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 |
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| Authors: | Daniel Erian Armanios Joshua B Fisher |
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| Institution: | 1. Water Science, Policy and Management, International Graduate School, Oxford University Centre for the Environment (OUCE), School of Geography and the Environment, Oxford University, Oxford, UK;2. Stanford Technology Ventures Program (STVP), Department of Management Science and Engineering, Huang Engineering Center, Stanford University, Stanford, CA, USA;3. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA;4. Environmental Change Institute, School of Geography and Environment, Oxford University, Oxford, UK |
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| Abstract: | 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 (ΔS), and evapotranspiration (ET). P was determined from the Tropical Rainfall Measuring Mission, ΔS 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 (R2 = 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 (R2 = 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 ΔS). 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 © 2012 John Wiley & Sons, Ltd. |
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| Keywords: | remote sensing hydrologic budget Rufiji Usangu runoff AIRS SRB TRMM GRACE MODIS |
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