ 700 cumec) | 0.46 |
Table 4. Relation between different Susceptibility factors and susceptibility index and the Pearson correlation coefficient (r)
Factors | Pearson correla- tion coefficient ( r) |
Cl_susceptlibity | 1 |
Population density (Person/Km2) | 0.51 |
Disabled people (%) | 0.17 |
Elderly (%) | 0.39 |
Children under 15(%) | 0.03 |
Illiteracy rate (%) | 0.34 |
Household size (%) | 0.25 |
Poverty Rate (%) | 0.14 |
Decadal growth rate (%) | 0.49 |
Female Population (%) | 0.36 |
Table 5. Relation between different Resilience factors and the resilience index and the Pearson correlation coefficient, r.
Factors | Pearson correlation coefficient ( r) |
CI_RESILIENCE | 1 |
% Of forest cover (with total GA) | 0.17 |
Road network (km) | 0.74 |
Communication penetration rate (%) | 0.81 |
Area having electricity(%) | 0.11 |
No of hospital / lakh population | 0.49 |
Awareness about hazard | 0.13 |
Past Experience about hazard | 0.27 |
The integrated flood vulnerability index for Brunei Darussalam
After obtaining all the index values of the vulnerability, the integrated flood vulnerabil- ity index has been prepared by integrating all index values into Eq. 7, and the final map is prepared by using ArcGIS software. The Tutong district has the highest vulnerability, with
7.5 %, followed by Temburong with 4.3 %. As seen in Fig. 14 and 15, Belait has the lowest vulnerability index, with 0.4 %. Tutong has an inferior communication network in compar- ison with other districts and also the hospital units, total length road connections, HDI is less as well as the number of the disabled and divorcee person is high in Tutong. Along with this, Tutong is also hydrologically unstable in comparison with the other districts of Brunei Darussalam. Since Brunei Darussalm has a high literacy rate, a very low unemployment rate, 100 % electricity, less populated, and supported by good household income, so no district in the country is under high or extremely vulnerable categories. Only the Tutong district has a moderate vulnerability index.
Figure 15. The integrated flood vulnerability index of different districts of Brunei.
5. Conclusion
The present study determined the district wise integrated flood vulnerability index for Brunei Darussalam. The important aspect of this study is to assign vulnerability rank to each district according to its vulnerability level relevant to the flood. An integrated approach was adopted where vulnerability is the function of exposure, susceptibility, and resilience. Sev- eral indicators have been selected to have an accurate representation of the vulnerability. Since each indicator has a different measurement unit, a normalization procedure was used to convert them into a single value of effective comparison. A significant problem concerning disaster assessment in Brunei Darussalm is the absence of documentation of relatively small chronic hazard events, especially annual floods, flash floods, and landslides, to global disaster databases. Due to a lack of datasets related to these events, it is quite challenging to study the nature and effectiveness of disaster in the country. Perhaps due to the lack of having a com-
prehensive dataset on related disasters, no extensive study was performed for the vulnerabili- ty assessment of Brunei Darussalam. Besides, the hydrological data such as runoff, discharge, depth of groundwater table, and district-wise rainfall data due to lack of rainfall stations in each district is not available in Brunei Darussalam. The present study, based on the data availability and few assumptions such as interpolation of rainfall, is a pioneer effort to estab- lish an integrated flood vulnerability index for Brunei Darussalam. The proposed integrated vulnerability assessment may work as a potential guideline for the center of flood-related policy and management, such as the National Disaster and Management Centre (NDMC) in Brunei Darussalam. The outcome of the present study would be a significant addition to better preparation and perception of disaster risk in Brunei Darussalam. The present study may be helpful to the governmental organization to plan for different mitigation measures to reduce vulnerability.
Acknowledgments: This research was supported by funding (IMRC/AISTD- F/R&D/P-1/2017) through the ASEAN-DST Collaborative Programmed funded by the Min- istry of Science and Technology, Government of India.
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DOI: https://doi.org/10.18485/ijdrm.2020.2.2.5
UDC: 005.334:627.51
005.591.6
Review Article
INNOVATIVE SOLUTIONS FOR FLOOD RISK MANAGEMENT
Vladimir M. Cvetković, 1,2,3,*, Jovana Martinović2,3
1 Faculty of Security Studies, University of Belgrade, Gospodara Vučića 50, 11040 Belgrade, Serbia
2 International Institute for Disaster Research, Dimitrija Tucovića 121, 11056 Belgrade, Serbia;
* Correspondence: vmc@fb.bg.ac.rs; vladimirkpa@gmail.com.
Received: 5 December 2020; Accepted: 25 December 2020; Published: 1 January 2021
Abstract: Starting from the importance of innovative solutions for improving the needs of different practitioners as flood risk managers, the purpose of this re- view was to describe and analyze, evaluates, and prioritizes the various available different innovative solutions that have sufficient potential to be useful and used by practitioners. A systematic review of the literature was conducted using the DAREnet knowledge base (an integral feature of the DAREnet online communi- ty platform) which identified critical challenges for flood management and the relevant field or source of innovation, as well as the current scientific literature in the field of disaster studies. A fourth stage selection procedure identified can- didate original or review papers and evaluated the degree to which papers met predetermined requirements for inclusion extracted from prior systematic re- views. Included in the study were over 100 studies that met the requirements for predetermined inclusion. The findings of this review showed that there is a huge untapped potential for innovative solutions in the field of prevention, prepared- ness, civil protection, communication, cooperation, etc. The findings of this re- view contribute to a growing body of knowledge regarding innovative solutions for flood risk management useful for practitioners.
Keywords: disasters, floods, risk management, innovative solutions, review, DAREnet.
Introduction
In disaster studies, there are different definitions of disaster risk management: a) disci- pline and profession that applies science, technology, planning and management to control extreme events that can injure or kill large numbers of people, cause great damage to prop- erty and disrupt life in society (Phillips & Jenkins, 2010, p. 26); b) risk management so that societies can live with natural and technical hazards and control the disasters they cause (Waugh, 2001, p. 98); c) discipline dealing with risk and risk avoidance (Haddow, Bullock, & Coppola, 2007, p. 76); g) state of responsibility and capacity for management of all types of disasters, through coordination of actions of a number of entities and protection and rescue forces (Flint & Brennan, 2006, p. 2). Certainly, it should be noted that there is a difference between traditional and modern disaster management and it is reflected in the modes of operation, organizational structure, character of information, goals and criteria of manage- ment (McLoughlin, 1985, p. 53). Dragićević et al. (2009) explicitly emphasize the modern approach to managing the risks of natural disasters, implying three main phases of analysis and planning: risk analysis (risk analysis) - identification of possible natural disasters that may occur in a particular area, as well as the consequences that may cause; risk assessment
- selection and selection of the most significant, priority risk in a certain area, based on a comparative analysis of all potential risks; and risk management - the final phase of a risk study in a particular territory.
Integrated management of natural disasters assumes that people can recognize, identify and assess many risks of natural disasters. It is a systematic approach that includes risk assess- ment, prevention, mitigation and preparation for natural disasters (Zhang, Okada, & Tatano, 2006). According to the Law on Disaster Risk Reduction (Official Gazette of the Republic of Serbia, 87/18), risk management is a set of measures and activities implemented with the aim of implementing disaster risk reduction policy, as well as administrative-operational and organizational skills and capacities for their implementation. Thus, it is a policy that is estab- lished and conducted to prevent new or reduce existing risks by implementing integrated and inclusive economic, social, educational, normative, health, cultural, technological, political and institutional measures, which strengthen the resilience and preparedness of the commu- nity. In recent decades, the focus has shifted from the concept of “disaster recovery and re- sponse” to the concept of “risk management and mitigation”. The change also relates to a shift from an approach that focuses primarily on hazard as a key causal factor and to reducing risk through the use of physical protection measures, to an approach that focuses on community vulnerability and ways to reduce that vulnerability by implementing a warnings (Cvetković, 2020). The three key phases in disaster risk management are: a) the pre-disaster phase (pre- ventive and proactive); b) disaster phase (reactive); and c) the disaster recovery phase. With- in the first phase, activities are undertaken aimed at reducing potential and material losses in the event of a natural disaster (Haque, 2005). Preparedness includes measures that enable authorities, communities and individuals to respond quickly to disasters in order to deal with them effectively (Brown, 1993). It involves designing sustainable disaster plans, developing warning systems, maintaining inventory and training emergency services (Edward, 2005). In contrast to preparedness, mitigation includes measures to reduce the impact of natural disasters in order to reduce the scale of future disasters. (Shneid, 2001). Thus, mitigation ac- tivities may relate to the disaster itself or to the elements exposed to the threat. Examples of mitigation measures are water management in drought-prone areas, relocating people away from areas prone to some types of natural disasters, and strengthening structures to reduce damage when a disaster strikes (Aleksandrina, Budiarti, Yu, Pasha, & Shaw, 2019; Chapman, 1999; Cvetković & Janković, 2020; Cvetkovic, 2019; Mano & Rapaport, 2019; Ocal, 2019; Perić & Cvetković, 2019; Vibhas, Adu, Ruiyi, Anwaar, & Rajib, 2019; Cvetković, 2020).
Methods
Aim
The purpose of this review was to describe and analyze, evaluates and prioritizes the var- ious available different innovative solutions that have sufficient potential to be useful, usable and used by practitioners. A systematic review of the literature was conducted using the
DAREnet knowledge base (https://cmt.sym.place/knowledge/group/152285/all) which iden- tified critical challenges for flood management and the relevant field or source of innovation, as well as the current scientific literature in the field of disaster studies.
Search strategy
To find appropriate research, a search of electronic databases was performed. DAREnet Knowledge Base, Web of science, SCOPUSS, google scholar, were the main source used for lit- erature searches. Darenet knowledge base is integral feature of the DAREnet online com- munity platform which identified critical challenges for flood management and the relevant field or source of innovation. It has a standards for describing, cross-referencing and cate- gorising the entries. Also, a vast range and types of potential innovations is structured and categorised: technical and non-technical, mature (on the market or high TRL) or emerging (low/medium TRL, requiring additional RTD), low cost or requiring major investments and third party support, limited or extensive training needs, etc (DAnube river region Resillience Exchange network, No 740750).
Inclusion and exclusion criteria
Articles were considered for review if the objective of the research was some kind of ino- vative solutions for flood risk management. Furthermore, articles were included for review if they met the following criteria: (1) peer-reviewed, (2) useful and used by practitioners and (3) related to these topics prevention, preparedness, civil protection, communication, cooperation, information, communication and cooperation, (4) related to subtopics as tech- nical equipment, tactical logistics, human factors/lessons-learned, standardisation, warning systems, flood risk maps, evacuation plans, supply and logistics and etc. that did not attempt to measure preparedness of nurses were excluded from review. Articles that included some unusable solution, insufficiently tested, scientifically unproven were excluded from review.
Search outcomes
The initial search resulted in 458 papers and this number diminished to 158 after a review of titles and abstracts found that 300 articles had no relevance to the objectives of the review. A full text reading of the remaining articles resulted in 100 studies that were considered ap- propriate for review.
Results and discussion
Results are divides in fourth parth: innovative solutions for flood prevention; innovative solutions for flood preparedness and mitigation; innovative solutions for flood response; and innovative solutions for flood recovery.
Innovative solutions for flood prevention/mitigation
Literature review identified a large number of innovative solutions for flood prevention (Wang et al., 2017; Priyadarshinee et al., 2015; Gevorkov et al. 2019; Petit-Boix et al. 2017; Kim & Lee, 2015). For example, Eijgenraam et al., 2017 proposed a dike height optimiza- tion model to determine economically efficient flood protection standards. Then, Klerk et
al. (2020) described a greedy search algorithm that can find (near) optimal combinations of reinforcement measures for dike segments. On the other side, Berkhahn et al. (2019) sug- gested a design strategy to maximize the stabilization of the dike structure. In order to make this computationally feasible, they used a greedy search algorithm, for which they derived heuristic rules that could be used for designing dike strengthening projects in flood pro- tection systems with a wide number of independent components. Then, Vuik et al. (2019) showed that marsh elevation change due to sediment accretion mitigates the increase in wave height, thereby elongating the lifetime of a dike-foreshore system. Liu et al. (2020) suggested a flood hazard resilience assessment model based on an updated random forest model used to address the issue of fuzziness in resilience assessments. The model uses the whale optimi- zation algorithm (WOA) to evaluate key parameters in the conventional random forest re- gression (RFR) model and incorporates the assessment index set by the Driving Forces-Pres- sure-State-Impact-Response (DPSIR) model to output the resilience index of the study area. Adeniyi et al. (2019) produced a maturity model for assessing flood resilience capability ma- turity of businesses, and technically provides an outline of steps for improving flood resil- ience of business premises.
On the other side, Petit-Boix et al. (2017), proposed use of green and grey stormwater management infrastructures, such as the filter, swale and infiltration trench (FST), to prevent flooding events. Estrela et al. (2017) discussed how Emergency Response (ER) structures can be modeled as a Cyber-Physical System (CPS) with control units, sensors, and actuators for environmental observing. Regarding to that, authors proposed the ways that salvaged electronic components can assist far away and economically deficient locations. In the field of information technologies that can be used in flood prevention, Petit-Boix -Suchoń’ (2017) showed the possibilities of using advanced methods of GPR signal processing and its analysis with the help of signal attributes for detecting zones threatening the stability of the structure of flood embankments. Author propose quick detection of potential weak zones of the em- bankments, and consequently give means to ameliorate them, which may prevent damage to the embankments during rise in the level of river water. On the other side, Priyadarshinee et al. (2015) were employing Wireless Sensor Networking (WSN) technology for predicting & preventing the flooding condition. WSN is preferred due to its cost effectiveness, faster trans- fer of data & accurate computation of required parameter for flood prediction & prevention. Another beauty of the WSN technology is that we could compute the required parameter by considering very few number of environmental parameter. Saravi et al. (2019) used the application of the state-of-the-art techniques i.e., Machin Learning (ML) approaches on big data, collected from previous flood events to learn from the past to extract patterns and infor- mation and understand flood behaviours in order to improve resilience, prevent damage, and save lives. The classification results can lead to better decision-making on what measures can be taken for prevention and preparedness and thus improve flood resilience. O’Donnell et al. (2018) evaluated the LAA (Learning and Action Alliance) framework as a catalyst for change that supports collaborative working and facilitates transition to more sustainable flood risk management.
In 2017, Wang et al. investigated the possibility of creating a kind of artificial flood-pre- vention stone using the alkali-activated process of Yellow River silt. The findings of their work revealed that the specimen made from the optimum proportion of the mix will fulfill the flood-prevention stone criterion. The results on the compressive strength of the artificial flood-prevention stone of alkali dose, slag content and curing age were analyzed. In order to stop unintended faults of the electric drives or the pumps themselves, Gevorkov et al. (2019) suggest a way to build a smart control device for fault diagnosis of pumping stations. Suryaman (2020), proposed flood control model using a pump house system interconnec-
tion to minimize water logging, accelerate the water flow process and maximize already cur- rent reservoir activity and work. Via one-dimensional numerical analysis, Kim & Lee (2015) demonstrated the efficacy and efficiencies of flood prevention measures and the purpose of this research is to help water management make effective decisions by using the XP-SWMM two-dimensional urban run off model in the flooded region and contrasting it with flood prevention measures. Örs (2018), studies the strategies and scenarios of green infrastructure applied to facilitate the convergence of the use of green infrastructures to reduce the danger of urban flooding and to promote new solutions for ecosystem services in policy and plan- ning principles, including the potential introduction of urban green developments. Niko- norov at al. (2016), based their work on analysis of flood events using GIS-environment and managerial solutions to prevent them. They developed the test models, which allow analyzing possible engineering solution with the aim of minimization of risks and consequences.
Wang et al. (2019) presented a new model for the forecast of urban flooding under heavy rainfall. The model divides an irregular metropolitan region into several grid cells with no spatial resolution constraint as long as DEM data of the same resolution are available. It is capable of representing regular inflow or outflow interactions between grid cells and of collecting the rapid generation of surface runoff in urban areas during heavy rainfall. The model also represents the usual features of urban environments, such as large impermeable surfaces and urban drainage networks, in order to predict urban flooding more realistically. From the other side, Petit-Boix et al. (2017) proposed an integrated eco-efficiency solution to flood prevention and preventative loss. Their aim was to assess the viability of post-disaster emergency actions carried out after a major catastrophe through an integrated hydrological, environmental and economic strategy. The Life Cycle Assessment (LCA) and Cost Assess- ment (LCC) were used to evaluate the eco-efficiency of these activities, and their net effect and payback were measured by combining avoided flood damage. Khalid and Ferreira (2020) presented a newly developed real-time total water flood guidance system that is fully auto- mated on the basis of the coupled wave model (ADCIRC + SWAN) and provides forecasting of the water level in the Chesapeake Bay for a lead time of 84 h twice a day on a web-based public interface. In addition, it has been shown that the bias adjustment scheme and the mul- ti-member ensemble forecast boost the overall flood forecast.
Integrated long-term memory (LSTM) and reduced order model (ROM) architectures were developed by Hu et al. in 2019. Furthermore, this combined LSTM-ROM is capable of reflecting the spatial-temporal propagation of floods, taking advantage of both ROM and LSTM. Wu et al. (2020) established an urban flood data warehouse with available structured and unstructured urban flood data. Based on this, a regression model to predict the depth of urban flooded areas was constructed with deep learning algorithm, named Gradient Boost- ing Decision Tree (GBDT). Insights into the factors for determining strategic goals for urban green space planning, in particular for flood protection and the co-leverage of flood adap- tation and mitigation steps were developed by Afriyanie et al., in 2020. They also showed how to re-frame urban green space design through socio-ecological sustainability in order to educate the decision-making phase in the implementation of inclusive urban ES. Fang et al. (2020) proposed a local space sequential long-term neural memory network (LSS-LSTM) for flood susceptibility prediction in Shangyou County, China.
Landholders should be allowed to use their land in a manner that increases its water reten- tion ability. However, questions of justice may occur when, based on the usage of other prop- erties, the landowner may gain or lose. Alvarez et al. (2019) sets out to study the feasibility of incorporating game theory in a cooperative game to tackle land use in a way that increases the water retention ability of landowners. They addressed the improvement of upstream wa- ter retention and centered on the function of forests as natural water retention features. Be-
sides that, Lourenço et al. (2020) explored a potential analytical method for community plan- ning and the creation of flood control options, using a multi-functional open space structure that integrates water dynamics into existing and future urban solutions. They also developed a series of recommendations to express local needs with environmental constraints, with the goal of helping to design urban flood protection alternatives, but at the same time increas- ing environmental value and retrofitting urban proximity. Sekuła et al., 2018 presented the possibilities of the ISMOP – IT Levee Monitoring System. This device is capable of gathering data from the reference and experimental control and measurement networks. The break- through is the use of a set of sensors to track changes in the levee body. It can be achieved by combining the outcomes of numerical simulations with the results of two classes of sensors installed: reference sensors and experimental sensors. Ward et al. (2020) suggested that it is necessary to understand interactions between these closely related phenomena in order to build better disaster risk mitigation (DRR) design initiatives and strategies. Examples have been shown: (a) how flood or drought DRR interventions can have (unintended) positive or negative impacts on the risk of the opposite danger; and (b) how flood or drought DRR meas- ures may have a negative effect on the opposite threat. In paper by Costache et al. 2020, new hybridisation of the FAHP, the Entropy Index (IoE), and the Vector Support Machine (SUM) have been proposed in order to forecast areas vulnerable to flooding. Moreno et al. (2020) attempted to develop and incorporate a model that helps forecast floods over the Magdale- na River by analyzing three artificial intelligence techniques (Artificial Neuronal Networks, Adaptive Neuro Fuzzy Inference Method, Support Vector Machine) and thus deciding which of these techniques are most successful in the case study.
The suggested mitigation control method is based on the prediction of hydrographs and the estimate of the amount of water to be collected. It contributes to an optimum peak flow Shah et al. (2017) introduced a new Innovative Decision Supportive Structure for Sustaina- bility Appraisal (SA) of flood mitigation schemes over the life cycle of the scheme, based on two major aspects: the project’s continuous flood mitigation and the economic growth of the floodplain. Li et al. (2020) suggested a multi-criteria GIS assessment framework to define target areas for green infrastructure sites, based on five criteria: 1) reduction of storm-water runoff; 2) protection of disadvantaged populations for social flooding; 3) protection of vul- nerable road infrastructure areas for floods; 4) protection of critical areas for floods and 5) environmental justice. By statistically evaluating open space performance for flood mitiga- tion purposes through a nationally representative sample of local jurisdictions, the Brody & Highfield (2013) study addressed this question. In their analysis of 2019, Dzulkarnain et al. demonstrated flood control in agriculture using a device dynamics approach. They used the information obtained from interviews with important government leaders. Du et al. (2019) indicated that the recently adopted Sponge City Plan considered concave green land (CGL) to be an important method to reduce pluvial floods. And, Phonphoton & Pharino (2019) established realistic ways to effect prevention and preparedness of MSWM facilities during floods. The Multi-Criteria Decision Analysis (MCDA) report uses a panel of responsible manufacturers and waste management and town planning experts to determine effective im- pact reduction alternatives. The research by Hu et al. (2019), measured the mitigating extent of urban floods by LIDs for the retrofit of urban areas at a viable level using a hydrological model. A number of storms of differing precipitation durations and intensity-duration-fre- quency curves have been used to test the hydrological output of LIDs. Phonphoton & Pharino (2019) established realistic ways to effect prevention and preparedness of MSWM facilities during floods. The Multi-Criteria Decision Analysis (MCDA) report uses a panel of responsi- ble manufacturers and waste management and town planning experts to determine effective impact reduction alternatives. Mei et al. (2018) applied an evaluation system focused on the Storm Water Management Model (SWMM) and Life Cycle Cost Analysis (LCCA) to conduct
integrated evaluations of the production of flood mitigation GIs to promote rigorous deci- sion-making on sponge city construction in urbanized watersheds. Haghighatafshar et al. (2018), coupled one-dimensional (1D) sewer and two-dimensional (2D) overland flow hy- drodynamic models were designed to test the flood control performance of the famed blue- green stormwater retrofit. In their 2018 report, Huang et al. developed a revolutionary sys- temic optimization model for megacity flood mitigation by integrating several Low Impact Construction (LID) instruments, taking into account the benefit-cost (B/C) analysis. This framework can be used to evaluate the effects of floods on the growth of megacity, to develop a technological methodology that allows an automated and efficient optimization process, to link up with the built-in Storm Water Management Model (SWMM) and to propose adaptive solutions using a combined layout design scheme. Besides that, Sadler et al. (2020) indicated that low-lying, low-relief coastal cities have seen increased flooding due to climate change. Also, they suggest the utility of model predictive control (MPC) of stormwater actuators to reduce flooding in a coastal urban setting made worse by sea level rise. Shah et al. (2017) introduced a new Innovative Decision Supportive Structure for Sustainability Appraisal (SA) of flood mitigation schemes over the life cycle of the scheme, based on two major aspects: the project’s continuous flood mitigation and the economic growth of the floodplain. Besides that, Hadid et al. (2019) proposed that one of the solutions to minimize the effects of the flooding would be the use of flood storage areas and the design of a management strategy to dispatch water volumes and reduce the peak flow.
The capacities of indigenous precipitation techniques (RWHT), which should be utilized as a viable flood mitigation solution, were examined by Tamagnone et al, in 2020. Their study analyzed the hydraulic performance in terms of the flow peak reduction (FPR) and the vol- ume reduction (VR) at the field and basin level of the most used micro-catchment RWHT in the sub Saharan regions. In order to replicate the extreme precipitation of Sahelian countries during rainy season, parameterised hyetographer were constructed. In their work, Cristiano et al. (2020) sought to define the potential retention capacity of the non-maintenance-cost spontaneous green roof of the CAM located at the entrance of the University of Cagliari (Italy) and to compare it to the C3 type of vegetation. The structure has been equipped with gauges to measure the flow of water in and out of the roof. Local observations are used for the calibration of a conceptual ecohydrological model. Tembata et al. (2020) estimated how for- ests decrease the occurrence of storms, resulting in two main results. Second, they confirmed that the rise in forest area mitigates the risk of flooding even after monitoring socio-eco- nomic and meteorological variables and time-invariant individual effects. Second, large-leaf and mixed-tree forests have a flood-reduction effect, while coniferous trees do not; these findings are stable to alternate model requirements. Alves el al. (2020) focused on a method for analyzing trade-offs when different benefits are pursued in the planning of stormwater infrastructure. A hydrodynamic model was coupled with an evolutionary optimization algo- rithm to evaluate different combinations of green-blue-grey measurements. This assessment includes the mitigation of floods as well as the improvement of co-benefits. Optimization has been confirmed as a useful decision-making tool to visualize trade-offs between flood management strategies.
Innovative solutions for flood preparedness
Literature review identified a large number of innovative solutions for flood preparedness (Abunyewah et al., 2020; Cvetković et al., 2018; Mei et al., 2018; Sadler et al., 2020; Haghigha- tafshar et al., 2018;Aleksandrina et al., 2019; Cvetković & Janković, 2020; Cvetković, Roder,
Öcal, Tarolli, & Dragićević, 2018; Kumiko & Shaw, 2019; Ocal, 2019; Jovana Perić & V. Cvet- ković, 2019; Tam, Chan, & Liu, 2019; Xuesong & Kapucu, 2019) and mitigation (Ezemonye
& Emeribe, 2014; Haghighatafshar et al., 2018; Shah et al., 2017; Hadid et al. 2019). Coughlan de Pérez et al. (2017), suggested that the detection of seasonal flood drivers should be used to enhance the prediction knowledge on flood preparedness to prevent misleading deci- sion-makers. On the other side, Rodriguez-Espíndola et al. (2018), introduced an emergency preparedness system focused on a mix of multi-objective optimisation and regional informa- tion systems to enable multi-organizational decision-making. A cartographic model is used to prevent the collection of flooded facilities, advising a bi-objective optimization model used to assess the location of emergency facilities, stock prepositioning, allocation of resources and delivery of relief, along with the amount of actors needed to carry out those operations. Demir et al. (2018) launched Iowa Flood Information System (IFIS) vision, deployment and case studies to include next-generation flood support decision supporting structures. IFIS is an end-to-end web-based framework that integrates different elements of the flood risk management decision-making process. The IFIS offers information on streams and weather patterns in real time, integrates sophisticated hydrological simulations for flood prediction and mapping, and multiple data collection and visualization methods to promote successful decision-making.
By using the Structural Equation Modeling (SEM), Abunyewah et al. (2020) established a model to assess the mediating and moderating impact of ‘group engagement’ on the relation- ship between ‘knowledge suficiency’ and ‘preparation intentions.’ Results have demonstrated that emergency intelligence, which is available, accurate and customized to the needs of the public, has a positive effect on disaster preparedness. They explored the role of group engage- ment in enhancing the efficacy of the IDM in disaster preparedness. Shah et al. (2020) found that awareness and training programs are needed at the school level to increase knowledge and preparedness for future floods. Besides that, Kanakis & McShane, 2016, demonstrated in their analysis that expected vulnerability to a potential extreme weather occurrence, social connectivity, and self-efficacy greatly predicts part of the variation in preparatory behaviour. Cvetković et al. (2018) proposed that emergency management agencies and land planners should account for differences (men seemed to be more confident in their abilities to cope with flooding, perceiving greater individual and household preparedness) in gender aware- ness and preparedness. Based on that, doing so may increase citizen participation and shared responsibility under flood hazard scenarios. Ezemonye & Emeribe (2014) recommended the exploration of family preparedness as the first coping technique to resolve the helpless nature of households in the event of a flood catastrophe. Sensitization of households on the need to save resources to boost flood impacts is required while improving institutional preparedness for disaster risk reduction.
Karunarathne & Lee (2020) showed empirical and convincing evidence of support for the social network and its spatial and temporal mechanisms of evolutionary patterns of pre- paredness and recovery for flood disasters, as demonstrated in the case of the 2017 mass flood incident in rural areas of Sri Lanka. The findings showed an important empiric finding that social support networks play a key role in the preparedness and regeneration of disasters be- fore, after and after floods. In 2019, Das demonstrated a groundbreaking study of flood maps through the method of analytical hierarchy (AHP) and hydro-geomorphic response to floods through geospatial analysis and unit stream power modeling. In a very interesting paper, au- thors demonstrated that the combination of dune restoration and revegetation is the best way to mitigate the effects of coastal erosion and floods under present and potential sea-level sce- narios. Also, they showed the possible advantages of incorporating and enhancing emerging green-based strategies, such as coastal hazard risk mitigation, to reduce coastal risk in both
present and future scenarios (Fernández-Montblanc et al. 2020). Hu et al. (2019) measured the degree of urban flood prevention by Low Impact Construction Technologies (LIDs) to retrofit urban areas to a viable level using a hydrological model. The findings showed that LIDs were successful alternatives for alleviating urban floods in the urbanized sector. On the other side, Sen et al. (2020) introduced a resilience evaluation system for housing infra- structure using a combination of Best Bad Process and Hierarchical Proof Justification based on Dempster-Shafer flood threat theory. Convertino et al. (2019) introduced an informa- tion-theoretic Portfolio Decision Model (iPDM) to maximize the structural benefit of the basin environment by analyzing all possible flood risk reduction plans. iPDM measures the expected ecological importance of all possible combinations of flood control systems (FCS) based on natural, social and economic asset parameters.
Flood warning and forecasting
Most flood warning systems research is pre-occupied with official or structured systems intended to alert other agencies and the public at risk through government organizations (Parker & Handmer, 1998). A wave run-up control system and a model to predict the wave run-up height on a seawall have been developed by Huang et al. (2020). To measure the wave run-up heights, electrical conductivity sensors have been mounted on the seaward slopes of seawalls. In order to relay the calculated data in real time to the desired remote position, the general packet radio service protocol was used. Intrieri et al. (2020) proposed a structure offering guidance about what the information transmitted in a flood warning alert should be and by what means of communication it should be issued, on the basis of the degree of criticality of the predicted flood, on the capabilities of the warning organization and on the particular benefits of each tool. A system of logistical aspects of emergency measures (Vibhas et al., 2019; Xuesong & Kapucu, 2019) has been developed by De Leeuw & Jonkman (2012) to promote the avoidance of disastrous flood protection breaches during acute scenarios. By combining a graphics processing unit (GPU) accelerated hydrodynamic model with NWP products, Ming et al. (2020) developed a new forecasting method to provide high-resolu- tion, catchment-scale prediction of rainfall-runoff and flooding processes caused by extreme rainfall. The goal of the research by Rio et al. (2019) was to design, create and implement an image-driven model of an early warning system based on an Android mobile phone so that the public will be expected to be able to obtain information from their respective cell phones about possible flash floods. Image processing forms the basis of this innovation by means of the Background Subtraction technique, which is used by an IP camera to automatically de- tect high amounts of water (TMA) on the control panel (Peil), which is the input parameter of the system and is converted into information for interested parties. Handmer (2001, p. 20) in his summary based on vide range of literary review (Parker & Fordham, 1996; Parker & Handmer, 1998) suggested that warning messages should: be timely and reliable, have local and individual meanings, be forward looking suggest appropriate responses, come from lo- cally credible sources, be reinforced socially (e.g. through personal networks), go to those at risk (usually a diverse group). On the other side, its suggested that warning systems should make provision for easy confirmation and extra information, use an appropriate range of message dissemination modes, employ multiple channels for dissemination, incorporate continuous learning and updating procedures, weaknesses in warning systems that should be avoided: complex arrangements for decision-making and/or communication, centrally run systems that are poorly connected to local needs, lack of sufficient time to accomplish all communication steps, decision bottlenecks where systems become overly reliant on, single persons, assumptions that the broadcast media will disseminate a warning, assumptions that
those at risk are a homogeneous group with, uniform needs, forgetting that convincing argu- ments are more likely to succeed, than are orders, failure to draw on the full range of available experience.
Yao et al. (2019) found that by using the WRF (the weather analysis and forecasting mod- el) precipitation projections, the Grid-Xinanjiang model is capable of providing better flood predictions. They also found that the precipitation forecasts’ temporal and spatial trends have a major influence on the estimation of both the timing and the severity of incoming floods. The, Yoon et al. (2014) revealed that for hydrological flood forecasting, the CMAX (The col- umn maximum) provides valuable information. In order to help disaster control, Hostache et al. (2018) contributed to the creation of more detailed global and near-real-time remote sensing flood forecasting systems. Using SAR images, they took advantage of recent algo- rithms for accurate and automated flood scale delineation and showed that near real-time sequential assimilation of SAR-derived flood extensions would greatly boost flood forecasts. Dersingh (2016) proposed the design and development of a flood alert system that includes an embedded module for data acquisition that can be installed in a remote area in order to regularly capture environmental data such as rainfall volume, water level, and image. The collected data is then transmitted over the Internet to a server through a cellular data net- work, and is stored in a database and analyzed on the basis of historical data to assess early flood alerts in the region. A web application and a mobile application have been designed and developed for users to view measured data. Moreover, the mobile application is capable of receiving a push notification of a warning message of potential. In very interesting paper, Intrieri et al. (2020) presented guidance about what should be the information transmitted in a flood warning notice and in what contact mechanism it should be given, based on the criticality level of the predicted flood, on the capabilities of the organization in charge for the warning and on the particular advantages of each medium. For example, during a red alert, the use of megaphones, loudspeakers or sirens by municipal staff, with the support of volun- tary associations, may be useful for alerting citizens in small towns or in specific areas at risk, for reaching people of all ages, particularly the elderly, and for those who do not follow any of the aforementioned channels and for reaching people of all ages, particularly the elderly.
Flood risk communication and management
In flood risk control, risk communication has a more and more central role, but there are a host of contradictory recommendations as to whether, when, how and to who is being com- municated (Demeritt & Nobert, 2014). Rollason et al. (2018) have shown that respondents want knowledge on where and how a flood will occur, so that they can consider their risk and feel responsible about their choices about how to react. Four designs that turn information requirements into new approaches to flood risk communication were also suggested. Creat- ed by study participants, these proposals satisfy their knowledge needs, improve their flood literacy and increase their response capacity. In the other hand, Haer et al. (2016), which analyzed numerous flood risk communication strategies, has found that customized, hu- man-centered, flood risk communication can be considerably more efficient than a tradition- al approach to top-down government communication, even though less people are targeting targeted communication. Communication on how to protect against floods is much more ef- fective than the traditional flood risk communication strategy, in addition to providing infor- mation on flood risks. Then, Pathak (2019) emphasized the need to provide a user-friendly method of crisis communication to support resilient societies. A robust emergency response infrastructure would integrate all communication networks, including television and radio,
smartphones, open source data and social media. Cantoni et al. (2020) endorsed a partici- patory approach in favor of public organizations by diverse classes of citizens (volunteering, awake, unaware) in various stages of the calamitous case (homeostatic process, disorderly period, rebooting phase). The model they propose envisages an impressive change in the way the citizen and the public administration act and abandon the dichotomous and distant relationship. In separate phases of the calamitous case (homeostatic operation, disorderly phase, booting phases) Cantoni et al., (2020) endorsed a participatory approach for public institutions by diverse classes of citizens (voluntary work, conscience and unknowledge). The model they propose envisages an impressive change in the way the citizen and the public administration act and abandon the dichotomous and distant relationship. Raza et al. (2020) suggested a user-centric solution to connectivity in disaster-affected regions and commu- nication outages. The proposed scheme would form ad hoc clusters to promote emergency coordination and link end-users/User Equipment (UE) to the central network. On the other side, Dong et al. (2020) proposed a probabilistic model for the estimation of the probability of cascading disruptions in co-located road and channel networks. The suggested Bayesian network analysis method combines systemic features of the network and analytical evidence on the distribution of floods to model the spread of floods. Lin et al. (2020) concluded that cross-scale risk coordination not only has a significant effect on individual decision-mak- ing on restoration and resettlement, but also has consequences for long-term planning and development. Also, Mel et al. (2020) suggested a method that uses hydrodynamic modeling and professional expertise to assess an equitable distribution of flood risk in the river system to mitigate flood risk by the optimum application of current control systems, without sub- stantial increased costs. The authors have acknowledged the importance of partnering with public institutions and technicians in charge of maintaining river networks, encouraging the sharing of information and skills, and optimizing the realistic effect of scientific study.
Flood mapping
Flood maps can contain a wide range of flood-related details and there are therefore unique subtypes of flood maps (Van Alphen, Martini, Loat, Slomp, & Passchier, 2009): land-use de- velopers are involved in the location of flood-prone areas, the agencies responsible for flood protection are involved in areas with high potential damage and casualties and authorities responsible for emergency preparation and response are involved in areas with high num- bers and number of vulnerable populations etc. There is no formal nomenclature or accepted flood mapping procedure in Europe (Merz, Thieken, & Gocht, 2007). Degiorgis et al. (2012) suggested strategies to classify flood-prone areas from automated elevation models. Adopted approaches are focused on characterization of patterns and geomorphological characteris- tics. On the other side, Sanders et al. (2020) showed that residents’ views and knowledge of floods are improved more by fine-resolution depth contour maps than by the Federal Emer- gency Management Agency (FEMA) flood hazard classification maps and that displaying fine-resolution depth contour maps helps to reduce discrepancies in interpretation of floods among subgroups within the population, generating mutual understanding. Also, Tripathy et al. (2020) implemented a new definition of spatial flood risk mapping and weather fore- casting in the medium term focused on expected risks, vulnerabilities (topographic and so- cio-economic) and exposure information. In addition, flood hazard maps can be based on various flood conditions, taking into account particular flood dynamics from a number of failure sites, presented as variations of flood probability, depth and current velocity (Van Alphen et al., 2009). Besides that, Panahi et al. (2020) identified the possible use for spatially explicit flash flood predictions and mapping of two architectures of deep learning neuronal
networks, i.e. convolutionary neural networks (CNNs). Some authors (Feng et al, 2020) pro- posed a novel process for mapping flood magnitude from location-based social media photos and applied it to a specific flood event as a proof of concept. The method involves the com- pilation and filtration of photographs from social media for flood-related eyewitness images, and the removal of identical images (and thus possibly duplicates). Moreover, flood-related photographs of people have been categorized according to water level in four stages of flood severity with reference to the various parts of the body in the picture.
Decision model for optimal flood management
There are a lot of innovative solutions regarding different types of a decision model for optimal flood management (Goodarzi et al., 2019; Lee et al., 2019, Jamali et al., 2020; Ty- ler et al., 2019). Goodarzi et al. (2019) proposed a decision-making model for determining flood warning level based on atmospheric ensemble forecasts. On the other side, Lee et al. (2019) presented a novel ensemble extension of the conditional bias-penalized Kalman fil- ter, referred to herein as the conditional bias-penalized ensemble Kalman filter (CBEnKF), and apply it to flood forecasting. Jamali et al. (2020) developed a modern applied modeling system that applies a semi-continuous simulation approach to the mitigation of flooding and the benefits of RWH water supply. Some authors, proposed the creation of a decision-mak- ing method for emergency planning and response, especially in the case of a flood accident (Nivolianitou et al., 2015). The suggested method is a simulator (i.e. computer-based soft- ware) capable of detecting ‘emergency machine’ failures, and also enhances the basic areas of the emergency system, such as physical infrastructure, human factors, procedures, reaction time and sequence of actions. The built tool can be used as a technological tool to model the operational and inter-organizational assets of a multi-actor civil protection community with the goal of highlighting powerful and weak elements of civil protection systems. Tyler et al. (2019) established seven realistic lessons that, if applied, could not only allow decision-mak- ers to better consider neighborhood flood risks, but could also reduce the effects of flood events and enhance community resilience to future flood disasters. These seven lessons in- clude: (1) understanding that the acquisition of open space and the protection of wetlands are some of the most important ways to reducing flood losses; (2) recognizing that, based on the community’s flood risks, various patterns of construction are more effective in reducing flood losses; (3) recognizing the risks and advantages of participation in FEMA’s Commu- nity Rating System program; (4) engaging community stakeholders in flood planning and recovery processes; (5) considering socially disadvantaged communities in flood risk man- agement programs; (6) focusing on a range of flood risk management tools; and (7) ensuring that flood reduction strategies are thoroughly implemented. On the other side, Zhang et al. (2018) described an innovative project in which disaster management planners in a dryland community in northwestern China treated flash floods as a resource rather than as a threat, and helped the community to benefit from this resource. The project produced ecological benefits (combating desertification), social benefits (flood control), and economic benefits (harvesting water for future use) that improved the community’s adaptive capacity and fa- cilitated sustainable development. Vinten et al. (2019) concluded that improving hydraulic management could mitigate the likelihood of flooding upstream, help protect mesotrophic wetlands, and facilitate low-flow downstream water sources. In addition, the authors found that: (a) installation of manually operated tilting wire, improved management of escape and flow routing from the common lade; (b) dredging of the common lade in combination or in place of tilting wire. On the other hand, Sanders et al. (2020) showed that collective flood modeling encourages the role of a wide variety of end-users in considering the risks of flood-
ing and offers clear evidence that Flood Risk Management can effectively implement and apply the co-produced expertise. Then, Pham et al. (2020) proposed and validated three en- semble models based on the Best First Decision Tree (BFT) and the Bagging (Bagging-BFT), Decorate (Bagging-BFT), and Random Subspace (RSS-BFT) ensemble learning techniques for an improved prediction of flood susceptibility in a spatially-explicit manner.
Flood education and training
Dufty (2008) defines community flood education as learning process or activity that builds community resilience to flooding. He higlighted that community flood education can include: public communications, information products and services e.g. publications, Internet sites, displays; training, development and industry-specific programs; community development programs e.g. public participation programs; comprehensive personal education programs
e.g. school curriculum, university curriculum. On other side, Dufty (2008) propouse new approach involves changes to the following aspects of community flood education: the par- ticipation of the learners; focus on building resilience; links with the ‘flood cycle’; evaluation of flood education programs; links with other flood mitigation and resilience-building plans and methods; longevity of the flood education program (Cvetković et al., 2017; Cvetković
& Filipović, 2018; Cvetković & Svrdlin, 2020; Cvetković, 2018). Charalambous et al. (2018) made suggestions for enhancing civic engagement: first, the need for a more participatory approach to the public participation process. Instead of discussing the measures selected by the authority, at public consultation sessions, members should be given time to address the benefits and drawbacks of possible flood control solutions in smaller groups and to prioritize all the measures proposed; secondly, there is a need for a clearer plan to advertise public consultation activities and to improve engagement in them. On the other side, Hijji et al. (2015) proposed an Expert System that could help anticipate, evaluate and improve civil de- fense flash flood training capabilities against scalable flash flooding risks. Then, Tanwattana
& Toyoda (2018) proposed using gaming simulation (GS) as a tool to strengthen communi- ty-based disaster risk management (CBDRM). Kankanamge et al. (2020) found that: (a) the use of Twitter is a promising approach to reflect citizen knowledge; (b) Tweets could be used to identify fluctuations in the severity of disasters over time; (c) the spatial analysis of tweets validates the applicability of geo-located messages to demarcate highly impacted disaster zones. Then, Tsai et al. (2020) integrated a serious game, Battle of Flooding Protection, and Kolb’s Experiential Learning Cycle to develop a learning package that would raise students’ level of interest in learning, inspire their self-awareness, and increase their willingness to participate in disaster-related citizen actions. Tran & Rodela (2019) investigated whether and how adaptive expertise (i.e. experimental and experimental knowledge) obtained from farm- ers’ day-to-day adaptation activities leads to local flood control and adaptation policies in selected areas. They find that while the highly bureaucratic operation of flood control causes input restrictions, the more informal structures placed in place at the local level offer versatile channels for transparent collaboration, mutual learning and information sharing between the various actors. Contrary to that, Banerski et al. (2020) explored whether the motivation of the local population could be improved by using 3D animation to imagine possible catastrophe situations and demonstrated the utility of using 3D animation in warning communications. Videos were given to groups of subjects living in flood-prone regions. Danger evaluation was only a major determinant of Self-Protection Motivation when the warning alert was deliv- ered in the form of 3D enhanced graphics. It increases incentive to respond by stimulating two cognitive processes and does not limit the ability to memorize directions within the post.
Flood volunteers
In the case of disasters, the initial response comes from first responders and as neces- sary from the relevant local authorities and possible volunteer organizations and volunteer activity in such situations is crucial, bearing in mind that most survivors are saved in the first 48 hours (Cvetković, Milašinović, & Lazić, 2018). Also, Oloruntoba (2005) notes that without good strategic planning, where volunteers should be sent, how to organize, monitor and direct them, they can become a serious obstacle to the successful functioning of disaster management. When it comes to motives for providing assistance, it has been found that its various forms are conditioned by various motives (Houle, Sagarin, & Kaplan, 2005; Gazley
& Brudney, 2005). Providing help is conditioned by social order, personal characteristics, attitudes and situational variables (Brand et al., 2008; Dass-Brailsford, Thomley, & de Men- doza, 2011; Forbes & Zampelli, 2014; Sloand, Ho, Klimmek, Pho, & Kub, 2012; Son & Wilson, 2012; Taniguchi & Marshall, 2014). Paciarotti et al. (2018) emphasized the importance of spontaneous volunteers during emergencies, and their appropriate management is crucial in achieving an efficient and effective volunteer service, even though it may be administered by a non-official responder organisation. On the other side, Ludwig et al. (2017) derived a technical concept that supports the task and activity management of spontaneous volunteers as well as the coordination both of the demands of affected people and the offers from spon- taneous volunteers.
Innovative solutions for flood response
Literature review identified a large number of innovative solutions for flood response (Boukerche & Coutinho, 2018; Liu et al., 2018; Tan et al., 2016; Lamond et al., 2012). Bouker- che & Coutinho (2018) proposed a novel architecture for smart disaster detection and re- sponse system for smart cities. They discussed the main building blocks of our envisioned smart system, as well as the critical challenges that will be faced ahead to implement our smart system. On the other side, Liu et al. (2018) evaluated the efforts and expertise gained in designing the Flood Prevention and Emergency Response System (FPERS) operated by Google Earth Engine, based on its applications during the three phases of the floods. FPERS incorporates various remote sensing images at the post-flood level, including Formosat-2 optical imagery to locate and track barrier dams, synthetic aperture radar imagery to derive an inundation map, and high-spatial-resolution photos taken to determine damage to river channels and infrastructure by unmanned aerial vehicles. At the pre-flood stage, an immense amount of geospatial data is incorporated into FPERS and classified as typhoon forecasting and archiving, disaster avoidance and notification, disaster occurrence and interpretation, or simple data and layers. During the flood season, three measures are put in motion to promote access to real-time data: to provide key statistics, to make sound recommendations and to improve decision-making. Tan et al. (2016) proposed an Agent-as-a-Service (AaaS)-based geospatial service aggregation to build a more efficient, robust and intelligent geospatial ser- vice system in the Cloud for flood emergency response. Salmoral et al. (2020) in their study evaluated how Unmanned Aircraft Systems (UAS) can be used in the preparation for and response to flood emergencies and develops guidelines for their deployment before, during and after a flood event. In order to unlock the full potential for Earth observation data in flood disaster response, Schumann et al. (2016) suggested in a call for action (i) stronger collaboration from the onset between agencies, product developers, and decision‐makers;
(ii) quantification of uncertainties when combining data from different sources in order to
augment information content; (iii) include a default role for the end‐user in satellite acquisi- tion planning; and (iv) proactive assimilation of methodologies and tools into the mandated agencies. Besides that, Lamond et al. (2012) demonstrated that waste management can be an effective response to flood risk but, in order to remain successful, it requires that suffi- cient commitment and engagement can be mobilised in the long term. Katuket al. (2009) introduced the architecture of a web-based flood response support system in Malaysia. The proposed architecture is of interest to the flood control agencies involved in order to plan future changes to the existing flood response protocol. Also, Bullemer et al. (2011) shown that operator efficiency under sensor flood conditions can be increased if the operator con- figuration allows the operator to strategically display alarm subsets connected with particular equipment areas rather than a catalog comprising all alarms.
Innovative solutions for flood recovery
Literature review identified a large number of innovative solutions for flood recovery (Zeng et al., 2019; Crow & Albright 2019; Lu et al., 2017; Tammar et al., 2020). For example, Zeng et al. (2019) presented the full methodology for a novel flood footprint accounting framework – the Flood Footprint Model – to assess the indirect economic impact of a flood event and simulate post-flood economic recovery situations throughout productions supply chains. Within the framework of Input-Output (IO) analysis, the model is built upon previ- ous contributions, with improvements regarding the optimization of available production imbalances; the requirements for recovering damaged capital; and an optimized rationing scheme, including basic demand and reconstruction requirements. Next to that, Crow & Albright (2019) analyzed intergovernmental relationships during disaster recovery. They dis- covered that learning within local governments is associated with higher levels of resource flows from state agencies as well as more collaborative intergovernmental relationships. They also indicated that state governments can improve processes for disaster recovery assistance and bring together disaster-affected local governments to promote learning during the re- covery process. As an effort to broaden the ProSe coverage and expand integrated global-lo- cal information exchange in the post-flood SAR activities, Rahman et al. (2019) proposed a novel network architecture in the form of a cyber-enabled mission-critical system (CE- MCS) for acquiring and communicating post-flood emergency data by exploiting TV white space spectrum as network backhaul links. Futher, Lu et al. (2017) investigated how to net- work smartphones for providing communications in disaster recovery. By bridging the gaps among different kinds of wireless networks, they have designed and implemented a system called TeamPhone, which provides smartphones the capabilities of communications in disas- ter recovery. Experimental results demonstrated that TeamPhone can properly fulfill com- munication requirements and greatly facilitate rescue operations in disaster recovery. Besides that, Tammar et al. (2020) developed a social capital framework centered on resilience and post-disaster recovery. Gupta & Nikam (2014) suggested that a variety of innovative flood control systems have been planned and installed on the major Mithi River in the area. Weath- er stations have been designed to send rainfall level data in real time (every 15 minutes) to the disaster emergency control room and over the internet to the public. (every 15 min) to the disaster emergency control room and through internet to the public. Futher, Driessen et al. (2018) concluded that six key governance strategies will enhance ‘flood resilience’ and will secure the necessary capacities. These strategies pertain to: (i) the diversification of flood risk management approaches; (ii) the alignment of flood risk management approaches to overcome fragmentation; (iii) the involvement, cooperation, and alignment of both public and private actors in flood risk management; (iv) the presence of adequate formal rules that
balance legal certainty and flexibility; (v) the assurance of sufficient financial and other types of resources; (vi) the adoption of normative principles that adequately deal with distribu- tional effects. On the other side, Thaler & Fuchs (2020) recommended a better link between financial disaster-aid compensation and voluntary payout programmes, especially to reduce the uneven socio-economic distribution during the recovery phase. Because of that, Gillil- and et al. (2020) highlighted critical needs for disaster planning and well user education in flood-prone areas, changes to flood risk maps, and concerns with the efficacy of disinfection strategies. Information and resources needs for flood-impacted well users are presented and recommendations on how to improve flood preparedness and recovery are made. Song et al. (2017) devised a new method to measure resilience via recovery capability to validate indi- cators from social, economic, infrastructural, and environmental domains. Their findings substantiate the possibility of using recovery measurement based on pollutant discharge to validate resilience metrics, and contribute more solid evidences for policy-makers and urban planners to make corresponding measures for resilience enhancement.
5. Conclusions
The results of the research show significant and progressive progress of innovative solu- tions in the field of flood risk management. It is interesting to mention that a large number of innovative solutions were created by conducting research after flood disasters that caused specific tangible and intangible consequences and also motivated researchers to find an ade- quate solution. However, in many countries the available innovative solutions are not imple- mented quickly enough for various reasons such as lack of money, lack of sufficient level of motivation, misunderstanding of the general public about the importance of such measures, unprofessional and unprofessional risk management in such situations. The paper reviews certain and selected innovative solutions, of which there are many more in practice, but due to technical limitations in writing the paper, we were unable to systematize them and give a brief overview of them. In the future, it is necessary to continue continuous research, develop national knowledge bases that would be nourished by innovative solutions and improve the exchange of knowledge and experience between developed and underdeveloped countries.
Author Contributions: V.M.C. had the original idea for this study and developed the study design. V.M.C., J.M. critically reviewed the papers and contributed to the content for revising and finalizing the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by European Union’s Horizon 2020 research and in- novation program under Grant Agreement No. 740750.
Acknowledgments: We would like to thank Scientific-Professional Society for Disaster Risk Management in Belgrade and International Institute for Disaster Research (http://up- ravljanje-rizicima.com/), which provided us professional advice throughout the writing and data interpretation.
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INTERNATIONAL INSTITUTE FOR DISASTER RESEARCH
During December 2020, the International Institute for Disaster Research based in Belgrade was established. Founder Assist. Prof. Vladimir M. Cvetkovic, together with the associates of the Scientific-Professional Society for Disater Risk Management, passed the Statute and on that occasion the following departments were formed:
Department for research of phenomenology, endangerment and resistance to disasters;
Department for Disaster Preparedness and Mitigation Research;
Department for Disaster Protection and Rescue Research;
Disaster Recovery Research Department;
Disaster Risk Management Department;
Department for Research on International Cooperation and the Legal Framework for Disaster Risk Reduction.
The main activity of the International Institute for Disaster Research is scientific research work in the field of disaster studies and is performed at the Institute whose headquarters are at the mentioned address. The scientific activity of the Institute is performed in accordance with the Law on Scientific Research Activity of Serbia and the set and adopted program orientation of the work. The main activity of the Institute is realized through basic, applications and developmental scientific research in the field of scientific discipline of disaster risk management.
Scientific-professional society for disaster risk management
Membership in the Scientific-professional society for disaster risk management is achieved by sending an email with a request to the following email address: upravljanje.rizcima.vs @gmail.com.
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ISSN 2620-2662 = International Journal of Disaster Risk Management COBISS.SR-ID 275206924