Water budget estimation using remote sensing observations and GLDAS-CLSM for Limpopo River Basin

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Abstract

River Basin Management is heavily reliant on satellite remote sensing technologies. Keeping track of a basin’s water supply and demand is essential for efficient and sustainable water resource management. In this study, The Limpopo River Basin’s monthly water budget components for the 2019 wet and dry seasons were determined using satellite measurements and the GLDAS-2.1 CLSM model. The water budget components, which include Precipitation, Evapotranspiration, Terrestrial Water Storage, and Runoff, were obtained from several satellite-based sources (GPM-IMERG, MODIS, GRACE & GRACE-FO). Runoff was calculated as a residual from the water balance equation because it could not be directly determined from remote sensing measurements. The datasets were prepared, investigated, and evaluated. The effectiveness of satellite remote sensing for estimating the water budget was assessed. The results showed good stability for the Precipitation and Evapotranspiration, but there were significant ambiguities in the Terrestrial Water Storage and Runoff. The precipitation results for the 2019 wet season were close from GPM-IMERG (~ 108 BCM) and GLDAS (~ 119 BCM). Both MODIS and GLDAS showed similar results for the Evapotranspiration for the 2019 dry season (18 BCM, 15 BCM respectively) The study demonstrated the benefits and drawbacks of GLDAS-2.1 CLSM models with satellite-based remote sensing for calculating water budgets. Since human impact is not considered in remote sensing and modeled data, caution should be used when employing them in ungauged areas. Given the limitations in GLDAS and remote sensing datasets, these data can be extremely helpful, especially in areas with limited data, for assessing seasonal and inter-annual changes in water components and river basin management.

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How to Cite
Alfaloji, M. (2022). Water budget estimation using remote sensing observations and GLDAS-CLSM for Limpopo River Basin. Advanced Remote Sensing, 2(2), 85–93. Retrieved from https://publish.mersin.edu.tr/index.php/arsej/article/view/760
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