Statistical and hydrological evaluation of TRMM-based Multi-satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the latest satellite precipitation products 3B42V7 ready for use in ungauged basins?

被引:266
作者
Xue, Xianwu [1 ,2 ]
Hong, Yang [1 ,2 ]
Limaye, Ashutosh S. [3 ]
Gourley, Jonathan J. [4 ]
Huffman, George J. [5 ]
Khan, Sadiq Ibrahim [1 ]
Dorji, Chhimi [6 ]
Chen, Sheng [1 ]
机构
[1] Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73072 USA
[2] Natl Weather Ctr, Adv Radar Res Ctr, Norman, OK 73072 USA
[3] NASA, George C Marshall Space Flight Ctr, Earth Sci Off, ZP11, Huntsville, AL 35805 USA
[4] NOAA, Natl Severe Storms Lab, Norman, OK 73072 USA
[5] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
[6] Minist Econ Affairs, Dept Hydromet Serv, Thimphu, Bhutan
关键词
CREST model; A-priori parameter estimation; Hydrologic modeling evaluation; Precipitation estimation; MODEL EVALUATION; ANALYSIS TMPA; RAINFALL; EQUIFINALITY; UNCERTAINTY; CLASSIFICATION; PREDICTION; NETWORK; WATER;
D O I
10.1016/j.jhydrol.2013.06.042
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The objective of this study is to quantitatively evaluate the successive Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products and further to explore the improvements and error propagation of the latest 3B42V7 algorithm relative to its predecessor 3B42V6 using the Coupled Routing and Excess Storage (CREST) hydrologic model in the mountainous Wangchu Basin of Bhutan. First, the comparison to a decade-long (2001-2010) daily rain gauge dataset reveals that: (1) 3B42V7 generally improves upon 3B42V6's underestimation both for the whole basin (bias from -41.15% to -8.38%) and for a 0.25 x 0.25 grid cell with high-density gauges (bias from -40.25% to 0.04%), though with modest enhancement of correlation coefficients (CC) (from 0.36 to 0.40 for basin-wide and from 0.37 to 0.41 for grid); and (2) 3B42V7 also improves its occurrence frequency across the rain intensity spectrum. Using the CREST model that has been calibrated with rain gauge inputs, the 3B42V6-based simulation shows limited hydrologic prediction NSCE skill (0.23 in daily scale and 0.25 in monthly scale) while 3B42V7 performs fairly well (0.66 in daily scale and 0.77 in monthly scale), a comparable skill score with the gauge rainfall simulations. After recalibrating the model with the respective TMPA data, significant improvements are observed for 3B42V6 across all categories, but not as much enhancement for the already-well-performing 3B42V7 except for a reduction in bias (from -26.98% to -4.81%). In summary, the latest 3B42V7 algorithm reveals a significant upgrade from 3B42V6 both in precipitation accuracy (i.e., correcting the underestimation) thus improving its potential hydrological utility. Forcing the model with 3B42V7 rainfall yields comparable skill scores with in situ gauges even without recalibration of the hydrological model by the satellite precipitation, a compensating approach often used but not favored by the hydrology community, particularly in ungauged basins. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:91 / 99
页数:9
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