TY - JOUR
T1 - A study of substitutability of TRMM remote sensing precipitation for gauge-based observation in Ganjiang River basin
AU - Tang, Guoqiang
AU - Li, Zhe
AU - Xue, Xianwu
AU - Hu, Qingfang
AU - Yong, Bin
AU - Hong, Yang
N1 - Publisher Copyright:
©, 2015, China Water Power Press. All right reserved.
PY - 2015/5/30
Y1 - 2015/5/30
N2 - Multi-satellite remote precipitation sensing products provide a new source of data for hydrological simulation in basins with no or little observation. In this study, TRMM precipitation products (3B42V7 and 3B42RTV7) were evaluated quantitatively, and then coupled with CREST a distributed hydrological model to explore whether TRMM satellite precipitation products can substitute ground observations in the Ganjiang River basin, a typical Chinese storm region. Results indicate that 3B42 and 3B42RT fit well with ground observations, with the monthly correlation coefficients exceeding 0.9 and bias less than 5%, while the indices for daily precipitation is slightly worse. Two scenarios were also designed: Scenario I used static parameters in which gauge precipitation was used to calibrate the CREST model and satellite precipitation was used to validate it; Scenario II used dynamic parameters in which the model was recalibrated based on both satellite precipitation products. Comparison shows that the model performs better after recalibration in Scenario II, proving that mainstream satellite precipitation products have the potential to substitute gauged-based observations after model recalibration.
AB - Multi-satellite remote precipitation sensing products provide a new source of data for hydrological simulation in basins with no or little observation. In this study, TRMM precipitation products (3B42V7 and 3B42RTV7) were evaluated quantitatively, and then coupled with CREST a distributed hydrological model to explore whether TRMM satellite precipitation products can substitute ground observations in the Ganjiang River basin, a typical Chinese storm region. Results indicate that 3B42 and 3B42RT fit well with ground observations, with the monthly correlation coefficients exceeding 0.9 and bias less than 5%, while the indices for daily precipitation is slightly worse. Two scenarios were also designed: Scenario I used static parameters in which gauge precipitation was used to calibrate the CREST model and satellite precipitation was used to validate it; Scenario II used dynamic parameters in which the model was recalibrated based on both satellite precipitation products. Comparison shows that the model performs better after recalibration in Scenario II, proving that mainstream satellite precipitation products have the potential to substitute gauged-based observations after model recalibration.
KW - Coupled Routing and Excess Storage Model
KW - Ganjiang River basin
KW - Hydrological simulation
KW - Remote sensing precipitation
KW - Tropical rainfall measuring mission satellite
UR - https://www.scopus.com/pages/publications/84937778984
U2 - 10.14042/j.cnki.32.1309.2015.03.005
DO - 10.14042/j.cnki.32.1309.2015.03.005
M3 - Article
AN - SCOPUS:84937778984
SN - 1001-6791
VL - 26
SP - 340
EP - 346
JO - Shuikexue Jinzhan/Advances in Water Science
JF - Shuikexue Jinzhan/Advances in Water Science
IS - 3
ER -