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地理学报(英文版)  2015, Vol. 25 Issue (2): 177-195    DOI: 10.1007/s11442-015-1161-3
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Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China
Haigen ZHAO1,2,3(),Shengtian YANG1,2,*(),Zhiwei WANG1,2,Xu ZHOU1,2,Ya LUO1,2,Linna WU1,2
1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Sciences, Beijing 100875, China
2. Research Center for Remote Sensing and GIS, Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, School of Geography, Beijing Normal University, Beijing100875, China
3. South China Institute of Environmental Sciences, MEP, Guangzhou 510655, China
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The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission (TRMM) data with rain gauge data and further to use this TRMM data to drive a Distributed Time-Variant Gain Model (DTVGM) to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year (2001-2010) daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R2 varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years (2001-2007) of data on daily hydrological processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamflow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.

Key wordsrainfall    TRMM    distributed hydrological model    DTVGM    hydrological simulation    Weihe River catchment
收稿日期: 2014-01-21      出版日期: 2015-06-24
作者简介: Zhao Haigen (1983-), PhD Candidate, specialized in hydrological simulation and remote sensing. E-mail:
. [J]. 地理学报(英文版), 2015, 25(2): 177-195.
Haigen ZHAO,Shengtian YANG,Zhiwei WANG,Xu ZHOU,Ya LUO,Linna WU. Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China. Journal of Geographical Sciences, 2015, 25(2): 177-195.
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Figure 1  
Figure 2  
Figure 3  
Figure 4  
Name Min Max Description Initial value
g1 0.20 0.50 Coefficient of time-variant gain factor 0.25
Ra 0.10 0.60 Initial ratio of soil water in the soil layer 0.20
Kr 0.0001 0.001 Storage-outflow coefficient for the soil layer 0.00015
C1 0.001 1.00 Dimensionless fitting parameter for ET 0.40
C2 0.60 0.80 Dimensionless fitting parameter for ET 0.60
C3 5.00 20.00 Dimensionless fitting parameter for ET 15.00
Table 1  
Year Areal average (mm/d) Standard deviation (mm) Maximum daily rainfall (mm/d) Maximum 5-day rainfall (mm/5d) Annual rainfall (mm/y)
Gauge TRMM Gauge TRMM Gauge TRMM Gauge TRMM Gauge TRMM
2001 1.29 1.35 2.99 2.91 23.01 21.77 94.15 87.76 468.91 496.30
2002 1.26 1.24 3.36 2.90 36.12 23.91 105.36 94.05 458.57 456.12
2003 2.15 2.14 4.87 4.34 36.82 31.14 142.07 118.28 782.92 781.17
2004 1.31 1.35 3.19 2.94 23.92 27.73 90.46 86.92 480.03 493.15
2005 1.56 1.73 3.84 3.94 27.04 32.03 120.48 121.09 570.38 631.24
2006 1.52 1.36 3.32 2.68 21.62 18.82 94.00 77.42 555.04 497.86
2007 1.58 1.52 3.54 3.65 25.73 35.32 99.00 121.90 575.02 556.21
2008 1.26 1.44 3.09 3.42 22.67 25.64 88.16 109.00 462.70 525.65
2009 1.40 1.47 3.07 3.25 23.26 24.62 85.92 99.89 512.63 525.22
2010 1.61 1.55 4.27 3.42 44.29 22.65 133.07 95.49 589.15 565.08
Table 2  
Figure 5  
Figure 6  
Scenario I Scenario II
Calibration period
Gauge 0.69 18.71 0.84 0.68 14.37 0.83
TRMM 0.59 21.96 0.78 0.60 18.02 0.78
Validation period
Gauge 0.55 -18.85 0.78 0.52 -23.85 0.74
TRMM 0.48 -15.38 0.71 0.50 -19.91 0.72
Table 3  
Figure 7  
Figure 8  
Scenario I Scenario II
Gauge 0.64 -0.84 0.83 0.64 -5.58 0.82
TRMM 0.67 2.52 0.84 0.68 -1.78 0.84
Table 4  
Figure 9  
Parameters Gauge TRMM
g1 0.23 0.22
Kr 0.0006 0.0002
C1 0.50 0.52
C2 0.78 0.66
C3 10.00 9.96
Ra 0.15 0.51
Table 5  
Figure 10  
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