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Article

Reliability of Satellite Data in Capturing Spatiotemporal Changes of Precipitation Extremes in the Middle Reaches of the Yellow River Basin

1
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(19), 3308; https://doi.org/10.3390/rs17193308
Submission received: 24 August 2025 / Accepted: 23 September 2025 / Published: 26 September 2025

Abstract

Extreme precipitation in the Middle Reaches of the Yellow River Basin (MRYRB) has increased significantly and unevenly, heightening the urgency for rapid and accurate monitoring of such extremes. Satellite precipitation data have proved effective in capturing precipitation extremes but have not been validated in the MRYRB. Thus, station-interpolated data were used to validate the reliability of satellite data (GPM IMERG) in characterizing spatiotemporal changes in nine extreme precipitation indices across the entire MRYRB and its ten sub-basins from 2001 to 2022. The results show that all frequency, intensity, and cumulative amount indices exhibit significantly increasing trends. Spatially, extreme precipitation exhibits a clear southeast–northwest gradient. The higher values occur in the southeastern sub-basins. Characterized by high-intensity, short-duration precipitation, the central sub-basins exhibit the lower values of extreme precipitation indices, yet have experienced the most rapid upward trends in those indices. The comparative analysis demonstrates that GPM reliably reproduces indices such as the number of days and amounts with precipitation above a threshold (R10, R20, R95p), maximum precipitation over five days (RX5day), and total precipitation (PRCPTOT) (with regression slopes close to 1, coefficient of determination R2 and Nash-Sutcliffe efficiency (NSE) greater than 0.7, and residual sum of squares ratio (RSR) less than 0.6, with negligible relative bias), particularly in the southern sub-basins. However, it tends to underestimate continuous wet days (CWD) and total precipitation when precipitation is over the 99th percentile (R99p). These findings advance current understanding of GPM applicability at watershed scales and offer actionable insight for water-sediment prediction under the world’s changing climate.
Keywords: GPM IMERG; extreme precipitation; sub-basins; performance validation GPM IMERG; extreme precipitation; sub-basins; performance validation

Share and Cite

MDPI and ACS Style

Yang, Q.; Xie, Q.; Xu, X. Reliability of Satellite Data in Capturing Spatiotemporal Changes of Precipitation Extremes in the Middle Reaches of the Yellow River Basin. Remote Sens. 2025, 17, 3308. https://doi.org/10.3390/rs17193308

AMA Style

Yang Q, Xie Q, Xu X. Reliability of Satellite Data in Capturing Spatiotemporal Changes of Precipitation Extremes in the Middle Reaches of the Yellow River Basin. Remote Sensing. 2025; 17(19):3308. https://doi.org/10.3390/rs17193308

Chicago/Turabian Style

Yang, Qianxi, Qiuyu Xie, and Ximeng Xu. 2025. "Reliability of Satellite Data in Capturing Spatiotemporal Changes of Precipitation Extremes in the Middle Reaches of the Yellow River Basin" Remote Sensing 17, no. 19: 3308. https://doi.org/10.3390/rs17193308

APA Style

Yang, Q., Xie, Q., & Xu, X. (2025). Reliability of Satellite Data in Capturing Spatiotemporal Changes of Precipitation Extremes in the Middle Reaches of the Yellow River Basin. Remote Sensing, 17(19), 3308. https://doi.org/10.3390/rs17193308

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