Search Results (1,802)

The construction of the Xinyang Urban Water Supply Project, centered on the Chushandian Reservoir, required a thorough investigation of high–low runoff encounters between the water source and receiving areas to optimize water allocation and operational scheduling. Based on the hydrological stations at Changtaiguan (CTG) on the main stream of the Huaihe River (HR) in the water source area and Miaowan (MW) on the main stream of the Honghe River in the receiving area, the trends and abrupt change characteristics of monthly runoff from 2014 to 2024 were analyzed using methods such as extremum symmetry mode decomposition (ESMD) and heuristic segmentation, with spatial encounter patterns determined using Copula functions. The results indicate that (1) the runoff in the water source area showed a quasi-6.05-month periodic characteristic on a monthly scale, while the runoff in the receiving area exhibited a quasi-6.72-month periodic characteristic on a monthly scale; (2) the water source area experienced runoff mutation in August 2015 (extreme drought) and June 2024 (extreme precipitation), with the receiving area responding 7 months earlier than the water source area, revealing differences in system vulnerability; (3) synchronous hydrological states were significantly more likely to occur (51.2%) compared with asynchronous conditions (25.2%), with the highest probability of “concurrent drought” (19.8%) and a high-risk “normal water source—receiving area drought” combination (14.1%). These findings provide theoretical and technical support for the optimized scheduling of the Chushandian Reservoir, improving the resilience and adaptability of the Xinyang Urban Water Supply Project to climate fluctuations and extreme hydrological events. Full article

Preferential flow in coal mining subsidence areas leads to shallow soil moisture loss, vegetation reducing and ecological degradation. However, the factors influencing the development of preferential flow remain unclear. This study analyzed the morphological characteristics of preferential flow using a staining tracer test in coal mining subsidence areas along the middle reaches of the Yellow River Basin. Characteristic parameters including the dye-stained area ratio, preferential flow ratio, length index, variation coefficient were comparatively evaluated under different initial soil moisture conditions. Results showed that shallow soils exhibited substrate flow, while preferential flow occurred in deeper soil layers below the matrix flow. As initial soil moisture increased, the extent of both substrate flow and preferential flow decreased. The dye-stained area ratio declined with increasing soil depth, and the relationship between dye-stained area and soil layer depth was best described by a cubic function. Higher initial soil moisture reduced maximum infiltration depth and length indices while increasing the coefficient of the stained pattern. Furthermore, a higher of initial soil water content corresponded to a lower preferential flow index. Overall, increased initial soil moisture may reduce the extent of preferential flow and the rapid infiltration of water into soil. These findings provides a basis for further hydrological studies in coal mining subsidence areas in arid and semi-arid regions and offer scientific support for ecological restoration efforts in mining areas. Full article

Understanding spatial variability in crop yields across fields is critical for developing precision agricultural strategies that optimize productivity while reducing negative environmental impacts. This variability often arises from a complex interplay of topographic features, soil characteristics, and hydrological conditions. This study investigates the influence of hydro-topographic factors on corn and soybean yield variability from 2016 to 2023 at the well-managed experimental sites in Beltsville, Maryland. A high-resolution surface digital elevation model (DEM) and subsurface DEM derived from ground-penetrating radar (GPR) were used to quantify topographic factors (elevation, slope, and aspect) and hydrological factors (surface flow accumulation, depth from the surface to the subsurface-restricting layer, and distance from each crop pixel to the nearest subsurface flow pathway). Topographic variables alone explained yield variation, with a relative root mean square error (RRMSE) of 23.7% (r² = 0.38). Adding hydrological variables reduced the error to 15.3% (r² = 0.73), and further combining with remote sensing data improved the explanatory power to an RRMSE of 10.0% (r² = 0.87). Notably, even without subsurface data, incorporating surface-derived flow accumulation reduced the RRMSE to 18.4% (r² = 0.62), which is especially important for large-scale cropland applications where subsurface data are often unavailable. Annual spatial yield variation maps were generated using hydro-topographic variables, enabling the identification of long-term persistent yield regions (LTRs), which served as stable references to reduce spatial anomalies and enhance model robustness. In addition, by combining remote sensing data with interannual meteorological variables, prediction models were evaluated with and without hydro-topographic inputs. The inclusion of hydro-topographic variables improved spatial characterization and enhanced prediction accuracy, reducing error by an average of 4.5% across multiple model combinations. These findings highlight the critical role of hydro-topography in explaining spatial yield variation for corn and soybean and support the development of precise, site-specific management strategies to enhance productivity and resource efficiency. Full article

Excessive nitrogen export from lowland polders is a key contributor to cultural eutrophication in downstream aquatic ecosystems. This study investigated the spatiotemporal characteristics, migration pathways, and sources of nitrogen pollution in a typical polder system. Eight surface water sampling campaigns were conducted at 13 sites in Quyuan Polder, Dongting Lake, from 2022 to 2023, combining ArcGIS spatial analysis, multivariate statistics, and dual-isotope (δ¹⁵N-NO⁻), δ¹⁸O-NO₃⁻) techniques. Nitrate and ammonium nitrogen dominated the nitrogen pool, accounting for ~76% of total nitrogen. Concentrations were higher in the dry season (2.48 mg/L) than in the wet season (1.89 mg/L) and differed significantly among hydrological periods (p < 0.05). Within the polder, total nitrogen and ammonium nitrogen were elevated, whereas nitrate nitrogen was higher at the outlet, reflecting distinct nitrogen profiles along the hydrological gradient. Nitrogen transport patterns were largely consistent with flow direction, driven by both upstream inputs and in situ generation. Isotopic signatures indicated that nitrate originated mainly from ammonium fertilizer and soil nitrogen, with contributions from manure and sewage. These findings enhance understanding of nitrogen dynamics in lowland catchments and provide a scientific basis for targeted pollution control in polder waters. Full article

Accurate and robust runoff simulation is crucial for effective reservoir regulation. Although it is clear that enhancing runoff simulation or optimizing reservoir operation strategies can improve the management of hydropower resources, the specific impact of enhanced simulated runoff on reservoir operation under optimized regulation has not been thoroughly examined. To investigate how high-precision runoff simulation influences reservoir performance, this study proposed a unidirectional coupling framework of the distributed hydrological model CREST and the LSTM model, incorporating the seasonal characteristics of the satellite-based precipitation product CHIRPS. The influence of simulated runoff on hydropower generation was examined from two perspectives: metrics’ accuracy and process-based analysis. The results showed that, following the unidirectional coupling, the Coupling scheme achieved improvements in NSE and R² by 6% and 4%, respectively, while RMSE decreased by 24%. Additionally, it accurately captured the seasonal variations and amplitude of runoff at the annual scale, and was able to reliably detect the periodic signals within runoff across various scales. After reservoir optimization operation, the simulated runoff derived from the Coupling scheme produced hydropower and surplus water values close to those obtained from observed runoff, with errors of 1.09% and −21.64%, respectively. Moreover, the Coupling scheme corrected the prominent peaks in hydropower generation seen in the CREST model across multiple periods, demonstrating a stronger capability for temporal runoff simulation closely aligned with observed runoff in terms of temporal structure. Full article

The frequency and intensity of paleofloods reveal long-term hydrological changes and their responses to regional climate variations. This study focuses on sediment core HDZ04 from the desert section of the upper Yellow River, analyzing sediment grain size and elemental characteristics to reconstruct paleoflood events over the past 30,000 years. Using the EMMA end-member model, four end-member components were extracted, and the proportion of the two coarser end-members was used as a proxy for flood dynamics. Pearson correlation analysis indicated that ln(Zr/Ti) correlates more significantly with grain size value than ln(Zr/Rb), establishing Zr/Ti as a reliableproxy for paleoflood reconstruction. Integrating physical and chemical indicators with OSL dating, the reconstructed paleoflood sequence shows high frequency and intensity from 30~12 ka, lower values during the early and middle Holocene, and a significant increase in the late Holocene (3~0 ka). Comparison with regional climate records indicates that cold and dry periods correspond to higher paleoflood frequency and intensity. This multi-proxy approach provides a transferable framework for reconstructing past flood events in other alluvial systems worldwide, enhancing our understanding of hydrological responses to climatic forcing. Full article

Groundwater flow systems (GFSs) and associated distribution of travel times provide critical insight into the regional subsurface hydrology, especially in arid regions experiencing intensive groundwater use. This study examines the impact of large-scale irrigation pumping on GFS patterns in the arid Kongqi River Basin, China. A three-dimensional (3D) steady-state groundwater flow model was constructed using MODFLOW, and flow paths were delineated through particle tracking to quantify travel time and residence time distributions. Two scenarios with and without pumping were compared. Results show that groundwater abstraction significantly alters GFS patterns, lowering water tables in pumping zones while raising them in irrigation areas fed by surface water. This hydrologic redistribution fragments recharge and discharge zones, particularly under the influence of evapotranspiration (ET) from shallow groundwater. Simulated travel times range up to ~506 ka, with median values decreasing from 9.7 ka (no-pumping) to 8.3 ka (pumping). Both travel time distribution (TTD) and residence time distribution (RTD) exhibit power-law characteristics, reflecting the dominance of slow flow paths in deep GFSs. While the modeling results provide valuable insight into current regional groundwater flow, it does not account for transient flow effects and hydrodynamic dispersion of solutions. Future research should incorporate groundwater isotope data to validate the model and assess time-dependent changes in GFSs. Full article

Urban flooding represents a growing global concern, especially in areas with rapid urbanization, unregulated urban sprawl and climate change conditions. Conventional flood modeling approaches do not effectively capture the complex dynamics between natural watershed behavior and urban infrastructure; they typically simulate these domains in isolation. This study introduces the Watershed-BIM methodology, a three-dimensional simulation framework that integrates Building and City Information Modeling (BIM/CIM), Geographic Information Systems (GIS), Flood Risk Assessment (FRA), and Flood Risk Management (FRM) into a single framework. Autodesk InfraWorks 2024, Civil 3D 2024, and RiverFlow2D v8.14 software are incorporated in the development. The methodology enhances interoperability and prediction accuracy by bridging hydrological processes with detailed urban-scale data. The framework was tested on a real-world flash flood event in Mandra, Greece, an area frequently exposed to extreme rainfall and runoff events. A specific comparison with observed flood characteristics indicates improved accuracy in comparison to other hydrological analyses (e.g., by HEC-RAS simulation). Beyond flood depth, the model offers additional insights into flow direction, duration, and localized water accumulation around buildings and infrastructure. In this context, integrated tools such as Watershed-BIM stand out as essential instruments for translating complex flood dynamics into actionable, city-scale resilience planning. Full article

Predicting future hydrological drought characteristics can assist relevant departments in taking proactive measures to mitigate drought losses. Based on the SWAT model and the Sixth International Coupled Model Comparison Program, this study employs an improved Mann–Kendall test, cumulative anomaly method, and continuous wavelet transform to investigate future runoff and hydrological drought characteristics in the upper reaches of the Xin’an River under different Shared Socioeconomic Pathways (SSPs). The SSPs scenario consists of three typical paths. SSP126 represents the sustainable development path (low carbon emissions, ecological protection first), SSP245 is the intermediate balance path (equal emphasis on economic growth and environmental protection), and SSP585 is the fossil fuel-intensive path (high emissions, high development intensity). The results indicate that from 2000 to 2020, under the influence of ecological compensation policies, the upper reaches of the Xin’an River transitioned from hydrological drought to hydrological wetness in 2012. Under the three future scenarios, runoff volumes increased by 41.72%, 40.74%, and 40.72% compared to the historical period, respectively, with peak runoff occurring in May, June, and July, alleviating hydrological drought conditions. Under the SSP245 and SSP585 scenarios, drought characteristics were more pronounced, with the number of drought-free months increasing by 21 and 30 months, respectively, compared to the SSP126 scenario, and the number of extremely dry months increased by 9 months and 17 months, respectively. The standard runoff index in the SSP126 scenario exhibits two oscillation cycles of 400 months and 359 months, respectively, while SSP245 and SSP585 both exhibit an oscillation cycle of 835 months. After discussion, it was concluded that ecological compensation policies can improve hydrological drought conditions. Drought characteristics become increasingly pronounced as carbon emissions intensify. This research can provide theoretical references for water allocation and drought prevention in river basins. Full article

Mid–long-term streamflow prediction (MLSP) plays a critical role in water resource planning amid growing hydroclimatic and anthropogenic uncertainties. Although AI-based models have demonstrated strong performance in MLSP, their capacity to quantify predictive uncertainty remains limited. To address this challenge, a DeepAR-based probabilistic modeling framework is developed, enabling direct estimation of streamflow distribution parameters and flexible selection of output distributions. The framework is applied to two case studies with distinct hydrological characteristics, where combinations of recurrent model structures (GRU and LSTM) and output distributions (Normal, Student’s t, and Gamma) are systematically evaluated. The results indicate that the choice of output distribution is the most critical factor for predictive performance. The Gamma distribution consistently outperformed those using Normal and Student’s t distributions, due to its ability to better capture the skewed, non-negative nature of streamflow data. Notably, the magnitude of performance gain from using the Gamma distribution is itself region-dependent, proving more significant in the basin with higher streamflow skewness. For instance, in the more skewed Upper Wudongde Reservoir area, the model using LSTM structure and Gamma distribution reduces RMSE by over 27% compared to its Normal-distribution counterpart (from 1407.77 m³/s to 1016.54 m³/s). Furthermore, the Gamma-based models yield superior probabilistic forecasts, achieving not only lower CRPS values but also a more effective balance between high reliability (PICP) and forecast sharpness (MPIW). In contrast, the relative performance between GRU and LSTM architectures was found to be less significant and inconsistent across the different basins. These findings highlight that the DeepAR-based framework delivers consistent enhancement in forecasting accuracy by prioritizing the selection of a physically plausible output distribution, thereby providing stronger and more reliable support for practical applications. Full article

This study examines the impact of catchment characteristics and design on the performance of urban lakes in terms of water quality and stormwater harvesting potential. Two urban lake systems in Western Sydney, Australia, were selected for comparison: Wattle Grove Lake, a standalone constructed lake, and Woodcroft Lake, part of an integrated wetland–lake system. Both systems receive runoff from surrounding residential catchments of differing sizes and land uses. Over a one-year period, continuous monitoring was conducted to evaluate water quality parameters, including turbidity, total suspended solids (TSS), nutrients (total nitrogen and total phosphorus), pH, dissolved oxygen, and biochemical oxygen demand. The results reveal that the lake with an integrated wetland significantly outperformed the standalone lake in terms of water quality, particularly in terms of turbidity and total suspended solids (TSS), achieving up to 70% reduction in TSS at the outlet compared to the inlet. The wetland served as an effective pre-treatment system, reducing pollutant loads before water entered the lake. Despite this, nutrient concentrations in both systems remained above the thresholds set by the Australian and New Zealand Environment and Conservation Council (ANZECC) Guidelines (2000), indicating persistent challenges in nutrient retention. Notably, the larger catchment area and shallow depth of Wattle Grove Lake likely contributed to higher turbidity and nutrient levels, resulting from sediment resuspension and algal growth. Hydrological modelling using the Model for Urban Stormwater Improvement Conceptualisation (MUSIC) software (version 6) complemented the field data and highlighted the influence of catchment size, hydraulic retention time, and lake depth on pollutant removal efficiency. While both systems serve important environmental and recreational functions, the integrated wetland–lake system at Woodcroft demonstrated greater potential for safe stormwater harvesting and reuse within urban settings. The findings from the study offer practical insights for urban stormwater management and inform future designs that enhance resilience and water reuse potential in growing cities. Full article

Global warming has intensified the hydrological cycle, resulting in more frequent extreme precipitation events and altered spatiotemporal precipitation patterns in urban areas, thereby increasing the risk of urban flooding and threatening socio-economic and ecological security. This study investigates the characteristics of summer extreme precipitation in the Poyang Lake City Group (PLCG) from 1971 to 2022, utilizing the China Daily Precipitation Dataset and NCEP/NCAR reanalysis data. Nine extreme precipitation indices were examined through linear trend analysis, Mann–Kendall tests, wavelet transforms, and correlation methods to quantify trends, periodicity, and atmospheric drivers. The key findings include: (1) All indices exhibited increasing trends, with RX1Day and R95p exhibiting significant rises (p < 0.05). PRCPTOT, R20, and SDII also increased, indicating heightened precipitation intensity and frequency. (2) R50, RX1Day, and SDII demonstrated east-high-to-west-low spatial gradients, whereas PRCPTOT and R20 peaked in the eastern and western PLCG. More than over 88% of stations recorded rising trends in PRCPTOT and R95p. (3) Abrupt changes occurred during 1993–2009 for PRCPTOT, R50, and SDII. Wavelet analysis revealed dominant periodicities of 26–39 years, linked to atmospheric oscillations. (4) Strong subtropical highs, moisture convergence, and negative OLR anomalies were closely associated with extreme precipitation. Warmer SSTs in the eastern equatorial Pacific amplified precipitation in preceding seasons. This study provides a scientific basis for flood prevention and climate adaptation in the PLCG and highlighting the region’s vulnerability to monsoonal shifts under global warming. Full article

Forest litter plays a critical role in regulating the water balance of forest ecosystems, particularly in semi-arid regions where hydrological stability is under pressure due to climate change. This study investigates the maximum water holding capacity (MWHC) of litter layers across three ecologically distinct regions in Türkiye—Kastamonu, Kütahya, and Muğla—to evaluate how structural and physicochemical characteristics influence the maximum water holding capacity (MWHC) of litter layers. Litter samples classified into humus, fermenting debris, and needles were analyzed for MWHC, pH, electrical conductivity (EC), and total dissolved solids (TDSs). The results revealed that both the type of litter and regional ecological conditions significantly affect MWHC, with humus layers and moist environments exhibiting the highest water holding capacity. Additionally, MWHC showed moderate positive correlations with EC and TDS, highlighting the importance of chemical composition in water dynamics. The findings underscore that forest litter should be regarded as a dynamic and functional hydrological component, not merely residual biomass. This perspective is vital for sustainable watershed planning and adaptive forest management. The study supports the development of integrated management strategies aligned with the United Nations Sustainable Development Goals (SDGs), particularly SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 15 (Life on Land). Full article

The Ili River Basin is characterized by complex topography and diverse climatic zones with limited in situ observations. This study evaluates the performance of six widely used precipitation datasets, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), ERA5_Land (European Centre for Medium-Range Weather Forecasts—ECMWF Reanalysis 5_Land), GPCC (Global Precipitation Climatology Centre), IMERG (Integrated Multi-satellite Retrievals for GPM), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and TerraClimate, against ground-based data from 2001 to 2023. The evaluation is conducted across multiple spatial scales and temporal resolutions. At the basin scale, most datasets exhibit strong correlations with in situ observations across all temporal scales (r > 0.7), except for PERSIANN, which demonstrates a relatively weaker performance during summer and winter (r < 0.6). All datasets except ERA5_ Land show low annual and monthly bias (<5%), although larger errors are observed during summer, particularly for IMERG and PERSIANN. Dataset performance generally declines with increasing elevation. Basin-wide gridded evaluations reveal distinct spatial variations across all elevation zones, with CHIRPS showing the strongest ability to capture orographic precipitation gradients throughout the basin. All datasets correctly identified 2008 as a drought year and 2016 as a wet year, even though the magnitude and spatial resolution of the anomalies varied among them. These findings highlight the importance of selecting precipitation datasets that are suited to the complex topographic and climatic characteristics of transboundary basins. Our study provides valuable insights for improving hydrological modeling and can be used for water sustainability and flood–drought mitigation support activities in the Ili River Basin. Full article

Impervious surfaces reduce natural infiltration, leading to increased runoff, erosion, and pollutant transport. The Alabama Department of Transportation (ALDOT) relies on implementing infiltration swales, a linear bioretention-based practice, along roadside drainage channels to reduce surface runoff. This study developed and constructed modified permeameters and infiltrometers to evaluate and optimize media used to construct infiltration swales. The average measured falling head infiltration rate of sandy topsoil used in the media matrix was 0.63 ft/day (0.19 m/day). A series of amended topsoil mixtures were tested to improve the infiltration rate of the media. In particular, the mixture of 80% topsoil and 20% pine bark fines (by weight) significantly improved the infiltration rates of the swale media. Through iterative testing, the F3 design with 6 in. (15.2 cm) mixture and 10 in. (25.4 cm) sand achieved up to 13.73 ft/day (4.18 m/day) of infiltration rate under constant head, far surpassing the infiltration rate of the current ALDOT design. SWMM bioretention cell models were developed to understand the swale infiltration process and revealed that the infiltration rates obtained from column tests were the saturated hydraulic conductivities of the soil layer when there was no other restriction on vertical flow. The simulated swale hydrological performance depends not only on variations in soil conductivity but also on other swale characteristics under field conditions. Findings from this research can be used to enhance the performance of infiltration-based stormwater practices. Full article