Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

Abstract

Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotranspiration, rainfall and land use. For our validation we used only those papers that covered study periods of one season to annual cycles because the accumulated water balance is the primary concern. Review papers covering shorter periods only (days, weeks) were not included in our review. Our review shows that by using remote sensing, the spatial distribution of evapotranspiration can be mapped with an overall accuracy of 95% (STD 5%) and rainfall with an overall accuracy of 82% (STD 15%). Land use can be identified with an overall accuracy of 85% (STD 7%). Hence, more scientific work is needed to improve spatial mapping of rainfall using multiple space-borne sensors. Actual evapotranspiration maps can be used with confidence in water accounting and hydrological modeling.