Flood Risk Mitigation Strategies Research Articles

Elevating Pakistan’s flood preparedness: a fuzzy multi-criteria decision making approach

In South Asia, Pakistan has a long and deadly history of floods that cause losses to various infrastructures, lives, and industries. This study aims to identify the most appropriate flood risk mitigation strategies that the government of Pakistan should adopt. The assessment of flood risk mitigation strategies in this study is based on certain criteria, which are analyzed using the fuzzy full consistency method. Moreover, flood risk mitigation strategies are evaluated by using the fuzzy weighted aggregated sum product assessment (WASPAS) method, considering previously prioritized criteria. According to the results, lack of governance, lack of funding and resources, and lack of flood control infrastructure are the most significant flood intensifying factors and act as major criteria for assessing flood risk mitigation strategies in Pakistan. Adopting hard engineering strategies (e.g., dams, reservoirs, river straightening and dredging, embankments, and flood relief channels), maintaining existing infrastructure, and adopting soft engineering strategies (flood plain zoning, comprehensive flood risk assessment, and sophisticated flood modeling) are identified as the top three flood risk mitigation strategies by the fuzzy WASPAS method. The highest weight (0.98) was assigned to the adoption of hard engineering strategies to mitigate flood risks. The study introduces a novel dimension by analyzing the real-time impact of the unprecedented 2022 floods, during which approximately one-third of the nation was submerged. This focus on a recent and highly significant event enhances the study’s relevance and contributes a unique perspective to the existing literature on flood risk management. The study recommends that the government of Pakistan should prioritize hard engineering strategies for effective flood risk mitigation. It also recommends that the government should incorporate these strategies in the national policy framework to reduce flood losses in the future.

From data to decisions: evaluating flood vulnerability in the Sindh watershed through Analytical Hierarchy Process

Floods are recurrent global catastrophes causing substantial disruptions to human life, extensive land degradation, and economic losses. This study aims to identify flood-triggering watershed features and employ a Multi-Criteria Decision-Making (MCDM) approach based on the Analytical Hierarchy Process (AHP) model to delineate flood-prone zones. Weights for various flood-influencing factors (slope, rainfall, drainage density, land-use/land-cover, geology, elevation, and soil) were derived using a 7 × 7 AHP decision matrix, reflecting their relative importance. A Consistency Ratio (CR) of 0.089 (within acceptable limits) confirms the validity of the assigned weights. The analysis identified approximately 128.51 km2 as highly vulnerable to flooding, particularly encompassing the entire stretch of riverbanks within the watershed. Historically, snow avalanches and flash floods have been the primary water-related disasters in the region, posing significant threats to critical infrastructure. In this context, this model-based approach facilitates the proactive identification of susceptible areas, thereby promoting improved flood risk mitigation and response strategies.

The heterogeneity of human flood adaptation characteristics in Central Asia based on human-flood distance

The Central Asian region is subject to frequent seasonal floods, resulting in substantial losses. These recurrent floods have induced certain changes in human flood adaptation characteristics in Central Asia, an area that is currently under-researched. This study, grounded in meticulously simulated flood inundation outcomes, multisource population distribution data, and flood protection infrastructure data, introduces an improved approach to calculating the distance between human and flood (HFD) and investigates human flood adaptation characteristics in Central Asia. Our findings indicate that residents in Central Asia get close to flood-prone areas from 1970 to 2007, with the exceptions of Turkmenistan (TKM) and Kyrgyzstan (KGZ). Notably, this trend is particularly pronounced in regions such as Xinjiang, China, and Tajikistan (TJK). An intricate exponential increase is observed in the population exposed to floods as the HFD decreases. Under future scenarios, KGZ exhibits the most significant trend of staying away from flood-prone areas, while TJK presents the opposite trend, and TKM experiences minimal changes. Additionally, compared with urban areas, rural areas of Central Asia exhibit a trend towards approaching floods. This study underscores the optimum nature of human flood adaptation when the HFD reaches 4.23 km, showing the potential for substantial benefits by implementing population evacuation within this threshold buffer zone. These insights highlight the complex interplay between human behaviours and floods and can inform the formulation of effective flood risk mitigation strategies.

A participatory systems dynamic modelling approach to understanding flood systems in a coastal community in Cameroon

In the face of increasing flood risks and the need for effective management both at national and local levels, this study highlights a participatory approach that transcends conventional stakeholder consultation but delves into drawing insights through conceptual models that unveil the potential of the Participatory System Dynamic Modelling approach to mitigate flood risks, even at the grassroots level effectively. Through active stakeholder engagement, the study focuses on identifying and analysing the intricate interdependencies and feedback loops within the Limbe flood risk management system that are crucial for recommending comprehensive and actionable flood risk mitigation strategies for Limbe's cross-sectoral dynamics. By including flood experts and community stakeholders in the conceptual model construction, the study utilises an evaluative framework that accounts for system processes and outcomes, ensuring a holistic understanding of the flood risk system, considering scientific knowledge and real-life experiences. The findings underscore the value of participatory modelling techniques in facilitating the identification and prioritisation of intervention options by diverse stakeholders, thereby promoting active engagement in local flood risk management, a vital step in addressing the escalating challenges posed by climate change and natural disasters.

A Global Map for Selecting Stationary and Nonstationary Methods to Estimate Extreme Floods

Comprehending the changing patterns of flood magnitudes globally, particularly in the context of nonstationary conditions, is crucial for effective flood risk management. This study introduces a unique approach that employs simulated discharge data to unravel these intricate variations. Through a comprehensive analysis of a substantial ensemble of General Circulation Models (GCMs) runoff datasets, we examine the dynamics of nonstationary flood magnitudes on a global scale. A pivotal aspect of our investigation is the development of a reference map, which helps delineate suitable scenarios for applying stationary or nonstationary methods in estimating extreme floods. This map is then employed to compare estimations of 100-year flood magnitudes using both methodologies across specific geographical areas. Our findings distinctly highlight the disparities arising from the use of stationary versus nonstationary approaches for estimating extreme floods. These insights underscore the significance of considering nonstationary for accurate flood risk assessment and mitigation strategies. The practical utility of our reference map in aiding informed decision making for stakeholders and practitioners further underscores its importance. This study contributes to the scholarly understanding of the evolving nature of flood phenomena and provides valuable insights for crafting adaptive measures in response to changing climatic conditions.

FloodSafeHome: evaluating financial benefits and savings of freeboard for improved decision-making in flood risk mitigation

Freeboard—elevation of a structure above the base flood elevation (BFE)—is a critical component in mitigating or avoiding flood losses. However, the unrevealed benefits and savings of freeboard installation have prevented communities from adopting this approach. To improve decision-making for residents, prospective residents, and other stakeholders in flood-vulnerable communities and enhance flood risk mitigation strategies, this study presents the methodology underlying a new webtool, FloodSafeHome, that estimates comprehensively the economic benefits and savings of freeboard installation for new construction of residential buildings. Specifically, the proposed evaluation framework has been designed to calculate monthly savings for individual buildings by assessing freeboard cost, insurance savings per year, and expected annual flood loss. This new evaluation method is built into a web-based, decision-making tool for use by the public and community leaders in three southeastern Louisiana parishes (i.e., counties), to identify expected future benefits of building residences with freeboard and enhance their decision-making processes with interactive risk/benefit analysis features. For example, results indicate the levels of freeboard that optimize the cost-benefit ratio for flood-insured homes in the study area. This approach is expected to improve long-term flood resilience and provide cost-efficient flood mitigation strategies, particularly in disaster vulnerable regions.

FLOOD RISK ASSESSMENT, CLIMATE CHANGE ADAPTATIONS AND MITIGATION STRATEGIES OF COMMUNITIES IN EDO STATE, NIGERIA

Despite flooding being one of the most common and destructive natural hazards, the risk it poses is systematically underestimated and still increasing due to climate change and growing concentrations of people and assets in flood-prone areas. The study carried out a flood risk assessment, climate adaptation and mitigation strategies of communities in Edo State, Nigeria. With the aid of questionnaires and GIS techniques, the flood risk level of communities within Edo states were analysed by capturing all the components of flood risk which include exposure and vulnerability. All analysis was carried out using descriptive statistics and Analytical Hierarchy Process (AHP) to determine the extent of the communities’ flood. The extent of risk showed that 778 communities were captured in risk analysis, 503 (64.65%) of the communities were found within low flood risk level while 150 (19.28%) communities and 125 (16.07%) communities were found to be within medium and high flood risk level respectively. The climate variables showed some level of fluctuation while the adopted adaptation measures such as expansion of floodplain and wetlands was based on political will of administrators, and the measure was perceived less effective. There was high level of awareness about government mitigation measures in the area and the main mitigation measure by government is construction of drainage system which was perceived to be effective. It was therefore concluded that all the adopted attributes contributed to the establishment of flood risk of Edo State and was categories into high, medium and low flood risk level. Hence, there is need to intensify the planning and execution of disaster management programs with the support of the produced flood risk map.

Spatial-Temporal Sensitivity Analysis of Flood Control Capability in China Based on MADM-GIS Model.

To facilitate better implementation of flood control and risk mitigation strategies, a model for evaluating the flood defense capability of China is proposed in this study. First, nine indicators such as slope and precipitation intensity are extracted from four aspects: objective inclusiveness, subjective prevention, etc. Secondly, the entropy weight method in the multi-attribute decision making (MADM) model and the improved three-dimensional technique for order preference by similarity to ideal solution (3D-TOPSIS) method were combined to construct a flood defense capacity index evaluation system. Finally, the receiver operating characteristic (ROC) curve and the Taylor plot method were innovatively used to test the model and indicators. The results show that nationwide, there is fine flood defense performance in Shandong, Jiangsu and room for improvement in Guangxi, Chongqing, Tibet and Qinghai. The good representativity of nine indicators selected by the model was verified by the Taylor plot. Simultaneously, the ROC calculated area under the curve (AUC) was 70%, which proved the good problem-solving ability of the MADM-GIS model. An accurate assessment of the sensitivity of flood control capacity in China was achieved, and it is suitable for situations where data is scarce or discontinuous. It provided scientific reference value for the planning and implementation of China’s flood defense and disaster reduction projects and emergency safety strategies.

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.

Advancing flood warning procedures in ungauged basins with machine learning

Flood prediction across scales and more specifically in ungauged areas remains a great challenge that limits the efficiency of flood risk mitigation strategies and disaster preparedness. Building upon the recent success of Machine Learning (ML) models on streamflow prediction, this work presents a prototype ML-based framework for flood warning and flood peak prediction. The fundamental elements of the proposed system consist of a) a Long-Short Term Memory (LSTM) model for classifying storm events to Flood/no-Flood given a threshold based on the 90th flow percentile and b) the flood peak prediction models. The selected ML-models for flood peak prediction are the Histogram based Gradient Boosting Regressor and the Random Forest. One of the strengths, and reason for selection, of these decision-tree models is their degree of interpretability. This is exploited in the study to help us spatially disentangle the role of both the static and dynamic drivers of flood peak response. Our analysis is presented for 18 distinct hydroclimatic regions across the contiguous US. Results reveal a significant regional dependence on both predictive performance and dominant flood predictors, which emphasize the variability in the complexity of a catchment’s hydrologic behavior as well as its impact on forecasting flood response. Evaluation of the drivers of flood peaks noted distinct dependencies among the dynamic and static predictors considered in our models for flood peaks of different severity. Specifically, low-moderate flood events showed a clear preponderance for the static catchment attributes over dynamic predictors like precipitation whereas precipitation was the dominant driver for the highest flood peaks. The proposed flood peak prediction models were compared against a state-of-the-art LSTM model and were shown to outperform in ungauged basins for the majority of basins. Overall, the proposed system classified storms correctly for >80% in all cases and exhibited a percent relative difference in flood peak estimates of <30% in most cases.

Present vs. Future Property Losses From a 100-Year Coastal Flood: A Case Study of Grand Isle, Louisiana

Louisiana, U.S.A., is among the world's most vulnerable places to coastal flooding. Increasing frequency/intensity of natural hazards under climate change scenarios is expected to exacerbate Louisiana's coastal flood risk. Although many factors are involved, land subsidence from marshland compaction and underground resource extraction, shoreline erosion accelerated by eustatic sea level rise (ESLR), and tropical-cyclone-induced storm surge are among the most important. While past research has focused on flood risk assessment and mitigation strategies, including climate change scenarios, few studies examine all of these factors collectively. This study shows present pluvial flood depth and the contributions of additional coastal subsidence and ESLR toward future (2050) pluvial flooding. Then, current tropical-storm-induced storm surge and future storm surge depth modeled by Louisiana's Coastal Protection and Restoration Authority (CPRA) under climate change scenarios are presented. Present and future 100-year pluvial flood and storm surge losses (separately, 2020$) to structures and their contents are estimated at the individual building level for Grand Isle, Louisiana, a barrier island town of ecological, economic, historical, recreational, cultural, and aesthetic treasure. Results suggest that the average 100-year pluvial flood depth in buildings will increase by 1.35 feet by 2050, with subsidence contributing over 82% of this total. Subsidence is projected to escalate structure and content losses by ~17% above losses in 2017, while ESLR may contribute ~3% above 2017 losses. A 100-year tropical-cyclone-induced storm surge event amid a “low” scenario of environmental change as defined by CPRA would increase Grand Isle's structure and content losses by 68–74% above the 2017 value by 2027, 141–149% by 2042, and 346–359% by 2067. The (“high”) scenario of environmental change would increase the 100-year storm surge losses by 85–91% above the 2017 value by 2027, 199–218% by 2042, and 407–415% by 2067. Outcomes from this study will offer a more realistic risk assessment model and will direct flood risk managers, property owners, and other stakeholders to build a comprehensive framework to minimize future flood risk in one of the most vulnerable sites in the U.S.A. to coastal flooding.

Participatory Approaches to Urban Flood Risk Mitigation and Adaptation Strategies Projects: A Scoping Review of the Global South Evidence

Participatory approaches to urban flood risk adaptation initiatives have been prominent amongst developed countries, particularly in Europe, since the 2000s and are now steadily on the rise in the Global South. In this article we focus on how international examples of community-based participatory research and practice have managed flooding risk mitigation and adaptation strategies, specifically in the Global South. While top-down resistance-based approaches that include infrastructure, technology, laws and regulations offer invaluable information for urban planners and policy-makers they however fall short on revealing the perceptions and behaviours that shape individual, household and community adaptation decision-making process. In addition, these top-down approaches tend to take a long-term view of change with new programmes or policies, implemented over time, failing to tackle current challenges. The aim of this scoping review is therefore to map out the key concepts underpinning this research area and the main sources of evidence addressing community-based flooding monitoring, mitigation and adaptation strategies to uncover practices that facilitate participatory models of working between researchers, urban developers/designers, government institutions, and local communities. Finally, this evidence-based synthesis serves as background to the presentation of a Mexican case-study in which a community-based participatory approach is employed to support a co-production process for the identification of local flood risk management options.

Mapping Coastal Flood Susceptible Areas Using Shannon’s Entropy Model: The Case of Muscat Governorate, Oman

Floods are among the most common natural hazards around the world. Mapping and evaluating potential flood hazards are essential for flood risk management and mitigation strategies, particularly in coastal areas. Several factors play significant roles in flooding and recognizing the role of these flood-related factors may enhance flood disaster prediction and mitigation strategies. This study focuses on using Shannon’s entropy model to predict the role of seven factors in causing floods in the Governorate of Muscat, Sultanate of Oman, and mapping coastal flood-prone areas. The seven selected factors (including ground elevation, slope degree, hydrologic soil group (HSG), land use, distance from the coast, distance from the wadi, and distance from the road) were initially prepared and categorized into classes based on their contribution to flood occurrence. In the next step, the entropy model was used to determine the weight and contribution of each factor in overall susceptibility. Finally, results from the previous two steps were combined using ArcGIS software to produce the final coastal flood susceptibility index map that was categorized into five susceptibility zones. The result indicated that land use and HSG are the most causative factors of flooding in the area, and about 133.5 km2 of the extracted area is threatened by coastal floods. The outcomes of this study can provide decision-makers with essential information for identifying flood risks and enhancing adaptation and mitigation strategies. For future work, it is recommended to evaluate the reliability of the obtained result by comparing it with a real flooding event, such as flooding during cyclones Gonu and Phet.

District based flood risk assessment in Istanbul using fuzzy analytical hierarchy process

Floods, among the most frequent and severe hazards in the world, threaten the sustainability of the built environment by causing immense damage to infrastructures, buildings, economies, social activities and beyond all, cause loss of lives. Istanbul is the most densely populated industrial, commercial and cultural center of Turkey. Besides, the population of Istanbul has increased over the last decade since the city attracts immigrants from all over Turkey, along with other countries. Therefore, it is vital to prioritize the districts of Istanbul by determining flood risk mitigation strategies since flood risk management is carried out at district level units in local municipalities in Istanbul. In this study, a new hierarchical procedure that consists of thirteen flood vulnerability and hazard criteria is proposed for the generation of Istanbul’s district-based flood risk map. To obtain the criteria weights the fuzzy analytical hierarchy process (AHP) was adopted. The sensitivity analysis conducted in this study reveals the stability and robustness of the proposed fuzzy AHP model. Among all the criteria, land use and the return period of a storm event were found as the most significant criteria for vulnerability and hazard clusters, respectively. Criteria weights calculated through the fuzzy AHP method were integrated with the data taken from various institutions with respect to each district to calculate risk scores of the districts. Consequently, district risk scores were used to generate a flood risk map of Istanbul. The findings show that high-risk districts are mainly at the center and highly populated areas of the city. Moreover, the accuracy of the proposed approach was validated through observations of the significant flood events experienced in the last two decades. Thus, the fuzzy AHP method can be considered as advantageous to make a quick and regional flood risk assessment. In addition, the proposed approach is useful to mitigate flood risk along with allocating a fair budget to the local municipalities for flood risk mitigation measures. The findings of this research could also provide useful procedures for professionals of the water resources and local authorities.

Flood risk perception and its determinants among rural households in two communities in Khyber Pakhtunkhwa, Pakistan

Risk perception plays a vital part in flood risk management and mitigation strategies. Therefore, this study aims at first to measure the risk perception of the vulnerable households in the rural areas of Pakistan and, second, to assess the determinants and to estimate their impacts on risk perception among different groups of households. Data were collected through questionnaire survey from 382 respondents in two districts of Khyber Pakhtunkhwa province, Pakistan. Risk perception was measured through a Likert scale for a set of indicators, and the composite index was calculated. Moreover, univariate and multivariate logistic models were applied to explore the relationship between dependent and independent variables. Results of risk perception show that 50.52% of the respondents perceived a high risk of floods in the study area. Results of regression models show that the age group 40–50 years was less likely to perceive a high risk of floods. Respondents with flood experience, education (higher secondary and above), household location (near the bank of streams) and household distance from the river (≤ 500) were more likely to perceive high floods risk. Furthermore, respondents in the riverine flood-prone areas perceived high flood risk than respondents in the flash flood-prone regions. The study contributes in terms of useful information about the risk perception of floods and the determinants of flood risk perception in rural areas. These findings can help the provincial disaster management authorities and local disaster management units in understanding flood risk and implementing relevant interventions at the local level that can be used in adaptation to floods and other climate-induced disasters.

Slackwater Sediments Record the Increase in Sub-daily Rain Flood due to Climate Change in a European Mediterranean Catchment

In this work we propose an original method to determine the magnitude of the discharge, the intensity of the precipitation and the duration of short-rain floods in small torrential basins ( 24 h). The need is evident for safety designs of civil infrastructures and flood risk mitigation strategies in the current climate change scenario.

Can Citizen Science Promote Flood Risk Communication?

This article explores the challenges facing citizen science as a means of joining the efforts of scientists and flood-risk affected stakeholders in motivating citizen involvement in identifying and mitigating flood risks. While citizen science harbors many advantages, including a penchant for collaborative research and the ability to motivate those affected by floods to work with scientists in elucidating and averting risk, it is not without challenges in its implementation. These include ensuring that scientists are willing to share authority with amateur citizen scientists, providing forums that encourage debate, and encouraging equal voice in developing flood risk mitigation strategies. We assess these challenges by noting the limited application of citizen science to flood-relevant problems in existing research and recommend future research in this area to meaningfully incorporate a “re-imagined” citizen science process that is based on the participatory theoretical framework. We also discuss one case study where the principles of collaboration, debate, and equal voice were put into play in an effort to apply citizen science and—in the long term—mitigate flood hazards in one set of communities.

Synthesized trade-off analysis of flood control solutions under future deep uncertainty: An application to the central business district of Shanghai

Coastal mega-cities will face increasing flood risk under the current protection standard because of future climate change. Previous studies seldom evaluate the comparative effectiveness of alternative options in reducing flood risk under the uncertainty of future extreme rainfall. Long-term planning to manage flood risk is further challenged by uncertainty in socioeconomic factors and contested stakeholder priorities. In this study, we conducted a knowledge co-creation process together with infrastructure experts, policy makers, and other stakeholders to develop an integrated framework for flexible testing of multiple flood-risk mitigation strategies under the condition of deep uncertainties. We implemented this framework to the reoccurrence scenarios in the 2050s of a record-breaking extreme rainfall event in central Shanghai. Three uncertain factors, including precipitation, urban rain island effect and the decrease of urban drainage capacity caused by land subsidence and sea level rise, are selected to build future extreme inundation scenarios in the case study. The risk-reduction performance and cost-effectiveness of all possible solutions are examined across different scenarios. The results show that drainage capacity decrease caused by sea-level rise and land subsidence will contribute the most to the rise of future inundation risk in central Shanghai. The combination of increased green area, improved drainage system, and the deep tunnel with a runoff absorbing capacity of 30% comes out to be the most favorable and robust solution which can reduce the future inundation risk by 85% (±8%). This research indicates that to conduct a successful synthesized trade-off analysis of alternative flood control solutions under future deep uncertainty is bound to be a knowledge co-creation process of scientists, decision makers, field experts, and other stakeholders.

Urban flood susceptibility analysis using a GIS-based multi-criteria analysis framework

Pluvial flooding is a common type of natural hazard caused by rainfall events with high intensity and short duration, which may lead to substantial property damages, transportation interruptions, and casualties. Modern cities are susceptible to pluvial flooding due to dense population and advanced economic development. To facilitate the development of better flood control and risk mitigation strategies, this study presents a new quantitative flood susceptibility analysis framework to estimate the potential flood extents and scale. The framework is based on the multi-criteria decision-making methods within a platform of the geographic information system (GIS). A composite urban flood risk index (FRI) is derived from various flood conditioning factors. The FRI consists of flood vulnerability index, hazard factors, and resilience capacity indicators. The flood-susceptible map is generated using the GIS spatial analysis tools and the analytic hierarchy process method. Zhengzhou city, China, is selected as the case study area. The result map shows that the highly susceptible areas are mainly located in Jinshui District, accounting for 64% of the total area of the risk zone. To further validate this framework, a flood inventory map is produced by mapping 74 test locations identified through survey data in this area, followed by plotting a receiver operating characteristic (ROC) curve. The ROC shows an area under the curve of 74.27%, which validates the proposed framework. Compared with other methods, the proposed framework is particularly suitable for application in data-scarce cases.

Flood risk analysis: causes and landscape based mitigation strategies in Dire Dawa city, Ethiopia

BackgroundIn flood prone areas, understanding flood causing factors, assessing the flood induced risks and adopting landscape based mitigation strategies can increase the knowledge, awareness and individual initiatives to protect themselves and their properties using appropriate flood management measures before and during flood events. Dire Dawa city is located in the foothill of southern mountains from where rivers crossing the city are originated. The multidimensional causes of flood hazard and limited landscape based mitigation strategies in the study area have worsen the impacts of flooding. This study was conducted in the Dire Dawa city watershed with the aims of assessing flood causing factors and to propose landscape based flood mitigation strategies.ResultsTo meet the intended objectives, the study employed the collection of both primary and secondary data. The primary data were collected from 110 households located in flood vulnerable villages. Moreover, the secondary data were collected from the Ethiopian Meteorology Agency, land use map of Dire Dawa city administration and government reports. Rainfall index method and descriptive statistics were used for analysis of primary data. The former was used to check the effect of intense rainfall and flood risk in terms of different duration yearly, monthly, daily and hourly basis, while the latter was used for identification of various factors precipitating flood risks of the study area. The analysis of secondary data employed morphometric analysis so as to identify flood susceptible sub-watersheds. Findings of the study indicated that flood risk in the study area has resulted from multiple factors such as intense rainfall, topography, encroachment to the river banks, institutional problems and aggravating factors resulted from power interruption during heavy rain and regime changes. More importantly, flood risk of the study area was found to be sensitive to hourly variation of rainfall distributions and varies on the location of the sub-watersheds. Following that, flood susceptibility of sub-watershed was ranked based on linear and shape morphometric parameters where higher values of linear and lower values of shape parameters were attributed to high flooding risk. Based on the prioritization of sub-watersheds’ susceptibility to flood risk through morphometric analysis, sub-watershed 5 and 18 were identified as the most flood risk susceptible watersheds demanding urgent landscape-based conservation measures. To this end suitable sites and sustainable water conservation structures are identified across the watersheds.ConclusionCheck dams, terracing, nala bunds, percolation tanks and storage tanks were proposed for different locations across the watershed as effective landscape-based flood risk mitigation strategies. The overall results of the study shows that managing the root causes of flooding at the upper catchments and adopting recommended proposed water conservation structures at proposed site helps to sustainably curb flood induced risks of Dire Dawa city.