High resolution mapping of agricultural water productivity using SEBAL in a cultivated African catchment, Tanzania. (August 2019)

• Record Type: Journal Article
• Authors: Nyolei, D.; Nsaali, M.; Minaya, V.; van Griensven, A.; Mbilinyi, B.; Diels, J.; Hessels, T.; Kahimba, F.
• Is Part Of: Physics and chemistry of the earth. Volume 112(2019)
• Page Start: 36
• Page End: 49
• Publication Date: 2019-08
• Subjects: Evapotranspiration -- Makanya -- SEBAL -- Remote sensing -- Water efficiency -- Water productivity; Geophysics -- Periodicals; Geochemistry -- Periodicals; Earth sciences -- Periodicals; Geodesy -- Periodicals; Astrophysics -- Periodicals; 550
• DOI: 10.1016/j.pce.2019.03.009
• Languages: English
• ISSNs: 1474-7065

Abstract

Abstract: The application of remote sensing techniques for WPET 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 WPET 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 WPET 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 WPET 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 WPET in the highlands and low WPET 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. Highlights: Paper focused on mapping spatial variability of biomass, yield and ET using Sentinel-2 and Landsat-8 and pySEBAL. A coupled phenological variability and supervised classification approach helped generate a high accuracy LULC layer. Integration of Landsat-8 and Sentinel-2 products supported downscaling of products to high resolution biomass and yield. Results showed low Water Productivity from high transmission and unproductive losses, pest/diseases and water shortages.