Occurrence of Extreme Rainfall and Flood Risks in Yopougon, Abidjan, Southeast Côte d’Ivoire from 1971 to 2022

Yopougon, located in the western part of the Autonomous District of Abidjan, is the most heavily populated municipality in Côte d’Ivoire. However, this area is prone to floods and landslides during the rainy season. The study aims to assess recent flood risks in the municipality of Yopougon of the Autonomous District of Abidjan. To achieve this objective, the study analyzed two types of data: daily rainfall from 1971 to 2022 and parameters derived from a Numerical Field and Altitude Model (NFAM). The study examined six rainfall parameters using statistical analysis and combined land use maps obtained from the NFAM of Yopougon. The results indicated that, in 67% of cases, extreme rainfall occurred mainly between week 3 of May and week 1 of July. The peak of extreme rainfall was observed in week 2 of June with 15% of cases. These are critical periods of flood risks in the Autonomous District of Abidjan, especially in Yopougon. In addition, there was variability of rainfall parameters in the Autonomous District of Abidjan. This was characterized by a drop of annual and seasonal rainfall, and an increase of numbers of rainy days. Flood risks in Yopougon are, therefore, due to the regular occurrence of rainy events. Recent floods in Yopougon were caused by normal rains ranging from 55 millimeters (mm) to 153 mm with a return period of less than five years. Abnormal heavy rains of a case study on June 20-21, 2022 in Yopougon were detected by outputs global climate models. Areas of very high risk of flood covered 18% of Yopougon, while 31% were at high risk. Climate information from this study can assist authorities to take in advance adaptation and management measures.

Decision Making for Managing Community Flood Risks:Perspectives of United States Floodplain Managers

To reduce flood losses,floodplain managers make decisions on how to effectively manage their community’s flood risks.While there is a growing body of research that examines how individuals and households make decisions to manage their flood risks,far less attention has been directed at understanding the decision-making processes for flood management at the community level.This study aimed to narrow this research gap by examining floodplain managers’perceptions of the quality of their community’s flood management decision-making processes.Data gathered from interviews with 200 floodplain managers in the United States indicate that most floodplain managers perceive their community’s flood management decision-making processes to be good.The results also indicate that communities participating in the Federal Emergency Management Agency’s Community Rating System,as well as communities with a higher level of concern for flooding and a lower poverty rate,are significantly more likely to report better flood management decision-making processes.

Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.

Amplification of Flood Risks by the Compound Effects of Precipitation and Storm Tides Under the Nonstationary Scenario in the Coastal City of Haikou,China

In the context of climate change,coastal cities are at increased risk of extreme precipitation and sea level rise,and their interaction will aggravate coastal floods.Understanding the potential change of compound floods is valuable for flood risk reduction.In this study,an integrated approach coupling the hydrological model and copulabased design of precipitation and storm tides was proposed to assess the compound flood risk in a coastal city—Haikou,China.The copula model,most-likely weight function,and varying parameter distribution were used to obtain the combined design values of precipitation and storm tides under the nonstationary scenario,which were applied to the boundary conditions of the 1D-2D hydrological model.Subsequently,the change of the bivariate return periods,design values,and compound flood risks of precipitation and storm tides were investigated.The results show that the bivariate return period of precipitation and storm tides was reduced by an average of 34%under the nonstationary scenario.The maximum inundation areas and volumes were increased by an average of 31.1%and 45.9%respectively in comparison with the stationary scenario.Furthermore,we identified that the compound effects of precipitation and storm tides would have a greater influence on the flood risk when the bivariate return period is more than 50 years,and the peak time lag had a significant influence on the compound flood risk.The proposed framework is effective in the evaluation and prediction of flood risk in coastal cities,and the results provide some guidance for urban disaster prevention and mitigation.

Barriers and Drivers for Mainstreaming Nature-Based Solutions for Flood Risks: The Case of South Korea

Nature-based solutions(NBS)are seen as a promising adaptation measure that sustainably deals with diverse societal challenges,while simultaneously delivering multiple benefits.Nature-based solutions have been highlighted as a resilient and sustainable means of mitigating floods and other hazards globally.This study examined diverging conceptualizations of NBS,as well as the attitudinal(for example,emotions and beliefs)and contextual(for example,legal and political aspects)barriers and drivers of NBS for flood risks in South Korea.Semistructured interviews were conducted with 11 experts and focused on the topic of flood risk measures and NBS case studies.The analysis found 11 barriers and five drivers in the attitudinal domain,and 13 barriers and two drivers in the contextual domain.Most experts see direct monetary benefits as an important attitudinal factor for the public.Meanwhile,the cost-effectiveness of NBS and their capacity to cope with flood risks were deemed influential factors that could lead decision makers to opt for NBS.Among the contextual factors,insufficient systems to integrate NBS in practice and the ideologicalization of NBS policy were found to be peculiar barriers,which hinder consistent realization of initiatives and a long-term national plan for NBS.Understanding the barriers and drivers related to the mainstreaming of NBS is critical if we are to make the most of such solutions for society and nature.It is also essential that we have a shared definition,expectation,and vision of NBS.

Flood Risk Mapping of the Benin Municipalities at the Intersection of the Coastal Sedimentary Zone and the Crystalline Surface

Climate change and population growth have led to the increase and/or intensification of flooding becoming a major issue. The objective of this study is to visualize flooding risk of municipalities at the intersection of the coastal sedimentary zone and the crystalline surface. The methodology adopted is based on geomatic approach, which involves documentary research, processing and assisted classification using remote sensing images and multi-criteria analysis of the Geographic Information System (GIS). Flooding risk is very high at 8.85% in Djidja, Toffo, Zè and Bonou municipalities. In other municipalities such as Agbangnizoun, Abomey, Bohicon, Za-Kpota and Cove, it is high of 46.85%. To the Southeast of the study area, it is located on the eastern and western banks of Oueme Valley. The medium risk represents 26.35% and is located in the municipalities of Ouinhi and Adjohoun. The other municipalities have a low rate of 17.95%. Risk modeling has made it possible to access the various levels of rising water that can cause flooding. Land-use planning decisions can be influenced by the results of this study.

Mapping of Flood Risk Zones Using Multi-Criteria Approach and Radar a Case Study of Ala and Akure-Ofosu Communities, Ondo State, Nigeria

Floods are among the worst natural catastrophes, devastating homes, businesses, public buildings, farms, and crops. Studies show that it’s not the flood itself that’s deadly but people’s vulnerability. This study investigates the Ala and Akure-Ofosu flood-prone zones;identifies elements that cause flooding in the study area;classifies each criterion by its effect;develops a flood risk map;estimates flood damage using Sentinel-1A SAR data;compares AHP results. Literature study and GIS-computer database georeferenced fieldwork data. Photos from the 2020 Sentinel 2A satellite have been organized. Built-up area, cropland, rock, the body of water, and forest Land use and cover, slope, rainfall, soil, Euclidean River Distance, and flow accumulation were mapped. These variables were integrated into a Multi-Criteria Analysis (MCA) using GIS tools, resulting in the creation of a flood risk map that categorizes the region into five risk zones: 5% of the area is identified as high-risk, 21% as low-risk, and 74% as moderate-risk. Copernicus SAR data from before and after the flood were processed on Google Earth Engine to map flood extent and ensured that the MCA map accurately reflected flood-prone areas. Periodic review, real-time flood susceptibility monitoring, early warning, and quick damage assessment are suggested to avoid flood danger and other environmental problems.

GIS-Based Identification of Flood Risk Zone in a Rural Municipality Using Fuzzy Analytical Hierarchy Process(FAHP)

Risk assessment is vital for humanities,especially in assessing natural and manmade hazards.Romblon,an archipelagic province in the Philippines,faces frequent typhoons and heavy rainfall,resulting in floods,with the Municipality of Santa Fe being particularly vulnerable to its severe damage.Thus,this research study intends to evaluate the flood risk of Santa Fe spatially using the fuzzy analytical hierarchy process(FAHP),taking into account data sourced fromvarious government agencies and online databases.GIS was utilized tomap flood-prone areas in the municipality.Hazard assessment factors included average annual rainfall,elevation,slope,soil type,and flood height.Distance to river,distance to road,types of building structure,mean age,gender ratio,and average annual incomewere considered parameters of vulnerability assessment.Exposure assessment considered land use,distance to evacuation facility,household number,and population density.Weights for each parameter were determined through pairwise comparison performed by experts.These weights were then incorporated into risk assessment estimation.The developed risk map identifies five high-risk barangays(small local government units).The study’s findings will enable local government units to establish flood mitigation programs,implement targeted mitigation measures,and formulate strategic response plans to lower risk and safeguard the residents of Santa Fe effectively.

Using Machine Learning to Determine the Efficacy of Socio-Economic Indicators as Predictors for Flood Risk in London

This study examines how socio-economic characteristics predict flood risk in London,England,using machine learning algorithms.The socio-economic variables considered included race,employment,crime and poverty measures.A stacked generalization(SG)model combines randomforest(RF),support vector machine(SVM),and XGBoost.Binary classification issues employ RF as the basis model and SVM as the meta-model.In multiclass classification problems,RF and SVM are base models while XGBoost is meta-model.The study utilizes flood risk labels for London areas and census data to train these models.This study found that SVM performs well in binary classifications with an accuracy rate of 0.60 and an area under the curve of 0.62.XGBoost outperforms other multiclass classification methods with 0.62 accuracy.Multiclass algorithms may perform similarly to binary classification jobs due to reduced data complexity when combining classes.The statistical significance of the result underscores their robustness,respectively.The findings reveal a significant correlation between flood risk and socio-economic factors,emphasizing the importance of these variables in predicting flood susceptibility.These results have important implications for disaster relief management and future research should focus on refining these models to improve predictive accuracy and exploring socio-economic factors.

Farmers＇ vulnerability to flood risk： A case study in the Poyang Lake Region

This paper quantitatively explores farmers＇ vulnerability to flood in the Poyang Lake Region （PLR） with the supports of GIS spatial functions. The analysis consists of three major steps, which is based on the spatial unit of township. Firstly, the spatial extent and characteristics of flood risk areas were determined using a digital elevation model （DEM） derived from the 1：50,000 topographic map. Secondly, for each of the township, six indices indicating the economic activities of local farmers were calculated. These indices are： rural population proportion, cultivated land proportion, GDP per unit area, employment proportion of primary industry, net rural income per capita and agricultural income proportion. These six indices were then normalized and used for later vulnerability assessment. Thirdly, the normalized indices （as GIS data layers） were overlaid with the flood risk areas to produce the risk coefficient for each township and to calculate the overall vulnerability for each township. The analysis results show that in the PLR there are high flood risk areas where the farmers＇ livings are seriously influenced or threatened. About 55.56% of the total 180 townships in the flood risk areas have a high degree of flood vulnerability. The townships under flood risk are mainly distributed in the areas around the Poyang Lake and the areas along the ＂five rivers＂.

From China’s Heavy Precipitation in 2020 to a “Glocal” Hydrometeorological Solution for Flood Risk Prediction

The prolonged mei-yu/baiu system with anomalous precipitation in the year 2020 has swollen many rivers and lakes,caused flash flooding,urban flooding and landslides,and consistently wreaked havoc across large swathes of China,particularly in the Yangtze River basin.Significant precipitation and flooding anomalies have already been seen in magnitude and extension so far this year,which have been exerting much higher pressure on emergency responses in flood control and mitigation than in other years,even though a rainy season with multiple ongoing serious flood events in different provinces is not that uncommon in China.Instead of delving into the causes of the uniqueness of this year’s extreme precipitation-flooding situation,which certainly warrants in-depth exploration,in this article we provide a short view toward a more general hydrometeorological solution to this annual nationwide problem.A“glocal”(global to local)hydrometeorological solution for floods(GHS-F)is considered to be critical for better preparedness,mitigation,and management of different types of significant precipitation-caused flooding,which happen extensively almost every year in many countries such as China,India and the United States.Such a GHS-F model is necessary from both scientific and operational perspectives,with the strength in providing spatially consistent flood definitions and spatially distributed flood risk classification considering the heterogeneity in vulnerability and resilience across the entire domain.Priorities in the development of such a GHS-F are suggested,emphasizing the user’s requirements and needs according to practical experiences with various flood response agencies.

Urban flood risk assessment under rapid urbanization in Zhengzhou City,China

With accelerated urbanization and climate change,urban flooding is becoming more and more serious.Flood risk assessment is an important task for flood management,so it is crucial to map the spatial and temporal distribution of flood risk.This paper proposed an urban flood risk assessment method that takes into account the influences of hazard,vulnerability,and exposure,by constructing a multi-index urban flood risk assessment framework based on Geographic Information System(GIS).To determine the weight values of urban flood risk index factors,we used the analytic hierarchy process(AHP).Also,we plotted the temporal and spatial distribution maps of flood risk in Zhengzhou City in 2000,2005,2010,2015,and 2020.The analysis results showed that,the proportion of very high and high flood risk zone in Zhengzhou City was 1.362%,5.270%,4.936%,12.151%,and 24.236%in 2000,2005,2010,2015,and 2020,respectively.It is observed that the area of high flood risk zones in Zhengzhou City showed a trend of increasing and expanding,of which Dengfeng City,Xinzheng City,Xinmi City,and Zhongmu County had the fastest growth rate and the most obvious increase.The flood risk of Zhengzhou City has been expanding with the development of urbanization.The method is adapted to Zhengzhou City and will have good adaptability in other research areas,and its risk assessment results can provide a scientific reference for urban flood management personnel.In the future,the accuracy of flood risk assessment can be further improved by promoting the accuracy of basic data and reasonably determining the weight values of index factors.The risk zoning map can better reflect the risk distribution and provide a scientific basis for early warning of flood prevention and drainage.

Modeling and Mapping Flood Hazard with a Flood Risk Assessment Tool: A Case Study of Austin, Texas

As a hazard, flood is an extremely important indicator of how a city is resilient to waterborne diseases and epidemics. Over many decades, flood as a hazard has been a major factor in inducing displacement of marginalized section of the people. Austin city within Central Texas has been identified as one of the major hotspots for flooding in recent decades. Thus, the objectives of the paper are two folded: 1) Empirically, we analyzed and mapped out the susceptibility levels from the factors of physical environments to assess the risk of urban flooding (rainfall data, surface water bodies and topography);in Austin, Texas and 2) Methodologically, we created a re-useable ArcGIS scripting tool that can be used by researchers to automate the process of flood risk modelling with certain criteria. The paper showcases a novel time sensitive building of a tool which will enable better visibility of flood within the city of Austin.

Flood Risk Analysis and Flood Potential Losses Assessment

The heavy floods in the Taihu Basin showed increasing trend in recent years. In this work, a typical area in the northern Taihu Basin was selected for flood risk analysis and potential flood losses assessment. Human activities have strong impact on the study area’s flood situation (as affected by the polders built, deforestation, population increase, urbanization, etc.), and have made water level higher, flood duration shorter, and flood peaks sharper. Five years of different flood return periods [(1970), 5 (1962), 10 (1987), 20 (1954), 50 (1991)] were used to calculate the potential flood risk area and its losses. The potential flood risk map, economic losses, and flood-impacted population were also calculated. The study’s main conclusions are: 1) Human activities have strongly changed the natural flood situation in the study area, increasing runoff and flooding; 2) The flood risk area is closely related with the precipitation center; 3) Polder construction has successfully protected land from flood, shortened the flood duration, and elevated water level in rivers outside the polders; 4) Economic and social development have caused flood losses to increase in recent years.

Flood risk assessment of check dams in the Wangmaogou watershed on the Loess Plateau of China

Check dams have been widely used in China’s Loess Plateau region due to their effectiveness in erosion and flood control.However,the safety and stability of the check dam decrease with the operation process,which increases the probability of dam failure during flood events and threatens local residents’ life and property.Thus,this study simulated flood process of the check dam failure in the Wangmaogou watershed in Yulin City,Shaanxi Province,China,calculated different types of inundation losses based on the flood inundation area within the watershed,and determined the number of key flood protection check dams by classifying the flood risk levels of the check dams.The results showed that 5 dams in the watershed were subject to overtopping during different rainfall return periods,which was related to their flood discharge capacity.Dam failure flood process showed a rapid growth trend followed by slow decrease,and the time of flood peak advanced with increase in the return period.After harmonization of evaluation scales,the magnitude of flood inundation losses can be ranked as:economic losses(212.409 million yuan) > life losses(10.368 million yuan) > ecological losses(6.433 million yuan).The risk value for both individual dams and the whole dam system decreases as the return period increases.The number of key flood protection check dams in the Wangmaogou watershed was 2,3,3,3,4,and 5 for floods with return periods of 10,20,30,50,100,and 200 years,respectively.The results provided a theoretical basis for the safe operation and risk evaluation of check dams in the Loess Plateau Hills watershed.

Assessing Future Flooding Risk in a Coastal Lagoon Using Hydrogeological Approaches and Analysis of the 2021 Flood Event: A Case Study of Tasi-Tolu Lagoon, Dili, Timor-Leste

This study aims to apply a hydrogeological approaches and analysis of the 2021 flood event of Tasi-Tolu Lagoon to achieve four specific goals. Firstly, the study seeks to determine the natural characteristics of the lagoon, which include factors such as size, depth, water quality, and ecosystem composition. Secondly, the influence of precipitation on the water volume in the lagoon will be examined. This analysis involves assessing historical rainfall patterns in the region, as well as the amount and frequency of precipitation during the 2021 flood event. Thirdly, the hydrogeologic and geologic conditions of the lagoon will be evaluated. This involves examining factors such as the type and structure of the soil and bedrock, the presence of aquifers or other underground water sources, and the movement of water through the surrounding landscape. Finally, the study seeks to assess the risk of future flooding in Tasi-Tolu Lagoon, based on the insights gained from the previous analyses. Overall, this study’s goal is to provide a comprehensive understanding of the hydrogeological factors that contribute to flooding in Tasi-Tolu Lagoon. This knowledge could be used to inform flood mitigation strategies or to improve our ability to predict and respond to future flooding events in the region.

Exploitation of Satellite Data for the Mapping of Areas at Risk of Flooding in Grand-Bassam (Côte d’Ivoire)

In order to better identify spatially the areas at risk of flooding for the riparian populations of Grand-Bassam during strong floods, a study aimed at developing hazard and vulnerability maps from RADAR Sentinel-1 and optical images Sentinel-2 has been put in place. The flood hazard study highlighted the flooded areas in Grand-Bassam. These areas represent 747.7 ha, or 1.02% of the total surface. The vulnerability map produced using the maximum likelihood method identified eight (8) land use classes. These are the classes Water, Dense forest, Secondary forest, Swamp forest, Industrial crops, Food crops, Habitats and bare soils. It made it possible to highlight the socio-economic interests of Grand-Bassam. The flood risk map developed from the intersection of the themes of the vulnerability map and that of the hazard has enabled the recognition of risk areas which are located near the source of the risk (Comoé River) and at low altitudes. These are Moossou, Petit Paris, Quartier Phare and Quartier France.

Community Based Flood Risk Management: Local Knowledge and Actor’s Involvement Approach from Lower Karnali River Basin of Nepal

Connecting to the disaster risk reduction (DRR) studies, community-based initiatives are found to be more effective in both developed and developing countries, with a specific focus on the empowerment of local communities to build resilience. Building on social capital theory, the paper investigates on local knowledge (LK) practices experienced by the actors in an emerging economy using the community-based flood risk management (CB-FRM) approach. The qualitative research method was used by collecting data from focused group discussions, and interviews with the key informants including actors from local governments and non-government organizations. Additionally, informal discussions, field visits, and desk studies were undertaken to support the findings. The findings reveal that the local communities carry out various local knowledge experiences to respond during disaster management phases. They own a creative set of approaches based on the LK and that empowers them to live in the flood-prone areas, accepting the paradigm shift from fighting with floods to living with that. The local actor’s involvement is recognized as an essential component for CB-FRM activities. Yet, their program’s implementation is more oriented towards humanitarian assistance in emergency responses. Even, they often overlook the role of LK. Additionally, the results show a high level of presence of local communities during the preparedness and recovery phases, while NGOs and local governments have a medium role in preparedness and low in recovery phase. The lack of local ownership has also emerged as the major challenge. The research provides valuable insights for integrated CB-FRM policies by adopting to LK practices.

Research on Flood Control Design Based on Joint Distribution of Flood Levels and Flood Peak Discharges

The return level of the joint distribution of flood levels and flood peak discharges was analyzed by Archimedean Gumbel-Hougaard copula and Kendall distribution functions.Using the annual maximum level(H)and discharge(Q)of flood peak at Boluo Hydrologic Station in the Dongjiang River in last 56 years,the"OR"return period,"AND"return period and Kendall return period of their joint distribution and the most likely design flood value were calculated.The main conclusions of this study can be summarized as follows:the Kendall return period can more accurately reflect the risk rate of the combination of flood elements,relative to"OR"return period and"AND"return period.The design value of univariate flood element based on the current specification can meet the design standard.While the design value calculated according to"OR"return period was on the high side,and the design value calculated by the"AND"return period was on low side.Based on the principle of maximum probability,the calculated design value of Kendall return period under the different combinations of flood peak discharge and water level can provide new options for flood control project safety and risk management.