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Search Results (1,168)

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20 pages, 4109 KiB  
Review
Hydrology and Climate Change in Africa: Contemporary Challenges, and Future Resilience Pathways
by Oluwafemi E. Adeyeri
Water 2025, 17(15), 2247; https://doi.org/10.3390/w17152247 - 28 Jul 2025
Viewed by 218
Abstract
African hydrological systems are incredibly complex and highly sensitive to climate variability. This review synthesizes observational data, remote sensing, and climate modeling to understand the interactions between fluvial processes, water cycle dynamics, and anthropogenic pressures. Currently, these systems are experiencing accelerating warming (+0.3 [...] Read more.
African hydrological systems are incredibly complex and highly sensitive to climate variability. This review synthesizes observational data, remote sensing, and climate modeling to understand the interactions between fluvial processes, water cycle dynamics, and anthropogenic pressures. Currently, these systems are experiencing accelerating warming (+0.3 °C/decade), leading to more intense hydrological extremes and regionally varied responses. For example, East Africa has shown reversed temperature–moisture correlations since the Holocene onset, while West African rivers demonstrate nonlinear runoff sensitivity (a threefold reduction per unit decline in rainfall). Land-use and land-cover changes (LULCC) are as impactful as climate change, with analysis from 1959–2014 revealing extensive conversion of primary non-forest land and a more than sixfold increase in the intensity of pastureland expansion by the early 21st century. Future projections, exemplified by studies in basins like Ethiopia’s Gilgel Gibe and Ghana’s Vea, indicate escalating aridity with significant reductions in surface runoff and groundwater recharge, increasing aquifer stress. These findings underscore the need for integrated adaptation strategies that leverage remote sensing, nature-based solutions, and transboundary governance to build resilient water futures across Africa’s diverse basins. Full article
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37 pages, 1037 KiB  
Review
Machine Learning for Flood Resiliency—Current Status and Unexplored Directions
by Venkatesh Uddameri and E. Annette Hernandez
Environments 2025, 12(8), 259; https://doi.org/10.3390/environments12080259 - 28 Jul 2025
Viewed by 402
Abstract
A systems-oriented review of machine learning (ML) over the entire flood management spectrum, encompassing fluvial flood control, pluvial flood management, and resiliency-risk characterization was undertaken. Deep learners like long short-term memory (LSTM) networks perform well in predicting reservoir inflows and outflows. Convolution neural [...] Read more.
A systems-oriented review of machine learning (ML) over the entire flood management spectrum, encompassing fluvial flood control, pluvial flood management, and resiliency-risk characterization was undertaken. Deep learners like long short-term memory (LSTM) networks perform well in predicting reservoir inflows and outflows. Convolution neural networks (CNNs) and other object identification algorithms are being explored in assessing levee and flood wall failures. The use of ML methods in pump station operations is limited due to lack of public-domain datasets. Reinforcement learning (RL) has shown promise in controlling low-impact development (LID) systems for pluvial flood management. Resiliency is defined in terms of the vulnerability of a community to floods. Multi-criteria decision making (MCDM) and unsupervised ML methods are used to capture vulnerability. Supervised learning is used to model flooding hazards. Conventional approaches perform better than deep learners and ensemble methods for modeling flood hazards due to paucity of data and large inter-model predictive variability. Advances in satellite-based, drone-facilitated data collection and Internet of Things (IoT)-based low-cost sensors offer new research avenues to explore. Transfer learning at ungauged basins holds promise but is largely unexplored. Explainable artificial intelligence (XAI) is seeing increased use and helps the transition of ML models from black-box forecasters to knowledge-enhancing predictors. Full article
(This article belongs to the Special Issue Hydrological Modeling and Sustainable Water Resources Management)
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20 pages, 2524 KiB  
Article
From Silos to Synergy: Improving Coordination in Local Flood Management
by Wibke de Boer, Lucas Flath, Michèle Knodt and Britta Schmalz
Water 2025, 17(15), 2212; https://doi.org/10.3390/w17152212 - 24 Jul 2025
Viewed by 198
Abstract
Flood risk governance has gained increasing attention as climate change and urbanization amplify flood risks. While much of the literature has focused on national and supranational governance frameworks, sectoral integration, and public participation, there remains a critical gap in understanding horizontal coordination within [...] Read more.
Flood risk governance has gained increasing attention as climate change and urbanization amplify flood risks. While much of the literature has focused on national and supranational governance frameworks, sectoral integration, and public participation, there remains a critical gap in understanding horizontal coordination within municipal administrations—particularly in medium-sized cities. This study examines how local governments coordinate flood risk management across different departments and administrative units, identifying key challenges and enabling factors. Using a case study of Mörfelden-Walldorf, a medium-sized city in southern Hesse, Germany, we analyze the internal governance dynamics shaping flood resilience. The research highlights institutional fragmentation, sectoral silos, and resource constraints as key barriers to effective coordination while also identifying mechanisms that facilitate cross-departmental collaboration. By integrating insights from the public administration literature with flood governance scholarship, this study contributes to a more nuanced understanding of local-level flood risk governance. The findings provide practical implications for enhancing municipal flood resilience through improved governance structures and coordination mechanisms. Full article
(This article belongs to the Section Water and Climate Change)
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27 pages, 48299 KiB  
Article
An Extensive Italian Database of River Embankment Breaches and Damages
by Michela Marchi, Ilaria Bertolini, Laura Tonni, Luca Morreale, Andrea Colombo, Tommaso Simonelli and Guido Gottardi
Water 2025, 17(15), 2202; https://doi.org/10.3390/w17152202 - 23 Jul 2025
Viewed by 185
Abstract
River embankments are critical flood defense structures, stretching for thousands of kilometers across alluvial plains. They often originated as natural levees resulting from overbank flows and were later enlarged using locally available soils yet rarely designed according to modern engineering standards. Substantially under-characterized, [...] Read more.
River embankments are critical flood defense structures, stretching for thousands of kilometers across alluvial plains. They often originated as natural levees resulting from overbank flows and were later enlarged using locally available soils yet rarely designed according to modern engineering standards. Substantially under-characterized, their performance to extreme events provides an invaluable opportunity to highlight their vulnerability and then to improve monitoring, management, and reinforcement strategies. In May 2023, two extreme meteorological events hit the Emilia-Romagna region in rapid succession, causing numerous breaches along river embankments and therefore widespread flooding of cities and territories. These were followed by two additional intense events in September and October 2024, marking an unprecedented frequency of extreme precipitation episodes in the history of the region. This study presents the methodology adopted to create a regional database of 66 major breaches and damages that occurred during May 2023 extensive floods. The database integrates multi-source information, including field surveys; remote sensing data; and eyewitness documentation collected before, during, and after the events. Preliminary interpretation enabled the identification of the most likely failure mechanisms—primarily external erosion, internal erosion, and slope instability—often acting in combination. The database, unprecedented in Italy and with few parallels worldwide, also supported a statistical analysis of breach widths in relation to failure mechanisms, crucial for improving flood hazard models, which often rely on generalized assumptions about breach development. By offering insights into the real-scale behavior of a regional river defense system, the dataset provides an important tool to support river embankments risk assessment and future resilience strategies. Full article
(This article belongs to the Special Issue Recent Advances in Flood Risk Assessment and Management)
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23 pages, 2274 KiB  
Review
Nature-Based Solutions for Water Management in Europe: What Works, What Does Not, and What’s Next?
by Eleonora Santos
Water 2025, 17(15), 2193; https://doi.org/10.3390/w17152193 - 23 Jul 2025
Viewed by 379
Abstract
Nature-based solutions (NbS) are increasingly recognized as strategic alternatives and complements to grey infrastructure for addressing water-related challenges in the context of climate change, urbanization, and biodiversity decline. This article presents a critical, theory-informed review of the state of NbS implementation in European [...] Read more.
Nature-based solutions (NbS) are increasingly recognized as strategic alternatives and complements to grey infrastructure for addressing water-related challenges in the context of climate change, urbanization, and biodiversity decline. This article presents a critical, theory-informed review of the state of NbS implementation in European water management, drawing on a structured synthesis of empirical evidence from regional case studies and policy frameworks. The analysis found that while NbS are effective in reducing surface runoff, mitigating floods, and improving water quality under low- to moderate-intensity events, their performance remains uncertain under extreme climate scenarios. Key gaps identified include the lack of long-term monitoring data, limited assessment of NbS under future climate conditions, and weak integration into mainstream planning and financing systems. Existing evaluation frameworks are critiqued for treating NbS as static interventions, overlooking their ecological dynamics and temporal variability. In response, a dynamic, climate-resilient assessment model is proposed—grounded in systems thinking, backcasting, and participatory scenario planning—to evaluate NbS adaptively. Emerging innovations, such as hybrid green–grey infrastructure, adaptive governance models, and novel financing mechanisms, are highlighted as key enablers for scaling NbS. The article contributes to the scientific literature by bridging theoretical and empirical insights, offering region-specific findings and recommendations based on a comparative analysis across diverse European contexts. These findings provide conceptual and methodological tools to better design, evaluate, and scale NbS for transformative, equitable, and climate-resilient water governance. Full article
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25 pages, 6316 KiB  
Article
Integration of Remote Sensing and Machine Learning Approaches for Operational Flood Monitoring Along the Coastlines of Bangladesh Under Extreme Weather Events
by Shampa, Nusaiba Nueri Nasir, Mushrufa Mushreen Winey, Sujoy Dey, S. M. Tasin Zahid, Zarin Tasnim, A. K. M. Saiful Islam, Mohammad Asad Hussain, Md. Parvez Hossain and Hussain Muhammad Muktadir
Water 2025, 17(15), 2189; https://doi.org/10.3390/w17152189 - 23 Jul 2025
Viewed by 616
Abstract
The Ganges–Brahmaputra–Meghna (GBM) delta, characterized by complex topography and hydrological conditions, is highly susceptible to recurrent flooding, particularly in its coastal regions where tidal dynamics hinder floodwater discharge. This study integrates Synthetic Aperture Radar (SAR) imagery with machine learning (ML) techniques to assess [...] Read more.
The Ganges–Brahmaputra–Meghna (GBM) delta, characterized by complex topography and hydrological conditions, is highly susceptible to recurrent flooding, particularly in its coastal regions where tidal dynamics hinder floodwater discharge. This study integrates Synthetic Aperture Radar (SAR) imagery with machine learning (ML) techniques to assess near real-time flood inundation patterns associated with extreme weather events, including recent cyclones between 2017 to 2024 (namely, Mora, Titli, Fani, Amphan, Yaas, Sitrang, Midhili, and Remal) as well as intense monsoonal rainfall during the same period, across a large spatial scale, to support disaster risk management efforts. Three machine learning algorithms, namely, random forest (RF), support vector machine (SVM), and K-nearest neighbors (KNN), were applied to flood extent data derived from SAR imagery to enhance flood detection accuracy. Among these, the SVM algorithm demonstrated the highest classification accuracy (75%) and exhibited superior robustness in delineating flood-affected areas. The analysis reveals that both cyclone intensity and rainfall magnitude significantly influence flood extent, with the western coastal zone (e.g., Morrelganj and Kaliganj) being most consistently affected. The peak inundation extent was observed during the 2023 monsoon (10,333 sq. km), while interannual variability in rainfall intensity directly influenced the spatial extent of flood-affected zones. In parallel, eight major cyclones, including Amphan (2020) and Remal (2024), triggered substantial flooding, with the most severe inundation recorded during Cyclone Remal with an area of 9243 sq. km. Morrelganj and Chakaria were consistently identified as flood hotspots during both monsoonal and cyclonic events. Comparative analysis indicates that cyclones result in larger areas with low-level inundation (19,085 sq. km) compared to monsoons (13,829 sq. km). However, monsoon events result in a larger area impacted by frequent inundation, underscoring the critical role of rainfall intensity. These findings underscore the utility of SAR-ML integration in operational flood monitoring and highlight the urgent need for localized, event-specific flood risk management strategies to enhance flood resilience in the GBM delta. Full article
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35 pages, 2334 KiB  
Article
Identification of Critical Exposed Elements and Strategies for Mitigating Secondary Hazards in Flood-Induced Coal Mine Accidents
by Xue Yang, Chen Liu, Langxuan Pan, Xiaona Su, Ke He and Ziyu Mao
Water 2025, 17(15), 2181; https://doi.org/10.3390/w17152181 - 22 Jul 2025
Viewed by 176
Abstract
Natech events, involving multi-hazard coupling and cascading effects, pose serious threats to coal mine safety. This paper addresses flood-induced Natech scenarios in coal mining and introduces a two-stage cascading analysis framework based on hazard systems theory. A tri-layered network—comprising natural hazards, exposed elements, [...] Read more.
Natech events, involving multi-hazard coupling and cascading effects, pose serious threats to coal mine safety. This paper addresses flood-induced Natech scenarios in coal mining and introduces a two-stage cascading analysis framework based on hazard systems theory. A tri-layered network—comprising natural hazards, exposed elements, and secondary hazards—models hazard propagation. In Stage 1, an improved adjacency information entropy algorithm with multi-hazard coupling coefficients identifies critical exposed elements. In Stage 2, Dijkstra’s algorithm extracts key risk transmission paths. A dual-dimensional classification method, based on entropy and transmission risk, is then applied to prioritize emergency responses. This method integrates the criticality of exposed elements with the risk levels associated with secondary disaster propagation paths. Case studies validate the framework, revealing: (1) Hierarchical heterogeneity in the network, with surface facilities and surrounding hydrological systems as central hubs; shaft and tunnel systems and surrounding geological systems are significantly affected by propagation from these core nodes, exhibiting marked instability. (2) Strong risk polarization in secondary hazard propagation, with core-node-originated paths being more efficient and urgent. (3) The entropy-risk classification enables targeted hazard control, improving efficiency. The study proposes chain-breaking strategies for precise, hierarchical, and timely emergency management, enhancing coal mine resilience to flood-induced Natech events. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)
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24 pages, 3066 KiB  
Article
Urban Flood Susceptibility Mapping Using GIS and Analytical Hierarchy Process: Case of City of Uvira, Democratic Republic of Congo
by Isaac Bishikwabo, Hwaba Mambo, John Kowa Kamanda, Chérifa Abdelbaki, Modester Alfred Nanyunga and Navneet Kumar
GeoHazards 2025, 6(3), 38; https://doi.org/10.3390/geohazards6030038 - 21 Jul 2025
Viewed by 311
Abstract
The city of Uvira, located in the eastern Democratic Republic of Congo (DRC), is increasingly experiencing flood events with devastating impacts on human life, infrastructure, and livelihoods. This study evaluates flood susceptibility in Uvira using Geographic Information Systems (GISs), and an Analytical Hierarchy [...] Read more.
The city of Uvira, located in the eastern Democratic Republic of Congo (DRC), is increasingly experiencing flood events with devastating impacts on human life, infrastructure, and livelihoods. This study evaluates flood susceptibility in Uvira using Geographic Information Systems (GISs), and an Analytical Hierarchy Process (AHP)-based Multi-Criteria Decision Making approach. It integrates eight factors contributing to flood occurrence: distance from water bodies, elevation, slope, rainfall intensity, drainage density, soil type, topographic wetness index, and land use/land cover. The results indicate that proximity to water bodies, drainage density and slope are the most influential factors driving flood susceptibility in Uvira. Approximately 87.3% of the city’s land area is classified as having high to very high flood susceptibility, with the most affected zones concentrated along major rivers and the shoreline of Lake Tanganyika. The reliability of the AHP-derived weights is validated by a consistency ratio of 0.008, which falls below the acceptable threshold of 0.1. This research provides valuable insights to support urban planning and inform flood management strategies. Full article
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25 pages, 16639 KiB  
Article
Hydraulic Modeling of Newtonian and Non-Newtonian Debris Flows in Alluvial Fans: A Case Study in the Peruvian Andes
by David Chacon Lima, Alan Huarca Pulcha, Milagros Torrejon Llamoca, Guillermo Yorel Noriega Aquise and Alain Jorge Espinoza Vigil
Water 2025, 17(14), 2150; https://doi.org/10.3390/w17142150 - 19 Jul 2025
Viewed by 468
Abstract
Non-Newtonian debris flows represent a critical challenge for hydraulic infrastructure in mountainous regions, often causing significant damage and service disruption. However, current models typically simplify these flows as Newtonian, leading to inaccurate design assumptions. This study addresses this gap by comparing the hydraulic [...] Read more.
Non-Newtonian debris flows represent a critical challenge for hydraulic infrastructure in mountainous regions, often causing significant damage and service disruption. However, current models typically simplify these flows as Newtonian, leading to inaccurate design assumptions. This study addresses this gap by comparing the hydraulic behavior of Newtonian and non-Newtonian flows in an alluvial fan, using the Amoray Gully in Apurímac, Peru, as a case study. This gully intersects the Interoceánica Sur national highway via a low-water crossing (baden), making it a relevant site for evaluating debris flow impacts on critical road infrastructure. The methodology integrates hydrological analysis, rheological characterization, and hydraulic modeling. QGIS 3.16 was used for watershed delineation and extraction of physiographic parameters, while a high-resolution topographic survey was conducted using an RTK drone. Rainfall-runoff modeling was performed in HEC-HMS 4.7 using 25 years of precipitation data, and hydraulic simulations were executed in HEC-RAS 6.6, incorporating rheological parameters and calibrated with the footprint of a historical event (5-year return period). Results show that traditional Newtonian models underestimate flow depth by 17% and overestimate velocity by 54%, primarily due to unaccounted particle-collision effects. Based on these findings, a multi-barrel circular culvert was designed to improve debris flow management. This study provides a replicable modeling framework for debris-prone watersheds and contributes to improving design standards in complex terrain. The proposed methodology and findings offer practical guidance for hydraulic design in mountainous terrain affected by debris flows, especially where infrastructure intersects active alluvial fans. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)
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21 pages, 3532 KiB  
Review
Climate Hazards Management of Historic Urban Centers: The Case of Kaštela Bay in Croatia
by Jure Margeta
Climate 2025, 13(7), 153; https://doi.org/10.3390/cli13070153 - 19 Jul 2025
Viewed by 491
Abstract
The preservation and protection of historic urban centers in climate-sensitive coastal areas contributes to the promotion of culture as a driver and enabler of achieving temporal and spatial sustainability, as it is recognized that urban heritage is an integral part of the urban [...] Read more.
The preservation and protection of historic urban centers in climate-sensitive coastal areas contributes to the promotion of culture as a driver and enabler of achieving temporal and spatial sustainability, as it is recognized that urban heritage is an integral part of the urban landscape, culture, and economy. The aim of this study was to enhance the resilience and protection of cultural heritage and historic urban centers (HUCs) in the coastal area of Kaštela, Croatia, by providing recommendations and action guidelines in response to climate change impacts, including rising temperatures, sea levels, storms, droughts, and flooding. Preserving HUCs is essential to maintain their cultural values, original structures, and appearance. Many ancient coastal Roman HUCs lie partially or entirely below mean sea level, while low-lying medieval castles, urban areas, and modern developments are increasingly at risk. Based on vulnerability assessments, targeted mitigation and adaptation measures were proposed to address HUC vulnerability sources. The Historical Urban Landscape Approach tool was used to transition and manage HUCs, linking past, present, and future hazard contexts to enable rational, comprehensive, and sustainable solutions. The effective protection of HUCs requires a deeper understanding of the evolution of urban development, climate dynamics, and the natural environments, including both tangible and intangible urban heritage elements. The “hazard-specific” vulnerability assessment framework, which incorporates hazard-relevant indicators of sensitivity and adaptive capacity, was a practical tool for risk reduction. This method relies on analyzing the historical performance and physical characteristics of the system, without necessitating additional simulations of transformation processes. Full article
(This article belongs to the Special Issue Coastal Hazards under Climate Change)
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14 pages, 2394 KiB  
Article
Digital-Twin-Based Structural Health Monitoring of Dikes
by Marike Bornholdt, Martin Herbrand, Kay Smarsly and Gerhard Zehetmaier
CivilEng 2025, 6(3), 39; https://doi.org/10.3390/civileng6030039 - 18 Jul 2025
Viewed by 331
Abstract
Earthen flood protection structures are planned and constructed with an expected service life of several decades while being exposed to environmental impacts that may lead to structural or hydraulic failure. Current maintenance procedures involve only repairing external damage, leaving internal processes contributing to [...] Read more.
Earthen flood protection structures are planned and constructed with an expected service life of several decades while being exposed to environmental impacts that may lead to structural or hydraulic failure. Current maintenance procedures involve only repairing external damage, leaving internal processes contributing to structural damage often undetected. Through structural health monitoring (SHM), structural deficits can be detected before visible damage occurs. To improve maintenance workflows and support predictive maintenance of dikes, this paper reports on the integration of digital twin concepts with SHM strategies, referred to as “digital-twin-based SHM”. A digital twin concept, including a standard-compliant building information model, is proposed and implemented in terms of a digital twin environment. For integrating monitoring and sensor data into the digital twin environment, a customized webform is designed. A communication protocol links preprocessed sensor data stored on a server with the digital twin environment, enabling model-based visualization and contextualization of the sensor data. As will be shown in this paper, a digital twin environment is set up and managed in the context of SHM in compliance with technical standards and using well-established software tools. In conclusion, digital-twin-based SHM, as proposed in this paper, has proven to advance predictive maintenance of dikes, contributing to the resilience of critical infrastructure against environmental impacts. Full article
(This article belongs to the Section Water Resources and Coastal Engineering)
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18 pages, 2446 KiB  
Review
Thematic Fragmentation and Convergence in Urban Flood Simulation Research: A 45-Year Bibliometric Mapping
by Ahmad Gamal, Mohammad Raditia Pradana, Bambang Hari Wibisono, Prananda Navitas and Jagannath Aryal
Urban Sci. 2025, 9(7), 280; https://doi.org/10.3390/urbansci9070280 - 17 Jul 2025
Viewed by 352
Abstract
Urban flooding presents a growing challenge amid rapid urbanization, climate variability, and fragmented governance. Although simulation and risk assessment tools have advanced considerably, their integration into urban planning remains limited. This study utilized a comprehensive bibliometric analysis of 1293 articles from the Scopus [...] Read more.
Urban flooding presents a growing challenge amid rapid urbanization, climate variability, and fragmented governance. Although simulation and risk assessment tools have advanced considerably, their integration into urban planning remains limited. This study utilized a comprehensive bibliometric analysis of 1293 articles from the Scopus database, selected through a PRISMA-guided workflow, to examine the temporal, structural, and conceptual evolution of simulation, flood risk, and planning in urban flood research from 1980 to 2025. The findings reveal a thematic progression from engineering-centric approaches to broader discourses on resilience, adaptation, and systemic risk. However, disciplinary fragmentation persists, with technical modeling, infrastructure planning, and governance still weakly connected. Despite a shared vocabulary around climate risk and resilience, practical integration into decision-making frameworks remains underdeveloped. The study highlights the need for more cohesive research-practice linkages and calls for frameworks that better align simulation outputs with urban planning imperatives. Full article
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33 pages, 39261 KiB  
Article
Assessing Geohazards on Lefkas Island, Greece: GIS-Based Analysis and Public Dissemination Through a GIS Web Application
by Eleni Katapodi and Varvara Antoniou
Appl. Sci. 2025, 15(14), 7935; https://doi.org/10.3390/app15147935 - 16 Jul 2025
Viewed by 309
Abstract
This research paper presents an assessment of geohazards on Lefkas Island, Greece, using Geographic Information System (GIS) technology to map risk and enhance public awareness through an interactive web application. Natural hazards such as landslides, floods, wildfires, and desertification threaten both the safety [...] Read more.
This research paper presents an assessment of geohazards on Lefkas Island, Greece, using Geographic Information System (GIS) technology to map risk and enhance public awareness through an interactive web application. Natural hazards such as landslides, floods, wildfires, and desertification threaten both the safety of residents and the island’s tourism-dependent economy, particularly due to its seismic activity and Mediterranean climate. By combining the Sendai Framework for Disaster Risk Reduction with GIS capabilities, we created detailed hazard maps that visually represent areas of susceptibility and provide critical insights for local authorities and the public. The web application developed serves as a user-friendly platform for disseminating hazard information and educational resources, thus promoting community preparedness and resilience. The findings highlight the necessity for proactive land management strategies and community engagement in disaster risk reduction efforts. This study underscores GIS’s pivotal role in fostering informed decision making and enhancing the safety of Lefkas Island’s inhabitants and visitors in the face of environmental challenges. Full article
(This article belongs to the Special Issue Emerging GIS Technologies and Their Applications)
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29 pages, 8743 KiB  
Article
Coupled Simulation of the Water–Food–Energy–Ecology System Under Extreme Drought Events: A Case Study of Beijing–Tianjin–Hebei, China
by Huanyu Chang, Naren Fang, Yongqiang Cao, Jiaqi Yao and Zhen Hong
Water 2025, 17(14), 2103; https://doi.org/10.3390/w17142103 - 15 Jul 2025
Viewed by 390
Abstract
The Beijing–Tianjin–Hebei (BTH) region is one of China’s most water-scarce yet economically vital areas, facing increasing challenges due to climate change and intensive human activities. This study develops an integrated Water–Food–Energy–Ecology (WFEE) simulation and regulation model to assess the system’s stability under coordinated [...] Read more.
The Beijing–Tianjin–Hebei (BTH) region is one of China’s most water-scarce yet economically vital areas, facing increasing challenges due to climate change and intensive human activities. This study develops an integrated Water–Food–Energy–Ecology (WFEE) simulation and regulation model to assess the system’s stability under coordinated development scenarios and extreme climate stress. A 500-year precipitation series was reconstructed using historical drought and flood records combined with wavelet analysis and machine learning models (Random Forest and Support Vector Regression). Results show that during the reconstructed historical megadrought (1633–1647), with average precipitation anomalies reaching −20% to −27%, leading to a regional water shortage rate of 16.9%, food self-sufficiency as low as 44.7%, and a critical reduction in ecological river discharge. Under future recommended scenario with enhanced water conservation, reclaimed water reuse, and expanded inter-basin transfers, the region could maintain a water shortage rate of 2.6%, achieve 69.3% food self-sufficiency, and support ecological water demand. However, long-term water resource degradation could still reduce food self-sufficiency to 62.9% and ecological outflows by 20%. The findings provide insights into adaptive water management, highlight the vulnerability of highly coupled systems to prolonged droughts, and support regional policy decisions on resilience-oriented water infrastructure planning. Full article
(This article belongs to the Special Issue Advanced Perspectives on the Water–Energy–Food Nexus)
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24 pages, 5886 KiB  
Article
GIS-Driven Multi-Criteria Assessment of Rural Settlement Patterns and Attributes in Rwanda’s Western Highlands (Central Africa)
by Athanase Niyogakiza and Qibo Liu
Sustainability 2025, 17(14), 6406; https://doi.org/10.3390/su17146406 - 13 Jul 2025
Viewed by 432
Abstract
This study investigates rural settlement patterns and land suitability in Rwanda’s Western Highlands, a mountainous region highly vulnerable to geohazards like landslides and flooding. Its primary aim is to inform sustainable, climate-resilient development planning in this fragile landscape. We employed high-resolution satellite imagery, [...] Read more.
This study investigates rural settlement patterns and land suitability in Rwanda’s Western Highlands, a mountainous region highly vulnerable to geohazards like landslides and flooding. Its primary aim is to inform sustainable, climate-resilient development planning in this fragile landscape. We employed high-resolution satellite imagery, a Digital Elevation Model (DEM), and comprehensive geospatial datasets to analyze settlement distribution, using Thiessen polygons for influence zones and Kernel Density Estimation (KDE) for spatial clustering. The Analytic Hierarchy Process (AHP) was integrated with the GeoDetector model to objectively weight criteria and analyze settlement pattern drivers, using population density as a proxy for human pressure. The analysis revealed significant spatial heterogeneity in settlement distribution, with both clustered and dispersed forms exhibiting distinct exposure levels to environmental hazards. Natural factors, particularly slope gradient and proximity to rivers, emerged as dominant determinants. Furthermore, significant synergistic interactions were observed between environmental attributes and infrastructure accessibility (roads and urban centers), collectively shaping settlement resilience. This integrative geospatial approach enhances understanding of complex rural settlement dynamics in ecologically sensitive mountainous regions. The empirically grounded insights offer a robust decision-support framework for climate adaptation and disaster risk reduction, contributing to more resilient rural planning strategies in Rwanda and similar Central African highland regions. Full article
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