Journal of Hydrology-Regional Studies最新文献_第2页

Meteoric water δ18O across the Dinarides: Role of topography, air-mass mixing, and precipitation seasonality 穿越Dinarides的大气水δ18O：地形、气团混合和降水季节性的作用

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-04 DOI: 10.1016/j.ejrh.2026.103214

Gabriela Sanchez Ortiz , Marlene Löberbauer , Nevena Andrić-Tomašević , Oleg Mandic , Davor Pavelić , Vedad Demir , Patrick W. Keys , Maud J.M. Meijers , Jeremy K.C. Rugenstein

Study region

Streams in the Dinarides ranging from coastal Croatia across the high-elevation basins of Bosnia and Herzegovina to the lee of the Dinarides.

Study focus

The topographic evolution of the Dinarides is poorly-constrained and its controlling geodynamic mechanisms remain unclear. The oxygen-isotope composition (δ¹⁸O) of authigenic minerals is a common paleo-altimeter for reconstructing past topography, proper interpretation requires thorough constraints on mechanisms modifying modern meteoric-water δ¹⁸O. To constrain modern δ¹⁸O patterns across the Dinarides, we collected new stream samples and integrated them with published water stable isotope data.

New hydrological insights for the region

Meteoric-water data show δ¹⁸O is higher at the coast (∼-6 ‰) and lower at the peak (∼-11 ‰). We use moisture trajectory models to show isotopic patterns across the Dinarides reflect two distinct moisture sources. The dominant source of moisture on the windward side originates from the Mediterranean and the leeward side has a continental source. This difference in moisture sources is reflected in d‐excess values, which are high along the windward margin—reflective of Mediterranean moisture—and low in the lee, reflective of summertime, continental-sourced moisture. We interpret orographic rainout as the primary-driver of modern precipitation and surface water δ¹⁸O with secondary influences from moisture sources and precipitation seasonality. Our findings have implications for understanding the climatic processes that deliver moisture as well as our understanding of the past topography of the Dinarides.

研究区域：迪纳里德斯山脉的河流从克罗地亚沿海地区穿过波斯尼亚和黑塞哥维那的高海拔盆地，一直延伸到迪纳里德斯山脉的背风处。研究重点Dinarides的地形演化约束较差，其控制地球动力学机制尚不清楚。自生矿物的氧同位素组成（δ18O）是重建过去地形的常用古高度计，正确的解释需要彻底限制现代大气水δ18O的改变机制。为了约束整个Dinarides的现代δ18O模式，我们收集了新的溪流样本，并将其与已发表的水稳定同位素数据进行了整合。区域大气水数据的新水文见解表明，δ18O在海岸较高（~ -6 ‰），在峰值较低（~ -11 ‰）。我们使用水分轨迹模型来显示横跨迪纳里德斯的同位素模式反映了两种不同的水分来源。迎风面主要的水汽来源来自地中海，背风面则有大陆来源。水分来源的差异反映在d -过剩值上，在迎风边缘高，反映地中海的水分，在背风边缘低，反映夏季大陆的水分。我们认为地形降水是现代降水和地表水δ18O的主要驱动因素，其次是水汽来源和降水季节性的影响。我们的发现对理解提供水分的气候过程以及我们对Dinarides过去地形的理解具有重要意义。

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引用次数: 0

Improving precipitation estimation and hydrological simulation in Tianshan Mountain basins via CNN-SE-EF fusion 基于CNN-SE-EF融合的天山流域降水估算与水文模拟

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-03 DOI: 10.1016/j.ejrh.2026.103179

Biao Cao , Qiying Yu , Yungang Bai , Zhenlin Lu , Shuo Wang , Mingsheng Wang , Hongbin Zhang , Caihong Hu

Study region

The Tianshan Mountains, a cold high-mountain, arid–humid transition zone with complex topography and mixed rain–snow runoff generation. We use 2000–2020 daily data from 19 stations as reference to evaluate and fuse multi-source precipitation for hydrologic application in the Tailan River basin and surrounding areas.

Study focus

We benchmark six precipitation products (CHM, CMORPH, ERA5-Land, GPM IMERG, PERSIANN, TRMM) using continuous (R², MAE, RMSE, BIAS) and event metrics (POD, FAR, CSI). To address nonlinear spatiotemporal structure and leverage atmospheric controls, we design a CNN–SE–EF fusion that couples a convolutional backbone with squeeze-and-excitation attention and five covariates (2-m temperature, 2-m dew point, 10-m wind u/v, surface pressure). Regional transferability is tested via extended triple collocation (ETC); hydrologic utility is assessed by forcing the Snowmelt Runoff Model (SRM).

New hydrological insights for the region

At low elevations, CHM and ERA5 perform best (lower FAR, higher POD/CSI, smaller MAE/RMSE, near-zero BIAS), whereas CMORPH and PERSIANN in high relief show higher false alarms and systematic underestimation. CNN–SE–EF outperforms CNN–SE and Bayesian averaging in R²/MAE/MSE, exhibits stronger cross-station stability, and delivers spatial skill superior to CLDAS v2.0 and GPCC. Fused precipitation improves SRM streamflow in the Tailan River (calibration/validation R² ≈ 0.76/0.91; volume bias ≈ 12.3 %), with remaining wet-season peak biases linked to simplified snow–ice and routing representations. The scheme is transferable to ungauged cold high-mountain basins.

研究区域：天山山脉是一个寒冷的高山干湿过渡带，地形复杂，雨雪混合产流。以2000-2020年19个台站的逐日降水资料为参考，对泰兰河流域及周边地区多源降水进行了评价和融合。我们使用连续（R²，MAE， RMSE， BIAS）和事件指标（POD， FAR， CSI）对六种降水产品（CHM， CMORPH, ERA5-Land, GPM IMERG， PERSIANN， TRMM）进行基准测试。为了解决非线性时空结构并利用大气控制，我们设计了一个CNN-SE-EF融合，该融合将卷积主干与挤压和激励关注以及五个协变量（2米温度、2米露点、10米风u/v、地表压力）耦合在一起。通过扩展三重配置（ETC）测试区域可转移性；通过强迫融雪径流模型（SRM）来评估水文效用。在低海拔地区，CHM和ERA5表现最好（FAR较低，POD/CSI较高，MAE/RMSE较小，BIAS接近于零），而CMORPH和PERSIANN在高海拔地区表现出较高的误报和系统性低估。CNN-SE - ef在R²/MAE/MSE上优于CNN-SE和贝叶斯平均，表现出更强的跨站稳定性，并提供优于CLDAS v2.0和GPCC的空间技能。融合降水改善了泰兰河SRM流量（校正/验证R²≈0.76/0.91；体积偏差≈12.3 %），剩余的雨季峰值偏差与简化的冰雪和路由表示有关。该方案可适用于未计量的寒冷高山盆地。

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引用次数: 0

Reconstruction of groundwater-induced gravity effects using a physical hydrological model at Lhasa Station, Tibetan Plateau 利用物理水文模型重建青藏高原拉萨站地下水重力效应

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-03 DOI: 10.1016/j.ejrh.2026.103188

Qianqian He , Min Zhao , Xiaodong Chen , Miaomiao Zhang , Wanhao Wang , Jianqiao Xu , Heping Sun

Study region

Lhasa Superconducting Gravimeter (SG) Observatory, Lhasa River alluvial plain

Study focus

The Lhasa SG Observatory is the only continuously operating SG station on the Tibetan Plateau. Surrounded by thick Quaternary sediments, this site provides a critical window into the interactions between tectonic processes and hydrological mass redistribution. Precisely isolating gravity interference caused by local groundwater storage changes is essential for detecting subtle geodynamic signals, such as crustal thickening. We integrated high-precision SG observations, meteorological forcing, and in-situ groundwater levels (2010–2020) into a 1D physically-based Richards equation framework. We reconstructed the spatiotemporal evolution of soil moisture within the 3-meter unsaturated zone to accurately quantify the gravity effects induced by localized hydrological dynamics.

New hydrological insights for the region

The physical model’s reconstruction exhibits strong consistency with SG residuals at an hourly scale (cross-correlation coefficient: 0.62), significantly outperforming global hydrological products like ERA5 (0.18) and GLDAS (0.55). Groundwater-induced gravity fluctuations reach an amplitude of 10.62 μGal (1 μGal = 1⋅10⁻⁸ m s^− 2), sufficient to mask contemporaneous tectonic signatures. Crucially, long-term regression identifies a persistent gravity decline of approximately –0.27 ± 0.002 μGal·a^⁻¹ driven by continuous groundwater depletion. This trend accounts for nearly 14 %–40 % of the observed absolute gravity variation rate. Neglecting station-scale hydrological corrections can thus lead to substantial misjudgments of crustal thickening rates and Moho subsidence magnitudes on the Tibetan Plateau.

研究区域拉萨河冲积平原拉萨超导重力仪观测站研究重点拉萨超导重力仪观测站是青藏高原唯一一个连续运行的超导重力仪观测站。该遗址被厚厚的第四纪沉积物所包围，为研究构造过程与水文质量再分配之间的相互作用提供了一个关键窗口。精确隔离由局部地下水储量变化引起的重力干扰对于探测地壳增厚等细微地球动力学信号至关重要。我们将高精度的SG观测、气象强迫和地下水位（2010-2020）整合到一个基于物理的一维Richards方程框架中。重建3米非饱和带土壤水分的时空演变，以准确量化局域水文动力引起的重力效应。物理模型的重建结果与小时尺度的SG残差具有很强的一致性（相关系数为0.62），显著优于ERA5（0.18）和GLDAS（0.55）等全球水文产品。地下水引起的重力波动幅值达到10.62 μGal (1 μGal = 1⋅10−8 m s− 2)，足以掩盖同生构造特征。至关重要的是，长期回归发现，由于地下水持续枯竭，重力持续下降约为-0.27 ± 0.002 μGal·a⁻¹。这一趋势占观测到的绝对重力变化率的近14% % - 40% %。因此，忽略站尺度的水文修正会导致对青藏高原地壳增厚率和莫霍沉降幅度的严重误判。

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引用次数: 0

Regional patterns of streamflow persistence, complexity, and chaos indicators within the United States 美国境内河流持续性、复杂性和混乱指标的区域模式

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-03 DOI: 10.1016/j.ejrh.2026.103184

Krzysztof Raczyński , Katarzyna Grala , Katarzyna Baran-Gurgul , John Cartwright , Jamie Dyer

Study Region

Streamflow records from 3135 gauging stations across the United States and Puerto Rico (1970–2023) were analyzed. Daily discharge was aggregated into non-overlapping calendar weekly, monthly, quarterly, and annual series; within each period Q_min, Q_avg, and Q_max were computed as the minimum, mean and maximum of daily discharge, respectively.

Study Focus

Streamflow integrates climatic, hydrological, and anthropogenic influences. This study characterizes how memory, complexity, and chaos indicators in streamflow vary across regions, flow regimes, and time scales. Fractal and multifractal analyses, recurrence-quantification metrics, and largest Lyapunov exponents are computed for each gauge and aggregation scale, then summarized with fuzzy C-means clustering to derive regional dynamical regimes.

New Hydrological Insights for the Region

Hurst exponents mostly between 0.75 and 0.95 indicate widespread long-range dependence, strongest for Q_min. Multifractality intensifies with temporal aggregation and is greatest for Q_max, reflecting enhanced variability in extremes. Recurrence analysis reveals a trade-off between strong recurrence structure and high dynamical complexity, with Q_avg comparatively stable across scales. Positive largest Lyapunov exponents suggest low-dimensional chaos embedded within persistent dynamics. Clustering of multifractality and recurrence metrics yields three coherent regimes: a high-persistence, low-entropy regime in the western and central United States (including Alaska), a transitional regime in the Great Plains and Appalachia, and a higher-entropy regime in the northeastern and Gulf Coast areas (including Puerto Rico). Taken together, these typologies support region-specific forecasting and water-management strategies under climate and land-use change by indicating where persistence-dominated dynamics favor long-memory model structures and where higher entropy implies shorter predictability horizons and a stronger role for probabilistic or ensemble forecasting.

研究区域分析了美国和波多黎各3135个测量站1970-2023年的流量记录。每日流量汇总为不重叠的日历周、月、季度和年系列；在每个时间段内，Qmin、Qavg和Qmax分别为日排放量的最小值、平均值和最大值。研究焦点：溪流整合了气候、水文和人为影响。本研究描述了记忆、复杂性和混沌指标在不同地区、流动状态和时间尺度上的变化。计算了各尺度和聚集尺度的分形和多重分形分析、递归量化度量和最大Lyapunov指数，然后用模糊c均值聚类进行总结，得出区域动态机制。RegionHurst指数大多在0.75 ~ 0.95之间，表明广泛的长期依赖性，Qmin最强。多重分形随着时间聚集而增强，Qmax最大，反映了极端情况下的变异性增强。递归分析揭示了强递归结构和高动态复杂性之间的权衡，Qavg在各个尺度上相对稳定。正的最大李雅普诺夫指数表明低维混沌嵌入在持续的动力学中。多重分形和重复度量的聚类产生了三种连贯的制度：美国西部和中部（包括阿拉斯加）的高持久性、低熵制度，大平原和阿巴拉契亚地区的过渡制度，以及东北部和墨西哥湾沿岸地区（包括波多黎各）的高熵制度。总而言之，这些类型学支持气候和土地利用变化下的区域特定预测和水资源管理策略，表明持久性主导的动态有利于长记忆模型结构，高熵意味着更短的可预测性范围和更强的概率或集合预测作用。

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引用次数: 0

Decoding the hydroclimatic variability in the Minjiang River, Southeast China: The influence of ENSO, PDO, AO, and anthropogenic regulations 解析闽江水文气候变率：ENSO、PDO、AO和人为调节的影响

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-03 DOI: 10.1016/j.ejrh.2026.103192

Xiaohe Lai , Xuan Lin , Huangjie Zou , Yan Liu , Qianli Sun , Aijun Wang , Feng Cai

Study region

Minjiang River (MJR), Southeast (SE) China

Study focus

The hydrological response mechanisms of rivers to coupled climatic and anthropogenic influences remain insufficiently understood. To address this gap, we analyzed the hydrological and climatic variations of the MJR using a suite of approaches, including the Bayesian Estimator of Abrupt Change, Seasonality and Trend (BEAST), Double Mass Curve (DMC), Continuous Wavelet Transform (CWT), Wavelet Coherence (WTC), and Multiscale Wavelet-Bayesian Coupled Regression (MWBCR).

New hydrologic Insights

The results revealed that sediment load exhibited an interannual (7-a, ENSO-like) periodicity, with a significant reduction due to damming prior to 1993, whereas its decadal (PDO-like) signal was obscured by intensive human interventions. Precipitation and water discharge fluctuated within a relatively narrow range but showed distinct interannual and decadal periodicities, reflecting the combined influences of the Arctic Oscillation (AO), ENSO, and PDO. Since the 1990s, precipitation variability has been strongly associated with frequent AOI shifts. Moreover, higher precipitation variability was closely linked to in-phase La Niña–cold PDO events, which enhanced typhoon landfalls in SE China. In contrast, out-of-phase ENSO–PDO conditions corresponded to relatively drier and less variable hydroclimatic conditions, characterized by reduced precipitation and fewer typhoon occurrences.

研究区域：中国东南部岷江流域研究重点河流对气候和人为耦合影响的水文响应机制尚不清楚。为了解决这一问题，我们使用贝叶斯突变、季节性和趋势估计器（BEAST）、双质量曲线（DMC）、连续小波变换（CWT）、小波相干（WTC）和多尺度小波-贝叶斯耦合回归（MWBCR）等方法分析了MJR的水文和气候变化。结果表明，泥沙负荷表现出年际（7-a，类似enso）的周期性，1993年以前由于筑坝而显著减少，而其年代际（类似pdo）的信号被密集的人类干预所掩盖。降水和水量波动范围较窄，但年际和年代际变化明显，反映了北极涛动（AO）、ENSO和PDO的综合影响。自20世纪90年代以来，降水变率与AOI的频繁变化密切相关。此外，较高的降水变率与La Niña-cold PDO同相事件密切相关，该事件增强了中国东南部的台风登陆。相反，非相位ENSO-PDO条件对应于相对干燥和变化较少的水文气候条件，其特征是降水减少和台风发生次数减少。

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引用次数: 0

Comparative assessment of environmental water requirements and river flow health in the Ghezel-Ozan River, Iran 伊朗gehezel - ozan河环境用水要求和河流流量健康的比较评估

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-03 DOI: 10.1016/j.ejrh.2026.103203

Kazem Sadeghian , Mehdi Vafakhah , Sayed M. Bateni , Mohammad Hasan Naderi , Jaber Aazami , Mohammad Sadegh Alavi-Yeganeh

Study Region

This study examines the Divandarreh-Bijar watershed, which covers an area of 5560.16 km² and through which the 180 km-long Qezlozan River flows, originating from the Chehel Cheshme Mountains.

Study Focus

This study assesses the suitability of the Ghezel-Ozan River for the native fish Capote razii in western Iran by applying conventional hydrological methods, hydraulic techniques, and model-based habitat-suitability approaches, and by evaluating the flow regime using the Flow Health Tool.

New Hydrological Insights for the Region

The main findings of this study are the following: (1) Capoeta razii has been identified as an ecological indicator species occurring in all types of mesohabitats; (2) The greatest fish diversity was found in the habitats of the run and riffle of the river rafts; (3) The deviation of the flow regime has increased considerably after 2012 as a result of the operation of the dams; (4) The EWRs ranged from 0.33 to 43.9 m3/s according to the different methods; (5) The Habitat Suitability model was the most representative of the environmental needs; and (6) To protect 75 % of suitable habitats, a minimum average flow of 10.09 m3/s is required. The best method to estimate environmental flows is to consider river health and the habitat requirements of native species.

本研究考察了Divandarreh-Bijar流域，该流域面积为5560.16平方公里，起源于Chehel Cheshme山脉的180公里长的Qezlozan河流经该流域。本研究通过应用常规水文方法、水力技术和基于模型的栖息地适宜性方法，以及使用流量健康工具评估流量状况，评估了伊朗西部Ghezel-Ozan河对本地鱼类卡波特razii的适宜性。本研究的主要发现如下：(1)在所有类型的中生境中，都可以发现卡波塔（Capoeta razii）是一种生态指示物种；(2)河筏的流水和流水生境鱼类多样性最大；(3) 2012年以后，由于大坝的运行，流型偏差明显增加；(4)不同方法的水冷比在0.33 ~ 43.9 m3/s之间；(5)生境适宜性模型最能反映环境需求；(6)为保护75%的适宜生境，最低平均流量要求为10.09立方米/秒。估计环境流量的最佳方法是考虑河流健康和本地物种的栖息地要求。

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引用次数: 0

Estimating the crop coefficient of meadow ecosystems and its driving factors using machine learning on the Qinghai–Tibet Plateau 青藏高原草甸生态系统作物系数及其驱动因子的机器学习估算

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-03 DOI: 10.1016/j.ejrh.2026.103204

Zhiming Xia , Bin Wang , Liping Guo , Xiaowei Guo

Study region

Qinghai–Tibet Plateau (QTP), China

Study focus

This study aims to improve crop coefficient (Kc) estimation for alpine meadows on the Qinghai–Tibet Plateau, where data scarcity and complex climate conditions make evapotranspiration (ET) evaluation difficult. We integrated lysimeter observations (2017–2022), meteorological data, and remote sensing vegetation indices using machine learning (ML) and partial least squares structural equation modeling (PLS-SEM) to develop a reliable Kc estimation framework. The random forest (RF) model achieved the best performance (R² = 0.70, RMSE = 0.17).

New hydrological insights for the region

The key environmental drivers identified were photosynthetically active radiation (PAR), vapor pressure deficit (VPD), soil temperature, and the Enhanced Vegetation Index (EVI), each showing pronounced nonlinear and threshold-type responses. The PLS-SEM results revealed that these variables influenced Kc both directly and indirectly through interactions among radiation, temperature, and vegetation growth. This study provides the first machine learning–based Kc estimation model for the QTP, improving the understanding of evapotranspiration processes under climate warming. The model performed well at the Haibei station, but it still requires broader multi-site validation to fully assess its spatial generalizability. Overall, this framework offers a practical and scalable approach for advancing water balance and ecohydrological research in data-scarce, high-altitude regions.

研究重点：青藏高原高寒草甸作物系数（Kc）估算方法的改进。青藏高原高寒草甸的作物系数（Kc）估算由于数据稀缺和复杂的气候条件导致蒸散发（ET）估算困难。我们利用机器学习（ML）和偏最小二乘结构方程模型（PLS-SEM），综合了2017-2022年的蒸渗仪观测数据、气象数据和遥感植被指数，建立了一个可靠的Kc估算框架。随机森林（RF）模型表现最佳（R²= 0.70,RMSE = 0.17）。发现的主要环境驱动因素是光合有效辐射（PAR）、蒸汽压亏缺（VPD）、土壤温度和增强植被指数（EVI），它们都表现出明显的非线性和阈值型响应。PLS-SEM结果表明，这些变量通过辐射、温度和植被生长的相互作用直接或间接地影响Kc。本研究提供了第一个基于机器学习的QTP Kc估计模型，提高了对气候变暖条件下蒸散发过程的认识。该模型在海北站运行良好，但仍需要更广泛的多站点验证，以充分评估其空间泛化性。总体而言，该框架为推进数据稀缺的高海拔地区的水平衡和生态水文研究提供了一种实用且可扩展的方法。

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引用次数: 0

Wetter conditions amplify simulated deep drainage differences between grasslands and forests in the Post Oak Savanna 更潮湿的条件放大了后橡树稀树草原草原和森林之间模拟的深层排水差异

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-03 DOI: 10.1016/j.ejrh.2026.103210

Mingxiu Wang , Briana M. Wyatt , Bradford P. Wilcox

Study region

The Post Oak Savanna (POS) ecoregion of Texas, U.S.

Study focus

Woody plant encroachment in the POS has been linked to reduced groundwater recharge, but it remains unclear whether the removal of these woody plants may increase groundwater recharge rates. To evaluate differences in recharge under contrasting vegetation covers, we simulated deep drainage at 18 paired grassland–forest sites using Hydrus-1D. The simulations were analyzed to assess spatiotemporal variability in deep drainage between paired sites, with these differences serving as a proxy for potential recharge changes due to woody plant removal. Additionally, simulations were used to identify the influence of precipitation and soil texture on the magnitude of deep drainage differences between grasslands and forests.

New hydrological insights for the region

Deep drainage was consistently higher in grasslands, which also showed greater variability, while forests had more uniformly limited deep drainage. The differences in deep drainage between forested and grassland sites were larger in wetter subregions and years, with precipitation playing a stronger role than sand content. Higher precipitation amplified deep drainage increases, and soils with lower sand content promoted stronger responses of deep drainage increases than sandier soils. These findings indicate strong promise for enhancing potential recharge through woody plant removal in the POS, but this potential is limited in the southern subregion where precipitation is low. This highlights the importance of regional differences when prioritizing restoration efforts to support groundwater sustainability.

研究区域美国德克萨斯州后橡树稀树草原（POS）生态区域木本植物的入侵与地下水补给减少有关，但目前尚不清楚这些木本植物的移除是否会增加地下水补给率。为了评估不同植被覆盖下补给的差异，我们使用Hydrus-1D模拟了18个成对的草地-森林样地的深层排水。研究人员分析了模拟结果，以评估配对地点之间深层排水的时空差异，并将这些差异作为木本植物移除导致的潜在补给变化的代理。此外，利用模拟方法确定了降水和土壤质地对草地和森林深层排水差异大小的影响。草原的深层排水始终较高，也表现出更大的变异性，而森林的深层排水则更均匀地有限。森林和草地在深层排水方面的差异在更湿润的分区和年份中更大，降水的作用强于含沙量。高降水放大了深排水增加，含沙量低的土壤对深排水增加的响应强于含沙量大的土壤。这些发现表明，通过去除POS中木本植物来增加潜在补给的可能性很大，但这种潜力在降水较少的南部次区域有限。这突出了在优先考虑恢复工作以支持地下水可持续性时区域差异的重要性。

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引用次数: 0

Numerical simulation evaluation of lithium leachate from landfills and risk to shallow groundwater 垃圾填埋场锂渗滤液的数值模拟评价及其对浅层地下水的危害

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-03 DOI: 10.1016/j.ejrh.2026.103218

Hongbo Liu , Litang Hu , Jingrui Wang , Lei Tian , Dingwei Qi , Jianchong Sun , Junpeng Lou

Study regions

Southeast inland region of China.

Study focus

The disposal of lithium slag, a byproduct of lithium-ion battery manufacturing, presents environmental risks by altering groundwater flow and contaminant transport. Because hydrogeological conditions are complex, reliable numerical models are needed to forecast changes in groundwater flow due to landfill fills and delineate long-term diffusion pathways. This study evaluates the hydrogeological impacts of landfilling native soil and lithium slag–soil mixtures at 6:4, 7:3, and 8:2 ratios using groundwater-modeling simulations. By incorporating uncertainties in hydraulic conductivity, dispersion, adsorption, and reaction rates, we identify robust monitoring strategies under worst-case scenarios.

New hydrological insights for the region

Field-calibrated simulations show landform changes and recharge variations accelerate contaminant migration by advection and dispersion. A groundwater-table rise of 2–4 m within 3–5 years raises contamination risk, especially in unlined landfills. With parameter uncertainty, native-soil plumes can extend up to 1700 m westward in 20 years. The 8:2 slag–soil mixture with a clay cap most effectively reduces leakage by more than 30 %. Entropy-based analysis identifies two high-sensitivity zones for early detection and guides monitoring-well placement. Engineered barriers are crucial to mitigating long-term groundwater contamination from lithium-rich waste. The findings provide technical guidance for preventing pollution at landfill sites under rising groundwater. These insights support risk-based remediation planning and monitoring design for landfill sites facing rising groundwater, and inform policy decisions.

研究区域：中国东南内陆地区。锂渣是锂离子电池生产的副产品，其处理会改变地下水流动和污染物运输，从而带来环境风险。由于水文地质条件复杂，需要可靠的数值模型来预测由于垃圾填埋引起的地下水流量变化，并描绘长期扩散路径。本研究利用地下水模型模拟，评估了按6:4、7:3和8:2比例填埋原生土和锂渣-土混合物的水文地质影响。通过结合水力导电性、分散性、吸附和反应速率的不确定性，我们确定了最坏情况下的稳健监测策略。野外校准模拟显示，地形变化和补给变化通过平流和分散加速了污染物的迁移。3-5年内地下水位上升2-4 米会增加污染风险，特别是在没有衬砌的垃圾填埋场。在参数不确定的情况下，原生土羽流在20年内可向西延伸1700 m。带粘土帽的8:2渣土混合物最有效地减少泄漏超过30% %。基于熵的分析确定了两个高灵敏度区域，便于早期发现并指导监测井的布置。工程屏障对于减轻富含锂的废物对地下水的长期污染至关重要。研究结果为地下水位上升条件下垃圾填埋场污染防治提供了技术指导。这些见解支持基于风险的填埋场修复规划和监测设计，以应对地下水上升，并为政策决策提供信息。

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引用次数: 0

Identifying precipitation gradients and revegetation ages combined effects deep soil moisture variability in the typical loess region 确定降水梯度和植被年龄对典型黄土地区深层土壤水分变异的影响

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies

Pub Date : 2026-02-03 DOI: 10.1016/j.ejrh.2026.103193

Yonggang Ma , Dang Wei , Junmei Liu , Bingbing Li

Study region

A Typical Loess Region (TLR) in the Chinese Loess Plateau

Study focus

Water scarcity is the primary constraint on ecological sustainability in the Typical Loess Region (TLR), where large-scale revegetation efforts have been implemented to combat severe soil erosion. However, the sustainability of these restored ecosystems is highly uncertain. This is because the water consumption of introduced vegetation often exceeds precipitation input, leading to progressive depletion of deep soil moisture (DSM) that supports plant survival during drought. While both spatial precipitation gradients and temporal revegetation age are known to influence DSM independently, their synergistic effects on DSM variability remain poorly quantified. Thus, to assess regional influences on DSM variability, we assembled 81 DSM profiles extending to depths of 10 m in TLR, spanning revegetation ages from 0 to 40 years. A polynomial function framework coupled with error propagation analysis was used to assess the combined effects.

New hydrological insights for the region

The results reveal that soil moisture and water storage generally increase with depth in shallow-rooted systems, reaching maximum levels at 5–10 m. However, under deep-rooted plants, they are highest at depths of 5–10 m, intermediate in 0–2 m, and the lowest in 2–5 m. With prolonged revegetation, soil moisture deficits intensify progressively across all soil layers, especially within the active and stable layers. Soil moisture conditions exhibit pronounced spatial heterogeneity, with mean moisture content and storage revealing increase gradient from northwest to southeast of the TLR. A transition from sufficient to stressed DSM conditions occurs when annual rainfall falls between 381.4 ± 130.5 and 450.5 ± 171.6 mm year⁻¹, triggered by a critical revegetation age of 25.7 ± 3.6 years. These findings highlight the need to integrate such thresholds into water resource management and ecosystem restoration strategies, especially in water-scarce and degraded regions.

研究区域中国黄土高原典型黄土区（TLR）研究重点水资源短缺是典型黄土区（TLR）生态可持续性的主要制约因素，该地区实施了大规模的植被恢复措施，以应对严重的土壤侵蚀。然而，这些恢复的生态系统的可持续性是高度不确定的。这是因为引进植被的耗水量往往超过降水投入，导致支持植物在干旱期间生存的深层土壤水分（DSM）逐渐枯竭。虽然已知空间降水梯度和时间植被恢复年龄都独立影响DSM，但它们对DSM变率的协同效应仍然缺乏量化。因此，为了评估区域对DSM变异性的影响，我们在TLR中收集了81条DSM剖面，延伸至10 m深度，跨越0至40年的植被恢复年龄。采用多项式函数框架与误差传播分析相结合的方法对综合效应进行评估。结果表明，在浅根系统中，土壤水分和储水量一般随深度增加而增加，在5-10 m处达到最大值。而在深根植物下，5 ~ 10 m最高，0 ~ 2 m居中，2 ~ 5 m最低。随着植被恢复时间的延长，土壤水分亏缺在各土层中逐渐加剧，尤其是在活动层和稳定层中。土壤水分条件具有明显的空间异质性，平均含水量和库存量呈现由西北向东南递增的梯度。当年降雨量介于381.4 ± 130.5和450.5 ± 171.6 mm之间时，临界植被恢复年龄为25.7 ± 3.6年，发生从充足到紧张的DSM条件过渡。这些发现突出表明，需要将这些阈值纳入水资源管理和生态系统恢复战略，特别是在缺水和退化地区。

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引用次数: 0