Assessing the Hydrological Utility of Multiple Satellite Precipitation Products in the Yellow River Source Region with Error Propagation Analysis
文献类型：期刊论文
| 作者 | Meng, Chengcheng1,2,4; Mo, Xingguo1,3,4; Han, Liqin2 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2026-02-07 |
| 卷号 | 18期号:4页码:537 |
| 关键词 | satellite precipitation dataset hydrological applicability SWAT model error propagation index spatial pattern |
| DOI | 10.3390/rs18040537 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | Highlights What are the main findings? In hydrological processes, the propagation of systematic and random errors in satellite-based precipitation products exhibits distinct statistical characteristics and spatial patterns. Hydrological simulations show that systematic bias in precipitation data tends to be amplified, while random error is suppressed, with the propagation ratio of random error exhibiting notable spatial clustering features. What are the implications of the main findings? The different propagation behaviors of systematic and random error in satellite-based precipitation data emphasize the need for targeted strategies in data modification for hydrological application. Error propagation patterns help to identify zones that are sensitive to precipitation errors and it is suggested that their distributions are associated with continuous watershed attributes, such as basin slope.Highlights What are the main findings? In hydrological processes, the propagation of systematic and random errors in satellite-based precipitation products exhibits distinct statistical characteristics and spatial patterns. Hydrological simulations show that systematic bias in precipitation data tends to be amplified, while random error is suppressed, with the propagation ratio of random error exhibiting notable spatial clustering features. What are the implications of the main findings? The different propagation behaviors of systematic and random error in satellite-based precipitation data emphasize the need for targeted strategies in data modification for hydrological application. Error propagation patterns help to identify zones that are sensitive to precipitation errors and it is suggested that their distributions are associated with continuous watershed attributes, such as basin slope.Abstract Satellite precipitation products (SPPs) generally exhibit varying accuracy and error characteristics, which influence their applicability in hydrological modeling. Based on gauge-observed precipitation and streamflow data, as well as runoff simulations from the SWAT model, this study evaluates the data accuracy, hydrological utility, and error propagation characteristics of eight SPPs derived from the GSMaP, IMERG, and PERSIANN algorithms in the Yellow River Source Region (YRSR), an alpine mountainous watershed. Results show that for estimating precipitation amounts and detecting precipitation events, post-processed GSMaP_Gauge (GGauge) performs best, followed by IMERG Final run data. These two datasets present good substitutability for gauge-based observations and demonstrate considerable potential in streamflow modeling. Specifically, after parameter recalibration, the performance of GGauge is comparable to that of gauge-derived simulations. Most propagation ratios of systematic bias (gamma RB) exceed one, while the ratios of random error (gamma ubRMSE) are below 1, indicating that, through hydrological simulation, systematic bias in precipitation data is more likely to be amplified, whereas random error is generally suppressed. Additionally, gamma ubRMSE exhibits more pronounced autocorrelation than gamma RB, with hotspots in the central region and cold spots in the western part of the YRSR, which is highly related to the basin slope. The statistical features and spatial patterns of error propagation indices help to identify zones that are sensitive to precipitation errors in the study area and highlight the need for targeted strategies to address different types of data error in the modification of SPPs for hydrological application. |
| URL标识 | 查看原文 |
| WOS关键词 | SOIL-MOISTURE ; MODEL ; RAINFALL ; UNCERTAINTY ; RUNOFF ; BASIN ; APPLICABILITY ; PERFORMANCE ; TOPOGRAPHY ; CATCHMENT |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001701533700001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/221348]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 通讯作者 | Mo, Xingguo |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 2.Henan Normal Univ, Sch Geog & Tourism, Xinxiang 453007, Peoples R China; 3.Univ Chinese Acad Sci, Sino Danish Coll, Beijing 101408, Peoples R China 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 101408, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Meng, Chengcheng,Mo, Xingguo,Han, Liqin. Assessing the Hydrological Utility of Multiple Satellite Precipitation Products in the Yellow River Source Region with Error Propagation Analysis[J]. REMOTE SENSING,2026,18(4):537. |
| APA | Meng, Chengcheng,Mo, Xingguo,&Han, Liqin.(2026).Assessing the Hydrological Utility of Multiple Satellite Precipitation Products in the Yellow River Source Region with Error Propagation Analysis.REMOTE SENSING,18(4),537. |
| MLA | Meng, Chengcheng,et al."Assessing the Hydrological Utility of Multiple Satellite Precipitation Products in the Yellow River Source Region with Error Propagation Analysis".REMOTE SENSING 18.4(2026):537. |
入库方式： OAI收割
来源：地理科学与资源研究所
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