High resolution mapping of agricultural water productivity using SEBAL in a cultivated African catchment, Tanzania

© 2019 Elsevier Ltd The application of remote sensing techniques for WP ET mapping in data scarce regions is gaining more recognition since it can cover large areas with minimal field observations. Important concerns are the generation of high-resolution WP ET maps and addressing the question on how accurate the results are. This study aims at high resolution (10 m) mapping and evaluation of the spatial variability of biomass, yield, ET and WP ET in the Makanya river catchment using the automated Surface Energy Balance Algorithm for Land (pySEBAL) with SENTINEL-2 and LANDSAT-8 images, local land use map and locally calibrated leaf area index (LAI) inputs. A coupled phenological variability and supervised classification approach on high resolution images generated a high accuracy LULC layer which was used to map the WP ET in the agricultural lands. The pySEBAL results were evaluated in view of local information on crop yields, water allocation and agricultural management practices in the different agro-ecological zones within the catchment. Calibration of high-resolution satellite LAI generated products with error estimates within acceptable levels of uncertainty. The simulated crop yields were in agreement with reported crop yields. The results showed relatively high WP ET in the highlands and low WP ET in the midland and lowland areas of the catchment. The latter was attributed to high transmission losses, low irrigation efficiencies, poor agricultural practices and pest/disease attack. When applying SEBAL in African cultivated catchments, it is highly recommended to use SENTINEL-2 data in addition to LANDSAT-8, and to use local information, especially for the ground truthing of land use maps, phenology, crop practices and crop yields. ispartof: PHYSICS AND CHEMISTRY OF THE EARTH vol:112 pages:36-49 ispartof: location:NAMIBIA, Swakopmund status: published