High Flood Risk Research Articles

Amplifying Flood Risk Across the Lower Yellow River Basin, China, Under Shared Socioeconomic Pathways

The ecological conservation and high-quality development of the Yellow River basin (YRB) has been adopted as a major national strategy of China. However, the YRB is still afflicted by floods. Here, we proposed a flood risk indicator using direct economic loss degree and improved the SNRD (station-based nonlinear regression downscaling model) and simulated extreme precipitation processes. The correlation coefficient of downscaled average extreme precipitation of CMORPH and CMIP6 data reached 0.817. Moreover, we evaluated flood risk and flood hazard across the YRB based on the sixth phase Coupled Model Intercomparison Project (CMIP6) data under different SSPs. Under SSP126, SSP245, and SSP585 scenarios, the areas with increasing flood hazards during 2015–2045 accounted for 65.2, 69.0, and 64.5% of the entire YRB. In the spatial pattern, flood hazards decreased from southeastern to northwestern parts of the YRB. When compared with the spatial pattern of flood risks in 2015, regions with high flood risks expanded slightly and regions with low flood risks shrunk slightly. Higher flood risks can be observed in the middle and lower YRB and particularly in the lower YRB. These findings are critical for the mitigation of flood risk across the YRB under warming climate.

Warming of 0.5 °C may cause double the economic loss and increase the population affected by floods in China

Abstract. Based on future scenario data and an improved quantitative natural-disaster risk assessment model, in this study, we analysed the response of the characteristics of flood events in China to 1.5 and 2 ∘C of global warming, quantitatively assessed the population affected and the economic risks of floods, and determined the integrated risk levels. The results indicate that, for the RCP4.5 (Representative Concentration Pathway) and RCP8.5 scenarios, the probability and distribution area of the floods increase with increasing temperature and the influence range of the floods of different levels expands more rapidly under the RCP4.5 scenario. The floods mainly affect the social economy in the regions with lower altitudes and smaller slopes in eastern China. As the increase in temperature intensifies, the population affected and the direct economic losses are aggravated. For 2 ∘C of global warming, under the RCP8.5 scenario, the population affected by floods increases by 2 million, and the economic risk nearly doubles compared with 1.5 ∘C of global warming. The economic risk under the RCP4.5 scenario even reaches 3 times that for 1.5 ∘C of global warming, but its proportion to the gross domestic product (GDP) is lower than that under the RCP8.5 scenario. Under both scenarios, the ranges of the zones of medium–high flood risk gradually expand westward and northward.

Flood hazard assessment and mapping using GIS integrated with multi-criteria decision analysis in upper Awash River basin, Ethiopia

Floods have destroyed people’s lives as well as social and environmental assets. Flooding is becoming more severe and frequent as a result of climate change and an increase in human-induced land-use changes, which puts pressure on river channels and causes changes in river morphology. The study was aimed to assess flood danger and map inundation areas in Ethiopia’s Teji watershed, which is prone to flooding. The basic flood-producing factors in this study were derived from soil, slope, elevation, drainage-density and land use land cover data. The opinions of public institutions and expert decisions were gathered to determine the weight of the factors in the analytic hierarchy process. The collected data were processed using the ArcGIS environment and the analytic hierarchy method to produce a flood danger map. According to the findings of this study, approximately 43.28 and 13.09% of the area were vulnerable to high and very high flood risk zones, respectively. As a result, flood prediction, early warning and management practices could be implemented on a regular and sustainable basis.

Assessment of Flood Risk and Mapping of Flood Risk Zones in Yenagoa, Bayelsa State, Nigeria

In recent years, most Nigerian cities have experienced several major flood episodes with serious catastrophes. Hence, this study was carried out to assess and map flood risk zones in Yenagoa. The Geographic Information System (GIS) and remote sensing technologies were used in generating and analyzing data to identify the different flood risk zones in Yenagoa. Environmental indices such as flood heights, land elevation and land cover images were analyzed using geo-statistical tools such as map overlay operations to produce a flood risk map. The flood risk map produced and the ground truthing carried out confirmed that the highest flood risk are located within residential areas where about 32% of the built-up area was vulnerable to moderate or high risk of flooding. The study revealed that both natural and anthropogenic factors are responsible for the severe flooding experienced in Yenagoa, especially due to heavy precipitation, elevation of the area, poor waste disposal, and inadequate urban development control amongst other factors. The city was classified into three flood risk zones-high, moderate and low, with about 48% of the area being either at moderate or high risk of flooding. It is therefore recommended that the Ministry of Physical and Urban Development should carryout proper urban development control, which will prevent building on flood plains, wetlands and natural drainage channels.

Exploring the additional value of class imbalance distributions on interpretable flash flood susceptibility prediction in the Black Warrior River basin, Alabama, United States

This study proposes a novel flash flood susceptibility prediction framework with a particular emphasis on the extent of imbalance between the number of flooding and non-flooding events as majority of the events result in non-flooding. The class imbalance issue and the magnitude of the imbalance was explored in this study to highlight the uncertain nature of the flooding phenomenon. Therefore, the Random Forest (RF) was initially adopted to evaluate five imbalance class distribution scenarios (i.e., 1x, 10x, 25x, 50x, 100x non-flood events, for each x flood event). Parameter configurations of developed models were determined with the state-of-the-art metaheuristic, the Cuckoo Search (CS) algorithm. The CS-RF model showed the highest (0.8455) prediction capability with regards to the area under the receiver operating characteristic (AUROC) once the extent of imbalance was set as 50x. The CS-RF model was then benchmarked with another bagging, i.e., Extra Trees, and two boosting, i.e., Adaptive Boosting (Adaboost) and eXtreme Gradient Boosting (XGBoost) algorithms, all integrated with the CS technique. Analysis results showed that the CS-RF is the most promising tree-based machine learning technique in flash flood susceptibility projection for the selected study area. According to the predictions, a flash flood susceptibility map was generated, where 9.35% of the basin was under very high flash flood risk. A recently developed model-agnostic game-theoretical method, SHapley Additive exPlanations (SHAP), was used for anatomizing the flash flood conditioning factors to highlight the contribution of each feature on the incident outcome prediction ensuring the transparency of the model findings. Overall, this study contributes to both theory and practice with particular focus on the model interpretability and existence of imbalance in the occurrence of flash flood events, assisting decision-makers in enhancing strategies to combat hazardous impacts of floods.

Flood Disaster Risk Model in Karawang Regency's Industrial Area, West Java Province, Indonesia

Telukjambe Barat and Telukjambe Timur Sub-Districts, Karawang Regency, have a high flood risk level due to changes in Land Use/Land Cover and the yearly occurrence of runoff water discharge. This research aims to analyze the rate and pattern of land-use change due to industrial development, examine the correlation of flood impacts with environmental-socio-economic factors, and develop a flood risk model in industrial areas. Data were collected through methods of system dynamics, remote sensing, geographic information system, questionnaire distribution, focus group discussions, and in-depth interviews with stakeholders. The results showed that floods in this regency are due to massive inland changes, such as the transition from vegetation and water bodies to industrial and residential areas and a strong relationship between environmental-social-economic factors. In other cases, areas with urban land conversion are likely to be flood-prone zones in places such as the Philippines, Belgium, and China. Based on the correlation test that has been conducted, the relationship with the highest level of closeness is the correlation between environmental factors and the impact of flooding, which has a value of 0.791. Therefore, the disaster risk model with an integrated spatial plan approach and an ecological perspective is an option for realizing sustainable development in industrial areas in Karawang Regency.

Reconciling biodiversity conservation and flood risk reduction: The new strategy for freshwater protected areas

AbstractAimNatural disaster risk reduction (DRR) is becoming a more important function of protected area (PAs) for current and future global warming. However, biodiversity conservation and DRR have been handled separately and their interrelationship has not been explicitly addressed. This is mainly because, due of prevailing strategies and criteria for PA placement, a large proportion of PAs are currently located far from human‐occupied areas, and habitats in human‐occupied areas have been largely ignored as potential sites for conservation despite their high biodiversity. If intensely developed lowland areas with high flooding risk overlap with important sites for biodiversity conservation, it would be reasonable to try to harmonize biodiversity conservation and human development in human‐inhabited lowland areas. Here, we examined whether extant PAs can conserve macroinvertebrate and freshwater fish biodiversity and whether human‐inhabited lowland flood risk management sites might be suitable to designate as freshwater protected areas (FPAs).LocationAcross Japan.MethodsWe examined whether extant PAs can conserve macroinvertebrate and freshwater fish biodiversity and analysed the relationship between candidate sites for new FPAs and flood disaster risk and land use intensity at a national scale across Japan based on distribution data for 131 freshwater fish species and 1395 macroinvertebrate species.ResultsWe found that extant PAs overlapped with approximately 30% of conservation‐priority grid cells (1 km2) for both taxa. Particularly for red‐listed species, only one species of freshwater fish and three species of macroinvertebrate achieved the representation target within extant PAs. Moreover, more than 40% of candidate conservation‐priority grid cells were located in flood risk and human‐occupied areas for both taxa.Main conclusionsFloodplain conservation provides suitable habitat for many freshwater organisms and helps control floodwaters, so establishing new FPAs in areas with high flood risk could be a win‐win strategy for conserving freshwater biodiversity and enhancing ecosystem‐based DRR (eco‐DRR).

Flood susceptibility modeling in the urban watershed of Guwahati using improved metaheuristic-based ensemble machine learning algorithms

The urban watershed of Guwahati is a highly flood-prone region and the fastest growing city situated on the bank of the Brahmaputra River. Therefore, this study aims to the urban flood susceptibility mapping of Guwahati city using metaheuristic optimization algorithms integrated with random forest (RF) machine learning algorithm. Further, the receiver operating characteristic (ROC) and multiple error measurements were applied to analyze the performances of the models used. The result showed that about one-third of the area of Guwahati city is under the high and very high flood risk while nearly 50% area comes under low and very low flood risk. The value of the area under curve (AUC) of ROC was above 0.80 for all the integrated models applied. However, the RF-bee colony (BCO) and the RF-based ant colony (ACO) are the two best flood susceptibility models that performed better in the analysis. The methodology adopted in the study is cost and time effective and can be used for the flood susceptibility modeling in other parts of the world. Further, the findings of this study can useful in the flood mitigation and planning process.

Flood risk analysis using gis-based analytical hierarchy process: a case study of Bitlis Province

Floods are the most common natural disasters on earth. Population growth with global warming and climate changes increases the impact of floods on people every year. Combating natural disasters such as floods is possible with effective disaster management. An effective disaster management can only be possible with a comprehensive risk analysis. Flood risks depend on many factors such as precipitation, flow, earth slope, soil structure, and population density. A holistic flood risk analysis considering all these factors will provide a more effective disaster management. This study focuses on an assessment of flood hazard analysis in Bitlis province of Turkey using analytical hierarchy method which is a multi-parameter modeling technique. Flood hazard zones were mapped according to the weight of the selected factor by using geographic information system. It is concluded that while especially the south-western regions are exposed to high flood risk due to high stream density and precipitation, the high slope and rugged nature of this region restrict the risk mainly to the vicinity of low elevation streams and high population regions.

Flood Hazard Mapping and Flood Preparedness Literacy of the Elderly Population Residing in Bangkok, Thailand

This research aimed at assessing flood hazard areas and flood literacy of the elderly population in Bangkok, Thailand and analyzing their flood preparedness through SWOT analysis. Expert interviews and a community survey were conducted. Using the analytic hierarchy process (AHP) and GIS technique, the results indicated that land-use, drainage density, and annual maximum rainfall were the most heavily weighted factors in flood hazard mapping in Bangkok. About half (50.32%) of Bangkok’s total area was defined as high flood hazard area. A total of 736 questionnaires were distributed in flood-prone areas and in the areas with the highest percentage of elderly population. The results of both SWOT and survey analysis found that many senior citizens have low digital and media literacy and limited experience in using information technology for flood preparedness. Lack of integration of disaster risk reduction and aging population policy, ineffective warning system, and lack of access to disaster preparedness training were the key barriers in reducing vulnerability to flood hazard. The survey revealed that the majority of elderly respondents (75%) have neither used online applications for their flood hazard management both before and during flood disaster nor shared/communicated information via online platforms. Some respondents (13%) used Facebook and Line applications to obtain information before a flood event. Very few of the elderly respondents (<2%) accessed the national/provincial web-based platform to find out flood-related information. Almost all respondents, especially who are living in high-risk flood zones, had never participated in the community training of flood preparedness and management. Therefore, effective strategies in enhancing social engagement of the elderly and their literacy skills in flood risk preparedness and management are urgently needed.

Alteración geomorfológica en relación a las acciones antrópicas en el cauce del río Caplina, Tacna, Perú

Natural phenomena are difficult to control and predict, but risk management can prevent and reduce the risks of flooding due to the overflow of the Caplina River. This work seeks to determine the anthropic alterations and geomorphological characteristics of the Caplina river basin that generate a high risk of flooding in its trajectory. Existing information was used regarding the hydraulics of the Caplina river basin, carried out by the Tacna Special Project (PET), National Water Authority (ANA), Local Water Authority (ALA), National Meteorology and Hydrology Service (SENAMHI) and the Geological Mining Metallurgical Institute (INGEMMET). With field work, it was possible to establish thematic maps referring to areas of geomorphological alteration due to anthropic action and crops, which made it possible to determine areas prone to overflow and flooding at critical points. After the evaluation carried out in the study area, it was determined that the study area has a very high level of risk and vulnerability.

A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level

Floods are frequently occurring events in the Assam region due to the presence of the Brahmaputra River and the heavy monsoon period. An efficient and reliable methodology is utilized to prepare a GIS-based flood risk map for the Assam region, India. At the regional and administrative level, the flood hazard index (FHI), flood vulnerability index (FVI), and flood risk index (FRI) are developed using multi-criteria decision analysis (MCDA) – analytical hierarchy process (AHP). The selected indicators define the topographical, geological, meteorological, drainage characteristics, land use land cover, and demographical features of Assam. The results show that more than 70%, 57.37%, and 50% of the total area lie in moderate to very high FHI, FVI, and FRI classes, respectively. The proposed methodology can be applied to identify high flood risk zones and to carry out effective flood risk management and mitigation strategies in vulnerable areas.

Assessing the disparities of the population exposed to flood hazards in Nigeria

The increased frequency and intensity of flooding and related disasters result from changing climatic conditions and other socio-economic factors. As flooding can be highly destructive and negatively impact human lives, this study attempts to estimate the population, capital stock and disparities in exposure to flooding hazards in Nigeria using GIS and Statistical methodologies. First, the study assessed the spatial distribution of the population and capital stock exposed to flood by utilising population and socio-economic datasets. Then, the distribution of the vulnerable groups affected is estimated by superimposing the population and socio-economic datasets onto the flood hazard maps. The results show that approximately 24.7 million (8.3%) of Nigeria’s Population were exposed to floods in 2015. Most exposed groups were primarily in urban areas irrespective of the income class. Additionally, the clusters of communities within the high-risk flood hazard zones had significantly increased, evident in the number of residents exposed to flood within the 15 years (2000-2015) growing exponentially. These findings further highlight a disturbing state of localities where people are generally less responsive to climate change and natural hazards. Overall, this study provides essential information for disaster risk management and policy formation at different levels of administration and identifies areas where varied and informal strategies are needed to mitigate flood risk and climate change in regions with diverse socio-economic conditions. In addition, this study provides empirical proof of the socio-economic disparities associated with flood exposure in Nigeria and presents valuable insights into the underlying factors.

Study Of Flood Disaster Risk Delta In Bojonegoro Regency

A disaster is an unexpected and often sudden event that causes destruction, serious damage, and human suffering. According to the Law of the Republic of Indonesia Number 24 of 2007 concerning Disaster Management, disasters are caused by natural factors and/or non-natural and human factors so that disasters can result in loss of life, environmental damage, loss of property, and psychological impacts. Bojonegoro Regency which has the widest area crossed by the Bengawan Solo river and 24,753 hectares of its area is a watershed so that almost every year Bojonegoro Regency is flooded when the Bengawan Solo river overflows. Floods in Bojonegoro Regency almost occur every year. Where the flood that occurred in Bojonegoro Regency was caused by the overflow of the Bengawan Solo river. As much as 63% of the total population of Bojonegoro Regency is exposed or at risk of flooding in 2012 to 2020. This study is to determine the Delta (Δ) risk of flood-prone areas in Bojonegoro Regency based on trends in land use change with a multitemporal perspective in Bojonegoro Regency. This study uses the latest methods, especially in terms of spatial modeling, namely TIN and Raster databases. The first step is to predict the trend of land use in Bojonegoro Regency. Which is then continued to identify flood hazards and land use vulnerabilities. Flood disaster-prone areas each year are predicted based on the previous stages using the Analytic hierarchy process which then produces disaster risk in each prediction year. The last step is to calculate the amount of change or Delta (∆) of Flood Disaster Risk in Bojonegoro Regency. The results of this study are Delta (∆) Low Flood Disaster Risk: experienced a change of -1.62% or decreased by 49.66 Ha from 2020 to 2040. Delta (∆) Moderate Flood Disaster Risk: experienced a change of 2.85% or experienced an increase of 17.67 Ha from 2020 to 2040. Delta (∆) High Flood Risk: experienced a change of 23.96% or an increase of 31.99 Ha from 2020 to 2040.

Predictable Changes in Extreme Sea Levels and Coastal Flood Risk Due To Long‐Term Tidal Cycles

AbstractWe demonstrate that long‐term tidally induced changes in extreme sea levels affect estimates of major flood hazard in a predictable way. Long‐term variations in tides due to the 4.4 and 18.6‐year cycles influence extreme sea levels at 380 global tide gauges out of a total of 581 analyzed. Results show coherent regions where the amplitudes of the modulations are particularly relevant in the 100‐year return sea level, reaching more than 20 cm in some regions (western Europe, north Australia, and Singapore). We identify locations that are currently in a positive phase of the modulation and therefore at a higher risk of flooding, as well as when (year) the next peak of the long‐term tidal modulations is expected to occur. The timing of the peak of the modulation is spatially coherent and influenced by the relative importance of each cycle (4.4 or 18.6‐year) over the total amplitude. An evaluation of four locations suggests that the potentially flooded area in a 100‐year event can vary up to ∼45% (in Boston) as a result of the long‐term tidal cycles; however, the flooded area varies due to local topography and tidal characteristics (6%–13%). We conclude that tidally modulated changes in extreme sea levels can alter the potentially inundated area in a 100‐year event and that the traditional, fixed 100‐year floodplain is inadequate for describing coastal flood risk, even without considering sea‐level rise.

Penguatan Ketangguhan Bencana Melalui Pendidikan Mitigasi Bencana Berbasis Traditional Ecological Knowledge (TEK) dan Optimalisasi Peran Social Capital (SC) bagi Masyarakat Nagari KBKA Pesisir Selatan

Nagari Kampung Baru Korong nan Ampek (KBKA) Koto XI Tarusan District, Pesisir Selatan Regency has a high risk of natural disaster threats, namely earthquakes, tsunamis, landslides and floods. Meanwhile, Nagari KBKA is a potential village as one of the producers of Gambir in West Sumatra. The high threat of disaster risk and the impact of disasters on community activities, including economic activities, need serious attention. Many disaster mitigation education programs have been carried out, but have not touched on the empowerment of the KBKA natural local potential and the KBKA social system. This Community Service activity aims to strengthen community resilience to disasters by optimizing the existing natural resources and human resources in Nagari KBKA. This activity is carried out in 3 stages in the time span of July - November 2021 involving students, teachers, youth groups and housewives. The forms of activity consist of 1) Socialization on the potential, characteristics, symptoms and risks of disasters in coastal, hilly and mountainous areas and the importance of preparedness aspects, 2) Training to identify and utilize various social capital owned by the KBKA community, 3) Training to identify plants/vegetation potential in a disaster emergency period for preventing disasters, medicinal plants and alternative food), 4) Training to understand natural phenomena and changes in animal behavior before a disaster occurs, 5) Workshop on processing waste into ecoenzymes and 6) Planting Bungur Trees to reduce the risk of erosion in watersheds . The results of the activity show 1) an increase in the knowledge of students and teachers about natural phenomena, animal behavior, and potential disaster prevention plants, 2) an increase in the enthusiasm of the community for disaster preparedness, and 3) the acquisition of disaster prevention skills through waste processing into ecoenzymes.

Flood Risk Perception and Its Attributes among Rural Households under Developing Country Conditions: The Case of Pakistan

Managing and communicating flood risks necessitates a strong understanding of how people perceive risk. It has become critical to examine risk perception to implement effective disaster risk management (DRM) measures. Socioeconomic determinants have an impact on risk perception, which in turn affects future adaptive capacity and disaster preparedness. First and foremost, this research attempts to determine how Pakistani people in rural areas perceive flood risk, and second, to examine the factors that can influence rural residents’ perceptions of flood risk. The data for this study were collected through face-to-face interviews with 600 respondents (household heads) from Charsadda and Nowshera districts that were severely affected by the 2010 flood. A flood risk perception index was developed (using a risk matrix) using relevant attributes on a Likert scale and classified into two categories: high and low perceived risk. Furthermore, a binary regression model was used to examine the influence of socioeconomic and institutional factors on rural households’ risk perception. Flood risk was perceived by 67 percent of the total sampled participants in the study regions. The results of binary logistic regression demonstrate that flood risk perception is strongly linked to socioeconomic variables such as age, education, house ownership, family size, past flood experience, and distance from the nearest river source, as well as institutional factors such as access to credit and extreme weather forecast information. The findings of the current study additionally revealed that flood risk perception varied among household heads based on education (1–10 years perceived high flood risk (51.47%)), age (age greater than 40 years perceived high flood risk (52.83%)), and monthly income levels (lower monthly income group perceived high flood risk (73.02%)). The findings of this study shed light on rural households’ perception of flood risk and the factors that shape such perceptions. These findings can assist provincial and local disaster management authorities in better understanding flood risk and adopting local actions that could be used to respond to flood and other climate-related disasters.

Flooding study in the desert climate zone: case study of M’zab valley (Algeria)

The aim of this research is the modelling and mapping of flood risk zones in the M’zab valley of Ghardaia city by combining the hazard map and the flood vulnerability map. The undertaken research utilizes the hydrologic engineering centre-hydrologic modelling system as the modelling tool to simulate the runoff in the watershed and hydrologic engineering centre – river analysis system to model the water levels of different river locations based on steady flow analysis and to define flood-prone areas. The flood risk map allows the identification of five classes ranging from a low to a very high risk of flooding. Thus, the low to very low-risk areas extend over roughly 70.58% of the total surface area of Ghardaia city. These areas, which are located in the southern part of the alluvial plain, are considered as low vulnerability regions, while areas with high-risk cover more than 20% of the city.

Assessing Coastal Road Flood Risk in Arctic Alaska, a Case Study from Hooper Bay

Rising waters and land subsidence are increasing relative sea levels in western and northern Alaska, forcing communities to relocate or armor in place. To appropriately plan and make equitable decisions, there is a need to forecast the risk of flood exposure in coastal Alaskan communities and to evaluate methods to mitigate that risk. This paper conducts use-inspired science to evaluate the current and future flood exposure of roads in Hooper Bay, Alaska, proposes a unit cost of flood exposure to estimate the cost of flooding, and compares various mitigation efforts including elevating roads and building dikes. Nine historic storms and their associated flood depths were subject to return-period analysis and modeled for several sea level rise scenarios. Based on the simulated road flood exposure (km hours/storm), and the storm-return period, an annual flood exposure (km hours/year) was computed. Then, the unit cost of flood exposure (USD/km hours) was determined as the ratio of the cost of flood mitigation (USD/year) to the annual flood exposure mitigated by the project. The analysis found that the unit cost of flood exposure, in conjunction with flood exposure calculations, does provide an approximate flood risk calculation, though a unitized cost of flood exposure needs to be divided into lump sum costs and materials costs. The analysis also found that dikes may be a more cost-effective alternative than road elevation. The flood risk calculation, based on the unit cost of flood exposure, could be made for all of the communities in a given region to identify those communities that face a high flood risk. Furthermore, if one divides the unit cost of flood exposure by the population, one obtains a cost/benefit ratio that potentially could be used to prioritize flood mitigation work.

Geomorphic Assessment of Flood Hazard Within the Urban Area of Chanchaga Local Government Area, Minna, Nigeria

assess flood hazard. It has been used to carry out Multi-Criteria Analysis (MCA) of various geomorphic factors by assigning weight based on the presumed impact of each factors on flooding. This study considered six factors which include; Slope, curvature, landcover, elevation, distance from river and soil using Rafinsenyi river in Chanchaga Local Government area, Minna-Nigeria, as study area. Review of literatures showed that methods of assigning weight are hypothetical and inconsistent, this research thus take input from researchers in field of hydraulics, hydrology and disaster management. The weight with 0.029 as the least consistency ratio was used. Data used include; DGPS data, Satellite Images, Digital Soil Data. Landcover Maps, Digital Elevation Models (DEM), Soil Maps and Profile Curvature maps were generated. Weighted overlay operation was carried out in ArcGIS to produce a Flood Risk Map. Livisol (Loam) soil reveals why farmers and traders indiscriminately settle along floodplain. 6 of the 20 hectares of study area lies between 216 and 220 metres above mean sea level, putting residential building at high risk of flooding.