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浏览/检索结果: 共241条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择作者升序作者降序发表日期升序发表日期降序题名升序题名降序提交时间升序提交时间降序 A spatially hybrid hydrological modeling approach using subbasin-specific model structures 期刊论文  OAI收割 ENVIRONMENTAL MODELLING & SOFTWARE, 2026, 卷号: 200, 页码: 106944 作者:  Wang, Yu-Jing;  Zhu, Liang-Jun;  Qin, Cheng-Zhi;  Zhu, A. -Xing   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/04/16 Watershed simulation  Hydrological modeling framework  Spatially hybrid modeling  Model structure  Spatial heterogeneity  SEIMS   Assessing the Hydrological Utility of Multiple Satellite Precipitation Products in the Yellow River Source Region with Error Propagation Analysis 期刊论文  OAI收割 REMOTE SENSING, 2026, 卷号: 18, 期号: 4, 页码: 537 作者:  Meng, Chengcheng;  Mo, Xingguo;  Han, Liqin   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/04/16 satellite precipitation dataset  hydrological applicability  SWAT model  error propagation index  spatial pattern   Hydrological Changes Drive the Seasonal Vegetation Carbon Storage of the Poyang Lake Floodplain Wetland 期刊论文  OAI收割 REMOTE SENSING, 2026, 卷号: 18, 期号: 2, 页码: 276 作者:  Yang, Zili;  Xia, Shaoxia;  Duan, Houlang;  Yu, Xiubo   |  收藏  |  浏览/下载：1/0  |  提交时间：2026/03/16 Poyang Lake  carbon storage  vegetation community  hydrological conditions  InVEST model   Flood predictions from metrics to classes by multiple machine learning algorithms coupling with clustering-deduced membership degree 期刊论文  OAI收割 JOURNAL OF GEOGRAPHICAL SCIENCES, 2026, 卷号: 36, 期号: 1, 页码: 149-176 作者:  Zhai, Xiaoyan;  Zhang, Yongyong;  Xia, Jun;  Zhang, Yongqiang;  Tang, Qiuhong   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/03/16 flood regime metrics  class prediction  machine learning algorithms  hydrological model   Simulating and predicting lake dynamics by fusing HBV modeling, machine learning approach and remote sensing data 期刊论文  OAI收割 JOURNAL OF HYDROLOGY, 2025, 卷号: 663, 页码: 134303 作者:  Naeem, Muhammad;  Zhang, Yongqiang;  Ma, Ning;  Tang, Zixuan;  Miao, Ping   |  收藏  |  浏览/下载：2/0  |  提交时间：2025/11/17 Hydrological dynamics  HBV model  Machine learning  Random Forest  CA-Markov model  Climate change  Lake area prediction  Water resource management   Shapelet-based decomposition stack machine learning model explains more middle river reaches water level hydrological process with high accuracy early warning 期刊论文  OAI收割 JOURNAL OF HYDROLOGY, 2025, 卷号: 662, 页码: 133927 作者:  Huan, Songhua   |  收藏  |  浏览/下载：0/0  |  提交时间：2025/10/20 Data decomposition  Hydrological process interpretation  River water level  Shapelet  Stack machine learning model   Does coal mining exert a greater influence than vegetation restoration on streamflow variation? Evidence from the Loess Plateau, China 期刊论文  OAI收割 JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2025, 卷号: 392, 页码: 126634 作者:  Luan, Jinkai;  Ma, Ning;  Zhang, Ran;  Li, Wei   |  收藏  |  浏览/下载：0/0  |  提交时间：2025/09/22 Coal mining  Streamflow  Vegetation restoration  Groundwater seepage  Hydrological model   The Alterations in Ecological Flow Indicators Caused by Coal Mining Operations 期刊论文  OAI收割 LAND DEGRADATION & DEVELOPMENT, 2025, 卷号: N/A 作者:  Luan, Jinkai;  Ma, Ning;  Zhang, Ran   |  收藏  |  浏览/下载：0/0  |  提交时间：2025/08/21 coal mining  ecological flow indicators  flow duration curve  groundwater seepage  hydrological model   A simple and effective approach to enhance the representation of spatial heterogeneity in lumped conceptual hydrological models: Application in the time-variant gain model 期刊论文  OAI收割 HYDROLOGY RESEARCH, 2025, 卷号: 56, 期号: 5, 页码: 419-438 作者:  Zhu, Yuntao;  Xia, Jun;  Ye, Aizhong;  Zou, Lei   |  收藏  |  浏览/下载：19/0  |  提交时间：2025/07/18 lumped hydrological models  numerical experiments  runoff generation mechanism  soil storage capacity curve  spatial heterogeneity  time-variant gain model   Comparison and integration of hydrological models and machine learning models in global monthly streamflow simulation 期刊论文  OAI收割 JOURNAL OF HYDROLOGY, 2025, 卷号: 650, 页码: 17 作者:  Zhang, Jiawen;  Kong, Dongdong;  Li, Jianfeng;  Qiu, Jianxiu;  Zhang, Yongqiang   |  收藏  |  浏览/下载：49/0  |  提交时间：2025/03/31 Streamflow simulation  Machine learning  Hydrological model  Multi-model weighting ensemble