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Remote Sens. 2018, 10(1), 41; doi:10.3390/rs10010041

Can Satellite Precipitation Products Estimate Probable Maximum Precipitation: A Comparative Investigation with Gauge Data in the Dadu River Basin

1
State Key Laboratory of Hydrosciene and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
2
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Institute of Water Resources and Hydropower Research, Beijing 100038, China
3
Department of Civil engineering and Environmental Science, University of Oklahoma, Norman, OK 73019, USA
4
Department of Hydrology and Water Resources, Nanjing University of Information Science & Technology, Nanjing 210044, China
*
Author to whom correspondence should be addressed.
Received: 30 July 2017 / Revised: 14 December 2017 / Accepted: 23 December 2017 / Published: 27 December 2017
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Abstract

Probable Maximum Precipitation (PMP) is an essential prerequisite in designing dams, spillways, and reservoirs in order to minimize the risk of overtopping infrastructure collapse, especially under today’s changing climate. This study investigates conventional PMP estimation approach by using both scarce in-situ observations and mainstream satellite precipitation products in the Dadu River basin, where plenty of reservoirs and dams are being built. The satellite data include Climate Prediction Center (CPC) MORPHing algorithm (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and Tropic Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42V7. The evaluation of satellite products shows that CMORPH and 3B42V7 agree well with gauge-based dataset for the period of 1998–2013 at both the grid and basin scales, also capturing the extreme precipitation events, with high Correlation Coefficients (CC) in terms of 0.68 and 0.71, respectively. Also, CMORPH and 3B42V7 show better performance for the magnitude and spatial distribution of 24-h PMP in such complex terrains. PERSIANN-CDR shows an overestimation in the upstream and an underestimation in the downstream. As among the first studies of satellite precipitation-based PMP estimation, this work sheds lights on the suitability of satellite precipitation in PMP estimation and could provide a reference for future extended spatially-distributed PMP estimation in vast ungauged regions. View Full-Text
Keywords: probable maximum precipitation (PMP); satellite precipitation; statistical method; the Dadu River basin probable maximum precipitation (PMP); satellite precipitation; statistical method; the Dadu River basin
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Yang, Y.; Tang, G.; Lei, X.; Hong, Y.; Yang, N. Can Satellite Precipitation Products Estimate Probable Maximum Precipitation: A Comparative Investigation with Gauge Data in the Dadu River Basin. Remote Sens. 2018, 10, 41.

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