Search Results (594)

Rapid urbanization has intensified two critical urban challenges: the urban heat island effect and stormwater runoff. This study evaluates the pilot-level field performance of a low-tortuosity permeable pavement (LTPP) system in potentially contributing to improved thermal regulation and hydraulic functionality. The system comprises a reduced-tortuosity upper block incorporated with bottom ash (BA) as a recycled fine aggregate and an underlying storage unit connected through an interlocking configuration, enabling direct infiltration while reducing clogging susceptibility and improving resistance to settlement and displacement. Field tests included thermal imaging, water-spraying infiltration-storage and vehicle-loading observations, and theoretical storage analysis. Initially, conventional permeable pavement (PP) dry surface temperature was measured at 44.2 °C, whereas the LTPP system already exhibited a lower temperature of 42.4 °C. During the evaporative stage after wetting, the LTPP system showed a lower temperature recovery rate, with a 2.91% increase between 90 and 120 min compared with 3.60% for conventional permeable pavement, indicating improved surface-temperature regulation. The storage calculations approximated that the LTPP system could theoretically buffer the simulated 15.63 mm/h rainfall by 6.65 to 7.32 h. It was also determined using historical rainfall data that the LTPP system, especially when provided with an outlet or drainage system, could effectively accommodate short- to medium-duration rainfall. Water-spraying tests confirmed rapid infiltration and subsurface storage, while vehicle-loading observations showed no noticeable displacement or settlement. These findings highlight the potential of a multifunctional permeable pavement design strategy that combines low-tortuosity flow paths, functional recycled aggregate selection, and subsurface storage for surface-temperature regulation and stormwater management. Full article

Background: After the Norwood operation, systemic and pulmonary circulations are supplied in parallel by a single right ventricle. Pulmonary blood flow depends on both native pulmonary vascular resistance and shunt/conduit resistance; therefore, balanced Qp:Qs can occur despite low native pulmonary resistance. Changes in systemic, pulmonary, or shunt/conduit resistance may alter flow distribution, systemic venous saturation, and oxygen delivery. Objective: To evaluate the predicted hemodynamic and oxygen delivery effects of systemic and pulmonary vasodilator conditions in a computational Norwood circulation model, and to assess the robustness of these effects using Monte Carlo simulation, dose–response analysis, nonlinear shunt modeling, afterload–responsive flow, and Rp/R-shunt sensitivity analysis. Methods: A lumped-parameter Norwood circulation model was used with a balanced baseline state: Qs = Qp = 1.0 L/min, total right ventricular flow = 2.0 L/min, and Qp:Qs = 1:1. The primary steady-state fixed-flow model was supplemented with sensitivity analyses incorporating afterload–responsive ventricular output, nonlinear shunt/conduit resistance, dose–response simulations, and a two-parameter Rp/R-shunt oxygen delivery surface. Results: In the fixed-flow model, nicardipine increased systemic flow and improved oxygen delivery, whereas pulmonary vasodilators shifted flow toward the pulmonary circulation and could reduce systemic flow. In the extended sensitivity analyses, predicted drug effects varied with ventricular flow reserve and the relationship between native pulmonary resistance and shunt/conduit resistance. Conclusions: In this Norwood circulation model, oxygen delivery depended primarily on systemic flow, ventricular response to afterload reduction, and the Rp/R-shunt relationship. Pulmonary vasodilators may improve modeled saturation but can reduce oxygen delivery when pulmonary runoff occurs without a compensatory increase in ventricular output. Full article

Substantial declines in acidifying emissions across Europe have led to pronounced chemical recovery of Norwegian surface waters. In recent decades, however, changes in water chemistry have increasingly coincided with climate change, complicating the attribution of observed trends to individual drivers. This study assesses whether ongoing climate change has produced detectable effects on freshwater chemistry in Norway and how these effects vary among catchments with differing sensitivities to acidification. In this study, the Model of Acidification of Groundwater In Catchments (MAGIC), which is based on current understanding of the processes governing acid–base chemistry in soils and waters, was used to simulate the effects of declining acid deposition. Deviations between observed and modelled water chemistry were provisionally interpreted as climate-related effects. However, these residuals may also reflect model or parameter uncertainty and other unaccounted-for processes. The analysis draws on long-term monitoring data (1986–2022) from 59 acid-sensitive Trend Lakes distributed across Norway, together with four Field Research Stations (1986–2020) representing contrasting hydroclimatic and biogeochemical conditions. Temporal trends were evaluated using the Mann–Kendall test and Sen’s slope estimator, while relationships between inferred climate effects and climatic variables were examined using Pearson’s correlation analysis. Across the Trend Lakes, inferred climate effects were predominantly positive for acid-neutralising capacity (ANC) and weathering-derived cations, suggesting that climate change may contribute to accelerated chemical recovery, particularly in catchments less sensitive to acidification. The inferred climate effects varied substantially among the Field Research Stations. Higher temperatures were generally associated with enhanced recovery, possibly through intensified silicate weathering, whereas increased precipitation and runoff appeared to dampen recovery. Overall, the results suggest that climate change exerts a measurable influence on freshwater chemistry in Norway, although the magnitude and direction of the response are strongly modulated by catchment-specific characteristics. While previous studies have identified climate-related influences on individual chemical variables, quantitative attempts to separate climate- and acid-deposition-related effects across a large number of acid-sensitive catchments remain rare. Here, we use deviations between observed water chemistry and MAGIC simulations of acid deposition recovery as a screening approach to investigate whether climate-related signals can be detected at the national scale and whether these signals vary among catchments with differing sensitivities to acidification. Full article

Plateau valley cities are increasingly exposed to flood risk because topographic constraints, ecological fragility, and rapid urbanization jointly intensify runoff sensitivity. Although dynamic and process-based assessments of flood regulation service (FRS) have advanced, limited attention has been given to how changes in urban green space (UGS) components are associated with marginal runoff-retention responses in a plateau valley setting. Taking central Lhasa as a case, this study combined Sentinel-2-based UGS mapping, intPLUS land-use scenario simulation, Soil and Water Assessment Tool (SWAT) runoff modeling, XGBoost, SHapley Additive exPlanations (SHAP), and accumulated local effects (ALE) to evaluate the FRS responses under multiple scenarios. A pressure–response overlay was further used to diagnose spatial mismatches between runoff pressure and modeled regulation response. Results showed that UGS expanded by 5212.66 ha from 2017 to 2025, indicating a marked greening trend, but the natural development scenario projected a 1403.80 ha decline by 2033. In contrast, the ecological protection scenario projected a 915.98 ha increase and produced a stronger modeled runoff-retention response, although the improvement remained spatially uneven across subbasins. Model-based interpretation identified forest land as the most influential predictor of runoff-depth-based FRS response, while grassland, park green space, and waterfront green space were generally associated with runoff-depth reduction and showed distinct nonlinear response patterns. Specifically, forest land and grassland showed diminishing marginal effects after higher increment ranges, park green space exhibited delayed effectiveness before clearer regulation benefits emerged, and waterfront green space reached effective response ranges at relatively low proportional increments. Spatial diagnosis further showed that 19 subbasins, accounting for 18.88% of the study area, remained response-lagged, mainly along urban expansion fringes where runoff pressure was not matched by sufficient modeled regulation response. The integrated framework provides a transferable, spatially explainable basis for plateau valley FRS assessment, whereas the identified thresholds and zoning implications remain case-specific and require local validation. Full article

Land Use and Land Cover (LULC) change is widely acknowledged as a pivotal driver of environmental change, exerting an escalating influence on surface hydrological processes. The accelerating pace of LULC alterations in response to burgeoning human populations underscores the pressing need for a comprehensive evaluation of their ramifications on surface runoff dynamics. This study investigates the impacts of LULC changes on flood behavior in a Mediterranean watershed in Crete, Greece (Geropotamos watershed). LULC data spanning the years 1990, 2006, and 2018 were procured from the European CORINE Land Cover database at a refined spatial resolution. The HEC-HMS hydrological model is employed to simulate peak discharge and associated hydrograph characteristics under varying recurrence intervals. Subsequently, selected river segments within the studied catchments undergo hydrodynamic flood modelling using the HEC-RAS hydraulic model. Flood depth maps are generated to illustrate the evolution of inundated areas relative to LULC change. The overarching objective of this research is to furnish a comprehensive understanding of how spatiotemporal variations in land use and land cover in-fluence flood characteristics, thereby facilitating informed decision making for sustainable planning. Full article

Extreme precipitation and compound hazards can increase the risk of inundation and accidental release of untreated effluent from water treatment facilities, with potential downstream impacts within a short emergency-response window. Few studies have linked site-scale surface-runoff behavior, feasible emergency-response scenarios, and resilience-based decision support for critical water infrastructure. This study presents a GIS-based scenario-comparison framework that couples high-resolution surface-runoff simulation with an AHP-informed resilience interpretation to evaluate untreated effluent runoff and temporary flood-defense strategies at a water treatment plant in Jeollabuk-do, South Korea. A 1 m digital elevation model derived from drone-based LiDAR data was used in ArcGIS Pro to simulate two-dimensional unsteady surface-runoff propagation, producing water-depth and flow-velocity fields at 30 s intervals over 20 min. Three scenarios were compared under identical topographic, release, and hydraulic assumptions, no response, primary defense-line deployment, and secondary defense-line deployment, adding a 335 m barrier along the downstream road. Under the no-response scenario, released water reached the river after approximately 6 min, with a cumulative river inflow of 329.27 m³. The primary defense line reduced cumulative river inflow by 16.8%, and the secondary defense line by 78.2%, while delaying river arrival to 8 min and 30 s. An approximate surface-water balance and time-series analysis showed that the defense lines primarily redistribute water into temporary upstream storage rather than eliminate it. The simulation-derived indicators were linked to four resilience components whose relative importance was estimated using the Analytic Hierarchy Process (AHP) from 205 expert and practitioner responses, which identified recovery speed as the highest-priority component; the weighted normalized indicators are summarized as a transparent scenario-level composite resilience indicator that increases from the no-response to the primary and secondary defense-line scenarios. Because the stormwater drainage network, pollutant transport, and operational deployment uncertainties were not explicitly modeled, the results should be interpreted as a comparative assessment of water-volume transport risk rather than a deterministic prediction of inundation or pollution impact. Within these stated assumptions, the results indicate that a strategically placed secondary defense line can substantially reduce downstream river inflow and secure additional response time, providing preliminary decision support for disaster-risk reduction and emergency-response planning at critical water infrastructure. Full article

Green roofs are used as nature-based solutions for urban stormwater management and for improving the thermal performance of buildings. Their hydrological performance depends on structural properties and rainfall characteristics, but the relative importance of these factors has not been fully quantified. Therefore, this study aimed to identify the key variables controlling the hydrological effectiveness of a green roof. A conceptual model of a flat roof representing a typical single-family building in south-eastern Poland was developed in the Storm Water Management Model (SWMM), with a modeled roof area of 232 m² and 100% of the roof surface covered by the green roof LID system. A total of 24,576 simulation cases were analyzed, considering different values of soil thickness, berm height, initial saturation, vegetation-related storage, rainfall duration, rainfall probability, and rainfall temporal distribution. The hydrological response was evaluated using peak runoff reduction and cumulative runoff volume ratio determined at selected times after rainfall. Predictive models based on the eXtreme Gradient Boosting (XGBoost) algorithm were developed, and their interpretation was performed using the SHapley Additive exPlanations (SHAP) method. The main novelty of the study is its application-oriented framework combining SWMM simulations, XGBoost modeling, and SHAP explainability to distinguish the factors controlling peak runoff reduction and delayed runoff release from a green roof. The results showed that peak runoff reduction ranged from 10.97% to 100.00%, with a median of 99.91%, indicating a generally high capacity of the analyzed system to attenuate peak flow. In contrast, the cumulative runoff volume ratio increased over time, with median values rising from 0.05% immediately after rainfall to 7.91% after 24 h, confirming the significant retention and detention potential of the green roof. SHAP analysis revealed that peak runoff reduction was governed primarily by berm height, whereas cumulative runoff volume was controlled mainly by initial substrate saturation. The results confirm that different mechanisms control short-term and long-term green roof performance. Full article

Indian metropolitan cities such as Mumbai grapple with rapid urbanisation, extreme urban density, high built-up areas, loss of green cover, and shrinking open spaces, resulting in increased impermeable surfaces, urban heat island effects, and frequent flooding occurrences. Modern stormwater management has increasingly been characterised by integrated grey-green approaches; however, cities in the Global North benefit from established policies, technical expertise, and financial resources that enable the systematic and large-scale integration of Blue-Green Infrastructure (BGI) through district-wide geospatial assessment frameworks, unlike many cities in the Global South. Despite growing interest in nature-based stormwater solutions, there remains a dearth of geospatial empirical research from India examining the placement, distribution, performance, and functionality of BGI integrated with existing stormwater management systems in cities such as Mumbai. Furthermore, hydrological modelling using tools such as the Storm Water Management Model (SWMM) for the design, planning, and implementation of BGI in Indian cities remains largely unexplored. This study explores the role of BGI strategies in improving urban stormwater management within high-density Indian cities under a 25-year return period extreme rainfall scenario. Using an integrated approach that combines QGIS-based spatial analysis with EPA-SWMM hydrologic-hydraulic modelling, the research examines runoff behaviour, identifies flooding hotspots, and evaluates the effectiveness of Low Impact Development (LID)-based BGI measures such as permeable pavements, infiltration trenches, and green roofs applied at the ward level in Mumbai’s F/North and G/North Wards. Detailed land use classification, spatial mapping, and rainfall simulation corresponding specifically to a 25-year return period rainfall event was used to assess pre- and post-intervention conditions. The findings indicate that the applied BGI measures led to a 12.6% reduction in peak runoff (137.6 m³/s to 120.2 m³/s) and a 5.5% decrease in total runoff volume (783,510 m³ to 740,410 m³). More importantly, the peak flooding flow rate decreased by 45% (94.1 m³/s to 51.7 m³/s), demonstrating that BGI measures can efficiently reduce peak flooding flows by extending runoff hydrographs during extreme rainfall events. These findings are specifically applicable to the simulated 25-year return period extreme rainfall scenario and may vary under different rainfall intensities or return periods. Less extreme events could potentially experience even greater relative reductions or prevent flooding altogether, while also easing downstream hydraulic loads. Overall, strategically placed BGI interventions can significantly reduce surface runoff and peak flow, thereby enhancing stormwater resilience within spatially constrained urban environments. This study provides a replicable, data-driven framework for catchment-scale stormwater planning in dense Indian cities under extreme rainfall conditions, offering practical insights into methods, local contextual considerations, and spatial planning strategies for policymakers and urban planners seeking to retrofit and adapt existing infrastructure under increasing hydrologic stress and climate variability. Full article

This study investigates the synergistic regulation mechanism of water–heat–salt transport in the black soil of cold regions in Northeast China by combining field monitoring with HYDRUS-2D simulations. Four tillage treatments were evaluated: control group (CK), no-tillage with flat straw mulching (NM), ridge tillage with flat straw mulching (RM), and straw return with rotary tillage (RR). Monitoring data indicated that all straw incorporation treatments significantly improved soil moisture retention capacity. Compared with CK, soil water content under RM increased by 63.93% correspondingly; soil salinity in CK was 5.75–13.68% higher than that in straw-amended treatments. In addition, RM exerted a more prominent regulatory effect on soil temperature fluctuations relative to CK. Simulation results reveal that straw incorporation effectively reduces surface runoff, thereby substantially weakening the driving force for upward salt migration. Structural equation modeling (SEM) quantified path coefficients, revealing that straw incorporation optimizes the soil microenvironment. This integrated approach provides a mechanistic basis for black soil conservation in seasonally frozen regions, identifying RM as the optimal management practice to balance water retention and salt inhibition. Full article

Flash-flood and floodplain inundation simulations are highly sensitive to the spatiotemporal variability of convective rainfall, particularly during the initial runoff generation stage. However, coarse-resolution numerical weather prediction (NWP) forcing tends to smooth localized rainfall extremes, limiting its ability to accurately represent hydrological responses in low-relief floodplains. In this study, we couple a diffusion-enhanced radar nowcasting model, Diff_ConvLSTM, with a spatial resolution of 1 km and a temporal resolution of 6 min, to assess the hydrological value of high-resolution rainfall forcing over the middle Yangtze River floodplain. We introduce a monotone piecewise cubic Hermite interpolation scheme to ensure a stable transition from discrete high-frequency rainfall inputs to continuous hydrodynamic integration. Evaluation using a radar dataset from 2023 to 2024 shows that Diff_ConvLSTM better preserves intense convective echoes and rainband structures compared to the baseline ConvLSTM, increasing the Probability of Detection at the 40 dBZ threshold by 65.8%. A forcing-replacement experiment for the flood event on 30 June 2023 demonstrates that AI-based nowcasting rainfall forcing reduces peak-discharge underestimation, improves volumetric consistency, and produces inundation patterns that are closer to the observation-driven reference than those generated by low-resolution forecast forcing, although positive biases in inundation area and water depth persist. An additional event in 2024 confirms that the improvements are primarily reflected in discharge magnitude and flood volume representation, while enhancements in peak timing remain limited. Overall, the results illustrate both the added value and the remaining limitations of AI-enhanced nowcasting for hydrologically informed flood forecasting. Full article

In this study, we evaluate the potential of blue roofs (BRs) to mitigate future increases in rainfall intensity projected by climate models. Using hourly EURO-CORDEX regional climate model data and a scaling-based methodology, we derived rainfall depth–duration–frequency curves for RCP4.5 and 8.5 for the future (up to 2100). The hydrological performance of a pilot BR tray in Catania, Italy, was then simulated under future design storms. Results show BRs can significantly reduce peak flows. Runoff volumes are reduced, but in most scenarios, they do not fully counterbalance the increase in rainfall intensity expected for the future. Peak attenuation ranges from 38% to 58%, depending on precipitation features and emission pathways, confirming BRs as effective adaptation measures. Full article

Assessing environmental flows downstream of reservoirs under changing climate and increasing water demand remains a critical challenge in catchment management. This study presents an integrated framework for optimizing environmental flow releases by explicitly linking reservoir operation with climate change and population growth. The key novelty lies in the development of a modified objective function that incorporates environmental flow requirements alongside evolving hydrological and demand conditions. Reservoir inflows were simulated using an artificial intelligence-based rainfall–runoff model, employing a neuro-fuzzy inference system to capture nonlinear relationships between climate variables and runoff. Future rainfall projections were derived from four general circulation models (ACCESS1.0, CanESM2, MIROC5, and NorESM-M1) across four-time horizons (2021–2040, 2041–2060, 2061–2080, and 2081–2100). The simulated inflows were coupled with a reservoir operation model to optimize environmental flow releases, with system performance evaluated using reliability and vulnerability metrics. Results show that climate change alone has a limited impact on environmental flow supply; however, when combined with population-driven increases in water demand, significant reductions in system performance occur. In the worst-case scenario, the reliability of meeting environmental flow requirements drops below 20%, accompanied by a marked increase in system vulnerability. These findings demonstrate that water demand pressures play a dominant role in shaping future environmental flow availability. The proposed framework provides a robust and adaptable approach for integrating hydrological variability and socio-economic drivers into reservoir management, supporting more informed decision-making for balancing water supply and ecosystem sustainability under future uncertainty. Full article

Urban flood modelling in heavily engineered catchments requires model structures that capture not only surface runoff processes but also hydraulic infrastructure and operational controls. This study applies a TELEMAC-2D rain-on-grid framework to two urban sub-catchments of the Emscher River (North Rhine-Westphalia, Germany) to quantify the relative effects of surface calibration, explicit infrastructure representation, and operational rules on the simulated flood response. A stepwise model development workflow was implemented, including land use-based calibration of Manning’s n and SCS Curve Numbers, explicit integration of culverts and bridges, and rule-based representation of retention basins and pumping stations. Model performance was evaluated using hydrograph shape, peak discharge, peak timing, event volume, and inundation behaviour across different antecedent moisture conditions (AMC). The results show that surface calibration alone was insufficient to consistently reproduce observed hydrographs. In the Rossbach sub-catchment area, integrating retention basins, pumping stations, and operational rules improved model performance from NSE = −0.129 under AMC I to NSE = 0.773 under AMC III. RMSE decreased from 3.380 to 1.515 m³ s⁻¹, peak discharge error from −6.198 to −0.492 m³ s⁻¹, and volume bias from −0.664 to +0.038. A targeted, routing-focused calibration further improved timing behaviour but increased volume bias, indicating residual deficiencies in the representation of rapid urban conveyance pathways. The findings show that reliable urban flood simulation in infrastructure-rich catchments depends not only on calibrating surface parameters but also on explicitly representing hydraulic structures, operational controls, and antecedent wetness conditions. Full article

Accurate streamflow information is critical for early flood and drought warning. However, global hydrological forecasting systems are affected by residual errors in meteorological forcing, model structure, and routing, which propagate into simulated streamflow. Within the GEOGLOWS River Forecast System (RFS), ERA5 runoff biases are routed into streamflow simulations. The most effective operational bias-correction method, MFDC-QM, requires local discharge observations and cannot be applied consistently in ungauged basins. This study evaluates a pre-routing, grid-scale runoff bias-correction framework that adjusts ERA5 runoff before routing by combining Flow Duration Curve (FDC) mapping and Sparse Cumulative Distribution Function (CDF) matching, using GSCD as a spatially distributed reference runoff data. Baseline GEOGLOWS RFS, pre-routing correction, and MFDC-QM were compared for 1980–2025 using 16,517 gauging stations, Kling–Gupta Efficiency (KGE), and paired significance tests. Globally, the median KGE increased modestly from 0.16 to 0.22, compared with 0.48 for MFDC-QM. Results demonstrate a clear regional dependence: pre-routing correction produced statistically significant gains in South America and Africa (p < 0.05), where ERA5 runoff exhibits stronger residual biases, but had limited effects in Europe and North America, where dense hydrometeorological networks likely impose stronger observational constraints on the underlying reanalysis. These patterns show that pre-routing correction is most valuable where residual forcing bias is large and observational constraints are limited, complementing observation-based post-processing in ungauged, data-limited regions. Full article

During severe drought conditions, water supply risks tend to be concentrated at critical water intake nodes and vulnerable river segments, while the conventional total balance method is inadequate for depicting the spatial evolution of these risks. This study developed a node-based water supply security assessment framework for the Feng River Basin, a representative watershed in the piedmont transition zone. The framework coupled SWAT-simulated runoff with a supply–demand balance model and evaluated water supply reliability at both the node and basin scales. Two scenarios were compared: an artificial water system scenario and an artificial water system with an engineering-based water resource allocation scenario. Dry (P = 75%) and extremely dry (P = 95%) conditions were considered to examine the performance of artificial regulation under drought stress. The results showed that basin-scale water supply reliability remained relatively stable, ranging from 0.833 to 0.853 under different scenarios. However, the node-scale results revealed strong spatial heterogeneity. Nodes 1 and 3 maintained full or nearly full reliability, whereas Nodes 4, 6, and 7 showed relatively low reliability and higher water shortage risk. Under the P = 75% scenario, engineering-based water resource allocation increased basin-scale reliability from 0.848 to 0.853, indicating a slight improvement in supply–demand balance. In contrast, under the P = 95% scenario, reliability decreased from 0.839 to 0.833 after introducing water resource allocation, suggesting that transfer-based interventions may have limited effectiveness when natural inflow is severely reduced. In particular, Node 7 showed a marked decline in reliability under the allocation scenario, indicating that water supply risks may be redistributed and concentrated at specific intake nodes under extreme drought conditions. The scenario comparison further indicates that water diversion strategies may produce a dual effect of local improvement and global reconfiguration. Insufficient supply intensity may result in engineering interventions that cause downstream water reduction impacts, leading to a spatial redistribution and shifting of risks rather than their systemic eradication. This study seeks to transition the evaluation paradigm from “total safety” to “node safety,” establishing a scientific foundation for enhancing the emergency response system in critical areas of the basin. Full article