DEVELOPMENT OF FLOOD DAMAGE CURVES FOR COTONOU CITY, BENIN BLANDINE OUIKOTAN (1), BERRY GERSONIUS (2) & HANS VAN DER KWAST (3) (1) e-mail: b.ouikotan@unesco-ihe.org (2) e-mail: b.gersonius@unesco-ihe.org (3) h.vanderkwast@unesco-ihe.org 1. INTRODUCTION In West Africa, flooding is becoming more serious since a while, in terms of the number and frequency of floods occurring as well as the damage and the deaths it causes. During the last decade, more than 100 disasters flooding events were recorded and about 1,200 persons were killed (EM-DAT,2013). In 2009, 16 among the 17 West African countries were stroke by floods and 600,000 people were affected. Senegal was among the most affected countries (Di Baldassarre et al., 2010) and the cost of damage was estimated to US$ 42.32 Million for the whole country and US$ 35.43 Mi for Dakar, the capital city (Faye, 2011). In 2010, 15 West African countries were hit by damaging floods (EM-DAT, 2013) and cities like Cotonou, Lome, Accra, Lagos, Dakar have registered the greatest number of affected people (Gouvernement.Republique.du.Benin, 2011). For Benin, the 2010 events seemed to be Benin s worst flood which had overwhelmed two-third of the country. 9.3% of the total population was affected (EM-DAT, 2013) and the country was among the top ten countries in the world affected by floods according to the Centre for Research in Epidemiology Disasters. Significant damages were recorded with massive losses of human lifes, houses, harvests, animals and properties especially in Cotonou, the most urbanized city and the economic capital of Benin where 9325 people were displaced and 3108 homeless. Cotonou is located in the southern part of Benin at latitude 6 21' N and longitude 2 23' E. It has a surface area of 79 km 2 and shelters most of the administrative buildings, companies' headquarters, an international market covering 18 hectares, the single airport and the harbour of the country, the two-thirds of Benin industries and carries out 98% of the volume of imports of Benin (GAI, 2006). Like most of the coastal cities in West Africa, Cotonou, has been facing floods each year. The ongoing urban development in flood-prone areas, the parcelling of wetlands zones and the lack of long term planning of prevention measures are increasing the risk of flooding. To date, there are no proper tools for flood risk assessment to support the choice of mitigation and adaptation measures. This paper tries to fill this gap by developing flood damage curves for Cotonou city. Flood damage curves are essential tool for flood risk assessment to support the choice of mitigation and adaptation measures. Damage functions are essential and represent the standard approach for flood damage assessment (Prettenthaler et al., 2010). 2. DIFFERENT TYPES OF FLOOD DAMAGE Flood damage refers to all varieties of harm caused by flooding (Messner and Meyer, 2006) and multiple types of damage can be encountered during or after a flood event. An overview of the different types is given by Jonkman (2007) and Merz et al. (2010). Flooding affects all people, buildings, infrastructure and natural spaces which fall within the flooded area. It also affects people who are outside the flooded area and directly or indirectly use the affected facilities such as roads, hospitals, schools, industries, wetlands, water bodies etc. Damage or losses are then categorized as direct or indirect. Direct damages are caused by physical or direct contact of floodwaters with humans, buildings, infrastructure or any other object. Indirect damages are those induced by direct impacts but do occur outside the flooded area (Merz et al., 2010, Balica, 2012, Jonkman, 2007, Frauke, 2010). Each of the two categories is divided into two sub-categories of damage; tangible and intangible damage depending on whether or not the damage can be assessed in monetary (replacement) values. Some examples for the different types of damage are: Direct, tangible: damage to private or public buildings and contents; destruction of infrastructure such as roads, railroads; erosion of agricultural soil; destruction of harvest; damage to livestock; evacuation and rescue measures; business interruption inside the flooded area; clean up costs. Direct, intangible: loss of life; injuries; loss of memorabilia; psychological distress, damage to cultural heritage; negative effects on ecosystems. Indirect, tangible: disruption of public services or business outside the flooded area; induced production losses to companies outside the flooded area (e.g. suppliers of flooded companies); cost of traffic disruption; loss of tax income due to migration of companies after the floods. 1
, the Netherlands Indirect, intangible: trauma; societal disruption; loss of trust in authorities. 3. DATA AND METHODS Data was mainly collected from households, municipality and the National Institute of Statistics and Economic Analyses (INSAE). According to Cotonou Municipality land registration office, there were 182003 households and 49292 of them are in flood prone areas, in 2010. For the household survey, a questionnaire was used for the interview. 82 head of households or women (representing the head of household) were interviewed. Data collected include the socio-economic profile of the interviewee, the type of residential dwelling, the characteristics of the structure of the buildings and contents, the economical value of the exposed items, the characteristics (flood depth and duration of flooding) of the 2010 flood event used as a reference flood event, the damage on the structure of the buildings, the cost of displacement of people from the flooded area and the cleaning cost etc. Replacement cost of the buildings contents and depreciated value of items are derived from INSAE data base. Many factors or features related to flood event influence the damages. These are flood depth, velocity of floodwaters, duration of flooding, sediment or pollution load of floodwaters etc. Although these factors are relevant, most assessment focused only on the flood depth. There are usually two approaches to derive the depth-damage functions: the first approach is based on damage data of past floods (a posteriori evaluation). This approach used the actual costs of damage (recovery cost) or the most frequently the results of compensation assessment. The second approach is based on a hypothetical analysis of cost simulation from a representative case of each type of building or after a survey on the potential damage that can be produced after a flood event (Dutta et al., 2003, Torterotot, 1993). Nascimento et al. (2007) tried to combine both approaches and applied the methodology to Itajuba city in Brazil. For our case, we adapted the methodology described by Nascimento et al. (2007) to Cotonou context by considering two flood factors: the depth and the duration of flood. We identified two categories of damage for the buildings. These are structural damages and contents damages. For the structural damages, a posteriori evaluation was done using 2010 flood event as reference. The different damages on the structure of the buildings were recorded and the repair cost will be estimated. The damages on the contents of the buildings were evaluated on the basis of a priori analysis. The flood damage curves were built for each type of buildings. In this paper, we present only the first results of the ongoing household's survey on the different categories of buildings in Cotonou city, the type of structural damages encountered and the cost of displacement of people during floods. 4. RESULTS AND DISCUSSION From the first results, buildings in the flood prone areas were classified in three categories as shown in Table 1 below using the material used for the foundation, the walls, the roofs and the covering. Table 1: Characteristics of different type of buildings in Cotonou flood prone areas Type of Basement foundation Walls Roofs Floor covering buildings I Bricks of cement Bamboos Steel sheets Layer of cement mortar II Bricks Bricks Steels sheets Layer of cement mortar III Reinforced Concrete Bricks Reinforced Concrete or Steels sheets or tiles Reinforced concrete with layer of cement mortar/tiled Depending on the duration and the depth of the floodwaters, the type of damage and the nature of the repairs were recorded. The results are shown in Table 2 below. Table 2: Damage and nature of repairs on the flooded buildings Type of buildings Flood depth Flood duration Type of Damage Nature of repairs Type I < 50cm < 1month Cracks and fissures on the Repair of the cracked Type I >50cm and <100cm >1month Cracks and fissures in the total surface area of the Repair of the total surface area of the Type I >100cm 3 months Total damage of the house Construction of new house Type II 20 cm - 50 cm <1 month Cracks and fissures in the Repair of the cracked Type II 50 cm - 100 cm >1 month Cracks and fissures in the Repair of the total surface area of the 2
Type II >100cm 3 months Cracks and fissures in the, separation of the from the wall, cracks in the wall Type III 20 cm - 50 cm <1 month No damage Repair of the cracked, Repair of the cracked wall Type III 50 cm - 100 cm 3 month Cracks in the tiled Replacement of the tiled The table shows the average status of houses in the flooded area, but the cracked walls are more pronounced in some districts than others may be because of the soil properties. From the above results, the curve of displacement costs versus flood depth is built as shown in figure 1. There is no correlation between the flood depth and the displacement costs. This is explained by the strategies developed by each household to organise the displacement of its family during the flood. Displacement cost (FXOF) Flood depth (cm) Figure1: Cost of displacement versus flood depth 5. REFERENCES DI BALDASSARRE, G., MONTANARI, A., LINS, H., KOUTSOYIANNIS, D., BRANDIMARTE, L. & BLÖSCHL, G. 2010. Flood fatalities in Africa: From diagnosis to mitigation. Geophysical Research Letters, 37, L22402. DUTTA, D., HERATH, S. & MUSIAKE, K. 2003. A mathematical model for flood loss estimation. Journal of Hydrology, 277, 24-49. EM-DAT. 2013. Emergency events database, OFDA/CRED International Disaster Database [Online]. http://www.cred.be/emdat: Université Catholique de Louvain, Brussels. [Accessed December 2013]. FAYE, M. M. 2011. Cadre de gestion environnementale et sociale du PROGEP: Rapport final Agence de Développement Municipal (ADM). GAI 2006. Document sur le secteur eau et assainissement à Cotonou dans le cadre du partenariat entre la ville de Delft et la ville de Cotonou Mairie de Cotonou. Gouvernement.Republique du Benin, Banque Mondiale & Nations Unies. 2011. Inondations au Bénin: Rapport d'évaluation des besoins post catastrophe. Banque Mondiale. INSAE 2003. Troisième recensement général de la population et de l habitation - Synthèse des résultats-février 2002. Direction des études démographiques: INSAE, Bénin. JONKMAN, S. N. 2007. Loss of life estimation in flood risk assessment: Theory and applications. PhD Thesis, TU Delft. MERZ, B., KREIBICH, H., SCHWARZE, R. & THIEKEN, A. 2010. Review article "Assessment of economic flood damage". Nat. Hazards Earth Syst. Sci., 10, 1697-1724. MESSNER, F. & MEYER, V. 2006. Flood damage, vulnerability and risk perception Challenges for flood damage research. In: SCHANZE, J., ZEMAN, E. & MARSALEK, J. (eds.) Flood Risk Management: Hazards, Vulnerability and Mitigation Measures. Springer Netherlands. NASCIMENTO, N., MACHADO, M. L., BAPTISTA, M. & DE PAULA E SILVA, A. 2007. The assessment of damage caused by floods in the Brazilian context. Urban Water Journal, 4, 195-210. TORTEROTOT, J. P. 1993. Le coût des dommages dus aux inondations: estimation et analyse des incertitudes PhD, Ecole Nationale des Ponts et Chaussées 3
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