1 GIS-Based Climate Change Induced Flood Risk 2 Mapping in Uhunmwonde Local Government 3 Area, Edo State, Nigeria 4 5 Obot Akpan IBANGA 1*, Osaretin Friday IDEHEN 2 6 7 1Department of Geography and Regional Planning, University of Benin, Benin City, Edo 8 State, Nigeria. 9 1Department of Geography and Regional Planning, Igbinedion University, Okada, Edo State, 10 Nigeria 2 11 12 1413 15 . 16 ABSTRACT Introduction: Flood is one of the climate change induced hazards occurring in most parts of the world. It exposes humanity and many socio-ecological systems to various levels of risks. In Nigeria, extreme rainfall events and poor drainage system have caused inundation of several settlements to flooding. To contain the disaster, risk mapping were among the measures recommended. Aims: The aim of this paper is to highlight flood risk zones (FRZ) in Uhunmwonde Local Government Area (LGA), Edo State, Nigeria. Methodology: Flood risk (FR) was mapped using hazards and vulnerability and implemented using geographic information system (GIS)-based multi-criteria analysis analytic hierarchy process (MCA-AHP) framework by incorporating seven environmental and two socio-economic factors. Elevation, flow accumulation, soil water index of wettest quarter, normalized difference vegetation index, rainfall of wettest quarter, runoff of wettest quarter and distance from rivers constituted the hazard component while population density and area of agricultural land use was the vulnerability layer. The climate change induced flood risk was validated using the responses of 150 residents in high, moderate and low flood risk zones. Results: The resulting flood risk map indicated that about 40.4% of Uhunmwonde LGA fell within high flood risk zone, 35.3% was categorized under moderate flood risk zone whereas low flood risk zone extended up to about 24.3% of the LGA. The high number of respondents who reported occurrence of flooding with frequency being very often and the fact that flooding was a very serious environmental threat during on-the-spot field assessment validated the generated climate change induced flood risk. Conclusion: The utilitarian capabilities of GIS-based MCA-AHP framework in integrating remotely-sensed biophysical and climate change related flood inducing indicators with socio- economic vulnerabilities to arrive at composite flood risk was demonstrated. 17 18 Keywords: [Flood hazard, vulnerability, flood risk, GIS, Mapping, Uhunmwonde LGA] 19 20 1. INTRODUCTION 21 22 Flooding has been acknowledged as one of the direct consequences of climate change [1] 23 due to increase in the frequency and intensity of tropical cyclones, hurricanes, typhoons and 24 other moisture-laden extreme weather phenomena [2]. The warmer than normal global 25 temperature [3] is an invitation for increase in convective activities in the earth’s atmosphere 26 [4] with resultant increase in the amount and duration of rainfall [5]. Melting of ice caps in the 27 Polar Regions directly linked to global warming and worldwide changes in the level of water 28 in the oceans leading to upsurge in coastal and river flooding have also been documented 29 [3,6,7]. The current worldwide mean annual increase of 3-4mm in water levels in the oceans 30 and the predicted rise to about 15mm at the end of the present century is also responsible 31 for the frequency and magnitude of flooding [8]. 32 However, a shift in climate has been ascribed to the actions of man which modifies 33 atmospheric processes as well as the noticeable natural spatial and temporal fluctuations in 34 global climatic pattern [3, 9]. In contrast, flood or flooding is the accumulation of excessive 35 quantity of water in an area without flowing away easily [10]. In most cases, the 36 accumulation of such abnormal large volume of water in an area that is not usually covered 37 by water is also hampered by poor percolation and runoff [10, 11]. At the global, national, 38 regional and local scales, substantial evidence on the climate change induced floods and 39 flooding abound. 40 Approximately 80% of the world’s population spread across just 15 nations which 41 suffer from severe impact of flooding annually. India, Bangladesh and China topped the list 42 while over 167,000 people in the United States of America (USA) are exposed to flooding 43 every year [12]. In 2017, over three billion dollars’ worth of properties and cultivated farmland 44 in several places in USA were lost to climate change induced flooding. This was as result of 45 increase in the frequency and intensity of rainfall coupled with increased development in 46 floodplains, increased impermeable surfaces (roads, pavements, and parking lots), 47 destruction of natural areas [13]. In the United Kingdom (UK), two days continuous rainfall in 48 October 2019 similar to the already reported monthly value as a result of successive stormy 49 activities made several locations to be inundated to flood waters [5]. Nigeria occupied the 50 10th position in terms of food occurrence and vulnerability annually [12]. 51 In climate change debates, flood risk has been conceptualized as the product of 52 three principal components namely: hazard or exposure, sensitivity or elements at risk and 53 vulnerability [6, 7, 14]. Risk practitioners view risk as the product of the probability of an 54 event’s occurrence and its magnitude (i.e., probability × magnitude = risk). However, in 55 environment and development debates, this relationship include an exponent to account for 56 social values or societal impacts (i.e., probability × magnitude n), although n may be difficult 57 to measure [15]. Also, several efforts have been made to assess climate change induced 58 flood risk both in developed and developing countries. Identifying the environmental factors 59 inducing flood, the elements at risk as well as the strategies adopted by the vulnerable 60 population is particularly essential in flood risk mitigation and contingency planning [16]. 61 Key datasets common in climate change induced flood mapping include elevation, 62 slope, aspect, geology, distance from river, distance from road, distance from fault, soil type, 63 land use and land cover, rainfall, normalized difference vegetation index (NDVI), stream 64 power index, topographic wetness index, sediment transport index and curvature [16-22]. 65 Methodological frameworks include socio-economic, biophysical, and integrated [23]. 66 Manlosa and Valera [24] deployed socio-economic approach to assess micro scale flood 67 damage in a Lakeshore Community of Jabonga in the province of Agusan del Norte in the 68 Philippines. It was found that monthly household income, land area farmed, number of 69 livestock owned, frequency of flood incidence in the homes, flood velocity, and duration of 70 inundation at the work area were the determinants of household flood vulnerability in the 71 hazard zone. This study however neglected the roles of sociopolitical and environmental 72 variables in shaping societal vulnerability. 73 Udo and Eyoh [25] also used biophysical approach to map river inundation and flood 74 hazard in Edo State. It was found that 25% were very high hazard zones while 30% of the 75 state was classified high hazard places. The lowly hazard areas covered 4354 square 76 kilometers (22.2%) and no hazard covered 8.2% of the study area. Espada et al [26] used 77 integrated framework to assess the vulnerability of core suburbs of Brisbane City, 78 Queensland, Australia to flooding. Findings revealed that 36% (about 813 hectares) and 79 14% (roughly 316 hectares) of the study area were exposed to very high flood risk and low 80 adaptation capacity, respectively. Geographical information system (GIS), remote sensing 81 (RS), multi-criteria analysis (MCA) and analytical hierarchy process (AHP) have also been 82 deployed in the execution of integrated based flood risk mapping [16-22, 25, 26] 83 The basic principle in MCA is the allocation of weights to various flood hazard, 84 sensitivity and vulnerability indicators based on perceived and established criteria [22]. In 85 MCA, AHP accredited to [27] which involve the use of chain of command configurations in 86 the representation of indicators in addition to prioritizing viable options using expert 87 decisions have been widely used. The AHP framework uses pairwise rating scale ranging 88 from one (equally important) to nine (absolutely more important) in measuring the impact of 89 each indicator to the overall outcome of the phenomenon under study [28]. 90 Flood is one of the environmental problems occurring in most parts of the world. It 91 exposes humanity and many socio-ecological systems to various levels of vulnerabilities. In 92 Nigeria, 35 states including Edo and 380 Local Government Area (LGA) including 93 Uhunmwonde were inundated due to heavy rainfall and poor drainage system in 2018 94 [29].The 2019 flooding affected the 36 states and over 124 LGAs rendering 210,117 people 95 vulnerable in addition to 171 deaths while households were rendered homeless [30]. In 96 Uhunmwonde Local Government Area (LGA), several households were displaced leading to 97 the establishment of temporary camp at Egor, the LGA headquarters. The 2020 rainfall 98 prediction by the Nigeria Meteorological Agency (NiMet) showed that the southern parts of 99 Nigeria (where Edo State including Uhunmwonde LGA is located) is expected to have 100 extended period of rainfall [31]. The implication of the 2020 rainfall forecast is increased 101 probability of climate change induced flooding across the zone. 102 Thus, in order to avert the 2020 flood impact at the present and in the future as well as to 103 contain flooding, the Nigeria Hydrological Services Agency (NIHSA) recommended 104 measures such as flood sensitisation campaigns, flood risk mapping and flood vulnerability 105 studies [29]. Climate change induced food risk mapping in Uhunmwonde LGA is therefore, 106 one of such attempt to respond to the clarion call made by NIHSA.