Journal of Hydrology-Regional Studies最新文献_第5页

Reconstruction of global long-term daily streamflow dataset using machine learning models for revealing streamflow changes 利用机器学习模型重建全球长期日流量数据集，揭示流量变化

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-19 DOI: 10.1016/j.ejrh.2026.103148

Yingying Gao , Zengliang Luo , Huan Liu , Lunche Wang , Xi Chen , Huan Li

Study regions

314 major global watersheds.

Study focus

In the context of widespread streamflow observation data gaps and significant basin heterogeneity worldwide, this study aims to construct a high-precision, long-term global daily-scale streamflow reconstruction dataset. Focusing on 314 major river basins globally (1980–2020), we systematically evaluate the performance of four machine learning models—Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM)—in reconstructing streamflow sequences and identify optimal modeling strategies suitable for different basin conditions. To reduce input data uncertainty, the study concentrates on reconstructing streamflow at basin outlets, leveraging their larger catchment areas and relatively reliable meteorological forcing information. The resulting dataset provides a high-quality resource for analyzing global streamflow variability and its climatic drivers.

New hydrological insights for the region

Based on the reconstructed dataset, a study of long-term streamflow patterns in global river basins, with a focus on the changing characteristics of extreme flows (high and low flows) and their climatic drivers, reveals the following: African river basins show the highest proportion of significant increasing trends in both long-term and extreme streamflow; South America and Australia have a relatively large number of river basins (approximately 58 % and 59 %, respectively) where long-term streamflow shows a significant decrease. Globally, the proportion of river basins with significantly increasing mid- to long-term streamflow is generally below 10 %, while a higher proportion of basins show rising trends in low flows and mean flows, reflecting a possible trend toward wetter conditions in most regions. Additionally, ENSO plays an important regulatory role in streamflow variability, particularly in tropical regions, where El Niño and La Niña events correspond to significant alternating dry and wet anomalies in streamflow responses.

研究区域314个全球主要流域。在全球范围内广泛存在的河流观测数据缺口和明显的流域异质性背景下，本研究旨在构建高精度、长期的全球日尺度河流重建数据集。以1980-2020年全球314个主要河流流域为研究对象，系统评估了随机森林（RF）、梯度增强决策树（GBDT）、极端梯度增强（XGBoost）和光梯度增强机（LightGBM）四种机器学习模型在重建河流序列中的性能，并确定了适合不同流域条件的最佳建模策略。为了减少输入数据的不确定性，研究集中在流域出水口重建水流，利用其更大的集水区和相对可靠的气象强迫信息。由此产生的数据集为分析全球流量变率及其气候驱动因素提供了高质量的资源。基于重建数据集，对全球河流流域的长期流量模式进行了研究，重点研究了极端流量（高流量和低流量）的变化特征及其气候驱动因素，结果表明：非洲流域的长期和极端流量都呈现出显著增加趋势的比例最高；南美洲和澳大利亚有相对较多的流域（分别约为58% %和59% %），其中长期流量显着减少。在全球范围内，中长期流量显著增加的流域比例一般在10% %以下，而较高比例的流域在低流量和平均流量方面呈上升趋势，反映了大多数地区可能的湿润趋势。此外，ENSO在径流变率中起着重要的调节作用，特别是在热带地区，El Niño和La Niña事件对应于径流响应中显著的干湿交替异常。

{"title":"Reconstruction of global long-term daily streamflow dataset using machine learning models for revealing streamflow changes","authors":"Yingying Gao , Zengliang Luo , Huan Liu , Lunche Wang , Xi Chen , Huan Li","doi":"10.1016/j.ejrh.2026.103148","DOIUrl":"10.1016/j.ejrh.2026.103148","url":null,"abstract":"<div><h3>Study regions</h3><div>314 major global watersheds.</div></div><div><h3>Study focus</h3><div>In the context of widespread streamflow observation data gaps and significant basin heterogeneity worldwide, this study aims to construct a high-precision, long-term global daily-scale streamflow reconstruction dataset. Focusing on 314 major river basins globally (1980–2020), we systematically evaluate the performance of four machine learning models—Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM)—in reconstructing streamflow sequences and identify optimal modeling strategies suitable for different basin conditions. To reduce input data uncertainty, the study concentrates on reconstructing streamflow at basin outlets, leveraging their larger catchment areas and relatively reliable meteorological forcing information. The resulting dataset provides a high-quality resource for analyzing global streamflow variability and its climatic drivers.</div></div><div><h3>New hydrological insights for the region</h3><div>Based on the reconstructed dataset, a study of long-term streamflow patterns in global river basins, with a focus on the changing characteristics of extreme flows (high and low flows) and their climatic drivers, reveals the following: African river basins show the highest proportion of significant increasing trends in both long-term and extreme streamflow; South America and Australia have a relatively large number of river basins (approximately 58 % and 59 %, respectively) where long-term streamflow shows a significant decrease. Globally, the proportion of river basins with significantly increasing mid- to long-term streamflow is generally below 10 %, while a higher proportion of basins show rising trends in low flows and mean flows, reflecting a possible trend toward wetter conditions in most regions. Additionally, ENSO plays an important regulatory role in streamflow variability, particularly in tropical regions, where El Niño and La Niña events correspond to significant alternating dry and wet anomalies in streamflow responses.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103148"},"PeriodicalIF":5.0,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024507","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}

引用次数: 0

Vapor pressure deficit dominated actual evapotranspiration changes in the Southeast River Basin of China from 1981 to 2021: A PML-based attribution analysis 1981 - 2021年中国东南河流流域水汽压亏缺主导实际蒸散发变化——基于pml的归因分析

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-19 DOI: 10.1016/j.ejrh.2026.103137

Linqiao Ran , Fangleng He , Xingwei Chen , Ying Chen , Meibing Liu , Haijun Deng

Study area

The Southeast River Basin is one of China's nine major river basins. As a typical monsoon humid region, it has exhibited significant actual evapotranspiration（ET_a） growth in recent years.

Study focus

Existing studies in this basin predominantly rely on publicly available global datasets, lacking process-based mechanism analyses. This study employs Penman-Monteith-Leuning (PML) model to simulate daily-scale ET_a from 1981 to 2021. Owing to insufficient observed ET_a data, the three-cornered hat method was employed to assess simulation accuracy,then use detrending experiment to systematically analyse the spatiotemporal evolution and component variations of ET_a, identifying the dominant factors.

New hydrological insights for the region

The PML model demonstrated the highest stability in cross-validation across three datasets. Since 1981, ET_a in this basin has exhibited significant growth (4.39 mm year⁻¹, p < 0.05), with the fastest increase occurring in spring (1.45 mm year⁻¹). Spatially, trends are most pronounced in the northwestern and central regions, while northeastern and coastal areas exhibit weaker trends or even declines. Component-wise, transpiration accounts for 71.20 % of ET_a. Trend analysis indicates that vapour pressure deficit (VPD) is the primary driver (contributing 38.70 %), followed by leaf area index (LAI, 18.41 %). These findings mark a shift from trend description to mechanistically driven quantitative understanding, providing robust data support and theoretical foundations for comprehending ET_a dynamics and ecohydrological processes in the southeastern of China.

研究区域东南河流域是中国九大流域之一。作为典型的季风湿润区，近年来实际蒸散量（ETa）增长显著。该盆地的现有研究主要依赖于公开的全球数据集，缺乏基于过程的机制分析。本文采用Penman-Monteith-Leuning （PML）模型模拟了1981 - 2021年的日尺度ETa。由于ETa观测数据不足，采用三角帽法对模拟精度进行评估，然后利用去趋势实验系统分析ETa的时空演变和成分变化，找出主导因素。在跨三个数据集的交叉验证中，PML模型显示出最高的稳定性。1981年以来，该盆地ETa呈显著增长（4.39 mm year−1,p <； 0.05），其中春季增长最快（1.45 mm year−1）。从空间上看，西北和中部地区趋势最为明显，东北和沿海地区趋势较弱甚至下降。在组分方面，蒸腾作用占ETa的71.20 %。趋势分析表明，水汽压亏缺（VPD）是主要驱动因子（贡献38.70 %），其次是叶面积指数（LAI，贡献18.41 %）。这些发现标志着从趋势描述到机制驱动的定量理解的转变，为理解中国东南部ETa动态和生态水文过程提供了强有力的数据支持和理论基础。

{"title":"Vapor pressure deficit dominated actual evapotranspiration changes in the Southeast River Basin of China from 1981 to 2021: A PML-based attribution analysis","authors":"Linqiao Ran , Fangleng He , Xingwei Chen , Ying Chen , Meibing Liu , Haijun Deng","doi":"10.1016/j.ejrh.2026.103137","DOIUrl":"10.1016/j.ejrh.2026.103137","url":null,"abstract":"<div><h3>Study area</h3><div>The Southeast River Basin is one of China's nine major river basins. As a typical monsoon humid region, it has exhibited significant actual evapotranspiration（ET<sub>a</sub>） growth in recent years.</div></div><div><h3>Study focus</h3><div>Existing studies in this basin predominantly rely on publicly available global datasets, lacking process-based mechanism analyses. This study employs Penman-Monteith-Leuning (PML) model to simulate daily-scale ET<sub>a</sub> from 1981 to 2021. Owing to insufficient observed ET<sub>a</sub> data, the three-cornered hat method was employed to assess simulation accuracy,then use detrending experiment to systematically analyse the spatiotemporal evolution and component variations of ET<sub>a</sub>, identifying the dominant factors.</div></div><div><h3>New hydrological insights for the region</h3><div>The PML model demonstrated the highest stability in cross-validation across three datasets. Since 1981, ET<sub>a</sub> in this basin has exhibited significant growth (4.39 mm year<sup>−1</sup>, p < 0.05), with the fastest increase occurring in spring (1.45 mm year<sup>−1</sup>). Spatially, trends are most pronounced in the northwestern and central regions, while northeastern and coastal areas exhibit weaker trends or even declines. Component-wise, transpiration accounts for 71.20 % of ET<sub>a</sub>. Trend analysis indicates that vapour pressure deficit (VPD) is the primary driver (contributing 38.70 %), followed by leaf area index (LAI, 18.41 %). These findings mark a shift from trend description to mechanistically driven quantitative understanding, providing robust data support and theoretical foundations for comprehending ET<sub>a</sub> dynamics and ecohydrological processes in the southeastern of China.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103137"},"PeriodicalIF":5.0,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024493","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}

引用次数: 0

How well do U.S. National Water Model short-range forecasts predict flood event timing and magnitude? 美国国家水模型短期预测对洪水事件时间和规模的预测有多好？

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-19 DOI: 10.1016/j.ejrh.2026.103108

Iman Maghami , Daniel P. Ames , Amin Aghababaei , Abin Raj Chapagain , Jacob M. Anderson , Jerson J. Garcia

Study region

Continental United States (CONUS).

Study focus

The National Water Model (NWM), operational since 2016, provides real-time, continuous hydrologic forecasts across the CONUS. Prior studies have evaluated NWM performance, but comprehensive assessments across multiple regions, lead times, and settings remain limited. This study evaluates NWM version 2.1 short-range forecasts for multiple flood events during 2021–2023, analyzing performance across varying watershed characteristics, flood magnitudes (return periods), and lead times. We used data from 306 U.S. Geological Survey gauges across 16 study areas, several with multiple floods per site, to assess forecast accuracy in terms of hydrograph skill, peak discharge, flood volume, and time-to-peak bias.

New hydrologic insights for the region

Results show that forecast accuracy improves with shorter lead times and smaller floods but varies by watershed traits and climate. Systematic underestimation of peak discharge and flood volume occurred across all basin types. Urban, regulated, arid, and low-order watersheds tend to show higher forecast errors. We qualitatively inspected hydrograph shapes, finding that while many forecasts captured rising and falling limbs, some exhibited systematic anomalies, such as consistently declining, delayed forecasts, and failure to detect sharp flood peaks, highlighting structural issues in model response. Findings provide insight into the strengths and limitations of NWM short-range flood forecasts and offer a baseline for evaluating future NWM versions and the emerging NextGen modeling framework.

研究区域美国大陆（CONUS）。国家水模型（NWM）自2016年开始运行，为整个CONUS提供实时、连续的水文预测。先前的研究已经评估了NWM的性能，但对多个地区、交货时间和环境的综合评估仍然有限。本研究评估了NWM 2.1版本对2021-2023年多个洪水事件的短期预测，分析了不同流域特征、洪水规模（回归期）和提前期的表现。我们使用的数据来自306 U.S.地质调查局测量了16个研究区域，每个站点有多个洪水，以评估水文技术、峰值流量、洪水量和峰值时间偏差方面的预测准确性。结果表明，预报精度随着提前时间的缩短和洪水的减少而提高，但因流域特征和气候而异。所有流域类型均存在对洪峰流量和洪量的系统性低估。城市、管制、干旱和低阶流域往往表现出较高的预测误差。我们定性地检查了水文曲线的形状，发现虽然许多预测捕获了上升和下降的分支，但有些预测显示出系统性异常，例如持续下降、延迟预测和未能检测到尖锐的洪峰，突出了模型响应中的结构性问题。研究结果有助于深入了解NWM短期洪水预报的优势和局限性，并为评估未来NWM版本和新兴的NextGen建模框架提供基线。

{"title":"How well do U.S. National Water Model short-range forecasts predict flood event timing and magnitude?","authors":"Iman Maghami , Daniel P. Ames , Amin Aghababaei , Abin Raj Chapagain , Jacob M. Anderson , Jerson J. Garcia","doi":"10.1016/j.ejrh.2026.103108","DOIUrl":"10.1016/j.ejrh.2026.103108","url":null,"abstract":"<div><h3>Study region</h3><div>Continental United States (CONUS).</div></div><div><h3>Study focus</h3><div>The National Water Model (NWM), operational since 2016, provides real-time, continuous hydrologic forecasts across the CONUS. Prior studies have evaluated NWM performance, but comprehensive assessments across multiple regions, lead times, and settings remain limited. This study evaluates NWM version 2.1 short-range forecasts for multiple flood events during 2021–2023, analyzing performance across varying watershed characteristics, flood magnitudes (return periods), and lead times. We used data from 306 U.S. Geological Survey gauges across 16 study areas, several with multiple floods per site, to assess forecast accuracy in terms of hydrograph skill, peak discharge, flood volume, and time-to-peak bias.</div></div><div><h3>New hydrologic insights for the region</h3><div>Results show that forecast accuracy improves with shorter lead times and smaller floods but varies by watershed traits and climate. Systematic underestimation of peak discharge and flood volume occurred across all basin types. Urban, regulated, arid, and low-order watersheds tend to show higher forecast errors. We qualitatively inspected hydrograph shapes, finding that while many forecasts captured rising and falling limbs, some exhibited systematic anomalies, such as consistently declining, delayed forecasts, and failure to detect sharp flood peaks, highlighting structural issues in model response. Findings provide insight into the strengths and limitations of NWM short-range flood forecasts and offer a baseline for evaluating future NWM versions and the emerging NextGen modeling framework.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103108"},"PeriodicalIF":5.0,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024491","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}

引用次数: 0

Attention in MLP: A new architecture for urban sewer overflow and flood depth prediction MLP的关注：城市下水道溢流和洪水深度预测的新架构

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-17 DOI: 10.1016/j.ejrh.2025.103088

Song-Yue Yang , Bing-Chen Jhong , Rui-Wen Lin , Ming-Chang Tsai

Study region

This research focuses on the vicinity of the A8 Metro Station in Guishan District, Taoyuan City, Taiwan, an area prone to frequent urban flooding. With storm sewer water level and surface flood depth data available, the region offers diverse rainfall conditions and topographical variations. This enables a thorough assessment of model performance for managing overflow risks and inundation.

Study focus

We propose an innovative Attentive Multilayer Perceptron (AM-MLP) architecture, comparing it against widely used sequence models (long short-term memory (LSTM), gated recurrent unit (GRU), and bidirectional LSTM (BiLSTM)). We systematically evaluate sewer water level and flood depth forecasts to test whether attention mechanisms can compensate for MLP’s weak sequence handling. A unified experimental setup ensures fair baseline comparisons, highlighting each model’s strengths and weaknesses.

New hydrological insights for the region

This study provides valuable hydrological insights for the study area around the A8 Metro Station in Guishan District, Taoyuan City, Taiwan. The results demonstrate how the AM-MLP model improves urban flood and sewer overflow predictions in regions with limited or discontinuous data. The model’s ability to capture key hydrological factors, such as variations in rainfall and drainage system limitations, allows for more accurate flood depth and sewer water level forecasts. These insights contribute to better flood risk management and urban resilience planning in regions facing extreme rainfall events.

研究区域本研究以台湾桃园市桂山区A8地铁站附近为研究对象，该区域为城市洪涝频发区。随着雨水下水道水位和地表洪水深度数据的可用性，该地区提供了不同的降雨条件和地形变化。这使得对管理溢出风险和淹没的模型性能进行全面评估成为可能。我们提出了一种创新的关注多层感知器（AM-MLP）架构，并将其与广泛使用的序列模型（长短期记忆（LSTM），门控循环单元（GRU）和双向LSTM (BiLSTM)）进行了比较。我们系统地评估下水道水位和洪水深度预测，以测试注意力机制是否可以补偿MLP的弱序列处理。统一的实验设置确保公平的基线比较，突出每个模型的优点和缺点。本研究为台湾桃园市桂山区地铁A8站周边研究区提供了有价值的水文见解。结果表明，在数据有限或不连续的地区，AM-MLP模型如何改善城市洪水和下水道溢流预测。该模型能够捕捉关键的水文因素，如降雨变化和排水系统限制，从而可以更准确地预测洪水深度和下水道水位。这些见解有助于在面临极端降雨事件的地区更好地进行洪水风险管理和城市韧性规划。

{"title":"Attention in MLP: A new architecture for urban sewer overflow and flood depth prediction","authors":"Song-Yue Yang , Bing-Chen Jhong , Rui-Wen Lin , Ming-Chang Tsai","doi":"10.1016/j.ejrh.2025.103088","DOIUrl":"10.1016/j.ejrh.2025.103088","url":null,"abstract":"<div><h3>Study region</h3><div>This research focuses on the vicinity of the A8 Metro Station in Guishan District, Taoyuan City, Taiwan, an area prone to frequent urban flooding. With storm sewer water level and surface flood depth data available, the region offers diverse rainfall conditions and topographical variations. This enables a thorough assessment of model performance for managing overflow risks and inundation.</div></div><div><h3>Study focus</h3><div>We propose an innovative Attentive Multilayer Perceptron (AM-MLP) architecture, comparing it against widely used sequence models (long short-term memory (LSTM), gated recurrent unit (GRU), and bidirectional LSTM (BiLSTM)). We systematically evaluate sewer water level and flood depth forecasts to test whether attention mechanisms can compensate for MLP’s weak sequence handling. A unified experimental setup ensures fair baseline comparisons, highlighting each model’s strengths and weaknesses.</div></div><div><h3>New hydrological insights for the region</h3><div>This study provides valuable hydrological insights for the study area around the A8 Metro Station in Guishan District, Taoyuan City, Taiwan. The results demonstrate how the AM-MLP model improves urban flood and sewer overflow predictions in regions with limited or discontinuous data. The model’s ability to capture key hydrological factors, such as variations in rainfall and drainage system limitations, allows for more accurate flood depth and sewer water level forecasts. These insights contribute to better flood risk management and urban resilience planning in regions facing extreme rainfall events.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103088"},"PeriodicalIF":5.0,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981448","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}

引用次数: 0

Optimizing the contributions of sand dam water storage through understanding their spatiotemporal variability: Evidence from the Shashe catchment, Limpopo, River Basin 基于时空变异性的沙坝蓄水贡献优化——来自林波波河流域沙舍流域的证据

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-17 DOI: 10.1016/j.ejrh.2025.103102

Girma Yimer Ebrahim , Jonathan F. Lautze , Matthew McCartney , Fortune Batiya , Stephen Hussey , Joyce Dube

Study region

Shashe catchment, Limpopo River basin, Zimbabwe

Study focus

Sand dams, small structures built in ephemeral rivers to capture and store river flows in the sand, provide an important water source for rural communities that lack formal infrastructure. While their potential benefits are increasingly recognized, the spatiotemporal variability in the water they store remains unstudied. This knowledge gap constrains evidence-driven planning for sand dam development and limits the incorporation of sand dams into an integrated storage framework, a key approach to enhance resilience by satisfying storage needs from a diverse range of sources. To address this gap, this study uses in situ data to report on the spatiotemporal variability of water storage in sand dams in the Shashe catchment of the Limpopo River Basin. Five sand dams and two natural (i.e., undammed) sites were monitored weekly for water level fluctuations from January to December 2024.

New hydrological insight for the region

Results indicate that all sand dams greatly improve water availability during the dry season compared to natural sites. Sand dams built on larger rivers are nonetheless more effective at maintaining water supply throughout the dry season. Seepage is identified as the primary pathway for water loss from the sand dams. To unlock the full potential of sand dams, planners should actively consider siting parameters, namely the river width, sediment accumulation thickness, sand accumulation area, and catchment area. Utilizing these criteria to inform planning can enhance the contribution and impact of sand dams, building more resilient and sustainable water systems.

研究区域津巴布韦林波波河流域沙舍集水区研究重点沙坝是建在短暂河流上的小型结构，用于捕获和储存河流中的沙子，为缺乏正规基础设施的农村社区提供了重要的水源。虽然人们越来越认识到它们的潜在好处，但它们储存的水的时空变异性仍未得到研究。这种知识差距限制了以证据为导向的沙坝开发规划，并限制了将沙坝纳入综合储存框架，这是通过满足各种来源的储存需求来增强弹性的关键方法。为了解决这一差距，本研究利用现场数据报告了林波波河流域沙舍流域沙坝储水量的时空变化。从2024年1月至12月，每周监测5个沙坝和2个自然（即无水坝）地点的水位波动情况。结果表明，与自然场地相比，所有沙坝在旱季都大大提高了水的可用性。尽管如此，建在较大河流上的沙坝在整个旱季都能更有效地维持供水。渗流是沙坝失水的主要途径。为了充分发挥沙坝的潜力，规划者应积极考虑选址参数，即河流宽度、泥沙堆积厚度、积沙面积和集水区面积。利用这些标准为规划提供信息，可以增强沙坝的贡献和影响，建立更具弹性和可持续性的水系统。

{"title":"Optimizing the contributions of sand dam water storage through understanding their spatiotemporal variability: Evidence from the Shashe catchment, Limpopo, River Basin","authors":"Girma Yimer Ebrahim , Jonathan F. Lautze , Matthew McCartney , Fortune Batiya , Stephen Hussey , Joyce Dube","doi":"10.1016/j.ejrh.2025.103102","DOIUrl":"10.1016/j.ejrh.2025.103102","url":null,"abstract":"<div><h3>Study region</h3><div>Shashe catchment, Limpopo River basin, Zimbabwe</div></div><div><h3>Study focus</h3><div>Sand dams, small structures built in ephemeral rivers to capture and store river flows in the sand, provide an important water source for rural communities that lack formal infrastructure. While their potential benefits are increasingly recognized, the spatiotemporal variability in the water they store remains unstudied. This knowledge gap constrains evidence-driven planning for sand dam development and limits the incorporation of sand dams into an integrated storage framework, a key approach to enhance resilience by satisfying storage needs from a diverse range of sources. To address this gap, this study uses in situ data to report on the spatiotemporal variability of water storage in sand dams in the Shashe catchment of the Limpopo River Basin. Five sand dams and two natural (i.e., undammed) sites were monitored weekly for water level fluctuations from January to December 2024.</div></div><div><h3>New hydrological insight for the region</h3><div>Results indicate that all sand dams greatly improve water availability during the dry season compared to natural sites. Sand dams built on larger rivers are nonetheless more effective at maintaining water supply throughout the dry season. Seepage is identified as the primary pathway for water loss from the sand dams. To unlock the full potential of sand dams, planners should actively consider siting parameters, namely the river width, sediment accumulation thickness, sand accumulation area, and catchment area. Utilizing these criteria to inform planning can enhance the contribution and impact of sand dams, building more resilient and sustainable water systems.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103102"},"PeriodicalIF":5.0,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024492","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}

引用次数: 0

Corrigendum to “How mixing and thermal stratification in tributary embayments respond to reservoir regulations: Interactions between buoyancy and shear forces” [J. Hydrol. Reg. Stud. 63 (2026) 103096] “支流河口的混合和热分层如何响应储层规律：浮力和剪切力之间的相互作用”[J]。二聚水分子。Reg。螺杆63 (2026)103096]

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-17 DOI: 10.1016/j.ejrh.2026.103146

Zheng Jing , Xiangyu Shi , Xianqiang Tang , Rui Li , Zhengui Wang , Lidi Shi

引用次数: 0

Integrated GIS-based multi-criteria approach for rainwater harvesting site selection in the Moulouya Basin, Morocco 基于gis的摩洛哥Moulouya流域雨水收集选址综合多准则方法

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-16 DOI: 10.1016/j.ejrh.2026.103123

Amiri Mustapha , Qadem Zohair , Qadem Abdelghani , Ali Salem

Study region

Upper and middle Moulouya basin, Morocco

Study focus

In Morocco's Moulouya basin, recurrent droughts and rising temperatures have intensified the demand for surface water and the unsustainable exploitation of groundwater, particularly for agricultural purposes.This study aims to identify potential zones for rainwater harvesting (RWH) to reduce water shortages and improve water resource management in the upper and middle Moulouya basin. Geographic Information Systems (GIS), Remote sensing (RS) and WETSPASS model were integerted with Analytical Hierarchy Process (AHP) and Multi-Influencing Factor (MIF) methodologies to produce suitability maps for RWH sites.

New hydrogeological insights from the region

The results classified the study zones into five suitability classes: "unsuitable" to " very suitable", with around very suitable area 1588 km² and 2228 km² in MIF and AHP method respectively. The integrated models were validated using the receiver operating characteristic (ROC) curve and correlation coefficient, revealing area under the curve (AUC) values of 0.87 for AHP and 0.93 for MIF. The correlation coefficient was 0.79 and 0.77 in MIF and AHP, respectively, indicating moderate to high predictive accuracy, respectively. The findings of this study provide a valuable tool for decision-makers, hydrologists and planners to address water management challenges in the Moulouya basin. The integrated approaches are applicable for basins in other areas with similar hydrogical conditions particularly in regions prone to severe drought.

研究区域摩洛哥穆卢亚盆地中上游研究重点在摩洛哥穆卢亚盆地，经常性干旱和气温上升加剧了对地表水的需求和对地下水的不可持续开采，特别是用于农业目的。本研究旨在确定穆罗亚流域中上游地区潜在的雨水收集区，以减少水资源短缺和改善水资源管理。将地理信息系统（GIS）、遥感（RS）和WETSPASS模型与层次分析法（AHP）和多影响因子法（MIF）相结合，生成水源地选址适宜性图。结果将研究区划分为“不适宜”至“非常适宜”5个适宜级，MIF法和AHP法分别在非常适宜面积1588 km²和2228 km²左右。采用受试者工作特征（ROC）曲线和相关系数对综合模型进行验证，AHP和MIF的曲线下面积（AUC）分别为0.87和0.93。MIF和AHP的相关系数分别为0.79和0.77，预测准确率为中高。这项研究的发现为决策者、水文学家和规划者解决穆卢亚盆地的水管理挑战提供了一个有价值的工具。综合方法适用于具有类似水文条件的其他地区的流域，特别是容易发生严重干旱的地区。

{"title":"Integrated GIS-based multi-criteria approach for rainwater harvesting site selection in the Moulouya Basin, Morocco","authors":"Amiri Mustapha , Qadem Zohair , Qadem Abdelghani , Ali Salem","doi":"10.1016/j.ejrh.2026.103123","DOIUrl":"10.1016/j.ejrh.2026.103123","url":null,"abstract":"<div><h3>Study region</h3><div>Upper and middle Moulouya basin, Morocco</div></div><div><h3>Study focus</h3><div>In Morocco's Moulouya basin, recurrent droughts and rising temperatures have intensified the demand for surface water and the unsustainable exploitation of groundwater, particularly for agricultural purposes.This study aims to identify potential zones for rainwater harvesting (RWH) to reduce water shortages and improve water resource management in the upper and middle Moulouya basin. Geographic Information Systems (GIS), Remote sensing (RS) and WETSPASS model were integerted with Analytical Hierarchy Process (AHP) and Multi-Influencing Factor (MIF) methodologies to produce suitability maps for RWH sites.</div></div><div><h3>New hydrogeological insights from the region</h3><div>The results classified the study zones into five suitability classes: \"unsuitable\" to \" very suitable\", with around very suitable area 1588 km² and 2228 km² in MIF and AHP method respectively. The integrated models were validated using the receiver operating characteristic (ROC) curve and correlation coefficient, revealing area under the curve (AUC) values of 0.87 for AHP and 0.93 for MIF. The correlation coefficient was 0.79 and 0.77 in MIF and AHP, respectively, indicating moderate to high predictive accuracy, respectively. The findings of this study provide a valuable tool for decision-makers, hydrologists and planners to address water management challenges in the Moulouya basin. The integrated approaches are applicable for basins in other areas with similar hydrogical conditions particularly in regions prone to severe drought.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103123"},"PeriodicalIF":5.0,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981423","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}

引用次数: 0

Analyzing historical snow trends in interior Alaska 分析阿拉斯加内陆的历史降雪趋势

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-16 DOI: 10.1016/j.ejrh.2025.103065

Anna M. Wagner , Katrina E. Bennett , Ross E. Alter , Elias J. Deeb , Nawa Raj Pradhan

Study region

The Chena River watershed in Interior Alaska, USA

Study focus

This study examines 40 years (water years 1982–2021) of snowpack characteristics to consider its hydrological implications in the 5350 km² Chena River basin. Using observations and a fine-scale physics model, we analyzed trends of snow water equivalent (SWE), snow onset and disappearance, and snow cover duration (SCD).

New hydrological insights for the region

Results indicate a decline in SWE across the modeled domain, averaging a decrease of 3 mm per decade, with larger decreases (up to 10 mm per decade) at lower elevations. While domain-averaged SWE trends were not statistically significant, observed SCD showed statistically significant decreases: −5.2, −5.0, and −4.4 days per decade at Teuchet Creek, Fairbanks F.O., and Little Chena Ridge, respectively. Notably, observations at SNOTEL stations and modeling revealed no statistically significant change in domain-averaged Rain-on-Snow (ROS) events over the 40-year period, contrasting some regional future estimates of increased ROS frequency. Peak streamflow did not consistently correlate with peak SWE levels, suggesting that other environmental factors such as ROS events and rapid temperature increases (e.g., a 10°C spike observed in 1992) are key drivers of hydrological outcomes. These findings improve understanding of complex subarctic hydrological processes impacting permafrost and highlight the need for adaptive water resource management to mitigate multi-factor risks like flooding and wildfire, requiring proactive planning.

本研究考察了40年（1982-2021年）的积雪特征，以考虑其在5350 km²的Chena河流域的水文意义。利用观测资料和精细尺度物理模型，分析了积雪水当量（SWE）、积雪起消和积雪持续时间（SCD）的变化趋势。结果表明，整个模拟区域的SWE下降，平均每十年减少3 毫米，在低海拔地区减少幅度更大（每十年减少10 毫米）。虽然区域平均SWE趋势在统计上不显著，但观测到的SCD在统计上显著减少：在Teuchet Creek， Fairbanks F.O和Little Chena Ridge分别为- 5.2,- 5.0和- 4.4天/ 10年。值得注意的是，SNOTEL站的观测和模型显示，40年来区域平均雨雪（ROS）事件在统计上没有显著变化，这与一些区域未来对ROS频率增加的估计形成了对比。峰值流量并不总是与峰值SWE水平相关，这表明其他环境因素，如ROS事件和快速温度升高（例如，1992年观测到的10°C峰值）是水文结果的关键驱动因素。这些发现提高了对影响永久冻土的复杂亚北极水文过程的理解，并强调了适应性水资源管理的必要性，以减轻洪水和野火等多因素风险，需要积极规划。

{"title":"Analyzing historical snow trends in interior Alaska","authors":"Anna M. Wagner , Katrina E. Bennett , Ross E. Alter , Elias J. Deeb , Nawa Raj Pradhan","doi":"10.1016/j.ejrh.2025.103065","DOIUrl":"10.1016/j.ejrh.2025.103065","url":null,"abstract":"<div><h3>Study region</h3><div>The Chena River watershed in Interior Alaska, USA</div></div><div><h3>Study focus</h3><div>This study examines 40 years (water years 1982–2021) of snowpack characteristics to consider its hydrological implications in the 5350 km² Chena River basin. Using observations and a fine-scale physics model, we analyzed trends of snow water equivalent (SWE), snow onset and disappearance, and snow cover duration (SCD).</div></div><div><h3>New hydrological insights for the region</h3><div>Results indicate a decline in SWE across the modeled domain, averaging a decrease of 3 mm per decade, with larger decreases (up to 10 mm per decade) at lower elevations. While domain-averaged SWE trends were not statistically significant, observed SCD showed statistically significant decreases: −5.2, −5.0, and −4.4 days per decade at Teuchet Creek, Fairbanks F.O., and Little Chena Ridge, respectively. Notably, observations at SNOTEL stations and modeling revealed no statistically significant change in domain-averaged Rain-on-Snow (ROS) events over the 40-year period, contrasting some regional future estimates of increased ROS frequency. Peak streamflow did not consistently correlate with peak SWE levels, suggesting that other environmental factors such as ROS events and rapid temperature increases (e.g., a 10°C spike observed in 1992) are key drivers of hydrological outcomes. These findings improve understanding of complex subarctic hydrological processes impacting permafrost and highlight the need for adaptive water resource management to mitigate multi-factor risks like flooding and wildfire, requiring proactive planning.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103065"},"PeriodicalIF":5.0,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981422","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}

引用次数: 0

Variation characteristics of water reserves in high mountains and surrounding areas in Arid Central Asia 中亚干旱区高山及周边地区水量变化特征

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-16 DOI: 10.1016/j.ejrh.2026.103138

Bing Bai , Ping Yue , Xueyuan Ren , Qiang Zhang , Tiejun Zhang , Xin Zhang

Study region

Arid Central Asia.

Study focus

We investigated 2003–2021 trends in air temperature, precipitation, and evapotranspiration (ET) across Arid Central Asia and its high-mountain regions. Using terrestrial water storage derived from GRACE, we applied robust trend analysis and significance testing to quantify spatiotemporal variability at monthly, seasonal, and interannual scales. We further revealed contrasting terrestrial water storage responses in high-mountain areas and adjacent representative subregions under both co-directional and counter-directional changes in the climate driving and ecological vegetation regulation.

New hydrogeological insights from the region

This work provides new insights into the variability of terrestrial water storage anomalies across multiple time scales in arid Central Asia and in high elevation regions that function as inland water towers. We use terrestrial water storage derived from GRACE together with reanalysis products. Under regional warming, explanations of mountain terrestrial water storage that rely only on precipitation and evapotranspiration are insufficient, because abundant runoff from snow and glacier melt prevents a clean closure of surface and subsurface water budgets. GRACE offers an integrated, observation based measure of all water compartments and therefore adds a valuable large scale perspective. We find a marked decline of terrestrial water storage in the Tianshan Mountains of −11.13 cm/a, whereas the Kunlun and Qilian Mountains ranges show increases of 7.81 cm/a and 5.18 cm/a, respectively. A comparison of the Oases located in the Hexi Corridor and the Tarim Basin as defined in this study indicates that human activities do not always deplete water resources. With sound planning and effective institutions, well designed interventions can enhance watershed water retention and storage capacity.

研究区域：中亚干旱地区。研究重点研究了2003-2021年中亚干旱地区及其高山地区气温、降水和蒸散（ET）的 趋势。利用GRACE获取的陆地储水量，我们采用稳健趋势分析和显著性检验来量化月、季和年际尺度上的时空变异。进一步揭示了气候驱动和生态植被调控的同向和反向变化对高山区及其相邻代表性分区陆地储水量的影响。本研究为研究中亚干旱地区和具有内陆水塔功能的高海拔地区陆地蓄水异常在多个时间尺度上的变异性提供了新的见解。我们使用从GRACE获得的陆地储水和再分析产品。在区域变暖的情况下，仅依靠降水和蒸散发来解释山地陆地储水是不够的，因为来自雪和冰川融化的大量径流阻止了地表和地下水收支的完全封闭。GRACE提供了一个综合的、基于观测的所有水隔间测量，因此增加了一个有价值的大尺度视角。天山地区陆地储水量下降幅度明显，为- 11.13 cm/a，而昆仑山和祁连山地区陆地储水量分别增加了7.81 cm/a和5.18 cm/a。河西走廊绿洲与塔里木盆地绿洲的对比表明，人类活动并不总是消耗水资源。通过合理的规划和有效的制度，设计良好的干预措施可以增强流域的保水和蓄水能力。

{"title":"Variation characteristics of water reserves in high mountains and surrounding areas in Arid Central Asia","authors":"Bing Bai , Ping Yue , Xueyuan Ren , Qiang Zhang , Tiejun Zhang , Xin Zhang","doi":"10.1016/j.ejrh.2026.103138","DOIUrl":"10.1016/j.ejrh.2026.103138","url":null,"abstract":"<div><h3>Study region</h3><div>Arid Central Asia.</div></div><div><h3>Study focus</h3><div>We investigated 2003–2021 trends in air temperature, precipitation, and evapotranspiration (ET) across Arid Central Asia and its high-mountain regions. Using terrestrial water storage derived from GRACE, we applied robust trend analysis and significance testing to quantify spatiotemporal variability at monthly, seasonal, and interannual scales. We further revealed contrasting terrestrial water storage responses in high-mountain areas and adjacent representative subregions under both co-directional and counter-directional changes in the climate driving and ecological vegetation regulation.</div></div><div><h3>New hydrogeological insights from the region</h3><div>This work provides new insights into the variability of terrestrial water storage anomalies across multiple time scales in arid Central Asia and in high elevation regions that function as inland water towers. We use terrestrial water storage derived from GRACE together with reanalysis products. Under regional warming, explanations of mountain terrestrial water storage that rely only on precipitation and evapotranspiration are insufficient, because abundant runoff from snow and glacier melt prevents a clean closure of surface and subsurface water budgets. GRACE offers an integrated, observation based measure of all water compartments and therefore adds a valuable large scale perspective. We find a marked decline of terrestrial water storage in the Tianshan Mountains of −11.13 cm/a, whereas the Kunlun and Qilian Mountains ranges show increases of 7.81 cm/a and 5.18 cm/a, respectively. A comparison of the Oases located in the Hexi Corridor and the Tarim Basin as defined in this study indicates that human activities do not always deplete water resources. With sound planning and effective institutions, well designed interventions can enhance watershed water retention and storage capacity.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103138"},"PeriodicalIF":5.0,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981427","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}

引用次数: 0

Spatio – temporal hydrological cycle characteristics in the upper reaches of the Yangtze River: A multi-source remote sensing and machine learning perspective 长江上游水文循环时空特征：多源遥感与机器学习视角

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-01-16 DOI: 10.1016/j.ejrh.2026.103142

Yang Shi , Yousheng Zhang , Minglei Hou , Jiahua Wei

Study region

The upper reaches of the Yangtze River (URYR) of China

Study focus

This study investigates the spatio-temporal variations of hydrological cycle components in the upper reaches of the Yangtze River (URYR) from 1980 to 2030 using multi-source remote sensing data and machine learning. A long short-term memory network with an attention mechanism (LSTM-AT) is initially developed to predict exploitable water resources (EWR) in the URYR.

New hydrological insights for the region

Significant spatial and temporal variations are identified over the past four decades (1980–2015) and projected through 2030. Precipitation ranges from about 230 mm in the arid northwest to over 1600 mm in the humid southeast, with evapotranspiration varying from less than 100 mm at high altitudes to over 800 mm in low-lying areas. Runoff and terrestrial water storage exhibit similar spatial gradients, and runoff shows strong dependence on precipitation, particularly in the Min–Tuo River basin. LSTM-AT predictions suggest that the regional water balance remains dynamically stable, while EWR in the upper Jinsha River shows a fluctuating upward trend of 2.13 ± 0.87 mm/yr, underscoring the need for adaptive water resource management under ongoing environmental change. By leveraging an attention-based deep learning framework and interpretable feature-weight analysis, this work also provides new insight into the dominant hydro-climatic and human-regulation drivers shaping annual water availability in this highly regulated basin.

利用多源遥感数据和机器学习技术，研究了1980 - 2030年长江上游地区水循环成分的时空变化特征。初步建立了一个具有注意机制的长短期记忆网络（LSTM-AT）来预测长江流域的可开发水资源。在过去40年（1980-2015年）中发现了显著的时空变化，并预测了到2030年的变化。降水范围从干旱的西北约230 mm到潮湿的东南1600 mm以上，蒸散量从高海拔小于100 mm到低洼地区超过800 mm不等。径流与陆地储水量表现出相似的空间梯度，径流对降水的依赖性较强，特别是在岷沱河流域。LSTM-AT预测表明，区域水平衡保持动态稳定，而金沙江上游的EWR呈波动上升趋势（2.13 ± 0.87 mm/yr），表明在持续变化的环境下需要进行适应性水资源管理。通过利用基于注意力的深度学习框架和可解释的特征权重分析，这项工作还提供了新的见解，以了解在这个高度调节的盆地中，主要的水文气候和人类调节驱动因素对年可用水量的影响。

{"title":"Spatio – temporal hydrological cycle characteristics in the upper reaches of the Yangtze River: A multi-source remote sensing and machine learning perspective","authors":"Yang Shi , Yousheng Zhang , Minglei Hou , Jiahua Wei","doi":"10.1016/j.ejrh.2026.103142","DOIUrl":"10.1016/j.ejrh.2026.103142","url":null,"abstract":"<div><h3>Study region</h3><div>The upper reaches of the Yangtze River (URYR) of China</div></div><div><h3>Study focus</h3><div>This study investigates the spatio-temporal variations of hydrological cycle components in the upper reaches of the Yangtze River (URYR) from 1980 to 2030 using multi-source remote sensing data and machine learning. A long short-term memory network with an attention mechanism (LSTM-AT) is initially developed to predict exploitable water resources (<em>EWR</em>) in the URYR.</div></div><div><h3>New hydrological insights for the region</h3><div>Significant spatial and temporal variations are identified over the past four decades (1980–2015) and projected through 2030. Precipitation ranges from about 230 mm in the arid northwest to over 1600 mm in the humid southeast, with evapotranspiration varying from less than 100 mm at high altitudes to over 800 mm in low-lying areas. Runoff and terrestrial water storage exhibit similar spatial gradients, and runoff shows strong dependence on precipitation, particularly in the Min–Tuo River basin. LSTM-AT predictions suggest that the regional water balance remains dynamically stable, while <em>EWR</em> in the upper Jinsha River shows a fluctuating upward trend of 2.13 ± 0.87 mm/yr, underscoring the need for adaptive water resource management under ongoing environmental change. By leveraging an attention-based deep learning framework and interpretable feature-weight analysis, this work also provides new insight into the dominant hydro-climatic and human-regulation drivers shaping annual water availability in this highly regulated basin.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103142"},"PeriodicalIF":5.0,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981835","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}

引用次数: 0