Search Results (379)

In this case study, we used the Delta Simulation Model II (DSM2) to study the salt balance at the land–water interface in the river delta of California’s San Francisco Estuary. Drainage, a source of water and salt for adjacent channels in the study area, is affected by channel salinity. The DSM2 approach has been adopted by several hydrodynamic models of the estuary to enforce water volume balance between diversions, evapotranspiration and drainage at the land–water interface, but does not explicitly enforce salt balance. We found deviations from salt balance to be quite large, albeit variable in magnitude due to the heterogeneity of hydrodynamic and salinity conditions across the study area. We implemented a procedure that approximately enforces salt balance through iterative updates of the baseline drain salinity boundary conditions (termed loose coupling). We found a reasonable comparison with field measurements of drainage salinity. In particular, the adjusted boundary conditions appear to capture the range of observed interannual variability better than the baseline periodic estimates. The effect of the iterative adjustment procedure on channel salinity showed substantial spatial variability: locations dominated by large flows were minimally impacted, and in lower flow channels, deviations between baseline and adjusted channel salinity series were notable, particularly during the irrigation season. This approach, which has the potential to enhance the simulation of extreme salinity intrusion events (when high channel salinity significantly impacts drainage salinity), is essential for robustly modeling hydrodynamic conditions that pre-date contemporary water management infrastructure. We discuss limitations associated with this approach and recommend that—for this case study—further improvements could best be accomplished through code modification rather than coupling of transport and island water balance models. Full article

This study applies the Weighted Overlay Analysis (WOA) method integrated with GIS to assess landslide susceptibility along Al Figrah Road in Al-Madinah Al-Munawarah, western Saudi Arabia. Seven key conditioning factors, elevation, slope, aspect, drainage density, lithology, soil type, and precipitation were integrated using high-resolution remote sensing data and expert-assigned weights. The output susceptibility map categorized the region into three zones: low (93.5 million m²), moderate (271.2 million m²), and high risk (33.1 million m²). Approximately 29% of the road corridor lies within the low-risk zone, 48% in the moderate zone, and 23% in the high-risk zone. Ten critical sites with potential landslide activity were detected along the road, correlating well with the high-risk zones on the map. Structural weaknesses in the area, such as faults, joints, foliation planes, and shear zones in both igneous and metamorphic rock units, were key contributors to slope instability. The findings offer practical guidance for infrastructure planning and geohazard mitigation in arid, mountainous environments and demonstrate the applicability of WOA in data-scarce regions. Full article

Water supply and sewage drainage pipes have a critical role to play in the provision of clean water and sanitation, and pipe material selection influences infrastructure life, water quality, and microbial communities. Zinc-containing compounds are highly valued due to their mechanical properties, anticorrosion behavior, and antimicrobial properties. However, the effect of zinc salts, such as zinc sulfate heptahydrate and zinc chloride, on biofilm-forming bacteria, including Escherichia coli and Enterococcus faecalis, is not well established. This study investigates the antibacterial properties of these zinc salts under simulated pipeline conditions using minimum inhibitory concentration assays, biofilm production assays, and antibiotic sensitivity tests. Findings indicate that zinc chloride is more antimicrobial due to its higher solubility and bioavailability of Zn²⁺ ions. At higher concentrations, zinc salts inhibit the development of a biofilm, whereas sub-inhibitory concentrations enhance the growth of biofilm, suggesting a stress response in bacteria. zinc chloride also enhances antibiotic efficacy against E. coli but induces resistance in E. faecalis. These findings highlight the dual role of zinc salts in preventing biofilm formation and modulating antimicrobial resistance, necessitating further research to optimize material selection for water distribution networks and mitigate biofilm-associated risks in pipeline systems. Full article

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

The integration of traditional geomorphological approaches with advanced artificial intelligence techniques represents a promising frontier in flood risk assessment for arid regions. This study presents a comprehensive analysis of the Wadi Ranuna basin in Medina, Saudi Arabia, combining detailed morphometric parameters with advanced Geospatial Artificial Intelligence (GeoAI) algorithms to enhance flood susceptibility modeling. Using digital elevation models (DEMs) and geographic information systems (GISs), we extracted 23 morphometric parameters across 67 sub-basins and applied XGBoost, Random Forest, and Gradient Boosting (GB) models to predict both continuous flood susceptibility indices and binary flood occurrences. The machine learning models utilize morphometric parameters as input features to capture complex non-linear interactions, including threshold-dependent relationships where the stream frequency impact intensifies above 3.0 streams/km², and the compound effects between the drainage density and relief ratio. The analysis revealed that the basin covers an area of 188.18 km² with a perimeter of 101.71 km and contains 610 streams across six orders. The basin exhibits an elongated shape with a form factor of 0.17 and circularity ratio of 0.23, indicating natural flood-moderating characteristics. GB emerged as the best-performing model, achieving an RMSE of 6.50 and an R² value of 0.9212. Model validation through multi-source approaches, including field verification at 35 locations, achieved 78% spatial correspondence with documented flood events and 94% accuracy for very high susceptibility areas. SHAP analysis identified the stream frequency, overland flow length, and drainage texture as the most influential predictors of flood susceptibility. K-Means clustering uncovered three morphometrically distinct zones, with Cluster 1 exhibiting the highest flood risk potential. Spatial analysis revealed 67% of existing infrastructure was located within high-risk zones, with 23 km of major roads and eight critical facilities positioned in flood-prone areas. The spatial distribution of GBM-predicted flood susceptibility identified high-risk zones predominantly in the central and southern parts of the basin, covering 12.3% (23.1 km²) of the total area. This integrated approach provides quantitative evidence for informed watershed management decisions and demonstrates the effectiveness of combining traditional morphometric analysis with advanced machine learning techniques for enhanced flood risk assessment in arid regions. Full article

Urban pluvial flooding (UPF) is an increasingly critical issue due to rapid urbanization and intensified precipitation driven by climate change that yet remains understudied in the Caribbean. This study analyzes the effects of UPF resulting from the transformation of a natural karstic landscape into an urbanized area considering a sub-watershed in Chetumal, Southern Mexican Caribbean, as a case study. Hydrographic numerical modeling was conducted using the IBER 2.5.1 software and the SCS-CN method to estimate surface runoff for a critical UPF event across three stages: (i) 1928—natural condition; (ii) 1998—semi-urbanized (78% coverage); and (iii) 2015—urbanized (88% coverage). Urbanization led to the orthogonalization of the drainage network, an increase in the sub-watershed area (20%) and mainstream length (33%), flow velocities rising 10–100 times, a 52% reduction in surface roughness, and a 32% decrease in the potential maximum soil retention before runoff occurs. In urbanized scenarios, 53.5% of flooded areas exceeded 0.5 m in depth, compared to 16.8% in non-urbanized conditions. Community-based knowledge supported flood extent estimates with 44.5% of respondents reporting floodwater levels exceeding 0.50 m, primarily in streets. Only 43.1% recalled past flood levels, indicating a loss of societal memory, although risk perception remained high among directly affected residents. The reported UPF effects perceived in the area mainly related to housing damage (30.2%), mobility disruption (25.5%), or health issues (12.9%). Although UPF events are frequent, insufficient drainage infrastructure, altered runoff patterns, and limited access to public shelters and communication increased vulnerability. Full article

Green roofs are increasingly being adopted as sustainable, nature-based solutions for managing urban stormwater, mitigating the urban heat island effect, and saving energy in buildings. However, the long-term performance of their individual components—particularly filter geotextiles—remains understudied, despite their critical role in maintaining system functionality. The filter layer, responsible for preventing clogging of the drainage layer with fine substrate particles, directly affects the hydrological performance and service life of green roofs. While most existing studies focus on the initial material properties, there is a clear gap in understanding how geotextile filters behave after prolonged exposure to real-world environmental conditions. This study addresses this gap by assessing the mechanical and structural integrity of geotextile filters after five years of use in both extensive and intensive green roof systems. By analyzing changes in surface morphology, microstructure, and porosity through tensile strength tests, digital imaging, and scanning electron microscopy, this research offers new insights into the long-term performance of geotextiles. Results showed significant retention of tensile strength, particularly in the machine direction (MD), and a 56% reduction in porosity, which may affect filtration efficiency. Although material degradation occurs, some geotextiles retain their structural integrity over time, highlighting their potential for long-term use in green infrastructure applications. This research emphasizes the importance of material selection, long-term monitoring, and standardized evaluation techniques to ensure the ecological and functional resilience of green roofs. Furthermore, the findings contribute to advancing knowledge on the durability and life-cycle performance of filter materials, promoting sustainability and longevity in urban green infrastructure. Full article

Tropical peatlands store approximately 105 gigatons of carbon (GtC), serving as vital long-term carbon sinks, yet remain critically underrepresented in climate policy. Indonesia peatlands contain 57GtC—the largest tropical peatland carbon stock in the Asia–Pacific. However, decades of drainage, fires, and lax enforcement practices have degraded vast peatland areas, turning them from carbon sinks into emission sources—as evidenced by the 1997 and 2015 peatland fires which emitted 2.57 Gt CO₂eq and 1.75 Gt CO₂eq, respectively. Using system theory validated against historical data (1997–2023), we develop a causal loop model revealing three interconnected feedback loops driving irreversible collapse: (1) drainage–desiccation–oxidation, where water table below −40 cm triggers peat oxidation (2–5 cm subsistence) and fires; (2) fire–climate–permafrost, wherein emissions intensify radiative forcing, destabilizing monsoons and accelerating Arctic permafrost thaw (+15% since 2000); and (2) economy–governance failure, perpetuated by palm oil’s economic dominance and slack regulatory oversight. To break these vicious cycles, we propose a precautionary framework featuring IoT-enforced water table (≤40 cm), reducing emissions by 34%, legally protected “Global Climate Stabilization Zones” for peat domes (>3 m depth), safeguarding 57 GtC, and ASEAN transboundary enforcement funded by a 1–3% palm oil levy. Without intervention, annual emissions may reach 2.869 GtCO₂e by 2030 (Nationally Determined Contribution’s business-as-usual scenario). Conversely, rewetting 590 km²/year aligns with Indonesia’s FOLU Net Sink 2030 target (−140 Mt CO₂e) and mitigates 1.4–1.6 MtCO₂ annually. We conclude that integrating peatlands as irreplaceable climate infrastructure into global policy is essential for achieving Paris Agreement goals and SDGs 13–15. Full article

Mining activities in Pakistan’s mineral-rich provinces threaten freshwater security through groundwater depletion, contamination, and flood-induced pollution. This study develops an Inclusive Disaster Risk Reduction (IDRR) framework integrating governance, social, environmental, and technical (GSET) dimensions to holistically assess mining-induced water hazards across Balochistan, Khyber Pakhtunkhwa, and Punjab. Using GIS-based spatial risk mapping with multi-layer hydrological modeling, we combine computational analysis and participatory validation to identify vulnerability hotspots and prioritize high-risk mines. Community workshops involving women water collectors, indigenous leaders, and local experts enhanced map accuracy by translating indigenous knowledge into spatially referenced mitigation plans and integrating gender-sensitive metrics to address gendered water access disparities. Key findings reveal severe groundwater depletion, acid mine drainage, and gendered burdens near Saindak and Cherat mines. Multi-sectoral engagements secured corporate commitments for water stewardship and policy advances in inclusive governance. The framework employs four priority-ranked risk categories (Governance-Economic 15%, Social-Community 30%, Environmental 40%, Technical-Geological 15%) derived via local stakeholder collaboration, enabling context-specific interventions. Despite data limitations, the GIS-driven methodology provides a scalable model for regions facing socio-environmental vulnerabilities. The results demonstrate how community participation directly shaped village-level water management alongside GSET analysis to craft equitable risk reduction strategies. Spatially explicit risk maps guided infrastructure upgrades and zoning regulations, advancing SDG 6 and 13 progress in Pakistan. This work underscores the value of inclusive, weighted frameworks for sustainable mining–water nexus management in Pakistan and analogous contexts. Full article

Agricultural water resource management is increasingly challenged by climate variability, land degradation, and socio-economic pressures, particularly in the Mediterranean region. This study, conducted in 2023–2024 within the REACT4MED project (PRIMA initiative), addresses sustainable water use through a comparative analysis of organic and conventional farms in the Stornara and Tara area (Puglia, Italy). The research aimed to identify critical indicators for sustainable water management and develop ecosystem restoration strategies that can be replicated across similar Mediterranean agro-ecosystems. An interdisciplinary, participatory approach was adopted, combining technical analyses and stakeholder engagement through three workshops involving 30 participants from diverse sectors. Fieldwork and laboratory assessments included soil sampling and analysis of parameters such as pH, electrical conductivity, soil organic carbon, nutrients, and salinity. Cartographic studies of vegetation, land use, and pedological characterization supplemented the dataset. The key challenges identified were water loss in distribution systems, seawater intrusion, water pumping from unauthorized wells, and inadequate public policies. Soil quality was significantly influenced by salt stress, hence affecting crop productivity, while socio-economic factors affected farm income. Restoration strategies emphasized the need for water-efficient irrigation, less water-intensive crops, and green vegetation in infrastructure channels while incorporating also the native flora. Enhancing plant biodiversity through weed management in drainage channels proved beneficial for pathogen control. Proposed socio-economic measures include increased inclusion of women and youth in agricultural management activities. Integrated technical and participatory approaches are essential for effective water resource governance in Mediterranean agriculture. This study offers scalable, context-specific indicators and solutions for sustainable land and water management in the face of ongoing desertification and climate stress. Full article

Accurately estimating storm hydrographs for various return periods is crucial for planning and designing hydrological infrastructure, such as dams and drainage systems. A key aspect of this estimation is the separation of baseflow from storm runoff. This study proposes a method for deriving storm hydrographs for different return periods based on hydrological station records. The proposed approach uses three baseflow separation methods: constant, linear, and master recession curve. A significant advantage of the proposed method over traditional rainfall–runoff approaches is its minimal parameter requirements during calibration. The methodology is tested on records from the Lengupá River watershed in Colombia, using data from the Páez hydrological station, which has a drainage area of 1090 km². The results indicate that the linear method yields the most accurate hydrograph estimates, as demonstrated by its lower root mean square error (RMSE) of 0.35%, compared to the other baseflow separation techniques, the values of which range from 2.92 to 3.02%. A frequency analysis of hydrological data was conducted using Pearson Type III and Generalized Extreme Value distributions to identify the most suitable statistical models for estimating extreme events regarding peak flow and maximum storm hydrograph volume. The findings demonstrate that the proposed methods effectively reproduce storm hydrographs for return periods ranging from 5 to 200 years, providing valuable insights for hydrological design, which can be employed using the data from stream gauging stations in rivers. Full article

Manmade detention ponds have historically been impacted by anthropogenic activities such as rainwater runoff, car emissions, and drainage from infrastructures, which can lead to complications for pond ecosystems. Sediment samples collected from the northern, southern, western, and eastern regions of a small pond on a suburban high school campus on Long Island, NY, were analyzed for potential chemical changes resulting from an inundation of water by a broken water main. Incorporating synchrotron X-ray techniques, sediment was analyzed using Submicron Resolution Spectroscopy, Tender Energy X-ray Spectroscopy, and X-ray Powder Diffraction to examine heavy metals, light elements, and minerals. Results include a Zn:Cu ratio increase from 4:1 to 10:1 in the eastern zone and a higher heavy metal presence in the western zone for all elements examined, with greater distribution throughout the pond post-inundation. Lighter elements appear to remain relatively unchanged. The appearance of diopside in the eastern zone post-inundation samples suggests contamination from the water main break, while the presence of carbonate minerals in the western zone is consistent with erosion of asphalt material from the adjacent parking lot. Full article

Existing wet tropical urban drainage systems often fail to accommodate runoff generated during extreme rainfall. Water-sensitive urban design (WSUD) systems have the potential to retrofit the existing urban drainage system by enhancing infiltration and retention functions. However, studies supporting this assumption were based on temperate or arid climatic conditions, raising questions about its relevance in wet tropical catchments. To answer these questions, in this study a comprehensive modelling study of WSUD effectiveness in a tropical environment was implemented. Engineers Park, a small sub-catchment of 0.27 km² at Saltwater Creek, Cairns, Queensland, Australia was the study site in which the flood mitigation capabilities of grey and WSUD systems under major (1% Annual Exceedance Probability—AEP), moderate (20% AEP), and minor (63.2% AEP) magnitudes of rainfall were evaluated. A detailed one-dimensional (1D) and coupled 1D2D hydrodynamic model in MIKE+ were developed and deployed for this study. The results highlighted that the existing grey infrastructure within the catchment underperformed during major events resulting in high peak flows and overland flow, while minor rainfall events increased channel flow and shifted the location of flooding. However, the integration of WSUD with grey infrastructure reduced peak flow by 0% to 42%, total runoff volume by 0.9% to 46%, and the flood extent ratio to catchment area from 0.3% to 1.1%. Overall, the WSUD integration positively contributed to reduced flooding in this catchment, highlighting its potential applicability in tropical catchments subject to intense rainfall events. However, careful consideration is required before over-generalization of these results, since the study area is small. The results of this study can be used in similar study sites by decision-makers for planning and catchment management purposes, but with careful interpretation. Full article

This study aims to assess the impacts of climate change on the tourism potential of Northeastern Brazil by analyzing historical trends and future climate projections, identifying climate risks, and proposing spatially targeted adaptation strategies. Historical daily climate data from the BR-DWGD and future projections from the MPI-ESM1-2-LR model under the SSP2 4.5 scenario were used to evaluate extremes in temperature and precipitation. Principal component analysis and spatial cluster analysis were applied to identify five climatically homogeneous zones across the region. Results indicate generalized warming trends and intensifying rainfall extremes, particularly in coastal clusters where tourism infrastructure is concentrated. Inland zones, especially those with semi-arid climates, exhibit rising temperatures, prolonged droughts, and increasing water scarcity. These differentiated climatic patterns pose risks to infrastructure, ecosystem services, and the overall sustainability of tourism. In response, the study proposes adaptation measures tailored to each zone, including improved drainage systems, sustainable cooling technologies, rainwater harvesting, and diversification of tourism activities. Emphasis is placed on community-based governance to enhance social equity and resilience. The findings highlight the relevance of spatialized climate analysis for guiding adaptation planning and supporting a more inclusive and climate-resilient tourism sector in the region. Full article

Landslides in Ecuador are one of the most common deadly events in natural hazards, such as the one on 26 March 2023. A large-scale landslide occurred in Alausí, Chimborazo province, causing 65 fatalities and 10 people to disappear, significant infrastructural damage, and the destruction of six neighborhoods. This study presents a detailed case analysis of the anthropogenic factors that could have contributed to the instability of the affected area. Field investigations and a review of historical, geological, and social information are the basis for analyzing the complex interactions between natural and human-induced conditions. Key anthropogenic contributors identified include unplanned urban expansion, ineffective drainage systems, deforestation, road construction without adequate geotechnical support, and changes in land use, particularly agricultural irrigation and wastewater disposal. These factors increased the area’s susceptibility to slope failure, which, combined with intense rainfall and past seismic activity, could have caused the rupture process’s acceleration. The study also emphasizes integrating geological, hydrological, and urban planning assessments to mitigate landslide risks in geologically sensitive regions such as Alausí canton. The findings conclude that human activity could be an acceleration factor in natural processes, and the pressure of urbanization amplifies the consequences. This research underscores the importance of sustainable land management, improved drainage infrastructure, and land-use planning in hazard-prone areas. The lessons learned from Alausí can inform risk reduction strategies across other mountainous and densely populated regions worldwide, like the Andean countries, which have similar social and environmental conditions to Ecuador. Full article