Journal of Hydrology最新文献_第10页

Integrated evaluation of snow density reanalysis products in the Northern Hemisphere 北半球雪密度再分析产品的综合评价

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-02-03 DOI: 10.1016/j.jhydrol.2026.135071

Yizhuo Li , Xin Miao , Xinyun Hu , Le Wang , Xueliang Zhang , Pengfeng Xiao , Weidong Guo

Snow density, as a key snow element, not only reflects the physical characteristics of snow cover but also plays a vital role in data assimilation, climate modeling, and hydrological cycle studies. However, systematic evaluations of snow density in reanalysis datasets are still lacking. In this study, we use 4,319 snow stations across major snow-covered regions in the Northern Hemisphere, to assess the applicability of snow density data from five widely used reanalysis datasets (ERA5-Land, GLDAS-Noah, GLDAS-CLSM, GLDAS-VIC, and JRA-3Q) during water year 2001–2023. Our results indicate that ERA5-Land and GLDAS-Noah better capture the spatial patterns and temporal variability of snow density across the study regions. Using these two datasets and in-situ observations, we analyze long-term trends of snow density in Canada, Russia, and the Western U.S. We find that, reanalysis datasets fail to reproduce the observed interannual trends. Reanalysis products tend to underestimate observed interannual changes of snow density in early winter or shift them to late winter months. Moreover, the impact of snow density biases on snow depth biases in reanalysis datasets varies by region and dataset through offsetting or amplifying snow water equivalent biases. This study provides a comprehensive evaluation of snow density accuracy in reanalysis datasets, and reveals the distinct spatiotemporal trends in snow density under global warming. Our results also highlight the divergent contribution of snow density biases to snow depth biases in reanalysis datasets across regions.

雪密度作为雪的关键要素，不仅反映了积雪的物理特征，而且在数据同化、气候模拟和水文循环研究中起着至关重要的作用。然而，在再分析数据集中对雪密度的系统评价仍然缺乏。在本研究中，我们利用北半球主要积雪地区的4319个雪站，评估了5个广泛使用的再分析数据集（ERA5-Land、GLDAS-Noah、GLDAS-CLSM、GLDAS-VIC和JRA-3Q） 2001-2023水年雪密度数据的适用性。结果表明，ERA5-Land和GLDAS-Noah较好地捕捉了研究区域积雪密度的空间格局和时空变化。利用这两个数据集和现场观测数据，我们分析了加拿大、俄罗斯和美国西部积雪密度的长期趋势。我们发现，再分析数据集不能再现观测到的年际趋势。再分析结果倾向于低估初冬观测到的雪密度年际变化或将其转移到冬末月份。此外，在再分析数据中，雪密度偏差对雪深偏差的影响因区域和数据集而异，主要通过抵消或放大雪水等效偏差。本研究对再分析数据集的积雪密度精度进行了综合评价，揭示了全球变暖背景下积雪密度的明显时空变化趋势。我们的研究结果还强调了各地区再分析数据集中雪密度偏差对雪深偏差的不同贡献。

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引用次数: 0

Metagenomic insight reveals the microbial structure and function of nitrous oxide emission from agricultural ditches 宏基因组揭示了农业沟渠排放一氧化二氮的微生物结构和功能

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-02-02 DOI: 10.1016/j.jhydrol.2026.135085

Zhangmu Jing , Qingqian Li , Shengqiang Tu , Yanjie Wei , Peng Yuan , Xiaoling Liu , Hongjie Gao

Nitrous oxide (N₂O) is a potent greenhouse gas, with agricultural activities representing its major source. However, the emission mechanism of nitrous oxide efficient by agricultural activities has not yet been fully studied. This study employs metagenomic analysis to elucidate the microbial community structure and functional potential associated with N₂O emissions in river and ditch systems of the Yangtze River Delta. The N₂O dissolved concentration in the rivers (0.08 ± 0.03 μmol N·L⁻¹) was significantly lower than that in the ditches (0.21 ± 0.14 μ mol N·L⁻¹) (P < 0.05). According to eight wind-based models, agricultural ditches emissions were 3.53–4.70 times higher than those of the rivers. All models significantly overestimated fluxes (P < 0.05), revealing a systematic overestimation of EF values when using the Intergovernmental Panel on Climate Change (IPCC) methodology. Particulate organic carbon supported microbial activity by providing energy and adhesion sites, while electrical conductivity (EC) served as an indicator of ion inputs from surrounding land use, serving as a critical abiotic driver of EF values in the ditches. The co-occurrence network showed that denitrification genes (norB, nirS, nosZ) formed a tightly clustered subnetwork exclusively in the ditches, indicating broader nitrification niches and stronger functional coupling among denitrifiers in these systems. Metagenomic evidence revealed that EF value correlated significantly with denitrification genes, notably napAB, nirK, norBC and nirK/nosZ (P < 0.05), underscoring denitrification as the primary biotic driver of N₂O production. These findings demonstrate the value of metagenomic approaches in revealing microbial mechanisms behind N₂O emissions and support the development of more accurate, EF estimates for greenhouse gas inventories in agricultural landscapes.

一氧化二氮（N2O）是一种强有力的温室气体，农业活动是其主要来源。然而，农业活动对氧化亚氮的有效排放机制尚未得到充分的研究。本研究采用宏基因组分析方法，探讨了长三角河沟系统中与N2O排放相关的微生物群落结构和功能潜力。河流中N2O溶解浓度（0.08±0.03 μmol N·L−1）显著低于沟渠中（0.21±0.14 μmol N·L−1）（P < 0.05）。根据八个基于风的模型，农业沟渠的排放量是河流排放量的3.53-4.70倍。所有模型都显著高估了通量（P < 0.05），表明在使用政府间气候变化专门委员会（IPCC）方法时，系统高估了EF值。颗粒有机碳通过提供能量和粘附位点来支持微生物活动，而电导率（EC）作为周围土地利用离子输入的指标，是沟渠中EF值的关键非生物驱动因素。共现网络表明，反硝化基因（norB, nirS, nosZ）在沟渠中形成了紧密聚集的子网络，表明这些系统中硝化生态位更广泛，反硝化菌之间的功能耦合更强。元基因组学证据显示，EF值与反硝化基因显著相关，尤其是napAB、nirK、norBC和nirK/nosZ (P < 0.05)，强调反硝化是N2O产生的主要生物驱动因素。这些发现证明了宏基因组方法在揭示N2O排放背后的微生物机制方面的价值，并支持对农业景观中温室气体清单进行更准确的EF估算。

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引用次数: 0

A novel deep learning coupled model for extracting flood control scheduling rules for reservoir groups 基于深度学习耦合模型的水库群防洪调度规则提取

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-02-03 DOI: 10.1016/j.jhydrol.2026.135083

Ling Kang , Xilong Wu , Liwei Zhou , Yunliang Wen

Traditional rule curves designed for single reservoirs often underperform when multiple, hydrologically linked reservoirs must be coordinated during extreme events. We propose a coupled model—BiTCN-STA-SHAP—that integrates a bidirectional temporal convolutional network (BiTCN), a spatio-temporal attention (STA) module, and Shapley Additive Explanations (SHAP) for interpretability to extract flood-control scheduling rules for a reservoir group (i.e., multiple hydrologically or geographically connected reservoirs operated jointly). Using five reservoirs in the Yangtze River Basin as a case study, the model maps the previous T = 6 days of inflows, interval inflows, outflows, and water levels to the current-day outflow for each reservoir. Development data were partitioned by flood events into training and validation subsets; the 1998 historical flood was held out for independent testing, and the 100-year design flood was used as a stress test. Compared with LSTM and TCN baselines, BiTCN-STA-SHAP achieved strong development performance (reservoir-level NSE > 0.90; group-mean NSE ≥ 0.94) and the best independent-test results (group-mean NSE = 0.97; MAPE = 7.75%). Under the 100-year stress test, it remained superior across most reservoirs, indicating robustness to extreme out-of-sample conditions. SHAP analyses reveal physically consistent patterns: previous-day inflow/outflow dominate, Jinping Level I–Ertan and Xiluodu–Xiangjiaba show strong linkages, and features related to the Three Gorges Reservoir are most influential.

当在极端情况下必须协调多个水文相连的水库时，为单个水库设计的传统规则曲线往往表现不佳。我们提出了一个耦合模型- BiTCN-STA-SHAP，该模型集成了双向时间卷积网络（BiTCN）、时空关注（STA）模块和Shapley加性解释（SHAP）的可解释性，以提取水库组（即多个水文或地理上连接的水库联合运行）的防洪调度规则。该模型以长江流域5个水库为例，将前T = 6天的流入、间隔流入、流出和水位映射到每个水库当前的流出。开发数据按洪水事件划分为训练子集和验证子集；1998年历史洪水作为独立测试，100年设计洪水作为压力测试。与LSTM和TCN基线相比，BiTCN-STA-SHAP具有较强的开发性能（油藏水平NSE >； 0.90，组平均NSE≥0.94）和最佳的独立测试结果（组平均NSE = 0.97, MAPE = 7.75%）。在100年的压力测试中，它在大多数油藏中都保持优越，表明了对极端样本外条件的稳健性。

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引用次数: 0

Sensitivity and scale dependence of discretization and roughness in the hydrodynamic modeling of surface runoff caused by torrential rainfall 暴雨径流水动力模拟中离散化和粗糙度的敏感性和尺度依赖性

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-02-02 DOI: 10.1016/j.jhydrol.2026.135088

David Feldmann , Patrick Laux , Andreas Heckl , Marinko Nujić , Brian Böker , Manfred Schindler , Harald Kunstmann

Hydrodynamic surface runoff simulations are an effective method for assessing flash flood risks. In engineering, the lack of observations for model calibration poses a challenge. Therefore, understanding the sensitivity to specific model parameters is crucial for reliable flood protection planning. This study analyzes how surface discretization and roughness affect surface runoff generation and depression storage in a hydrodynamic 2D-model in a southern German alpine region.

We compare the runoff generation across five discretization methodologies at 211 selected locations within the model domain. These locations are associated with subcatchments ranging in size from 0.2 to 4 km².

The discretization methodologies comprise a one-meter grid refined with survey data, a two-meter grid, a high-resolution and low-resolution irregular mesh and a four-meter grid. These are combined with seven different depth-dependent and constant roughness parameterizations.

The sensitivity analysis shows that a higher depth-dependent roughness is needed to achieve comparable results to those of a coarse resolution model. Significant differences were observed with varying roughness parameterizations and meshing approaches. Modest alterations to surface resolution have the potential to yield deviations of up to 20% in maximum runoff. Coarser resolution models tend to create artificial depressions, leading to unrealistic water storage on hillsides.

These findings aid in identifying the sources of sensitivity in hydrodynamic surface runoff modeling, especially in ungauged basins and provide guidance on specific model setups. This is particularly relevant given the continued use of coarse-resolution models due to computational constraints and the availability of various roughness parameterizations, while calibration data are scarce.

水动力地表径流模拟是评估山洪风险的有效方法。在工程中，缺乏用于模型校准的观测值是一个挑战。因此，了解对特定模型参数的敏感性对于可靠的防洪规划至关重要。本研究在德国南部高山地区的水动力2d模型中分析了地表离散化和粗糙度如何影响地表径流产生和洼地储存。我们比较了在模型域中211个选定位置的五种离散化方法的径流生成。这些地点与面积从0.2平方公里到4平方公里不等的子集水区有关。离散化方法包括用调查数据细化的1米网格、2米网格、高分辨率和低分辨率不规则网格以及4米网格。这些结合了7种不同的深度依赖和恒定粗糙度参数化。灵敏度分析表明，要获得与粗分辨率模型相当的结果，需要更高的深度相关粗糙度。不同的粗糙度参数化和网格划分方法观察到显著的差异。对地表分辨率的适度改变有可能使最大径流产生高达20%的偏差。较粗分辨率的模型倾向于制造人工洼地，导致山坡上不切实际的水储存。这些发现有助于确定水动力地表径流模型的敏感性来源，特别是在未测量的流域，并为具体的模型设置提供指导。考虑到由于计算限制和各种粗糙度参数化的可用性而继续使用粗分辨率模型，而校准数据很少，这一点尤为重要。

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引用次数: 0

Sediment transport mechanisms in sediment-starved subaqueous deltas: insights from storm-induced gravity flows 沉积物匮乏的水下三角洲的沉积物输送机制：来自风暴引起的重力流的见解

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-12 DOI: 10.1016/j.jhydrol.2026.134958

Chunye Hu , Fan Zhang , Jin Li , Xiaolei Liu , Fei Xing , Renzhi Li , Hao Wu , Heyu Yu , Ya Ping Wang

Subaqueous deltas worldwide are increasingly threatened by erosion, driven by the dual pressures of intensified storms and reduced fluvial sediment supply. An abandoned river delta, devoid of sediment input from its watershed, offers an ideal end-member case for investigating delta erosion processes. This study provides direct observational evidence of storm-driven sediment dynamics in such a sediment-starved delta, based on in situ measurements during both typical weather conditions and winter storms on the Abandoned Yellow River Delta, China. During storms, fluid mud layers, wave-induced seabed liquefaction, and gravity flows were directly observed. Fluid mud developed through two mechanisms: wave-induced liquefaction combined with strong bed shear stress; and suspended sediment settling during slack water under weak waves. To enable a more systematic assessment of gravity flow dynamics, we extended a previous analytical model by incorporating additional transport processes. Using this model, it was quantified that gravity flows contributed ∼ 49% of the total sediment transport exported from the subaqueous delta near the 10-m isobath, despite occurring during only ∼ 7% of the 18-day observation. These results highlight that storm-driven gravity flows can develop and play a pivotal role in controlling sediment balance even in sediment-starved subaqueous deltas. Our findings provide new insights into sediment dynamics of sediment-starved deltas under intensified storm forcing and offer a framework for understanding their long-term morphological evolution.

在风暴加剧和河流沉积物供应减少的双重压力下，世界各地的水下三角洲日益受到侵蚀的威胁。一个废弃的河流三角洲，缺乏来自其流域的泥沙输入，为研究三角洲侵蚀过程提供了一个理想的端元案例。本研究通过对中国黄河三角洲典型天气条件和冬季风暴的现场测量，提供了在这样一个沉积物匮乏的三角洲中风暴驱动沉积物动力学的直接观测证据。在风暴期间，直接观察到流体泥层、波浪引起的海底液化和重力流。流体泥浆的形成有两种机制：波致液化与强床层剪切应力相结合；以及在弱波下的松弛水域中悬浮沉积物的沉降。为了能够更系统地评估重力流动力学，我们通过纳入额外的输送过程来改进先前的分析模型。使用该模型，我们首次在沉积物匮乏的三角洲的风暴条件下量化，重力流贡献了离开水下三角洲10米等深区域的沉积物运输总量的 ~ 49%，尽管在18天的观测中，重力流仅占 ~ 7%。这些结果强调，即使在沉积物匮乏的水下三角洲，风暴驱动的重力流也可以发展并在控制沉积物平衡方面发挥关键作用。我们的发现为研究强风暴作用下沉积物匮乏三角洲的沉积动力学提供了新的见解，并为理解其长期形态演变提供了一个框架。

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引用次数: 0

Hidden contribution of canopy interception to afforestation-driven evapotranspiration enhancement 林冠截留对造林驱动蒸散发增强的潜在贡献

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-22 DOI: 10.1016/j.jhydrol.2026.135005

Zheng Li , Panxing He , Jianhua Xiao , Zhiming Han , Jun Ma

Evapotranspiration (ET) and its components (plant transpiration, soil evaporation, and canopy interception) are central processes within regional and global water cycles. However, earlier research has examined how afforestation and deforestation influence total ET, systematic quantitative assessment of how these actions shift the relative contributions of ET components—especially under varying afforestation intensities—remains limited. In this study, we evaluated the changing patterns of ET and its components across multiple afforestation and deforestation scenarios using a global 30 m forest cover dataset and 500 m PML_V2 ET data. Our results indicate that, despite a clear trade-off between plant transpiration and soil evaporation, afforestation increased total ET by boosting both plant transpiration and canopy interception. This effect was particularly strong in tropical rainforests and temperate forests, where afforestation produced a more marked rise in ET. The increase mainly stemmed from shifts in leaf area and canopy structure, which enhanced precipitation interception and subsequent evaporation rather than soil infiltration, thereby lowering soil evaporation. Canopy interception played a crucial role under afforestation, especially when afforestation intensity was high, where its contribution to total ET grew substantially, becoming the primary driver of ET enhancement while compensating for the opposing tendencies of plant transpiration and soil evaporation. The response of ET components differs notably among forest types, with evergreen broadleaf forests showing the strongest shifts, whereas evergreen needleleaf and deciduous needleleaf forests exhibited more moderate changes. Through a global-scale assessment, this study is the first to quantify how afforestation intensity alters the components of ET, particularly canopy interception, offering useful guidance for ecological restoration and water resource strategies suited to different forest types.

蒸散发（ET）及其组分（植物蒸腾、土壤蒸发和冠层截流）是区域和全球水循环的核心过程。然而，早期的研究已经考察了造林和毁林如何影响总ET，系统的定量评估这些行动如何改变ET组分的相对贡献，特别是在不同的造林强度下，仍然有限。在这项研究中，我们利用全球30 m森林覆盖数据和500 m PML_V2 ET数据，评估了多种造林和毁林情景下的ET及其组分的变化模式。我们的研究结果表明，尽管植物蒸腾和土壤蒸发之间存在明显的权衡关系，但造林通过增加植物蒸腾和冠层截留来增加总蒸散发。这种效应在热带雨林和温带森林中尤为明显，在这些地区，植树造林使ET的增加更为明显。增加的主要原因是叶面积和冠层结构的变化，这种变化增强了降水拦截和随后的蒸发，而不是土壤入渗，从而降低了土壤蒸发。在造林条件下，特别是造林强度高时，冠层截留对总蒸散发的贡献显著增加，在补偿植物蒸腾和土壤蒸发相反趋势的同时，成为蒸散发增强的主要驱动力。不同森林类型对ET组分的响应存在显著差异，其中常绿阔叶林的变化最为强烈，而常绿针叶林和落叶针叶林的变化较为温和。通过全球尺度的评估，本研究首次量化了造林强度如何改变ET的组成，特别是冠层拦截，为适应不同森林类型的生态恢复和水资源战略提供了有用的指导。

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引用次数: 0

Imprints of terrestrial water fluxes on tropospheric stable water isotopes revealed by satellite observations and complex network analysis 卫星观测和复杂网络分析揭示的陆地水通量对对流层稳定水同位素的影响

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-02-05 DOI: 10.1016/j.jhydrol.2026.135087

Rohit Pradhan , Raghavendra P. Singh , Nimisha Singh , Shard Chander , Praveen K. Gupta , Mihir K. Dash

Understanding the interaction between terrestrial and atmospheric water fluxes is critical for improving predictions of the hydrological cycle. In this study, we investigate the relationship between isotopic composition of atmospheric water vapor (δD₀₀₄) and the surface water balance (ET-P), using satellite-observed (AIRS) and model-based (isoGSM) datasets. Results show strong positive correlations (r > 0.7) between δD₀₀₄ and ET–P over tropical forested regions, especially the Amazon, Congo Basin, and Southeast Asia. Nudged isoGSM demonstrated superior overall performance compared to free-running isoGSM, while AIRS satellite data proved more effective in the tropics. We construct a complex network between ET–P and δD₀₀₄ using time-lagged correlation across a 31-year period, identifying nearly 1.4 million significant links (p < 0.001). The resulting network reveals both short- and long-range teleconnections, with a bimodal distribution of link lengths and dominant zero-lag interactions. High node connectivity was concentrated over the equatorial Pacific, eastern Indian Ocean, and tropical forests, showcasing the intertwined roles of vegetation and large-scale ocean–atmosphere dynamics. Regional case studies over the Amazon, Congo, and Northeast India highlighted distinct teleconnection patterns mediated by SST anomalies, Walker circulation, and moisture recycling. Our results demonstrate the utility of water vapor isotopes in constructing climate networks and offer a novel diagnostic tool for evaluating the performance of isotope-enabled climate and hydrological models.

了解陆地和大气水通量之间的相互作用对于改进水文循环的预测至关重要。本文利用卫星观测（AIRS）和基于模式的（isoGSM）数据，研究了大气水汽（δD004）同位素组成与地表水平衡（ET-P）之间的关系。结果表明，热带森林地区，特别是亚马逊河流域、刚果盆地和东南亚地区，δD004与ET-P呈显著正相关（r > 0.7）。与自由运行的isoGSM相比，推动的isoGSM显示出更优越的整体性能，而AIRS卫星数据在热带地区被证明更有效。我们在ET-P和δD004之间构建了一个复杂的网络，使用31年的时间滞后相关性，确定了近140万个显著联系（p < 0.001）。由此产生的网络揭示了短距离和远距离的遥距连接，具有链路长度的双峰分布和占主导地位的零滞后相互作用。高节点连通性集中在赤道太平洋、东印度洋和热带森林，显示了植被和大尺度海洋-大气动力学的相互交织作用。对亚马逊、刚果和印度东北部的区域案例研究强调了海温异常、Walker环流和水分再循环介导的明显遥相关模式。我们的研究结果证明了水蒸气同位素在构建气候网络中的效用，并为评估同位素支持的气候和水文模型的性能提供了一种新的诊断工具。

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引用次数: 0

Regional mechanisms of hillslope erosion and soil and water conservation pathways on the Loess Plateau 黄土高原坡面侵蚀区域机制与水土保持路径

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-26 DOI: 10.1016/j.jhydrol.2026.135023

Qilin He , Peng Zhang , Binbin Li , Nan Shen , Mingyi Yang , Fengbao Zhang

Under climate change, soil erosion on the Loess Plateau has intensified, and the pronounced southeast–northwest gradients in climate, soils, and vegetation have produced marked regional differences in erosion processes. However, the mechanisms underlying these spatial variations remain insufficiently understood. Using seven years of observations from 32 monitoring stations, covering 672 natural rainfall events, hillslope runoff and soil loss were quantified across geomorphically distinct subregions. The result indicates that soil erosion is primarily controlled by rainfall, slope, and land use, while extreme rainfall and inadequate land management substantially amplify erosion risks. From light to torrential rain, runoff depth increased more than ninefold and soil loss more than thirty-fivefold, while bare land produced over seven times more soil loss than forestland. A southeast–northwest transition in dominant controls was identified: runoff generation becomes increasingly rainfall-driven, while the influence of land use and vegetation diminishes. Soil-loss pathways displayed distinct regional patterns—controlled primarily by the joint influence of runoff and land use in sandy regions, by topography–land use interactions in valley plains, and by runoff dynamics in hilly–gully and mountainous areas. Together, these results clarify the key processes underlying spatial variability in dryland erosion and provide a robust framework for assessing erosion risks and supporting adaptive land-management strategies under increasingly extreme climatic conditions.

气候变化背景下，黄土高原土壤侵蚀加剧，气候、土壤和植被呈明显的东南-西北梯度，侵蚀过程存在明显的区域差异。然而，这些空间变化背后的机制仍然没有得到充分的了解。利用32个监测站7年的观测数据，覆盖672个自然降雨事件，对不同地貌分区的山坡径流和土壤流失进行了量化。结果表明，土壤侵蚀主要受降雨、坡度和土地利用的控制，而极端降雨和土地管理不足极大地放大了侵蚀风险。从小雨到暴雨，径流深度增加了9倍以上，土壤流失量增加了35倍以上，而裸地造成的土壤流失量是林地的7倍以上。确定了主导控制的东南-西北过渡：径流产生越来越多地由降雨驱动，而土地利用和植被的影响减弱。土壤流失路径显示出明显的区域模式，主要受沙质地区径流和土地利用的共同影响，河谷平原地区地形-土地利用相互作用以及丘陵沟壑区和山区径流动态的控制。总之，这些结果阐明了旱地侵蚀空间变异性的关键过程，并为评估侵蚀风险和支持日益极端气候条件下的适应性土地管理战略提供了强有力的框架。

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引用次数: 0

Quantitative assessment of the reservoir-induced impact on multivariate flood risk via the nonstationary Vine Copula model 利用非平稳Vine Copula模型定量评价水库对多变量洪水风险的影响

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-25 DOI: 10.1016/j.jhydrol.2026.134997

Pengcheng Xu , Zhilang Zhang , Dong Wang , Vijay P. Singh , Gengxi Zhang , Xiaolei Fu , Huanyu Yang

Flood events in the Yellow River Basin (YRB) are increasingly influenced by both climate change and intensified human activities, calling for advanced multivariate models to capture their nonstationary characteristics. A dynamic Vine Copula (DVC) framework that integrates nonstationary univariate distributions with time-varying copula parameters is proposed for detecting human activities (including urbanization and reservoir operation) and a climate change-induced impact on the multivariate flood occurrence likelihood at YRB. Unlike traditional static copula approaches, this framework enables the dynamic quantification of changing dependencies among flood characteristics and systematically attributes the contributions of multiple covariates. Based on the daily mean streamflow, a comparative analysis between peaks-over-threshold (POT)-derived characteristics (PDC) and annual maximum series (AMS)-derived characteristics (ADC) reveals that the nonstationary DVC model based on ADC provides more robust and interpretable insights for nonstationary hydrological event analysis. Specifically, our findings indicate that reservoir operations show the strongest statistical association with flood risk alterations in recent decades. The regression lines showed that it caused a decrease of 2.5° to 31.9° in the angles of flood peak and flood volume, respectively. The interval time in PDC signals additional nonstationary influences. This study advances the methodology for multivariate flood risk assessment under nonstationary conditions, offering a novel tool for disentangling and quantifying the impacts of human and climate drivers in large river basins.

黄河流域洪水事件日益受到气候变化和人类活动加剧的双重影响，需要先进的多变量模型来捕捉其非平稳特征。提出了一个将非平稳单变量分布与时变Copula参数相结合的动态Vine Copula （DVC）框架，用于检测人类活动（包括城市化和水库运行）和气候变化对长江流域多变量洪水发生可能性的影响。与传统的静态耦合方法不同，该框架能够动态量化洪水特征之间变化的依赖关系，并系统地归因于多个协变量的贡献。基于日平均流量，对比分析了峰值-超阈值（POT）衍生特征（PDC）和年最大序列（AMS）衍生特征（ADC），发现基于ADC的非平稳DVC模型为非平稳水文事件分析提供了更强的鲁棒性和可解释性。具体来说，我们的研究结果表明，近几十年来，水库运行与洪水风险变化的统计关联最强。回归曲线显示，洪峰角和洪量角分别减小2.5°~ 31.9°。PDC中的间隔时间信号有额外的非平稳影响。该研究提出了非平稳条件下的多变量洪水风险评估方法，为大流域人类和气候驱动因素的影响分离和量化提供了一种新的工具。

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引用次数: 0

A dynamic soft-constrained deep learning paradigm for spatial downscaling of satellite gravimetry terrestrial water storage 卫星重力测量陆地蓄水空间降尺度的动态软约束深度学习范式

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-24 DOI: 10.1016/j.jhydrol.2026.135015

Metehan Uz , Kazım Gökhan Atman , Orhan Akyılmaz , C.K. Shum

The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) satellite gravimetry missions have contributed significantly to our knowledge of variations in Earth’s Terrestrial Water Storage anomalies (TWSA) throughout the last two decades. However, the ability to quantifying hydrometeorological and other climate/weather episodes is hindered by limitations in the current TWSA spatiotemporal resolutions at monthly sampling and approximately coarser than 300 km. In this study, we used Deep Learning (DL) approach that is specifically developed for accurate and effective spatial downscaling of TWSA time series from NASA’s Jet Propulsion Laboratory (JPLM). Each TWSA maps of JPLM are downscaled from 300 km to 50 km spatial resolution spanning from April 2002 through December 2022 by using inherent spatiotemporal correlations of WaterGAP Hydrology Model (WGHM) TWSA. For this purpose, a novel dynamic soft-constrained loss function is introduced and applied that adaptively balances while optimizing the TWSA signal with low-resolution JPLM observations against high-resolution spatial patterns derived from the WGHM hydrological model and ERA5 inputs. Internal validation shows that while the downscaled TWSA preserves basin-averaged temporal dynamics (trends, seasonality) from JPLM, the correlations and spectral analyses show it successfully incorporates WGHM TWSA’s high-resolution spatial variability. External validation of downscaled TWSA products also demonstrates their ability to capture El Niño Southern Oscillation (ENSO)-driven interannual variability, glacial mass loss trends, spectral consistency with Soil Moisture Active Passive (SMAP) satellite-derived surface soil moisture at high-resolution band and similar predictive skill against previous studies. Furthermore, the validation against groundwater well observations indicates that the downscaled TWSA effectively represents the spatial patterns of long-term groundwater depletion in heavily stressed aquifers and significantly enhancing the spatial localization of depletion or recharging signals relative to the coarse-resolution JPLM TWSA.

重力恢复和气候实验（GRACE）和GRACE后续（GRACE- fo）卫星重力测量任务在过去二十年中为我们了解地球陆地储水异常（TWSA）的变化做出了重大贡献。然而，量化水文气象和其他气候/天气事件的能力受到当前TWSA在每月采样和大约小于300公里的时空分辨率的限制。在这项研究中，我们使用了深度学习（DL）方法，该方法是专门为NASA喷气推进实验室（JPLM）的TWSA时间序列精确有效的空间降尺度而开发的。利用WaterGAP水文模型（WGHM） TWSA的固有时空相关性，将2002年4月至2022年12月期间JPLM的每张TWSA图从300 km空间分辨率降维到50 km空间分辨率。为此，本文引入并应用了一种新的动态软约束损失函数，该函数可以根据WGHM水文模型和ERA5输入的高分辨率空间模式，利用低分辨率JPLM观测数据自适应平衡并优化TWSA信号。内部验证表明，虽然缩小后的TWSA保留了JPLM的盆地平均时间动态（趋势、季节性），但相关性和光谱分析表明，它成功地融合了WGHM TWSA的高分辨率空间变异性。缩小TWSA产品的外部验证也证明了它们能够捕获El Niño南方涛动（ENSO）驱动的年际变化、冰川质量损失趋势、与高分辨率波段土壤水分主动式被动（SMAP）卫星衍生的地表土壤水分的光谱一致性，以及与先前研究类似的预测技能。基于地下水井观测的验证表明，相对于粗分辨率JPLM TWSA，缩小后的TWSA有效地反映了重应力含水层地下水长期枯竭的空间格局，显著增强了枯竭或补给信号的空间局域化。

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引用次数: 0