Low Flood Risk Research Articles

Flood detection in the Upper Krishna Basin through integrated geospatial analysis: leveraging decision frameworks and statistical measures

ABSTRACT Floods threaten the environment and human settlements across river basins globally, including the Upper Krishna Basin in India. This research delves into evaluating flood hazard areas within the Upper Krishna Basin utilizing the Analytical Hierarchy Process (AHP), Frequency Ratio (FR), and Statistical Index (SI). These methodologies prioritize and classify flood-prone regions by integrating spatial and non-spatial criteria. The findings reveal significant variations in flood risk classification across the Upper Krishna Basin based on the three models. The AHP model identifies 3.37% of the region as low flood risk, with 22.90% classified as moderate risk, and 68.27% as high risk. In contrast, the FR model designates 3.76% as low risk, 10.50% as moderate risk, and 42.21% as high risk. Meanwhile, the SI model identifies 1.04% of areas with low risk, 35.38% with under-high risk, and 57.87% with very high risk. Validation using Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) values demonstrates the superior reliability of the SI model. These findings offer valuable insights for decision-makers to allocate resources and implement effective flood mitigation measures.

University student flood risk perceptions and flood probability knowledge in Greater Sydney

AbstractWhile flood risk perception has been studied extensively in general populations, there remains a dearth of focus on youth perspectives – a key demographic to mobilising knowledge to achieve disaster risk reduction targets. This study aimed to evaluate university students’ perceptions of flood risk and their understanding of common flood probabilities in the Greater Sydney region of Australia. We surveyed 262 university students to better understand how flood preparedness, knowledge, and experience predict flood risk perceptions. Using ordinal logistic regression, we identified that students with past flood experience and women were more likely to have higher flood risk perceptions. In contrast, students with higher flood preparedness were more likely to have lower flood risk perceptions. Age, degree level (e.g. bachelor’s, master’s), place of residence, and flood knowledge were inconclusive predictors of risk perception. We also assessed differences in how students rated the likelihood of three equivalent flood probabilities presented in different ways: (1) a 1-in-100 year flood; (2) a flood with a 1% of happening in a given year; and (3) a flood with a 55% chance in an 80-year lifetime. Using Friedman and Kruskal-Wallis tests, we compared differences within student responses and across different risk perception groups. We found that students perceived equivalent flood probabilities stated over longer periods of time to be more likely to occur. This study contributes to understanding student perceptions of flood risk, presenting recommendations on how governments and higher educational institutions can improve building students’ knowledge of flood hazards.

Stormwater quality and microbial ecology in an urban rain garden system

Rain gardens are an alternative to traditional drainage, able to lower flood risk and reduce environmental contamination from stormwater. Removal of contaminants by rain gardens is driven by both physical processes (such as filtration and sedimentation) and biological metabolic processes by soil microorganisms. To better understand rain garden performance, this study explored the impact of rain gardens on pollution removal and microbial composition and function using rain gardens fed real stormwater from a busy road. Each rain garden had different grain size and hydraulic conductivities as these parameters have been argued to impact pollution removal. All four rain gardens were able to reduce the contaminant load in the stormwaters, reducing the concentration of dissolved metals, suspended solids and chemical oxygen demand. Significantly, road salting in the winter did not cause dissolved metals to be released from the rain gardens, suggesting that rain gardens can continue to reduce contaminant loads during winter salting regimes. Some variation in pollutant removal was seen between the soils tested, but overall no clear trend could be identified based on grain size and hydraulic conductivity with all rain gardens performing broadly similarly. The rain garden soil altered the microbial community in the stormwater, resulting in greater taxonomic evenness and functional richness in the effluent water compared to the influent. Functional richness of the soils was also higher than that of the input waters, indicating that the microbes in the rain gardens were able to perform a wider range of functions than those of the influent. Effluent and soil microbiology was more impacted by sampling date than soil grain size, which may be a result of the soil communities maturing and changing over time. As greater numbers of rain gardens are installed to tackle flooding from climate change, it is important to ensure the environment is protected from urban contaminants in the stormwater. The results in this study further highlight the ability of rain gardens to undertake this important task.

Evaluation of urban flood susceptibility through integrated Bivariate statistics and Geospatial technology.

Flood disasters are frequent natural disasters that occur annually during the monsoon season and significantly impact urban areas. This area is characterized by impermeable concrete surfaces, which increase runoff and are particularly susceptible to flooding. Therefore, this study aims to adopt Bi-variate statistical methods such as frequency ratio (FR) and weight of evidence (WOE) to map flood susceptibility in an urbanized watershed. The study area encompasses an urbanized watershed surrounding the Chennai Metropolitan area in southern India. The essential parameters considered for flood susceptibility zonation include geomorphology, soil, land use/land cover (LU/LC), rainfall, drainage, slope, aspect, Topographic Wetness Index (TWI), and Normalized Difference Vegetation Index (NDVI). The flood susceptibility map was derived using 70% of randomly selected flood areas from the flood inventory database, and the other 30% was used for validation using the area under curve (AUC) method. The AUC method produced a frequency ratio of 0.806 and a weight of evidence value of 0.865 contributing to the zonation of the three classes. The study further investigates the impact of urbanization on flood susceptibility and is further classified into high, moderate, and low flood risk zones. With the abrupt change in climatic scenarios, there is an increase in the risk of flash floods. The results of this study can be used by policymakers and planners in developing a preparedness system to mitigate economic, human, and property losses due to floods in any urbanized watershed.

Flood Mapping Using HEC-RAS and HEC-HMS: A Case Study of Upper Citarum River at Dayeuhkolot District, Bandung Regency, West Java

Dayeuhkolot district is an area within Citarum River watershed that often experiences flood during the rainy season due to overflow discharge. This research identifies the flood area by using hydrodynamic modeling in Dayeuhkolot district. The model utilized satellite rainfall data. The hydrodynamic modeling of HEC-RAS 5.0.5 and HEC-HMS simulate the flow regimes and the hydrological characteristics in the study area, respectively. The results reveal that the increase in water level in two river tributaries within Citarum River watershed had caused the flooding at Dayeuhkolot district. Furthermore, the percentage of flood areas with low, medium, and high flood risk is 34.7%, 34.5%, and 30.8%, respectively. The flood map developed in this study could support the establishment of a strategy for managing the floodplain area and flood-affected areas.

Integrated GIS and analytic hierarchy process for flood risk assessment in the Dades Wadi watershed (Central High Atlas, Morocco)

Flood risk assessment is crucial for delineating flood hazard zones and formulating effective mitigation strategies. Employing a multi-criteria decision support system, this study focused on assessing a Flood Risk Index (FHI) at the Dades Wadi watershed scale. Seven main flood-causing criteria were broadly selected, namely flow accumulation, distance from hydrographic network, drainage network density, land use, slope, rainfall, and permeability. The relative importance of each criterion prioritized as per their contribution toward flood risk, which were employed a blend of the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS)/Remote Sensing (RS) techniques. The significance of each criterion was determined based on their contribution to flood hazard, and their relative importance was established through an AHP pair-wise comparison matrix. The efficacy of the AHP model was performed with a consistency ratio of 0.08, which indicated that each flood criterion weight is confirmed. Among the flood-causing criteria, the hydrologic flow accumulation factor was identified as the most influential (weight: 3.11), while permeability exhibited the least prominence (weight: 0.58). Approximately 40.36% of the total area, equivalent to around 1319, 89 km2, was concentrated within very high flood-risk zones situated near rivers. In contrast, an area of approximately 399,943 km2 (56.33%) exhibited a low to very low flood risk zone. The validation of the FHI map encompassed the application of the Receiver Operating Characteristic Curve (ROC) technique, revealing an Area Under the Curve (AUC) of 85%.

Measuring community resilience inequality to inland flooding using location aware big data

Understanding community resilience is critical for effective resource allocation and planning. However, classical resilience measures often fall short in capturing the diverse characteristics of each stage: preparation, resistance, recovery, and adaptability. We propose a multi-stage resilience assessment framework integrating morphological indicators to measure community resilience. Applying this framework to evaluate disparities in community resilience after the inland flooding in Changsha, we find that morphological indicators provide a more accurate description of resilience priority and ability compared to speed indicators. The analysis reveals stronger complementarity and lower redundancy among resilience indicators. Moreover, we establish a strong connection between resilience, driving factors, and government actions. Neighborhoods with high flood risk and socioeconomic status encounter the severest impact and highest recovery priority, leading to substantial government engineering measures. Conversely, vulnerable communities facing high flood risk and low socioeconomic status display the lowest resistance and recovery ability, emphasizing the necessity for tailored initiatives like increasing green infrastructure and constructing flood buffer zones. Additionally, low river flood risk communities with high socioeconomic status experience minimal flood impact, underscoring the significance of prioritizing low-lying regions susceptible to surface water flooding. The study informs government decision-making, emphasizing differentiated strategies for enhancing community resilience across regions and stages.

Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS

Floods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the region by employing a GIS-based Multi-Criteria Decision Analysis (MCDA) approach and big climate data records. By using a comprehensive flood risk assessment model, a flood hazard map was developed by considering nine influential factors: rainfall, regional temperature variation, distance to the river, elevation, slope, Normalized difference vegetation index (NDVI), Topographic wetness index (TWI), land use/land cover (LULC), curvature, and soil type. The analytical hierarchy process (AHP) analysis assigned weights to each factor and integrated with geospatial data using a GIS to generate flood risk maps, classifying hazard levels into five categories. The study assigned higher importance to rainfall, distance to the river, elevation, and slope compared to NDVI, TWI, LULC, curvature, and soil type. The weighted overlay flood risk map obtained from the reclassified maps of nine influencing factors identified 6% of the total area as very high, 36% as high, 41% as moderate, 16% as low, and 1% as very low flood risk. The accuracy of the flood risk model was demonstrated through the Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) analysis, yielding a commendable prediction accuracy of 0.773. This MCDA approach offers an efficient and direct means of flood risk modeling, utilizing fundamental GIS data. The model serves as a valuable tool for decision-makers, enhancing flood risk awareness and providing vital insights for disaster management authorities in the Hunza-Nagar Valley. As future developments unfold, this study remains an indispensable resource for disaster preparedness and management in the Hunza-Nagar Valley region.

Flood hazard zonation using GIS-based multi-parametric Analytical Hierarchy Process

Flood is considered to be a serious environmental hazard, especially in the tropical countries owing to its devastating consequence on human life. Tripura, a small hilly state of northeast India has faced large scale flood events over the last few decades. The present study is an attempt to identify flood hazard zones along the lower course of the Dhalai River flowing through the Dhalai district of Tripura State. An integrated approach of remote sensing and GIS coupled together with Analytical Hierarchy Process (AHP) was applied to identify the flood hazard zones of the study area and nine parameters were selected for this purpose. Thematic maps of the parameters were reclassified after assigning ranks to different classes. A pair-wise comparison matrix among all the parameters was prepared using AHP to determine the relative weight of each parameter. Finally, flood hazard zoning (FHZ) map of the study area was prepared by multiplying the reclassified values with the weighted values using raster calculator of Arc GIS 10.1. The outcome of the study revealed that 109.69 km2 (27.65%) of the study area fall under low flood risk category. At the same time, around 114.46 km2 (28.85%) and 90.43 km2 (22.80%) areas fall under moderate and high flood risk zone respectively. The study also disclosed that the high risk zone has maximum concentration of agricultural land (68.63%) and settled area (9.77%) in comparison to the other two zones which has increased vulnerability of flood hazard. The results validated the efficiency of AHP technique in generating fast and cost effective information regarding flood hazard assessment, especially in no data regions. Hence, the derived information could be very much helpful for the planners to prepare proper strategies to reduce the vulnerability of this hazard.

Flood Risk Spatial Modeling Based on Geographical Information Systems and Remote Sensing in the Pemangkat Regensi

Flood is a disaster that occurs every year in Indonesia with various risks. This study aims to create a spatial model of flood risk and determine the distribution of flood risk in Pemangkat, Sambas Regency. The method used is surveying and interpreting secondary data from the Digital Elevation Model, topographic maps, and land cover images. The data collected includes area, elevation, slope, distance from the river, land use, and rainfall. The tool used is a set of Geographic Information System tools, namely Arcgis 10.8. Data analysis using Weighted Sum for generated Flood risk map and Geographically Weighted Regression for flood risk spatial modeling. The results showed that the Pemangkat sub-district had flood risk classes, namely very low, low, moderate, high, and very high classes. Very high to high flood-risk classes are spread in the cities of Pemangkat and Sabatuan. In contrast, medium to deficient classes are spread in Jelutung, Gugah Sejahtera, Penjajap, Harapan, Lonam, and Parapakan. Very low flood risk area is 8.17 ha (8.16%), low 16.97 ha (16.97%, medium 28.17 ha (28.16%), high 32.28 ha (32.28%) and very high 14.41ha (14.39%). The values obtained from the analysis show that GWR modeling is excellent because R2 is relatively tiny, 0.39.

Generative processes of social vulnerability to flood risk: A proposal for the strategic management of social impacts

The mainstream approach of social vulnerability to flood risk faces some challenges regarding its ability to address the complexity of its causal processes. The objective of this study was to analyse the causal processes of social vulnerability to flood impacts from a relational perspective. To this end, a social network analysis was performed that identified the conditions and causes of social vulnerability and systematically articulated the relationships between them. This analysis was tested on the specific case of flood risk on the coast of the province of Alicante (SE Spain). To ascertain the conditions and causes of social vulnerability to flood risk, a multidisciplinary group of local experts was consulted, and the resulting data processed in a relational way using Atlas.ti and Gephi softwares. The result was a social vulnerability network comprising 84 nodes and 189 edges distributed into four dimensions: the adaptive capacity of tourists, socio-economic structure, land use planning and risk management. The information was ranked for betweenness centrality, revealing the components with highest causal power of social vulnerability to social impacts in flooding events: low flood risk awareness, economic growth based on real estate boom, property speculation and lack of political interest in flood risk management. This proposal places emphasis on the driving forces of social vulnerability and not exclusively on the specific adaptive conditions of the population, which allows a strategic identification and management of generative forces that ultimately induce the social impacts of floods.

GIS-assisted Flood-risk Potential Mapping of Ilorin and its Environs, Kwara State, Nigeria

The incessant reoccurrence of flooding disasters across Nigeria has mandated an urgent outlook on flood-risk management techniques. Ilorin and its environs have suffered immensely from annual flood reoccurrence. This study aims to assess flood risk within Ilorin and its environs and proffer adequate flood mitigation strategies that governments and policymakers can adopt to placate future flooding events within the state. Satellite imagery data were acquired and analyzed for flood-risk assessment of the area. Ten highly influential flood causative factors were synergized using Multi-Criteria Decision-Making techniques in this research; they are Land Surface Temperature, Elevation, Soil Moisture Index, and Distance to Stream, Drainage Density, Stream Power Index, Normalized Difference Vegetation Index, Land Use Land Cover, Slope, and Topographic Wetness Index. Findings showed that approximately 47.2% of the study area had low flood risk, while moderate and high flood-risk zones occupied 33.5% and 19.29%, respectively. Most parts of Ilorin and its environs are safe from flood disasters; only about one-quarter of the total area under investigation lies in the high flood-risk zones; these areas mostly fall within the shores of major streams, rivers, and dams within the state. A plot of previous flood cases in the state placed the affected areas in the high and moderate zones of flood risk, confirming the efficacy of geospatial techniques in flood-risk assessment. It is hoped that this study's findings and recommendations can be implemented to prevent future devastating flooding occurrences within the state.

Risk assessment for hurricane-induced pluvial flooding in urban areas using a GIS-based multi-criteria approach: A case study of Hurricane Harvey in Houston, USA

As one of the most destructive nature hazards, hurricane-induced flooding generates serious adverse impacts on populations, infrastructure, and the environment globally. In urban areas, complex characteristics such as high population and infrastructure densities increase flood disaster risks. Consequently, the assessment of flood risks is becoming increasingly important for understanding potential impacts on an urban area and proposing disaster risk mitigation strategies. After conducting a comprehensive literature review, this study finds that most urban flood risk assessments often overlook urban ecosystem elements, focusing more on social and economic aspects. Hence, the role of urban ecosystems cannot be fully understood. To address this gap, this study proposes a social-ecological systems (SES) flood risk assessment framework for urban areas. Based on this framework, a comprehensive list of indicators collected through a literature review is provided for urban flood risk assessments. A comparative study of flood risk during Hurricane Harvey (2017) in Houston, Texas, USA, is carried out using the improved analytic hierarchy process (IAHP) weighting method and the equal weighting method for indicator weighting. Results are then compared with the damage data of Hurricane Harvey published by the U.S. Federal Emergency Management Agency (FEMA). The analysis identifies that the western part of Houston had the highest flood risks, while the center of Houston was at lower flood risk. Comparisons between the results from the IAHP and equal weighting methods show that the latter produces a broader range of high flood risk areas than the former. This study also highlights the role of urban ecosystems in mitigating flood risks and advocates for more holistic, social-ecological assessments of flood risk. Such assessments could utilize the proposed framework and the indicator list but contextualize these to the specific urban area's contexts being investigated.

ANALYZING THE IMPACT OF SEA LEVEL RISE ON COASTAL FLOODING AND SHORELINE CHANGES ALONG THE COAST OF LOUISIANA USING REMOTE SENSORY IMAGERY

Abstract. Sea level rise poses risks to coastal areas which is increasingly rendering such areas susceptible to flood and shoreline retreat. Notably, coastal areas like Southern Louisiana located along the Gulf of Mexico has experienced endangering events of land subsidence due to flood inundations resulting from incessant distribution of hurricanes and tropical storms. This research therefore employed remote sensing data to analyze the impacts of sea level rise on coastal flooding and shoreline retreat along the coast of Louisiana. That is, by assessing Sentinel-2 imagery data to evaluate flood prone and flood extent areas particularly during the Louisiana floods and Hurricane Harvey. Based on this, the results show most of the inland parishes in coastal Louisiana such as Assumption, St. James, Livingston, Lafourche and Terrebonne were within high flood risk zones of about 9.3. These parishes also suffered severe damage in terms of affected croplands, potentially flooded areas and affected urban areas. On the other hand, most of the parishes in close proximity to the waterbodies such as the Gulf of Mexico were interestingly within low flood risk zones of about 6.1 suggesting proximity to waterbodies not being the only indicating factor of a flood prone area. This research also highlights that Louisiana's shorelines are rapidly receding at a rate that could result in the loss of one million acres of the state’s land in the next four decades. Hence, the results from this research are anticipated to contribute to sustainable shoreline setback plans and mitigative strategies to protect Louisiana's coast.

A review of the effects of solar radiation management on hydrological extremes

Solar radiation management (SRM) is one of the proposed climate mitigation strategies to cool the planet rapidly. The injection of aerosol particles into the stratosphere for reflecting solar radiation back to the space is one of the SRM methods that are widely discussed. Theoretically, SRM might lower the earth’s temperature within a few months of deployment, reducing the impacts of climate change on natural disasters, i.e., floods and drought, which lead to huge losses in economic and human life. Solar radiation variability was identified to be a substantial factor that induced the hydrological changes, particularly in precipitation extreme. The effects of SRM on hydrological cycles, however, fluctuate depending on the location and environment. Hence, this article reviews the past SRM studies that related to the analysis of the hydrological cycle changes. A total of 17 articles were identified and collected from the Web of Science and Scopus databases. The results show that there have been an increasing number of articles in recent years studying the effects of SRM on the hydro-climatic changes. The Geoengineering Model Intercomparison Project (GeoMIP) and the Geoengineering Large Ensemble (GLENS) are two commonly used SRM-based general circulation models. In general, SRM is projected to slow down the global hydrological cycle. In comparison to the RCP 8.5 scenario, SRM generally tends to lower flood risk in many parts of the world. However, the majority of SRM research in hydrology has been conducted on a global scale, which results in a lack of robust basin-scale assessment needed for flood control policy formulation. In addition, more SRM climate models and scenario experiments should be considered to minimize the uncertainty in the framework for hydro-climatic modelling framework.

Flood Risk Perception among the Inhabitants of a Flood-prone Area in Iran

Background: Misunderstanding of disaster hinders people from devoting enough attention to disaster preparedness programs. Flood is one of the main natural hazards in Iran. Objectives: The present study aimed to determine flood risk perception among residents of a flood-prone area in Iran in 2021. Methods: This cross-sectional study was conducted on 201 inhabitants of three villages along the Hesar-Golestan River in northeast Iran. A researcher-made questionnaire was used to assess their flood risk perception and opinions about the causes of the flood. Flood risk perception was assessed using ten questions with a 5-point Likert scale. Risk perception was calculated at three levels: low (scores 10 to 23), medium (scores 24 to 37), and high (scores 38 to 50). Multi-stage sampling technique was used for sampling. Results: The majority of participants (81%) had a moderate risk perception. The mean risk perception score was 30±5, which indicates a moderate risk perception. According to the participants, the three main causes of floods were environmental degradation and soil erosion, unplanned development and construction in flood-prone areas, and heavy seasonal rainfall, respectively. There was a significant relationship between gender and age with some opinions about the causes of floods. Conclusion: The risk perception of participants was at a moderate level. Low or moderate flood risk perception can lead to insufficient attention, inaction, or insufficient efforts to reduce the risk and increase preparedness for floods. Taking measures such as educating people about the causes and consequences of floods using appropriate and effective methods can help to manage disasters better.

The Use of Sentinel-2A Images to Estimate Potential Flood Risk With A Multi-Index Approach in The Mempawah Watershed

Natural disasters in Indonesia have become an annual cycle, an example is flooding. This study aims to determine the flood risk potential in the Mempawah watershed and the places likely to be flooded. The method used was a survey and interpretation of secondary data from topographic maps, Sentinel-2A images, and Digital Elevation Model images. Furthermore, the secondary data analysis used includes the Standardized Precipitation Index (SPI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Soil Adjusted Vegetation Index (SAVI), and Inverse Distance Weighted (IDW). The result showed that the Mempawah watershed has high, medium, and low flood risk potential. Areas with high flood potential have an area of 1,511,967 ha, those with medium potential were 2,606,778 ha, and the places with low potential were 12,644,034 ha. The changes in class user's accuracy results reached 90.909%, while those with no change were 83.333%. It was also discovered that when the satellite analysis was > 70%, it was regarded as good. This means that the accuracy of the interpretation results and flood change detection approach was also good.
 Keywords : Sentinel-2A; Estimation Potential; Flood Risk; Watershed
 Copyright (c) 2023 Geosfera Indonesia and Department of Geography Education, University of Jember
 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

Flood risk and shelter suitability mapping using geospatial technique for sustainable urban flood management: a case study in Palembang city, South Sumatera, Indonesia

ABSTRACT The populous city of Palembang is one of the most flood-prone cities in the Indonesian region. After some decades, the magnitude, duration, and frequency of floods have increased. Thus, this study aimed to develop flood risk and flood shelter suitability maps using the Analytic Hierarchy Process (AHP) and Geographical Information System (GIS) integration. Several flood-related factors that used in this study such as elevation, population, slope, land cover, distance from a river, drainage density, distance to a road, distance to a settlement, and soil type. Results found that the flood risk map of the study area was divided into three classes; 30.3% of the area was at high flood risk, while 60.5% was at moderate risk, and 9.2% of the area was at low flood risk. Moreover, flood shelter suitability assessments revealed that approximately 4.1% of flood shelters were highly suitable, 19.4% were moderately suitable, 60.5% were lowly suitable, and 16.1% were very lowly suitable. The highest suitability areas were predominantly found on the northwest and north sides of study area which were higher in elevation (ranging 13–41 m) and farther from the river. They could be assumed to be good choices for flood shelters.

Flood Hazard and Risk Area Identification: A Case of Gelana River Watershed, Southern Ethiopia

Floods are among the most devastating natural disasters in the world, claiming more lives and causing more damage to properties than any other natural phenomena. This study specifies flood hazard areas as well as flood risk areas of Gelana River Watershed. It specifically aims to investigate factors that create good conditions for flood hazard, generate flood hazard and risk areas from environmental and socio-economic factors using integration of Multi-Criteria Evaluation (MCE) and Geospatial Techniques. The research was conducted using quantitative research approach. Therefore, slope, elevation, soil type, land use land cover (LULC), and drainage density were the environmental factors developed for the generation of flood hazard. In addition, flood hazard, LULC and population data factors were developed to generate flood risk areas of Gelana river watershed. As the result, flood hazard map reveals 64.68, 1769.48, 1345.38, 244.37, 10.73 square kilometers of Gelana river watershed, is subjected to very high, high, moderate, low and very low flood hazardous respectively. It is revealed that 46.52% of the watershed has very high to high flood risk. The rest 47.20%, 6.24%, and 0.05% of the study area has medium, low and very low flood risk respectively. Therefore, the area incorporated under very high and high hazardous and risk areas are located around the Main River and lower course of the watershed.

Flood-Risk Insurance in Flood-Prone Areas of Nigerian Cities: A Case Study of Agiliti, Ketu, Lagos

Flooding, one of the effects of climate change, has become recurrent in Nigerian cities that are situated on floodplains. To recover from economic and financial losses after the flooding incidents, affected residents of such areas have been relying heavily on government relief efforts as well as assistance from family, friends and philanthropists. However, these sources have not always been reliable in terms of being available, coming in the right amounts as well as being timeous. There is therefore the need for more reliable and sustainable strategies for helping flood victims of Nigerian cities to recover economically and financially from flood incidents. Flood risk insurance is one of such more reliable and sustainable strategies. Unfortunately, empirical evidence points to a low level flood risk insurance by insurance companies, culture in parts of Nigerian cities that are prone to flooding. Agiliti, Ketu, a part of Lagos State that lies in close proximity to Ogun River, is known to have been affected by annual flooding in recent times. This paper has used this community as a case study to consider the level of flood-risk insurance culture among residents of flood-prone parts of Nigerian cities. The survey research method was adopted, with a structured questionnaire administered on 398 households. Based on descriptive statistics involving simple percentages, the researchers found a low level of life and property insurance in the study area. Accordingly, the study recommends education of residents on the key role of insurance in city resilience alongside increased marketing of flood-risk insurance by insurance companies, reduction of public mistrust of insurance companies and reduction of the burden of payment of premium by government and charitable organisations.