Journal of Hydrology-Regional Studies最新文献

{"title":"Landsat observations reveal Lake Poyang shrinkage over the past 30 Years: Possible association with local climate change and upstream dam construction","authors":"Yue Yuan ,&nbsp;Mingsheng Shang ,&nbsp;Dongmin Wang ,&nbsp;Guang Li ,&nbsp;Meiling Liu ,&nbsp;Ling Wu ,&nbsp;Shuaipeng Wang ,&nbsp;Botian Zhou","doi":"10.1016/j.ejrh.2025.102785","DOIUrl":"10.1016/j.ejrh.2025.102785","url":null,"abstract":"<div><h3>Study region</h3><div>Lake Poyang and its upstream hydrographic network</div></div><div><h3>Study focus</h3><div>Lake Poyang plays a critical role in freshwater supply, flood regulation, and ecosystem maintenance. However, it has experienced increasing freshwater resource scarcity in recent decades. Understanding the spatiotemporal dynamics of lake inundation and its driving forces is therefore essential. This study develops a deep learning-based identification framework that integrates a knowledge-guided adaptive fusion network with probability mapping. Using batch-processed Landsat imagery from 1994 to 2023 on the Google Earth Engine platform, lake inundation was mapped and temporal trends were analysed.</div></div><div><h3>New hydrological insights for the region</h3><div>The results reveal pronounced interannual and seasonal fluctuations in Lake Poyang’s inundation extent. Both the yearly mean and yearly minimum inundated areas exhibit statistically significant declining trends over the past 30 years (−16.43 km²/yr and −21.51 km²/yr, respectively). Causal analyses highlight the influence of local climatic conditions and upstream hydrological changes across multiple temporal scales. The findings offer a novel method for attributing freshwater resource change and caution against attributing Lake Poyang’s shrinkage solely to either local climate change or upstream dam construction.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102785"},"PeriodicalIF":5.0,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling integrated impacts of agro-hydrological interventions on blue and green water and crop yield in SWAT+","authors":"Temesgen Gashaw Tarkegn ,&nbsp;Pieter R. van Oel ,&nbsp;Abebe D. Chukalla ,&nbsp;Ram Lakhan Ray ,&nbsp;Gebrekidan Worku Tefera ,&nbsp;Amare Haileslassie ,&nbsp;Meron Teferi Taye ,&nbsp;Abeyou W. Worqlul ,&nbsp;Enyew Adgo ,&nbsp;Amare Bantider ,&nbsp;Yihun T. Dile","doi":"10.1016/j.ejrh.2025.102783","DOIUrl":"10.1016/j.ejrh.2025.102783","url":null,"abstract":"<div><h3>Study region</h3><div>Lake Tana sub-basin, Ethiopia</div></div><div><h3>Study focus</h3><div>This study evaluates integrated impacts of agro-hydrological interventions on blue and green water, and crop yield using SWAT+. The model was calibrated and validated with monthly streamflow data and long-term average maize yield. Assessed interventions included soil/stone bunds, conservation tillage, early and late planting, and fertilizer applications at 100 kg/ha and 200 kg/ha, using historical climate data from 1992–2021.</div></div><div><h3>New hydrologic insights</h3><div>SWAT+ is suitable for simulating hydrology and crop yield in the study area. At areal average scale, early and late planting reduced blue water by 0.3 % while increasing green water flow (GWF) by 0.4 %. Other practices had no discernible effect on blue water or GWF. Green water storage (GWS) increased under early planting (3.3 %) and conservation tillage (0.8 %) but declined with late planting (9.1 %). Crop yield increased with early planting (12.1 %), fertilizer application at 100 kg/ha and 200 kg/ha (16.0 % and 24.5 %, respectively), and the adoption of soil/stone bunds (0.4 %). Conversely, late planting and conservation tillage reduced crop yields. Spatial analysis revealed that intervention effects varied across regions in water and crop outcomes. Certain practices like early planting, increased crop yields but also led to unintended reductions in blue water. These findings highlight the need for integrated, region-specific agro-hydrological strategies to balance agricultural productivity with sustainable water resource management.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102783"},"PeriodicalIF":5.0,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecosystem drought recovery and its driving factors in southwest China","authors":"Zhongxi Ge ,&nbsp;Jingting Wang ,&nbsp;Bo-Hui Tang ,&nbsp;Peiyu Lai ,&nbsp;Liang Huang ,&nbsp;Menghua Li ,&nbsp;Zhen Zhang ,&nbsp;Dong Fan ,&nbsp;Yun Zhou","doi":"10.1016/j.ejrh.2025.102780","DOIUrl":"10.1016/j.ejrh.2025.102780","url":null,"abstract":"<div><h3>Study area</h3><div>Southwest China.</div></div><div><h3>Study focus</h3><div>Southwest China, with its karst topography and mismatched soil-water resources, is highly susceptible to drought stress. Drought recovery time, defined as the time required for ecosystems to restore their pre-drought functions following stress, is critical for evaluating impacts of droughts and ecosystem resilience. Previous studies have predominantly focused on the influence of factors such as temperature, precipitation, and gross primary production on ecosystem drought recovery time across large scales, with insufficient attention paid to southwest China: a region prone to frequent droughts and ecologically vulnerable. To investigate the characteristics of drought recovery time in different ecosystems across southwest China under the following two drought recovery trajectories when drought occurs at different time, as well as the impacts of multiple driving factors on drought recovery time: (1) drought recovery was completed prior to the winter of the dry year (R_SGS); (2) drought recovery extended into the winter and the subsequent year following the drought year (R_MGS), this study used Standardized Precipitation Evapotranspiration Index (SPEI) and solar-induced chlorophyll fluorescence (SIF) to identify drought recovery time. It categorized ecosystem drought recovery into two trajectories and utilized the Random Forest (RF) model to assess the importance of various bioclimatic factors, vegetation physiological conditions, and karst landform in influencing ecosystem drought recovery.</div></div><div><h3>New hydrological insights for the regions</h3><div>The results showed that: (1) The drought recovery time of different ecosystems in southwest China shows significant differences. (2) Precipitation during the drought response lag period significantly influenced drought recovery under R_SGS; according to the feature importance results identified by the RF model, the importance of spring phenology to drought recovery is 78 %-85 % under R_MGS. (3) Precipitation, temperature, vapor pressure deficit (VPD), and spring phenology all have significant impacts on drought recovery in both recovery trajectories. These findings highlight the key role of hydrological conditions and spring phenology in drought recovery and emphasize their importance in accurately quantifying ecosystem resilience and guiding future climate change adaptation strategies.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102780"},"PeriodicalIF":5.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145108020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal sites for rainwater harvesting and proposed dams: A geospatial and analytic hierarchy process-based feasibility study in Western Saudi Arabia","authors":"Eltaher M.M. Shams ,&nbsp;Rashad Sawires ,&nbsp;Sahar N.E. Tawfik ,&nbsp;Hanaa R. Youssef ,&nbsp;Tadahiro Kishida","doi":"10.1016/j.ejrh.2025.102782","DOIUrl":"10.1016/j.ejrh.2025.102782","url":null,"abstract":"<div><h3>Study region</h3><div>This study focuses on an arid zone of Saudi Arabia that is experiencing rapid urban growth and escalating water scarcity. The region encompasses major cities such as Mecca, Jeddah, Khulays, and Rabigh, where the demand for sustainable water resource management is becoming increasingly urgent due to the limited availability of natural freshwater sources. The challenge is further intensified by ongoing urbanization and large-scale economic developments, particularly around Mecca, Jeddah, King Abdullah Economic City, and Yanbu Industrial City, which place additional pressure on the region’s fragile water systems.</div></div><div><h3>Study focus</h3><div>The objective of this research is to assess and map the suitability of rainwater harvesting (RWH) sites using an integrated approach that combines Geographic Information System (GIS), the Analytic Hierarchy Process (AHP), and Multi-Criteria Decision Analysis (MCDA). The analysis incorporates hydrological, geological, and infrastructural criteria, guided by Food and Agriculture Organization (FAO) guidelines. The study also evaluates the performance and contribution of existing RWH infrastructure and identifies optimal locations for future dam construction.</div></div><div><h3>New hydrological insights for the region</h3><div>The results indicate that approximately 6000 km² (∼26 % of the study area) is highly suitable for RWH, with an estimated surface runoff potential of about 730 million m³ . Existing dams—Khlays, Rabiigh, and Fatima—play a significant role in regional water supply. Four primary locations—Ghoran, Thule, Qahah, and Fatima—were identified as optimal for new dam sites, with estimated water storage capacities calculated. These findings demonstrate the potential of integrated RWH planning to enhance renewable water resources, support long-term water security, and inform policy and infrastructure development in arid regions like Western Saudi Arabia.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102782"},"PeriodicalIF":5.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145108018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning insights into groundwater demand under changing surface water availability: Murray-Darling Basin, Australia","authors":"Stephanie R. Clark ,&nbsp;Dennis Gonzalez ,&nbsp;Guobin Fu ,&nbsp;Sreekanth Janardhanan","doi":"10.1016/j.ejrh.2025.102772","DOIUrl":"10.1016/j.ejrh.2025.102772","url":null,"abstract":"<div><h3>Study region</h3><div>In the Murray–Darling Basin (MDB) of Australia, climate change is leading to shifts in the availability of surface water which is driving an increased reliance on groundwater resources. Projected declines in rainfall and rising climate variability are expected to amplify this trend, heightening the role of groundwater in supplementing water demand.</div></div><div><h3>Study focus</h3><div>Quantifying this change is important for ensuring water resource resilience and sustainability into the future. This study explores hydroclimatic conditions associated with periods of elevated groundwater use and evaluates how future reductions in surface water reliability may influence extraction patterns. Relationships between surface water and groundwater dependence are analysed and groundwater requirements under a range of hypothetical future scenarios are simulated. The deep learning-based stress-testing framework used here accounts for simultaneous changes in important surface water components amid the inherent uncertainty of future conditions.</div></div><div><h3>New hydrological insights for the region</h3><div>Results show groundwater demand could increase by up to 16 % under plausible future reductions in rainfall and surface water storage, compared with modelled predictions based on 2010–2020 data. The study demonstrates the utility of machine learning for scenario testing under uncertainty and at multiple-aquifer scale. Findings emphasize the interconnected nature of surface and groundwater systems in the MDB and highlight the importance of conjunctive water management strategies to ensure long-term water security under changing climate conditions.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102772"},"PeriodicalIF":5.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145108019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecosystem service water use efficiency: A new perspective for coordinating ecosystem services and water consumption in the Loess Plateau","authors":"Yanmin Teng ,&nbsp;Chao Xu ,&nbsp;Yuan Zhang ,&nbsp;Meirong Su ,&nbsp;Yangjian Zhang ,&nbsp;Shiting Li ,&nbsp;Qionghong Chen ,&nbsp;Qianyuan Huang","doi":"10.1016/j.ejrh.2025.102770","DOIUrl":"10.1016/j.ejrh.2025.102770","url":null,"abstract":"<div><h3>Study region</h3><div>The Loess Plateau (LP), China</div></div><div><h3>Study focus</h3><div>Ecological restoration on the LP has substantially enhanced ecosystem services (ESs), but at the cost of significant water resource depletion, highlighting the urgent need to improve water use efficiency. Based on the concept of ecosystem water use efficiency, we proposed a new indicator—Ecosystem Services Water Use Efficiency (ES_WUE), defined as the ratio of ESs to actual evapotranspiration. We assessed three key ESs—water erosion prevention, wind erosion prevention, and carbon sequestration—across the LP from 2000 to 2020, and quantified corresponding ES_WUE. Subsequently, we examined their spatiotemporal patterns, and explored key influencing factors using multiple statistical models.</div></div><div><h3>New hydrological insights for the region</h3><div>The ES_WUE extends traditional water use efficiency by integrating multiple ESs, enabling a holistic evaluation that supports sustainable and balanced ecological restoration planning. Results showed that vegetation coverage precipitation, aridity index, slope, and elevation were the primary factor influencing spatial variations in ES_WUE. Temporal changes in aridity index, potential evapotranspiration, and vegetation coverage were the main drivers of ES_WUE dynamics. Grassland expansion was found to positively contribute to the three ES_WUE. Moreover, ESs had a stronger influence than actual evapotranspiration on spatiotemporal variations in ES_WUE. This study offers a novel perspective for ecological restoration in water-limited regions, emphasizing reducing water consumption for enhancing ESs by focusing on ES_WUE.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102770"},"PeriodicalIF":5.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling hydrological functioning of karst aquifer systems in Slovenia using geomorphological features and random forest algorithm","authors":"Mitja Janža ,&nbsp;Valter Hudovernik ,&nbsp;Luka Serianz ,&nbsp;Andrej Stroj","doi":"10.1016/j.ejrh.2025.102774","DOIUrl":"10.1016/j.ejrh.2025.102774","url":null,"abstract":"<div><h3>Study region</h3><div>Slovenia</div></div><div><h3>Study focus</h3><div>This study investigates the relationship between the hydrological functioning of karst aquifer systems and the geomorphological characteristics of their catchments. It is based on the analysis of discharge time series from 15 karst springs. Hydrograph analysis of these time series was used to estimate 11 hydrological parameters that characterize aquifer system functioning. A spatial analysis of morphological, geological, and hydrological data was carried out to assess 7 lumped geomorphological features of the catchments. These features (independent variables) and hydrological parameters (dependent variables) were used to develop random forest models for predicting the hydrological functioning of karst springs.</div></div><div><h3>New hydrological insights for the region</h3><div>The developed methodological approach provides a basis for improved characterization and prediction of the hydrological functioning of ungauged karst systems. Groundwater availability in these systems is largely controlled by aquifer retention capacity and spring discharge variability. These characteristics can be inferred from hydrological parameters that can be predicted using the developed random forest models. Feature importance analysis indicated that catchment area, cave density, and slope gradient are the most important geomorphological features for predicting the hydrological characteristics of spring discharge.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102774"},"PeriodicalIF":5.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of datasets in hydrological simulation in various basin scales：An investigation on hydrological lumped effect in the Lancang-Mekong region","authors":"Hui Liu ,&nbsp;Zhiqiang Dong ,&nbsp;Baiyin Baoligao ,&nbsp;Vannaphone Phetpaseuth ,&nbsp;Thongthip Chandalasane ,&nbsp;Wenxue Chen ,&nbsp;Xiangpeng Mu ,&nbsp;Dengfeng Liu ,&nbsp;Lajiao Chen ,&nbsp;Xiaochen Li ,&nbsp;Hongchang Hu ,&nbsp;Jie Wen","doi":"10.1016/j.ejrh.2025.102769","DOIUrl":"10.1016/j.ejrh.2025.102769","url":null,"abstract":"<div><h3>Study region</h3><div>Laos area in the Lancang-Mekong River Basin (LMRB).</div></div><div><h3>Study focus</h3><div>Choosing appropriate models and precipitation to capture hydrological conditions and manage water resources in various basin scales is crucial. However, when dealing with smaller-scale basins, the suitability of different datasets remains a challenge, particularly in regions characterized by high spatial heterogeneity. In this study, we utilized ERA5-Land data within LMRB and rain gauge data within Laos to calibrate seven mainstream stations and eleven tributary stations from 1981 to 2000 using the Xin'anjiang (XAJ) model. Subsequently, we evaluated the performance of four datasets from 2001 to 2009, including rain gauge data and three gridded datasets (ERA5-Land, IMERG-Final, and APHRODITE).</div></div><div><h3>New hydrological insights for the region</h3><div>Our analysis revealed that ERA5-Land data outperformed overall among the four datasets, with mainstream stations achieving an average Nash-Sutcliffe Efficiency (NSE) of 0.86 and a 19 % Mean Absolute Relative Error (MARE), while tributary stations exhibited an average NSE of 0.64 with a 59 % MARE. During the validation, the hydrological simulations based on the three gridded precipitation datasets outperformed the simulations using rain gauge data at the eight tributary stations in Laos. Furthermore, a discernible trend is observed among these stations: as the basin scales increase, simulation outcomes improve, emphasizing a distinct hydrological lumped effect. This study can provide a crucial reference for hydrological simulations and water resource management in Laos.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102769"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145108017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"System dynamics for assessing anthropogenic and climate change impacts on agro-hydrological sustainability, leveraging the newly developed evapotranspiration model. Case study: Qaranqu watershed","authors":"Vahid Nourani ,&nbsp;Shahin Fathi ,&nbsp;Yongqiang Zhang ,&nbsp;Sameh A. Kantoush ,&nbsp;Jinhui Jeanne Huang","doi":"10.1016/j.ejrh.2025.102781","DOIUrl":"10.1016/j.ejrh.2025.102781","url":null,"abstract":"<div><h3>Study region</h3><div>Qaranqu watershed, Iran</div></div><div><h3>Study focus</h3><div>Complex interactions among climate change, anthropogenic activities and water resource management examined via system dynamics and Penman-Monteith-Leuning (PML) Evapotranspiration (ET) model.</div></div><div><h3>New hydrological insights for the region</h3><div>Through crop pattern modification scenario, variations in vegetation type resulted in 6 and 3.8 million cubic meters per year in available water by PML and PM models, respectively, which is approximately 10 and 2.5 percent higher than the current available water trend due to increase in rainfed wheat areas and in turn, reduction in leaf area index. However, cessation of land development due to high ET in pastures might cause a decrease in available water about 1 million cubic meters in the early years and 18 million cubic meters in the later years, corresponding to 1–27 % of available water compared to the existing trend from 2020 to 2045. Also, cessation of agricultural land development has resulted in decrease in GDP for this sector in contrast to other economic sectors. Given that agricultural sector’s investment share regard to total investment has risen to 23 %, its GDP share may be decreased by 12 % until 2045. The shift of this investment to other economic sectors, by 10 and 13 percent in industry and services sectors, respectively, indicates changes in GDP ratio of these sectors to total GDP by 7 and 5 percent until 2045.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102781"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating statistical and machine learning approaches for sediment transport prediction in a typical coarse sandy region of the Yellow River Basin","authors":"Xuan Zhang ,&nbsp;Jian Luo ,&nbsp;Ruihong Yu ,&nbsp;Ping Miao ,&nbsp;Lanxuan Yin","doi":"10.1016/j.ejrh.2025.102777","DOIUrl":"10.1016/j.ejrh.2025.102777","url":null,"abstract":"<div><h3>Study region</h3><div>Inner Mongolia Autonomous Region (China).</div></div><div><h3>Study focus</h3><div>This study investigated the multiscale correlations among runoff, precipitation, potential evapotranspiration (PET), and normalized difference vegetation index (NDVI) with sediment load in the Ten Tributaries region from 2007 to 2021. Furthermore, sediment transport was predicted using statistical models and machine learning (ML) techniques to enhance understanding of sediment dynamics under varying environmental conditions.</div></div><div><h3>New hydrogeological insights from the region</h3><div>This work provided novel insights on the quantification of the scale-specific controls of sediment load in the coarse sandy region of the Yellow River. Multivariate empirical mode decomposition (MEMD) was employed to decompose the original time series of sediment load and its associated variables into five or six intrinsic mode functions (IMFs) and one residual component. Time-dependent intrinsic correlation (TDIC) analysis revealed that the relationships between sediment load and environmental factors exhibit dynamic, multi-scale properties. Runoff was the key factor affecting sediment load in Maobula and Xiliugou watershed. In Hantaichuan watershed, runoff dominated sediment load dynamics from IMF1 to IMF5, whereas PET governed the sediment transport process at IMF6. Three machine learning models, multilayer perceptron (MLP), convolutional neural networks (CNN) and particle swarm optimization-support vector regression (PSO-SVR) were applied to forecast sediment load in different basins. Integrating MEMD with ML significantly enhanced sediment load prediction accuracy.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102777"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145108015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}