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Keywords = hydrological systems

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22 pages, 3015 KiB  
Article
Determining Early Warning Thresholds to Detect Tree Mortality Risk in a Southeastern U.S. Bottomland Hardwood Wetland
by Maricar Aguilos, Jiayin Zhang, Miko Lorenzo Belgado, Ge Sun, Steve McNulty and John King
Forests 2025, 16(8), 1255; https://doi.org/10.3390/f16081255 (registering DOI) - 1 Aug 2025
Viewed by 70
Abstract
Prolonged inundations are altering coastal forest ecosystems of the southeastern US, causing extensive tree die-offs and the development of ghost forests. This hydrological stressor also alters carbon fluxes, threatening the stability of coastal carbon sinks. This study was conducted to investigate the interactions [...] Read more.
Prolonged inundations are altering coastal forest ecosystems of the southeastern US, causing extensive tree die-offs and the development of ghost forests. This hydrological stressor also alters carbon fluxes, threatening the stability of coastal carbon sinks. This study was conducted to investigate the interactions between hydrological drivers and ecosystem responses by analyzing daily eddy covariance flux data from a wetland forest in North Carolina, USA, spanning 2009–2019. We analyzed temporal patterns of net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RE) under both flooded and non-flooded conditions and evaluated their relationships with observed tree mortality. Generalized Additive Modeling (GAM) revealed that groundwater table depth (GWT), leaf area index (LAI), NEE, and net radiation (Rn) were key predictors of mortality transitions (R2 = 0.98). Elevated GWT induces root anoxia; declining LAI reduces productivity; elevated NEE signals physiological breakdown; and higher Rn may amplify evapotranspiration stress. Receiver Operating Characteristic (ROC) analysis revealed critical early warning thresholds for tree mortality: GWT = 2.23 cm, LAI = 2.99, NEE = 1.27 g C m−2 d−1, and Rn = 167.54 W m−2. These values offer a basis for forecasting forest mortality risk and guiding early warning systems. Our findings highlight the dominant role of hydrological variability in ecosystem degradation and offer a threshold-based framework for early detection of mortality risks. This approach provides insights into managing coastal forest resilience amid accelerating sea level rise. Full article
(This article belongs to the Special Issue Water and Carbon Cycles and Their Coupling in Forest)
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20 pages, 7673 KiB  
Article
Impact of Elevation and Hydrography Data on Modeled Flood Map Accuracy Using ARC and Curve2Flood
by Taylor James Miskin, L. Ricardo Rosas, Riley C. Hales, E. James Nelson, Michael L. Follum, Joseph L. Gutenson, Gustavious P. Williams and Norman L. Jones
Hydrology 2025, 12(8), 202; https://doi.org/10.3390/hydrology12080202 - 1 Aug 2025
Viewed by 128
Abstract
This study assesses the accuracy of flood extent predictions in five U.S. watersheds. We generated flood maps for four return periods using various digital elevation models (DEMs)—FABDEM, SRTM, ALOS, and USGS 3DEP—and two versions of the GEOGLOWS River Forecast System (RFS) hydrography. These [...] Read more.
This study assesses the accuracy of flood extent predictions in five U.S. watersheds. We generated flood maps for four return periods using various digital elevation models (DEMs)—FABDEM, SRTM, ALOS, and USGS 3DEP—and two versions of the GEOGLOWS River Forecast System (RFS) hydrography. These comparisons are notable because they build on operational global hydrology models so subsequent work can develop global modeled flood products. Models were made using the Automated Rating Curve (ARC) and Curve2Flood tools. Accuracy was measured against USGS reference maps using the F-statistic. Our results show that flood map accuracy generally increased with higher return periods. The most consistent and reliable improvements in accuracy occurred when both the DEM and hydrography datasets were upgraded to higher-resolution sources. While DEM improvements generally had a greater impact, hydrography refinements were more important for lower return periods when flood extents were the smallest. Generally, DEM resolution improved accuracy metrics more as the return period increased and hydrography and bare earth DEMs mattered more as the return period decreased. There was a 38.9% increase in the mean F-statistic between the two principal pairings of interest (FABDEM-RFS2 and SRTM 30 m DEM-RFS1). FABDEM’s bare-earth representation combined with RFS2 sometimes outperformed higher-resolution non-bare-earth DEMs, suggesting that there remains a need for site-specific investigation. Using ARC and Curve2Flood with FABDEM and RFS2 is a suitable baseline combination for general flood extent application. Full article
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32 pages, 17155 KiB  
Article
Machine Learning Ensemble Methods for Co-Seismic Landslide Susceptibility: Insights from the 2015 Nepal Earthquake
by Tulasi Ram Bhattarai and Netra Prakash Bhandary
Appl. Sci. 2025, 15(15), 8477; https://doi.org/10.3390/app15158477 (registering DOI) - 30 Jul 2025
Viewed by 178
Abstract
The Mw 7.8 Gorkha Earthquake of 25 April 2015 triggered over 25,000 landslides across central Nepal, with 4775 events concentrated in Gorkha District alone. Despite substantial advances in landslide susceptibility mapping, existing studies often overlook the compound role of post-seismic rainfall and lack [...] Read more.
The Mw 7.8 Gorkha Earthquake of 25 April 2015 triggered over 25,000 landslides across central Nepal, with 4775 events concentrated in Gorkha District alone. Despite substantial advances in landslide susceptibility mapping, existing studies often overlook the compound role of post-seismic rainfall and lack robust spatial validation. To address this gap, we validated an ensemble machine learning framework for co-seismic landslide susceptibility modeling by integrating seismic, geomorphological, hydrological, and anthropogenic variables, including cumulative post-seismic rainfall. Using a balanced dataset of 4775 landslide and non-landslide instances, we evaluated the performance of Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) models through spatial cross-validation, SHapley Additive exPlanations (SHAP) explainability, and ablation analysis. The RF model outperformed all others, achieving an accuracy of 87.9% and a Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) value of 0.94, while XGBoost closely followed (AUC = 0.93). Ensemble models collectively classified over 95% of observed landslides into High and Very High susceptibility zones, demonstrating strong spatial reliability. SHAP analysis identified elevation, proximity to fault, peak ground acceleration (PGA), slope, and rainfall as dominant predictors. Notably, the inclusion of post-seismic rainfall substantially improved recall and F1 scores in ablation experiments. Spatial cross-validation revealed the superior generalizability of ensemble models under heterogeneous terrain conditions. The findings underscore the value of integrating post-seismic hydrometeorological factors and spatial validation into susceptibility assessments. We recommend adopting ensemble models, particularly RF, for operational hazard mapping in earthquake-prone mountainous regions. Future research should explore the integration of dynamic rainfall thresholds and physics-informed frameworks to enhance early warning systems and climate resilience. Full article
(This article belongs to the Section Earth Sciences)
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22 pages, 22134 KiB  
Article
Adaptive Pluvial Flood Disaster Management in Taiwan: Infrastructure and IoT Technologies
by Sheng-Hsueh Yang, Sheau-Ling Hsieh, Xi-Jun Wang, Deng-Lin Chang, Shao-Tang Wei, Der-Ren Song, Jyh-Hour Pan and Keh-Chia Yeh
Water 2025, 17(15), 2269; https://doi.org/10.3390/w17152269 - 30 Jul 2025
Viewed by 295
Abstract
In Taiwan, hydro-meteorological data are fragmented across multiple agencies, limiting the effectiveness of coordinated flood response. To address this challenge and the increasing uncertainty associated with extreme rainfall, a real-time disaster prevention platform has been developed. This system integrates multi-source data and geospatial [...] Read more.
In Taiwan, hydro-meteorological data are fragmented across multiple agencies, limiting the effectiveness of coordinated flood response. To address this challenge and the increasing uncertainty associated with extreme rainfall, a real-time disaster prevention platform has been developed. This system integrates multi-source data and geospatial information through a cluster-based architecture to enhance pluvial flood management. Built on a Service-Oriented Architecture (SOA) and incorporating Internet of Things (IoT) technologies, AI-based convolutional neural networks (CNNs), and 3D drone mapping, the platform enables automated alerts by linking sensor thresholds with real-time environmental data, facilitating synchronized operational responses. Deployed in New Taipei City over the past three years, the system has demonstrably reduced flood risk during severe rainfall events. Region-specific action thresholds and adaptive strategies are continually refined through feedback mechanisms, while integrated spatial and hydrological trend analyses extend the lead time available for emergency response. Full article
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22 pages, 6878 KiB  
Article
Separate Versus Unified Ecological Networks: Validating a Dual Framework for Biodiversity Conservation in Anthropogenically Disturbed Freshwater–Terrestrial Ecosystems
by Tianyi Cai, Qie Shi, Tianle Luo, Yuechun Zheng, Xiaoming Shen and Yuting Xie
Land 2025, 14(8), 1562; https://doi.org/10.3390/land14081562 - 30 Jul 2025
Viewed by 283
Abstract
Freshwater ecosystems—home to roughly 10% of known species—are losing biodiversity to river-morphology alteration, hydraulic infrastructure, and pollution, yet most ecological network (EN) studies focus on terrestrial systems and overlook hydrological connectivity under human disturbance. To address this, we devised and tested a dual [...] Read more.
Freshwater ecosystems—home to roughly 10% of known species—are losing biodiversity to river-morphology alteration, hydraulic infrastructure, and pollution, yet most ecological network (EN) studies focus on terrestrial systems and overlook hydrological connectivity under human disturbance. To address this, we devised and tested a dual EN framework in the Yangtze River Delta’s Ecological Green Integration Demonstration Zone, constructing freshwater and terrestrial networks independently before merging them. Using InVEST Habitat Quality, MSPA, the MCR model, and Linkage Mapper, we delineated sources and corridors: freshwater sources combined NDWI-InVEST indicators with a modified, sluice-weighted resistance surface, producing 78 patches (mean 348.7 ha) clustered around major lakes and 456.4 km of corridors (42.50% primary). Terrestrial sources used NDVI-InVEST with a conventional resistance surface, yielding 100 smaller patches (mean 121.6 ha) dispersed across woodlands and agricultural belts and 658.8 km of corridors (36.45% primary). Unified models typically favor large sources from dominant ecosystems while overlooking small, high-value patches in non-dominant systems, generating corridors that span both freshwater and terrestrial habitats and mismatch species migration patterns. Our dual framework better reflects species migration characteristics, accurately captures dispersal paths, and successfully integrates key agroforestry-complex patches that unified models miss, providing a practical tool for biodiversity protection in disturbed freshwater–terrestrial landscapes. Full article
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19 pages, 4896 KiB  
Article
Calculation of Connectivity Between Surface and Underground Three-Dimensional Water Systems in the Luan River Basin
by Jingyao Wang, Zhixiong Tang, Belay Z. Abate, Zhuoxun Wu and Li He
Sustainability 2025, 17(15), 6913; https://doi.org/10.3390/su17156913 - 30 Jul 2025
Viewed by 165
Abstract
While water conservancy projects continuously enhance flood control and resource allocation capabilities, the adverse impacts on basin systems, particularly the structural disruption of surface water–groundwater continuity, have become increasingly pronounced. Therefore, establishing quantitative assessment of water system connectivity as a critical foundation for [...] Read more.
While water conservancy projects continuously enhance flood control and resource allocation capabilities, the adverse impacts on basin systems, particularly the structural disruption of surface water–groundwater continuity, have become increasingly pronounced. Therefore, establishing quantitative assessment of water system connectivity as a critical foundation for optimizing spatial water distribution, maintaining ecohydrological equilibrium, and enhancing flood–drought regulation efficacy is important. Focusing on the regulated reaches of the Panjiakou, Daheiting, and Taolinkou reservoirs in the Luan River Basin, this study established and integrated a three-dimensional assessment framework that synthesizes hydrological processes, hydraulic structural effects, and human activities as three fundamental drivers, and employed the Analytic Hierarchy Process (AHP) to develop a quantitative connectivity evaluation system. Results indicate that water conservancy projects significantly altered basin connectivity: surface water connectivity decreased by 0.40, while groundwater connectivity experienced a minor reduction (0.25) primarily through reservoir seepage. Consequently, the integrated surface–groundwater system declined by 0.39. Critically, project scale governs surface connectivity attenuation intensity, which substantially exceeds impacts on groundwater systems. The comprehensive assessment system developed in this study provides theoretical and methodological support for diagnosing river connectivity, formulating ecological restoration strategies, and protecting basin ecosystems. Full article
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18 pages, 3824 KiB  
Article
An Integrated TDR Waveguide and Data Interpretation Framework for Multi-Phase Detection in Soil–Water Systems
by Songcheng Wen, Jingwei Wu and Yuan Guo
Sensors 2025, 25(15), 4683; https://doi.org/10.3390/s25154683 - 29 Jul 2025
Viewed by 162
Abstract
Time domain reflectometry (TDR) has been validated for monitoring water level evolution and riverbed scouring in the laboratory. Previous studies have also validated the feasibility of field-based single hydrological parameter monitoring using TDR. However, the current research focuses on developing separated TDR sensing [...] Read more.
Time domain reflectometry (TDR) has been validated for monitoring water level evolution and riverbed scouring in the laboratory. Previous studies have also validated the feasibility of field-based single hydrological parameter monitoring using TDR. However, the current research focuses on developing separated TDR sensing systems, and integrated measurements of multiple hydrological parameters from a single reflected waveform have not been reported. This study presents an improved helical probe sensor specifically designed for implementation in geologically hard soils, together with an improved data interpreting methodology to simultaneously determine water surface level, bed elevation, and suspended sediment concentration from a single reflection signal. Experimental comparisons were conducted in the laboratory to evaluate the measuring performance between the traditional dual-needle probe and the novel spiral probe under the same scouring conditions. The experiments confirmed the reliability and superior performance of spiral probe in accurately capturing multiple hydrological parameters. The measurement errors for the spiral probe across multiple hydrological parameters were all within ±10%, and the accuracy further improved with increased probe embedding depth in the sand medium. Across all tested parameters, the spiral probe showed enhanced measurement precision with a particularly significant improvement in suspended sediment concentration detection. Full article
(This article belongs to the Section Environmental Sensing)
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22 pages, 9790 KiB  
Article
Assessing the Hazard of Flooding from Breaching of the Alacranes Dam in Villa Clara, Cuba
by Victor Manuel Carvajal González, Carlos Lázaro Castillo García, Lisdelys González-Rodriguez, Luciana Silva and Jorge Jiménez
Sustainability 2025, 17(15), 6864; https://doi.org/10.3390/su17156864 - 28 Jul 2025
Viewed by 751
Abstract
Flooding due to dam failures is a critical issue with significant impacts on human safety, infrastructure, and the environment. This study assessed the potential flood hazard that could be generated from breaching of the Alacranes dam in Villa Clara, Cuba. Thirteen reservoir breaching [...] Read more.
Flooding due to dam failures is a critical issue with significant impacts on human safety, infrastructure, and the environment. This study assessed the potential flood hazard that could be generated from breaching of the Alacranes dam in Villa Clara, Cuba. Thirteen reservoir breaching scenarios were simulated under several criteria for modeling the flood wave through the 2D Saint Venant equations using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS). A sensitivity analysis was performed on Manning’s roughness coefficient, demonstrating a low variability of the model outputs for these events. The results show that, for all modeled scenarios, the terrain topography of the coastal plain expands the flood wave, reaching a maximum width of up to 105,057 km. The most critical scenario included a 350 m breach in just 0.67 h. Flood, velocity, and hazard maps were generated, identifying populated areas potentially affected by the flooding events. The reported depths, velocities, and maximum flows could pose extreme danger to infrastructure and populated areas downstream. These types of studies are crucial for both risk assessment and emergency planning in the event of a potential dam breach. Full article
(This article belongs to the Section Hazards and Sustainability)
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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 265
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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24 pages, 10881 KiB  
Article
Dynamics of Water Quality in the Mirim–Patos–Mangueira Coastal Lagoon System with Sentinel-3 OLCI Data
by Paula Andrea Contreras Rojas, Felipe de Lucia Lobo, Wesley J. Moses, Gilberto Loguercio Collares and Lino Sander de Carvalho
Geomatics 2025, 5(3), 36; https://doi.org/10.3390/geomatics5030036 - 25 Jul 2025
Viewed by 286
Abstract
The Mirim–Patos–Mangueira coastal lagoon system provides a wide range of ecosystem services. However, its vast territorial extent and the political boundaries that divide it hinder integrated assessments, especially during extreme hydrological events. This study is divided into two parts. First, we assessed the [...] Read more.
The Mirim–Patos–Mangueira coastal lagoon system provides a wide range of ecosystem services. However, its vast territorial extent and the political boundaries that divide it hinder integrated assessments, especially during extreme hydrological events. This study is divided into two parts. First, we assessed the spatial and temporal patterns of water quality in the lagoon system using Sentinel-3/OLCI satellite imagery. Atmospheric correction was performed using ACOLITE, followed by spectral grouping and classification into optical water types (OWTs) using the Sentinel Applications Platform (SNAP). To explore the behavior of water quality parameters across OWTs, Chlorophyll-a and turbidity were estimated using semi-empirical algorithms specifically designed for complex inland and coastal waters. Results showed a gradual increase in mean turbidity from OWT 2 to OWT 6 and a rise in chlorophyll-a from OWT 2 to OWT 4, with a decline at OWT 6. These OWTs correspond, in general terms, to distinct water masses: OWT 2 to clearer waters, OWT 3 and 4 to intermediate/mixed conditions, and OWT 6 to turbid environments. In the second part, we analyzed the response of the Patos Lagoon to flooding in Rio Grande do Sul during an extreme weather event in May 2024. Satellite-derived turbidity estimates were compared with in situ measurements, revealing a systematic underestimation, with a negative bias of 2.6%, a mean relative error of 78%, and a correlation coefficient of 0.85. The findings highlight the utility of OWT classification for tracking changes in water quality and support the use of remote sensing tools to improve environmental monitoring in data-scarce regions, particularly under extreme hydrometeorological conditions. Full article
(This article belongs to the Special Issue Advances in Ocean Mapping and Hydrospatial Applications)
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24 pages, 12938 KiB  
Article
Spatial Distribution of Mangrove Forest Carbon Stocks in Marismas Nacionales, Mexico: Contributions to Climate Change Adaptation and Mitigation
by Carlos Troche-Souza, Edgar Villeda-Chávez, Berenice Vázquez-Balderas, Samuel Velázquez-Salazar, Víctor Hugo Vázquez-Morán, Oscar Gerardo Rosas-Aceves and Francisco Flores-de-Santiago
Forests 2025, 16(8), 1224; https://doi.org/10.3390/f16081224 - 25 Jul 2025
Viewed by 633
Abstract
Mangrove forests are widely recognized for their effectiveness as carbon sinks and serve as critical ecosystems for mitigating the effects of climate change. Current research lacks comprehensive, large-scale carbon storage datasets for wetland ecosystems, particularly across Mexico and other understudied regions worldwide. Therefore, [...] Read more.
Mangrove forests are widely recognized for their effectiveness as carbon sinks and serve as critical ecosystems for mitigating the effects of climate change. Current research lacks comprehensive, large-scale carbon storage datasets for wetland ecosystems, particularly across Mexico and other understudied regions worldwide. Therefore, the objective of this study was to develop a high spatial resolution map of carbon stocks, encompassing both aboveground and belowground components, within the Marismas Nacionales system, which is the largest mangrove complex in northeastern Pacific Mexico. Our approach integrates primary field data collected during 2023–2024 and incorporates some historical plot measurements (2011–present) to enhance spatial coverage. These were combined with contemporary remote sensing data, including Sentinel-1, Sentinel-2, and LiDAR, analyzed using Random Forest algorithms. Our spatial models achieved strong predictive accuracy (R2 = 0.94–0.95), effectively resolving fine-scale variations driven by canopy structure, hydrologic regime, and spectral heterogeneity. The application of Local Indicators of Spatial Association (LISA) revealed the presence of carbon “hotspots,” which encompass 33% of the total area but contribute to 46% of the overall carbon stocks, amounting to 21.5 Tg C. Notably, elevated concentrations of carbon stocks are observed in the central regions, including the Agua Brava Lagoon and at the southern portion of the study area, where pristine mangrove stands thrive. Also, our analysis reveals that 74.6% of these carbon hotspots fall within existing protected areas, demonstrating relatively effective—though incomplete—conservation coverage across the Marismas Nacionales wetlands. We further identified important cold spots and ecotones that represent priority areas for rehabilitation and adaptive management. These findings establish a transferable framework for enhancing national carbon accounting while advancing nature-based solutions that support both climate mitigation and adaptation goals. Full article
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11 pages, 15673 KiB  
Article
Automating GIS-Based Cloudburst Risk Mapping Using Generative AI: A Framework for Scalable Hydrological Analysis
by Alexander Adiyasa, Andrea Niccolò Mantegna and Irma Kveladze
Hydrology 2025, 12(8), 196; https://doi.org/10.3390/hydrology12080196 - 23 Jul 2025
Viewed by 288
Abstract
Accurate dynamic hydrological models are often too complex and costly for the rapid, broad-scale screening necessitated for proactive land-use planning against increasing cloudburst risks. This paper demonstrates the use of GPT-4 to develop a GUI-based Python 3.13.2 application for geospatial flood risk assessments. [...] Read more.
Accurate dynamic hydrological models are often too complex and costly for the rapid, broad-scale screening necessitated for proactive land-use planning against increasing cloudburst risks. This paper demonstrates the use of GPT-4 to develop a GUI-based Python 3.13.2 application for geospatial flood risk assessments. The study used instructive prompt techniques to script a traditional stream and catchment delineation methodology, further embedding it with a custom GUI. The resulting application demonstrates high performance, processing a 29.63 km2 catchment at a 1 m resolution in 30.31 s, and successfully identifying the main upstream contributing areas and flow paths for a specified area of interest. While its accuracy is limited by terrain data artifacts causing stream breaks, this study demonstrates how human–AI collaboration, with the LLM acting as a coding assistant guided by domain expertise, can empower domain experts and facilitate the development of advanced GIS-based decision-support systems. 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 190
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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23 pages, 1285 KiB  
Review
An Exploratory Review of Microplastic Pollution, Associated Microbiomes and Pathogens in Water
by Paulina Cholewińska, Konrad Wojnarowski, Hanna Moniuszko, Przemysław Pokorny and Dušan Palić
Appl. Sci. 2025, 15(15), 8128; https://doi.org/10.3390/app15158128 - 22 Jul 2025
Viewed by 328
Abstract
Microplastic particles (MPs) are an emerging global pollutant of increasing concern due to their widespread occurrence, persistence, and multifaceted impact on aquatic ecosystems. This study provides a comprehensive review of peer-reviewed literature from 2011 to 2025, analysing the presence, distribution, and microbiological associations [...] Read more.
Microplastic particles (MPs) are an emerging global pollutant of increasing concern due to their widespread occurrence, persistence, and multifaceted impact on aquatic ecosystems. This study provides a comprehensive review of peer-reviewed literature from 2011 to 2025, analysing the presence, distribution, and microbiological associations of MPs in surface waters across five continents. The findings confirm that MPs are present in both marine and freshwater systems, with concentrations varying by region, hydrology, and proximity to anthropogenic sources. Polyethylene and polypropylene were identified as the most common polymers, often enriched in river mouths, estuaries, and aquaculture zones. A key focus of this review is the plastisphere—microbial biofilms colonizing MPs—which includes both environmental and pathogenic bacteria such as Vibrio, Pseudomonas, and Acinetobacter. Notably, MPs serve as vectors for the spread of antibiotic resistance genes (ARGs), including sul1, tetA and ermF, and β-lactamase genes like blaCTX-M. This highlights their role in enhancing horizontal gene transfer and microbial dissemination. The results emphasize the need for standardized monitoring protocols and further interdisciplinary research. In light of the One Health approach, understanding the microbial dimension of MP pollution is essential for managing risks to environmental and public health. Full article
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24 pages, 8305 KiB  
Article
Development of Open-Source Tools for Event-Based Hydrological Modelling Using GIS and Python
by Andrés F. Almeida-Ñauñay, Ernesto Sanz, Antonio Berlanga, Miguel Ángel Patricio, José M. Molina and Sergio Zubelzu
Water 2025, 17(14), 2160; https://doi.org/10.3390/w17142160 - 21 Jul 2025
Viewed by 289
Abstract
Detailed modelling of water dynamics at the catchment is of paramount importance for the optimal management and allocation of water resources. The main objective of this work is to present a set of QGIS-based routines for processing easily available geographical information to deliver [...] Read more.
Detailed modelling of water dynamics at the catchment is of paramount importance for the optimal management and allocation of water resources. The main objective of this work is to present a set of QGIS-based routines for processing easily available geographical information to deliver inputs for integration into hydrological models developed in the Python environment. We present QGIS processes that deliver open format exchangeable files with physical information required for hydrological modelling, allowing a better tailoring of hydrological modelling tasks compared to other blinded existing models. We present the general framework by processing spatial information and running a set of hydrological models in different cases studies in the Spanish Ebro River basin, proving the utility of the proposed method for applying complex and tailored hydrological simulations. Full article
(This article belongs to the Section Hydrology)
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