Journal of Hydrology最新文献

{"title":"Performance evaluation of convolutional neural network and vision transformer models for groundwater potential mapping","authors":"Behnam Sadeghi ,&nbsp;Ali Asghar Alesheikh ,&nbsp;Ali Jafari ,&nbsp;Fatemeh Rezaie","doi":"10.1016/j.jhydrol.2025.132840","DOIUrl":"10.1016/j.jhydrol.2025.132840","url":null,"abstract":"<div><div>Due to excessive consumption and the increasing warming of the earth’s air, the level of groundwater in the world is decreasing, especially in arid and semi-arid countries that need water supply for various purposes from these sources. In this study, the data of 3546 wells and 15 spatial factors influencing the occurrence of groundwater, elevation, slope, plan curvature, profile curvature, terrain wetness index (TWI), valley depth, slope length (LS), river density, distance from river, distance from fault, geology, land cover, aspect, normalized difference vegetation index (NDVI), and rainfall have been used for modeling and groundwater potential mapping (GWPM). In the feature selection process, the wrapper base method, Boruta-XGBoost, and the variance inflation factor (VIF) test were used, and all factors except LS were confirmed and entered into the model. Convolutional neural network (CNN) and vision transformer (VIT) were used as learning models for Chaharmahal Bakhtiari province, one of Iran’s mountainous provinces. The area under receiver operating characteristic curve (AUC), root mean square error (RMSE), and some statistical metrics such as precision, recall and F1-score have been used for model validation. According to the obtained results, the VIT model is the most efficient with an AUC of 0.8530, RMSE (0.3900), precision (0.7740), recall (0.7600), and F1-score (0.7610) which gives the most promising values model, than the CNN model with an AUC of 0.8370, RMSE (0.4100), precision (0.7650), recall (0.7550) and F1-score (0.7560). These results show the appropriate power of both models in modeling and the relative superiority of the VIT method. Finally, the SHapley Additive exPlanations (SHAP) method was used to enhance model explainability. SHAP analysis highlighted land cover, rainfall, and geology as the most important factors in this study. Preparing the groundwater potential map helps managers and decision-makers manage these resources’ consumption and use the potential of groundwater as one of the practical criteria for allocating land use.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132840"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Groundwater–surface water exchange affects nitrate fate in a seasonal freeze–thaw watershed: Sources, migration and removal","authors":"Jiamei Wang ,&nbsp;Xin Hao ,&nbsp;Xinyi Liu ,&nbsp;Wei Ouyang ,&nbsp;Tianzhi Li ,&nbsp;Xintong Cui ,&nbsp;Jietong Pei ,&nbsp;Shangwei Zhang ,&nbsp;Weihong Zhu ,&nbsp;Ri Jin","doi":"10.1016/j.jhydrol.2025.132803","DOIUrl":"10.1016/j.jhydrol.2025.132803","url":null,"abstract":"<div><div>The interaction between groundwater and surface water (GW–SW) affects the hydrogeochemical cycle, leading to changes in nitrate sources, migration, and transformation within watersheds. Seasonal freeze–thaw cycles also complicate the above processes. This study employed hydrochemistry, stable isotope analysis, and statistical methods to investigate the dynamic characteristics of GW–SW exchange in a seasonal freeze–thaw watershed, identify the conversion intensities during different periods, and elucidate potential nitrate sources and their relative biogeochemical processes. GW and SW were replenished primarily by atmospheric precipitation, which switched to snowmelt water during the thawing period. Recharge sources and aquifer lithology controlled the seasonal variation in GW–SW exchange. From upstream to downstream, the conversion intensity ranges of SW loss into GW during the wet period were 54.6%, 32.7–55.5%, and 26.5–37.4%, respectively. The percentages of streams that gained GW during the dry period were 62.2–83.7%, 47.1–62.0%, and 35.2–46.0%, respectively. The primary sources of nitrate in GW and SW were fertilizers and livestock waste, with their contributions exhibiting seasonal variations with GW–SW interactions. Agricultural activities and livestock breeding led to high nitrate contents in groundwater, with manure and sewage accounting for up to 90% of the nitrate content during the dry period. Notably, GW–SW interactions during the wet and dry seasons enhanced the denitrification process, contributing to nitrate removal in groundwater. This study revealed that GW–SW interactions significantly impact the fate of nitrate in watersheds and the influence of human activities on watershed environments, providing technical support for watershed water resource management and diffuse pollution control.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132803"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved ALT retrieval in the Yellow River source region using time-series InSAR and multilayer soil moisture modeling","authors":"Zhengjia Zhang ,&nbsp;Qingguang Jin ,&nbsp;Lin Liu ,&nbsp;Mengmeng Wang ,&nbsp;Xuefei Zhang","doi":"10.1016/j.jhydrol.2025.132847","DOIUrl":"10.1016/j.jhydrol.2025.132847","url":null,"abstract":"<div><div>Ongoing climate warming and increased human activities have led to significant permafrost degradation on the Qinghai-Tibet Plateau (QTP). Mapping the distribution of active layer thickness (ALT) can provide essential information for understanding this degradation. Over the past decade, InSAR (Interferometric synthetic aperture radar) technology has been utilized to estimate ALT based on remotely-sensed surface deformation information. However, these methods are generally limited by their ability to accurate extract seasonal deformation and model subsurface water content of active layer. In this paper, an ALT inversion method considering both seasonal deformation from InSAR and smoothly multilayer soil moisture from ERA5 is proposed. Firstly, we introduce a ground seasonal deformation extraction model combining RobustSTL and InSAR, and the deformation extraction accuracy by considering the deformation characteristics of permafrost are evaluated, proving the effectiveness of RobustSTL in extracting seasonal deformation of permafrost. Then, using ERA5 soil moisture products, a smoothed multilayer soil moisture model for ALT inversion is established. Finally, integrating the seasonal deformation and multilayer soil moisture, the ALT can be estimated. The proposed model is applied to the Yellow River source region (YRSR) with Sentinel-1A images acquired from 2017 to 2021, and the ALT retrieval accuracy is validated with measured data. Experimental results show that the vertical deformation rate of the study area generally ranges from −30 mm/year to 20 mm/year, with seasonal deformation amplitude ranging from 2 mm to 30 mm. The RobustSTL method has the highest accuracy in extracting seasonal deformation of permafrost, with an RMSE (root mean square error) of 0.69 mm, and is capable of capturing the freeze–thaw characteristics of the active layer. The estimated ALT of the YRSR ranges from 49 cm to 450 cm, with an average value of 145 cm. Compared to the measured data, the proposed method has an average error of 37.5 cm, which represents a 21 % improvement in accuracy over existing methods.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132847"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement and modeling of canopy interception loss of evergreen, deciduous and mixed forests in a subhumid watershed on the Loess Plateau, China","authors":"Jiongchang Zhao ,&nbsp;Yang Yu ,&nbsp;Yawei Hu ,&nbsp;Matthias Beyer ,&nbsp;Jianjun Zhang","doi":"10.1016/j.jhydrol.2025.132820","DOIUrl":"10.1016/j.jhydrol.2025.132820","url":null,"abstract":"<div><div>Canopy interception, a significant yet inadequately comprehended hydrological phenomenon in terrestrial ecosystems, plays a crucial role in the water balance of forests. A profound understanding of the water retained and re-evaporated through interception storage is essential for developing a comprehensive understanding of forest hydrology. Integration this knowledge into hydrological models can help assess the effects of climate change on forests. In the Loess Plateau of China, extensive ecological restoration measures have been implemented to mitigate severe soil erosion and restore the fragile ecological environment. However, few studies have investigated the role of canopy interception in different tree species compositions (planted monoculture forests and mixed forests). This study monitored precipitation, throughfall, stemflow, and estimated canopy interception in three different forest stands during the 2021–2022 growing season in Shanxi Province, China. Canopy interception was quantified and simulated using the revised Gash model. The observed throughfall, stemflow and canopy interception for deciduous forest were 81.5 %, 1.6 % and 16.9 %, for evergreen forest were 84.2 %, 1.4 % and 14.4 %, respectively. The corresponding values for the mixed forest were 80.7 %, 2.0 % and 17.3 %. The revised model underestimated canopy interception to varying degrees in all three forest types, with the deciduous forest by 11.2 ± 1.8 %, evergreen forests by 21.1 ± 5.5 %, and mixed forest underestimating by, 16.7 ± 3.2 %. According to the statistical parameters (mean absolute error, mean bias error, root mean square error and Nash-Sutcliffe efficiency), the revised model can simulate the canopy interception dynamics of three forest types, with the best performance in simulating the deciduous forest, followed by mixed forest and evergreen forest. The study found that canopy interception loss was significantly influenced by a combination of canopy characteristics (including canopy storage capacity, canopy cover fraction, trunk storage capacity, and the percentage of precipitation diverted into stemflow) and climatic variables (such as average precipitation intensity and average evaporation rate). Among these factors, average precipitation intensity and canopy storage capacity were identified as the most influential variables across all three examined stands. Overall, the revised model was suitable for typical plantation forests and their mixed forests on Loess Plateau. Our study has important implications for understanding of the forest water balance in the Loess Plateau and also contributes to precipitation partitioning forecasts and efficient water resource management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132820"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Capillarity effect on groundwater dynamics during periodic forcing","authors":"Dawei Cheng ,&nbsp;Hongbin Zhan ,&nbsp;Xi Chen ,&nbsp;Shengke Yang ,&nbsp;Dongyong Sun ,&nbsp;Xiuyu Liang","doi":"10.1016/j.jhydrol.2025.132827","DOIUrl":"10.1016/j.jhydrol.2025.132827","url":null,"abstract":"<div><div>The capillarity effect, which refers to the movement of liquid in narrow spaces without the aid of external forces like gravity, plays a crucial role in water movement within soils and is often underrepresented in previous models. In cases where the capillary fringe is always below the soil surface, a new analytical model for saturated flow is developed, with the upper boundary located at the air-entry plane (<span><math><msub><mi>h</mi><mi>a</mi></msub></math></span>), to simulate groundwater dynamics under a single angular frequency harmonic forcing. This new analytical solution agrees well with previous experimental results and a specifically designed saturated–unsaturated flow finite element numerical model. The new model also addresses the assumptions regarding the upper boundary condition in previous models. The oscillatory behavior of the <em>h_a</em> plane are explored based on a simplified approximation of the new solution. The increase in hydraulic conductivity or time-averaged recharge rate will lead to an increase in phase lag and a decrease in amplitude decay. The increase of the initial <em>h_a</em> plane elevation, the average specific yield or the angular frequency of the harmonic forcing will lead to the decrease of the phase lag and the increase of the amplitude decay.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132827"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating basin-scale heterogeneous hydraulic diffusivity fields based on signal decomposition and river stage tomography","authors":"Bo-Tsen Wang ,&nbsp;Yu-Li Wang ,&nbsp;Chia-Hao Chang ,&nbsp;Chin-Tsai Hsiao ,&nbsp;Jordi Mahardika Puntu ,&nbsp;Ping-Yu Chang ,&nbsp;Jui-Pin Tsai","doi":"10.1016/j.jhydrol.2025.132828","DOIUrl":"10.1016/j.jhydrol.2025.132828","url":null,"abstract":"<div><div>River stage tomography (RST) is a potential method for delineating spatial heterogeneity in regional aquifers by analyzing groundwater head variations in response to river stage fluctuations. However, groundwater head data often reflect mixed signals from external stimuli, such as rainfall and river stage, which can compromise parameter estimation. To address this issue, we propose an integrated method combining empirical mode decomposition method (EMD), dynamically dimensional search algorithm (DDS), and RST. Synthetic case results demonstrate that the proposed method reconstructs river-induced head variations with high accuracy (R² = 0.9976, RMSE = 0.0099 m) and yields estimated hydraulic diffusivity (<em>D</em>) field closely matches the true <em>D</em> field. In the real case, the estimated <em>D</em> values align well with the sampled values (differences below 5 % for most wells), and the estimated <em>D</em> field is consistent with the expected aquifer structure within the study area. These findings demonstrate that the proposed method successfully extracts and reconstructs river-induced head variations from original head observations and accurately delineates regional aquifer features. This method shows the significant potential for enhancing RST studies by offering a robust approach for mixed-feature signal decomposition and reconstruction.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132828"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating how inflow forecast lead time affects the operating policies of cascade reservoirs with a focus on water quality issues","authors":"Yasaman Kazemnadi,&nbsp;Mahta Nazari,&nbsp;Reza Kerachian","doi":"10.1016/j.jhydrol.2025.132832","DOIUrl":"10.1016/j.jhydrol.2025.132832","url":null,"abstract":"<div><div>In recent years, due to the effects of climate change and the non-stationarity of hydrological data, the operation of reservoirs has shifted towards adaptive operation utilizing inflow forecasting data. Accurate long-term predictions of inflow to reservoirs are crucial for the adaptive operation of dams. By extending the prediction timeframe, we can incorporate more information about expected inflows over the coming months; however, this also leads to increased uncertainty in those predictions. Therefore, it is necessary to evaluate the effect of the lead time of predictions on the reliability of reservoir operating policies. This problem becomes even more challenging in multi-reservoir systems with objectives related to water quantity and quality (WQQ). This adds computational complexities and poses challenges regarding the run-time of simulation and optimization models. This paper presents an adaptive operation framework for operating a two-reservoir system taking into account both the amount and quality of allocated water to demands, along with the water quality within the reservoirs. Precipitation forecasts for lead times spanning from one to six months are obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF). These precipitation figures are then post-processed and transformed into runoff using a calibrated Soil and Water Assessment Tool (SWAT) model. The adaptive optimization model (AOM) is connected to a two-dimensional CE-QUAL-W2-based water quality simulation model (WQSM), allowing for an effective evaluation of the outflow quality from each gate and a thorough assessment of in-reservoir water quality throughout the optimization process. To reduce the computational cost of the adaptive simulation–optimization model, we use a combination of Parallel Cellular Automata and Local Search optimization algorithms, referred to as PCA-LS. To assess the effectiveness of the proposed methodology, it is implemented in the Karkheh watershed in Iran, which includes two significant reservoirs, Seimare and Karkheh. After comparing the outputs of the models with various rainfall forecast lead times, we found that a two-month lead time yields the most accurate results. The results of the AOM, which predicts rainfall with a two-month lead time, are compared to those of a model that uses perfect (observed) input data. This comparison reveals that the objective functions of the perfect and adaptive models differ by only 0.4%, demonstrating that the adaptive operation policies maintain a high level of accuracy when utilizing optimal rainfall prediction lead time.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132832"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel deep learning-based approach for reconstruction of historical long-term high-quality gridded meteorological dataset","authors":"Yookyung Jeong ,&nbsp;Dongkyun Kim ,&nbsp;Kyuhyun Byun","doi":"10.1016/j.jhydrol.2025.132850","DOIUrl":"10.1016/j.jhydrol.2025.132850","url":null,"abstract":"<div><div>Climate change presents a significant challenge, impacting both the environment and society. Addressing this challenge effectively necessitates in-depth analysis of climate trends and extreme events, relying on long-term, high-resolution meteorological data. However, such data is often lacking in many regions globally, with dense observation networks only recently becoming available. To tackle this issue, our study proposes a novel framework utilizing deep learning to reconstruct high-quality gridded meteorological data for historical periods. Specifically, our approach involves training deep learning models to bridge the gap between gridded products derived from sparse networks, which have existed from the past to the present, and gridded products from dense networks representing recent periods. This training enables us to simulate a gridded product for historical periods of interest using the trained deep learning model. To demonstrate and test our approach, we reconstruct the gridded daily meteorological data for the historical period (1973–1997) over South Korea, where a dense network has been in operation since the late 1990s. The simulated daily datasets by the developed models can capture complex geographic and topographic effects reasonably well, providing a realistic depiction of resulting climate variability. Furthermore, the extreme analysis suggests that the models accurately represent detailed variations between grid cells, contrasting with the limitations of the one derived from sparse observation network, which suffers from gridding artifacts. These findings emphasize the capability of the framework developed in this study to reconstruct high-resolution, high-quality datasets for historical periods without dense observation networks. This indicates the potential of our approach to produce long-term, high-quality gridded meteorological data crucial for hydrological models and climate change analyses, including extreme events.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132850"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How does the mixing assumption influence the distributed tracer-aided hydrological model?","authors":"Yi Nan ,&nbsp;Fuqiang Tian ,&nbsp;Zongxing Li","doi":"10.1016/j.jhydrol.2025.132839","DOIUrl":"10.1016/j.jhydrol.2025.132839","url":null,"abstract":"<div><div>Hydrological simulations bear large uncertainties in mountainous basins due to complex water sources and runoff pathways. Tracer-aided modelling is useful for improving hydrological simulation and reducing uncertainties. The mixing assumption is an important issue for tracer-aided hydrological models. Although numerous studies have shown that partial mixing phenomena are common in small-scale catchments and groundwater storages, no research has yet adopted the partial mixing assumption in distributed tracer-aided hydrological models, and the impact of the mixing assumption on distributed models has not been fully understood. This study developed a two-reservoir method to simulate the partial mixing processes in the groundwater storage for the tracer-aided hydrological model THREW-T. Adopting the model in a typical large mountainous basin on the Tibetan Plateau, we analyzed the influence of mixing assumption on the estimated contribution of subsurface runoff. Results showed that: (1) The model with the partial mixing assumption (THREW-PM) can effectively simulate the isotopic variation of subsurface runoff. The calibrated parameters related to partial mixing indicated a small active storage controlling hydrological response and (∼0.05) a long time required for complete mixing between active and passive storages (∼100 days). (2) The mixing assumption and isotope data had an important influence on the subsurface runoff estimated by the THREW-T model. Adopting the partial mixing assumption and calibrating the model toward the subsurface runoff isotope resulted in a 10 % difference in the estimated contribution. (3) The mixing assumption affected the models by influencing the isotope variation of subsurface runoff. As the temporal variation in the simulated isotope composition of subsurface runoff increased, the estimated contribution of subsurface runoff also increased. This study conducted the first analysis on how mixing assumptions influence distributed tracer-aided hydrological models, and highlighted the importance of tracer data from various water bodies in verifying the simulations of the tracer composition in runoff components, and, the consequently the separation among them.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132839"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of urban stormwater pollution on watershed diffuse loads under extreme precipitation conditions","authors":"Jingyi Hu ,&nbsp;Wei Ouyang ,&nbsp;Congyu Hou ,&nbsp;Kaiyue Ji ,&nbsp;Zhifeng Yang","doi":"10.1016/j.jhydrol.2025.132802","DOIUrl":"10.1016/j.jhydrol.2025.132802","url":null,"abstract":"<div><div>High-quality stormwater management is crucial for sustainable urban development and the protection of aquatic ecosystems, particularly because urbanization and climate-induced extreme events intensify runoff and pollution risks. Although urban stormwater pollution and its potential impacts have been addressed, its impacts on diffuse pollutant loads under compound climate have not been well evaluated. Our study focused on the Bahe River Basin and two river sections at the inlet and outlet of Xi’an city and quantified the impacts of extreme climate and high load risk. The contributions of different precipitation events to pollutant losses were explored using the Soil and Water Assessment tool (SWAT). Cropland was the main source of total nitrogen (TN) and total phosphorus (TP), accounting for 94 % and 91 % of the total pollution during single extreme precipitation events, respectively. However, during compound drought and extreme precipitation events, more than 50 % of the TP pollution originated from urban land. Attribution analysis showed that the heavy precipitation amount (R95P) and frequency (R20MM) were the main factors affecting TN and TP loads, accounting for 65–78 % and 83–88 % of the total impact. In addition, these factors have a greater impact downstream of the city, indicating that urban stormwater pollution increases the response of diffuse loads to climate extremes. The SWAT and copula function were combined to quantify the high-load probabilities under different climatic conditions. The probabilities of the TN and TP load exceeding the top 5 %–30 % were 4 %–19 % and 3 %–21 %, respectively, when the precipitation exceeded the top 20 %, and the probabilities of the TP load downstream of the city were more susceptible to high precipitation. Our study highlights the role of urban stormwater pollution on watershed diffuse loads in addition to point source pollution, with urban development potentially leading to more pollutants being transported to the receiving rivers.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132802"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}