Flood Risk Reduction Research Articles

Forecasting Gate-Front Water Levels Using a Coupled GRU–TCN–Transformer Model and Permutation Entropy Algorithm

Water level forecasting has significant impacts on transportation, agriculture, and flood control measures. Accurate water level values can enhance the safety and efficiency of water conservancy hub operation scheduling, reduce flood risks, and are essential for ensuring sustainable regional development. Addressing the nonlinearity and non-stationarity characteristics of gate-front water level sequences, this paper introduces a gate-front water level forecasting method based on a GRU–TCN–Transformer coupled model and permutation entropy (PE) algorithm. Firstly, an analysis method combining Singular Spectrum Analysis (SSA) and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is used to separate the original water level data into different frequency modal components. The PE algorithm subsequently divides each modal component into sequences of high and low frequencies. The GRU model is applied to predict the high-frequency sequence part, while the TCN–Transformer combination model is used for the low-frequency sequence part. The forecasting from both models are combined to obtain the final water level forecasting value. Multiple evaluation metrics are used to assess the forecasting performance. The findings indicate that the combined GRU–TCN–Transformer model achieves a Mean Absolute Error (MAE) of 0.0154, a Root Mean Square Error (RMSE) of 0.0205, and a Coefficient of Determination (R2) of 0.8076. These metrics indicate that the model outperforms machine learning Support Vector Machine (SVM) models, GRU models, Transformer models, and TCN–Transformer combination models in forecasting performance. The forecasting results have high credibility. This model provides a new reference for improving the accuracy of gate-front water level forecasting and offers significant insights for water resource management and flood prevention, demonstrating promising application prospects.

Cost benefit analysis of flood risk in the area of Thrace in Greece

Cost-benefit analysis can significantly aid the decision-making process for flood risk reduction and mitigation. Decision-makers can use it to weigh the expenses of various flood mitigation strategies against their possible upside in terms of lowering the risk of losses and damage. Decisions regarding how to allocate resources for flood risk management can be made more intelligently with the use of this information by policymakers and stakeholders. During severe rainfall or snowfall, these rivers are prone to flooding, which can harm structures such as homes, businesses, and infrastructure, have negative impacts to land uses and as a result they can cause high opportunity costs. Flooding in the Thrace region can have indirect and direct expenses, including property damage and lost commercial activity. These costs can include communication breakdowns and higher insurance rates. The predicted total economic losses from erosion for all of Greece are €356 million and €649 million for a 0.5- and 1-meter sea level increase, respectively.

An Urban Lake Drainage Catena: Influences of Terrain, Soils, and Precipitation

Urban lake drainage systems are heavily impacted by terrain, soil characteristics, and precipitation, which influence water infiltration and groundwater movement. This study focused on the drainage catena around Lake Nokomis in Minneapolis, Minnesota, where local residents have experienced wet basements and yards. The primary goal was to identify the factors contributing to these water-related problems, particularly soil permeability and how it responds to precipitation. By conducting soil borings, using pressure transducers, and measuring saturated hydraulic conductivity (Kfs), the study compared upland and lowland areas. Findings indicated that upland soils, primarily composed of sandy fill, had much higher infiltration rates, with Kfs values ranging from 72.4 cm/hr to 149 cm/hr. In contrast, lowland areas characterized by lacustrine and organic soils exhibited significantly lower Kfs values, ranging from 1 cm/hr to 14.8 cm/hr. Between 2022 and 2024, wet and dry seasons occurred, yet recorded more than 127.5 cm of rain and snow water equivalent, further contributing to groundwater rise and surface water presence in low-lying regions. The study concluded that increased precipitation, coupled with specific hydrogeologic conditions, was the main factor causing elevated groundwater levels and surface saturation in these areas. To address these challenges, Minnesota's water management authorities are encouraged to implement strategies that consider the increasing magnitude and intensity of precipitation events due to climate change. Incorporating hydrogeologic assessments into urban planning is recommended to better manage water infiltration, reduce flood risks, and strengthen the resilience of drainage systems to changing climate patterns.

Assessment of socio-economic strategies for managing regional flood risk in an urban coastal catchment

With the cascading flooding events over the past decades, several structural and non-structural measures have been effectively implemented for improved flood management. However, the uneven impacts of the flooding events have highlighted that socio-economic inequality amongst the community needs to be addressed along with hazards to devise long term and sustainable flood management strategies. This study aims to evaluate the impact of socio-economic adaptive scenarios over an urban coastal catchment for reduction in flood risk. Flood risk is estimated utilizing socio-economic aspects (vulnerability) and flood inundation (hazard), for the highly flood-prone coastal city of Mumbai, India. A multivariate approach is used for assessing socio-economic vulnerability, starting with Principal Component Analysis followed by Data Envelopment Analysis, for various socio-economic scenarios, i.e., by reducing percentage of certain feasible socio-economic sensitivity indicators, to identify the key indicators, which contribute to significant change in vulnerability. The flood hazard is assessed through a comprehensive hydrodynamic flood modelling approach to quantify the flood inundation depth and extent. The flood risk is, thereafter, evaluated by combining socio-economic vulnerability and flood hazard using bivariate risk mapping approach. The results indicate that, with the decrease in alteration percentage of certain feasible socio-economic sensitivity indicators, the overall vulnerability and flood risk may be reduced. The areas under very high and high vulnerability classes reduce gradually for all scenarios as the percentage reduction for various indicators is varied from 5 % to 15 %, total illiteracy being the most significant indicator. This study marks the first effort to discern socio-economic vulnerability indicators that have the potential to significantly diminish flood risk, thereby constituting a viable long-term flood risk mitigation strategy. This novel framework is generic and applicable to any flood prone catchments, to devise appropriate long-term flood management measures.

Sustainable Rain Solutions And Microbial Safety Research For Indian Water Crisis

Environmental Impact Awareness has always been the forefront of many surveys and solutions while trying to find the perfect know-it-all answer to the bigger question- “What do we have and What is getting depleted and finished?”. Water scarcity remains a pressing issue in arid and semi-arid regions of India, making rainwater harvesting a critical solution. This research investigates rainwater harvesting as a means to enhance water security, focusing on its benefits for water supply, flood risk reduction, and climate change mitigation. The paper outlines the stages of rainwater collection, transportation, and storage, emphasizing the technology required for active implementation while addressing sustainability concerns. Additionally, it reviews regulations such as the National Water Policy and microbial safety standards from the Bureau of Indian Standards (BIS) to ensure safe water. Findings on microbial testing, filtration technology, and community engagement for water conservation demonstrate a dual approach to water protection and public health. This study argues that rainwater harvesting not only serves as a water source but also has implications for antimicrobial resistance (AMR) in both potable and agricultural water. Ultimately, this work supports rainwater harvesting as a vital strategy for climate resilience and sustainable development in water-scarce regions

Agricultural land around river confluences could strongly suppress floods occurrences

Flooding poses a significant threat to socioeconomic systems, with risks expected to escalate in the future due to factors such as climate change and urbanization. Ecosystem-based disaster risk reduction (Eco-DRR) emphasizes the role of natural and seminatural ecosystems, particularly agricultural ecosystems, in disaster impact mitigation such as by flood prevention benefits. This study evaluates the effectiveness of Eco-DRR in agricultural land around river confluences across Japan, where frequent flooding occurs. Using flood occurrence data from 2010 to 2018 in 1,917 municipalities across Japan, statistical models were established incorporating agricultural land, urbanized areas, and the number of dams as explanatory variables to predict flood frequency. Previous studies have demonstrated that agricultural land located in the water storage zone contributes to flood suppression, whereas high land in urbanized areas is associated with increased flooding risk. Therefore, this condition was incorporated into the models. Two patterns were tested: one using all agricultural land and another focusing on agricultural land within a 1-km buffer around river confluences. The results demonstrate that agricultural land near river confluences significantly enhances flood suppression compared to all agricultural land. In contrast, urbanized areas within water storage zones were associated with increased flood risks. The findings suggest that conserving agricultural land in flood-prone confluence areas offers substantial flood mitigation benefits, whereas urban expansion in these areas heightens flood risks. Therefore, prioritizing the preservation of agricultural land around river confluences is crucial for flood risk reduction.

Actor-specific adaptation objectives shape perceived roles and responsibilities: lessons from Mumbai’s flood risk reduction and general considerations

Adaptation efforts need to be advanced significantly, involving multiple actors and a diverse portfolio of options. Despite this being well established, there is little understanding of different actors’ perceptions of adaptation goals and their associated expectations regarding roles and responsibilities to achieve them. In this analysis, we seek to address this gap by elucidating the diverging viewpoints held by various actor groups concerning adaptation objectives, target beneficiaries, and the distribution of roles and responsibilities for adaptation. Here, we use the case study of flood risk in Mumbai, drawing upon qualitative interview data collected through key informant interviews with diverse stakeholders including state, civil society, and academic actors. Interviews revealed stark disparities between state and non-state actors, in particular on the objective of efficiency, largely emphasized by state actors for physical infrastructure measures. Other contested objectives included ecosystem protection and fairness for vulnerable populations. The findings showed consensus on the importance of planning. Non-state actors heavily debated the lack of planning and implementation of institutional changes and ecosystem-based measures. They called for a stronger role of the state in caretaking and fairness for vulnerable populations, mainly through deeper institutional changes. Overall, the findings point to the urgent need for understanding how actors navigate competing priorities, make trade-offs, and negotiate conflicting viewpoints on the distribution of roles and responsibilities. This paper makes an empirical and conceptual contribution to the debates on “social contracts” for adaptation, offering an operationalization of the concept and application to a real-world example through an actor lens.

Briefing: How long-term monitoring of SuDS will inform next-generation guidance and modelling tools

Sustainable drainage systems (SuDS) are becoming more commonplace in urban environments due to the additional benefits they can provide alongside their core stormwater management function. In Mansfield, UK, Severn Trent Water is investing £76 million in retrofitting hundreds of SuDS to provide flood risk reduction to 90 000 people while simultaneously creating 5 ha of biodiversity-rich habitat. However, there is continued uncertainty about the long-term performance of these nature-based assets in comparison to traditional grey infrastructure. Through a new industrial–academic partnership, a long-term evaluation of SuDS performance across Mansfield will be used to inform the next generation of design guidance and modelling tools.

Multi-Source Remote Sensing Data for Wetland Information Extraction: A Case Study of the Nanweng River National Wetland Reserve

Wetlands play a vital role in regulating the global carbon cycle, providing biodiversity, and reducing flood risks. These functions maintain ecological balance and ensure human well-being. Timely, accurate monitoring of wetlands is essential, not only for conservation efforts, but also for achieving Sustainable Development Goals (SDGs). In this study, we combined Sentinel-1/2 images, terrain data, and field observation data collected in 2020 to better understand wetland distribution. A total of 22 feature variables were extracted from multi-source data, including spectral bands, spectral indices (especially red edge indices), terrain features, and radar features. To avoid high correlations between variables and reduce data redundancy, we selected a subset of features based on recursive feature elimination (RFE) and Pearson correlation analysis methods. We adopted the random forest (RF) method to construct six wetland delineation schemes and incorporated multiple types of characteristic variables. These variables were based on remote sensing image pixels and objects. Combining red-edge features, terrain data, and radar data significantly improved the accuracy of land cover information extracted in low-mountain and hilly areas. Moreover, the accuracy of object-oriented schemes surpassed that of pixel-level methods when applied to wetland classification. Among the three pixel-based schemes, the addition of terrain and radar data increased the overall classification accuracy by 7.26%. In the object-based schemes, the inclusion of radar and terrain data improved classification accuracy by 4.34%. The object-based classification method achieved the best results for swamps, water bodies, and built-up land, with relative accuracies of 96.00%, 90.91%, and 96.67%, respectively. Even higher accuracies were observed in the pixel-based schemes for marshes, forests, and bare land, with relative accuracies of 98.67%, 97.53%, and 80.00%, respectively. This study’s methodology can provide valuable reference information for wetland data extraction research and can be applied to a wide range of future research studies.

Analisis Tingkat Kerawanan Banjir di Sub Daerah Aliran Sungai (DAS) Kampar Kiri di Kecamatan Kampar Kiri

This study aims to describe and analyze the flood vulnerability level in the Kampar Kiri Sub-Watershed, Kampar Kiri District, as well as the extent of flood-prone areas impacting settlements in the region. The primary focus of this research is to understand the flood risk of the area and its effects on the existing settlements. The method applied in this study is Multi-Criteria Evaluation (MCE) using a Geographic Information System (GIS) approach. MCE is used to determine the weights of parameters affecting flood vulnerability and to select appropriate methods for analysis. This approach has proven effective and efficient in flood risk analysis, as demonstrated in previous studies. The parameters analyzed include slope, elevation, rainfall, soil type, land use, and distance from rivers, which are calculated using scoring methods and overlaid to produce a flood vulnerability map. The results indicate that the flood vulnerability level in the Kampar Kiri Sub-Watershed is categorized into three classes: not vulnerable, vulnerable, and highly vulnerable. The areas for each class are: not vulnerable with 16,854 hectares, vulnerable with 58,543 hectares, and highly vulnerable with 11,506 hectares. The extent of settlements in the vulnerability zones includes: vulnerable zone with an area of 277 hectares (approximately 20.83%), and highly vulnerable zone with an area of 1,054 hectares (approximately 79.17%). Based on these findings, it is recommended that the Kampar Kiri District government enhance land use planning to reduce flood risks, collaborate with the Kampar Public Works and Spatial Planning Office, and improve infrastructure such as drainage channels and flood protection embankments.

Assessment of Climate Change Impact on Flood Hazard Zones

AbstractThere have been many destructive pluvial and fluvial floods in Poland and the projection of increasing flood hazards in the future is a reason of considerable concern. The maps of river hazard zones are changing over time, and understanding these changes is of primary importance for flood risk reduction and climate change adaptation. This article aims to assess the impact of climate change on the spatial extent and depth classes of flood hazard zones for a selected reach of the River Warta in the western part of Poland. To this end, we integrated the Soil & Water Assessment Tool (SWAT) hydrological model of the Warta River Basin with the 1D hydraulic model HEC-RAS of the selected reach. The climate change effect was quantified based on the coupled model simulations forced with bias-corrected projections from the EURO-CORDEX project. Flood hazard maps were developed for two townships along the River Warta (Oborniki and Wronki), three greenhouse gas concentration scenarios (one for the baseline scenario in the reference period, 1971–2000; one for RCP 4.5 and one for RCP 8.5, for the time horizon 2021–2050) and for three return periods (10-, 100- and 500-year floods). Based on the ensemble mean, the increase in the flooded area projected in the future is more pronounced for RCP8.5 than for RCP4.5. This unique combination of software and data enabled the transformation of climate change impact into the land surface part of the hydrological cycle and assessment of changes in flood hazard and opens the way to assess the potential increases in the economic losses in the future.

Enhancing Co-Benefits and reducing Flood Risks through Nature-based Solutions and Assessments: A Case Study in the Dead Sea Region of Jordan

Enhancing Co-Benefits and reducing Flood Risks through Nature-based Solutions and Assessments: A Case Study in the Dead Sea Region of Jordan

Green spaces and flood vulnerability in urbanising regions: a case study in the Philadelphia metropolitan area

ABSTRACT Flooding continues to be one of the most significant natural hazards, disproportionately impacting vulnerable populations in urbanising regions. This study aims to examine the relationship between green space density and flood vulnerability in the Philadelphia Metropolitan Area by integrating social and geophysical data. The research focuses on identifying areas where high flood vulnerability coincides with low green space availability, as these are critical regions for targeted intervention. Using social vulnerability indicators such as income, age, and housing characteristics, combined with geophysical factors like soil permeability and drainage density, the study assesses flood vulnerability across census block groups. Local Indicators of Spatial Association (LISA) and discriminant analysis were employed to detect spatial clusters with elevated flood risks and low green space density. Results reveal that these high-risk clusters are concentrated in densely urbanised areas such as Norristown, where lower-income and elderly populations are overrepresented. These findings reinforce broader environmental justice concerns, as socially vulnerable communities face compounded risks from both inadequate flood protection and limited access to green spaces. The study emphasises the need for integrated flood management, combining green infrastructure with structural interventions, to guide urban planners and policymakers in reducing flood risks and promoting environmental equity.

Smart hotspot detection using geospatial artificial intelligence: A machine learning approach to reduce flood risk

This study employs Geospatial Artificial Intelligence (GeoAI) and the Random Forest Machine Learning (ML) algorithm to enhance flood hazard assessments in Portugal. It utilizes NASA's LP DAAC (2023) Digital Elevation Model (DEM) and slope data from EPIC WEBGIS PORTUGAL DATA, offering detailed topographical insights for environmental planning. Additionally, it incorporates data on proximity to water bodies from the Portuguese Environment Agency and the European Environment Agency, and soil characteristics from EPIC WEBGIS PORTUGAL DATA, facilitating a thorough examination of flood risks. This approach prioritizes long-term land features over short-term weather patterns, providing a comprehensive understanding of flood vulnerability. The study processes data at a 1 km x 1 km resolution, adapting TIFF maps for compatibility with the Random Forest model. The produced flood hazard maps identify potential flood hotspots at both national and city levels, crucial for urban planning. These maps aid in assessing the vulnerability of key infrastructure and assets, such as transport networks and buildings. The research highlights the importance of integrating additional data on assets and socioeconomic factors to enhance urban resilience. It sets the stage for future research aimed at improving predictive accuracy and underscores the necessity of extensive geospatial analytics in managing infrastructure risks.

Integrated hydrological modelling and streamflow characterization of Gangotri Glacier meltwater

Runoff from glaciated catchments is an integrated process that includes glacier melt, snowmelt, rainfall and surface and subsurface runoff of meltwater from glacierized and non-glacierized areas. Monitoring and quantifying the contribution of the hydrologic components (snow, ice and rain) to river discharge in the Himalayan basins is essential for decision-making in the water sector, particularly in water resources management and flood risk reduction in the region. An attempt has been made to characterize and hydrologically model streamflow (Bhagirathi River) for the Gangotri Glacier (Central Himalaya, India). A semi-distributed conceptual hydrological model is used for the streamflow modelling and assessing the major streamflow components (snow melt, glacier melt and rainfall runoff). Initially, the model was calibrated using the available in situ hydro-meteorological records for the ablation seasons of 2013–14 to 2015–16 (3 years), and further validated for the ablation seasons of 2016–17 to 2018–19 (3 years). The model performed well for all the studied years except for some months, where abrupt changes in the contrasting weather parameters (precipitation and temperature) were recorded. In the Gangotri Glacier Valley (upper Bhagirathi River catchment), snowmelt contributed the largest portion (55.5%) to total streamflow followed by glacier melt (29.7%) and rainfall runoff components (14.7%).

Design and Optimization of Water Level Control Gate System in Malwathu Oya River, Sri Lanka

This research focuses on improving flood management of the Malwathu Oya River in Anuradhapura Historical City, Sri Lanka, by designing an efficient gate system for the weir of Halpan Ela in the Malwathu Oya River. Frequent flooding threatens agriculture, infrastructure, and public safety in this region. This research aims to enhance water level control in the upper reach of Halpan Ela Anicut by evaluating rainfall patterns, tank spillway efficiency, and gate operation challenges. Historical data on rainfall and tank spillage were analyzed. Flow simulations revealed significant pressure differences, with the existing gate structure showing an upstream pressure of 114,492.5 Pa at a maximum flow of 1740 m3/s, compared to 105,406 Pa for the new flap gate system at the same flow rate. This represents a pressure difference of 9 kPa, equivalent to a 0.9 m water head. Despite the system’s estimated cost of USD 0.1 million, the potential reduction in river flood damage, which currently exceeds USD 0.2 million annually, demonstrates its value. This research emphasizes the effectiveness of the flap gate system in reducing flood risks in Anuradhapura City compared to the existing gate type, though it is only a part of a broader flood mitigation strategy.

Interregional watershed services: Valuation of the benefits of controlled embankment breaches to manage urban flood risk

The Lower Mekong delta of Vietnam, particularly Can Tho city, is highly susceptible to flooding which urgently calls for significant efforts to mitigate urban flood risks. A possible measure to reduce flood risk is the application of controlled embankment breaches (CEB) in a rural province upstream. Utilising a Protection Motivation Theory approach, this paper uses a contingent valuation to assess the welfare effects of a reduction of flood risks in the city resulting from CEB in the upstream region of the delta. The findings revealed that households residing in the downstream areas of Vietnamese Mekong Delta were willing to financially support the implementation of the CEB upstream in An Giang city, as a measure to alleviate urban flood threats in Can Tho city. These results suggest that interregional cooperation, involving the concept of payments for watershed services between regional jurisdictions, may help to effectively mitigate flood risk in a low-lying population centre in a major river delta. As such, these findings can inform policies for urban flood risk mitigation regarding the development of a more comprehensive flood risk reduction strategy in similar geographical contexts.

For resilient rural shorelines: reviewing Nature-based Solutions for flood risk reduction in small coastal communities

Coastal flood risk poses a serious, existential threat to shoreline populations around the world both now and in the future. Unsurprisingly, global decision makers are considering their options – one of these being Nature-based Solutions – for effective disaster risk reduction which specifically targets coastal flooding. While strides have been made in the field of Nature-based Solutions for coastal flooding, much of this attention has been directed towards the urban setting, with a wealth of scholastic documentation to support this notion. The sizeable rural populations scattered throughout the world's small coastal communities, meanwhile, have been largely neglected in academic literature. Without this information, it is impossible to properly capture the full potential of Nature-based Solutions in (global) flood risk modelling endeavours or understand their role in the future of equitable disaster risk reduction. In light of this gap, we have reviewed the limited amount of existing literature from around the world involving the implementation and effectiveness of Nature-based Solutions in small coastal communities. We analysed 28 peer-reviewed studies to gather common themes and insights about the barriers and opportunities unique to these rural shorelines. Takeaways we have identified include a near consistent scarcity of resources (e.g., technical, financial, institutional) to implement disaster risk reduction measures; an abundance of space and opportune land use regimes which make Nature-based Solutions a highly plausible option; amplified nature contributions to people leading to larger benefits reaped from investments into Nature-based Solutions; and the presence of local knowledge regarding societal norms, climate patterns, and ecosystem capabilities. We argue that these four common themes point to the fact that more attention must be given to coastal flooding-focused Nature-based Solutions in the rural setting. As such, we present this collation as a starting point for future projects of similar setting and scope. We also recommend improving benefit-cost analysis methods as well as including local knowledge and other perspectives in future global assessments of coastal flood risk.

Urban green streets and water management safety hubs in public schools lots

Abstract Green Stormwater Infrastructure (GSI) represents an effective approach to enhance urban resilience to climate change, contributing to runoff regulation and localized flood risk reduction. This study examines the potential for transforming open spaces in public schools into safety hubs for stormwater management in Mediterranean urban contexts, drawing on best practices from North America. Through a methodological analysis combining Research Through Design and an international literary scoping review, case studies of schools in the Metropolitan City of Naples are presented and compared with U.S. projects implementing GSI in school areas. The results highlight the importance of strategic coordination guidelines for local administrators, designers, and school principals, aimed at planning, designing, and managing highly performant green infrastructure networks. An integrated and shared metropolitan-level approach can maximize environmental benefits, transforming schools into community centers for urban resilience education and participatory management of risks related to extreme weather events.

Towards integrated multi-risk reduction strategies: A catalog of flood and earthquake risk mitigation measures at the building and neighborhood scales

The integration of risk reduction measures for earthquakes and floods is a promising concept in the field of multi-hazard disaster risk reduction. However, existing studies mostly discuss it conceptually, often missing a focus on decision-making. This paper introduces a novel approach by examining synergies and trade-offs between earthquake and flood risk reduction measures. The paper first conducts a detailed analysis of selected measures for these two hazards. It then explores how these individual risk mitigation measures can be strategically integrated at the building level to maximize synergies, potentially resulting in time and cost savings. Furthermore, it discusses the limitations of current decision-making procedures for single-hazard risk mitigation selection when applied to multi-hazard risk (MHR) scenarios. To address these challenges, the study proposes new decision variables to be incorporated into existing Multi-Criteria Decision-Making frameworks with the aim of facilitating strategic risk reduction prioritization for MHR scenarios, ensuring sustainability and community resilience. To aid implementation (i.e., the phase in which the measure would be selected and tested in a series of case study buildings), a catalog of analyzed risk reduction measures is developed and provided as Supplementary Material. In future developments, this catalog will facilitate the integration of these measures into decision-support tools for evidence-based multi-hazard disaster risk reduction.