Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates

被引:229
作者
Collischonn, Bruno [1 ,2 ]
Collischonn, Walter [2 ]
Morelli Tucci, Carlos Eduardo [2 ]
机构
[1] Agencia Nacl Aguas, BR-70610200 Brasilia, DF, Brazil
[2] Inst Pesquisas Hidraul, BR-91501970 Porto Alegre, RS, Brazil
关键词
satellite-estimated precipitation; TRMM; Amazon basin;
D O I
10.1016/j.jhydrol.2008.07.032
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Rainfall measurements by conventional raingauges provide relatively accurate estimates at a few points of a region. The actual rainfield can be approximated by interpolating the available raingauge data to the remaining of the area of interest. In places with relatively tow gauge density such interpolated rainfields will be very rough estimates of the actual events. This is especially true for tropical regions where most rainfall has a convective origin with high spatial variability at the daily level. Estimates of rainfall by remote sensing can be very useful in regions such as the Amazon basin, where raingauge density is very low and rainfall highly variable. This paper evaluates the rainfall estimates of the Tropical Rainfall Measuring Mission (TRMM) satellite over the Tapajos river basin, a major tributary of the Amazon. Three-hour TRMM rainfall estimates were aggregated to daily values and were compared with catch of ground-level precipitation gauges on a daily basis after interpolating both data to a regular grid. Both daily TRMM and raingauge-interpotated rainfields were then used as input to a large-scale hydrological model for the whole basin; the calculated hydrographs were then compared to observations at several streamgauges along the river Tapajos and its main tributaries. Results of the rainfield comparisons showed that satellite estimates can be a practical tool for identifying damaged or aberrant raingauges at a basin-wide scale. Results of the hydrological modeling showed that TRMM-based calculated hydrographs are comparable with those obtained using raingauge data. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:207 / 216
页数:10
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