Measuring water availability with limited ground data: assessing the feasibility of an entirely remote-sensing-based hydrologic budget of the Rufiji Basin, Tanzania, using TRMM, GRACE, MODIS, SRB, and AIRS

被引:35
作者
Armanios, Daniel Erian [1 ,2 ]
Fisher, Joshua B. [3 ,4 ]
机构
[1] Univ Oxford, Int Grad Sch, Ctr Environm OUCE, Sch Geog & Environm, Oxford OX1 3QY, England
[2] Stanford Univ, STVP, Dept Management Sci & Engn, Huang Engn Ctr, Stanford, CA 94305 USA
[3] CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA
[4] Univ Oxford, Environm Change Inst, Sch Geog & Environm, Oxford OX1 3QY, England
基金
美国国家科学基金会;
关键词
remote sensing; hydrologic budget; Rufiji; Usangu; runoff; AIRS; SRB; TRMM; GRACE; MODIS; PRECIPITATION ANALYSIS TMPA; MEASURING MISSION TRMM; RESOURCES MANAGEMENT; STORAGE VARIATIONS; GRAVITY RECOVERY; CURVE NUMBERS; DATA PRODUCTS; RIVER-BASINS; RAINFALL; RUNOFF;
D O I
10.1002/hyp.9611
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
This study explores the feasibility of an entirely satellite remote sensing (RS)-based hydrologic budget model for a ground data-constrained basin, the Rufiji basin in Tanzania, from the balance of runoff (Q), precipitation (P), storage change (S), and evapotranspiration (ET). P was determined from the Tropical Rainfall Measuring Mission, S from the Gravity Recovery and Climate Experiment, and ET from the Moderate Resolution Imaging Spectroradiometer, the surface radiation budget, and the Atmosphere Infrared Radiation Sounder. Q was estimated as a residual of the water balance and tested against measured Q for a sub-basin of the Rufiji (the Usangu basin) where ground measurements were available (R-2=0.58, slope=1.9, root mean square error=29 mm/month, bias=14%). We also tested a geographical information system (GIS)-driven (ArcCN-runoff) runoff model (R-2=0.64, slope=0.43, root mean square error=39 mm/month). We conducted an error propagation analysis from each of the model's hydrologic components (P, ET, and S). We find that the RS-based model amplitude is most sensitive to ET and slightly less so to P, whereas the model's seasonal trends are most sensitive to S. Although RS-GIS-driven models are becoming increasingly used, our results indicate that long-term water resource assessment policy and management may be more appropriate than instantaneous' or short-term water resource assessment. However, our analyses help develop a series of tools and techniques to progress our understanding of RS-GIS in water resource management of data-constrained basins at the level of a water resource manager. Copyright (c) 2012 John Wiley & Sons, Ltd.
引用
收藏
页码:853 / 867
页数:15
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