Sokoine University of Agriculture

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

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dc.contributor.author Nyolei, D.
dc.contributor.author Nsaali, M.
dc.contributor.author Minaya, V.
dc.contributor.author van Griensven, A.
dc.contributor.author Mbilinyi, B.
dc.contributor.author Diels, J.
dc.contributor.author Hessels, T.
dc.contributor.author Kahimba, F.
dc.date.accessioned 2020-05-19T11:19:08Z
dc.date.available 2020-05-19T11:19:08Z
dc.date.issued 2019
dc.identifier.uri http://www.suaire.suanet.ac.tz:8080/xmlui/handle/123456789/3060
dc.description Physics and Chemistry of the Earth 112 (2019) 36–49 en_US
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher Elsevier Ltd en_US
dc.subject Evapotranspiration en_US
dc.subject Makanya en_US
dc.subject SEBAL en_US
dc.subject Remote sensing en_US
dc.subject Water efficiency en_US
dc.subject Water productivity en_US
dc.title High resolution mapping of agricultural water productivity using SEBAL in a cultivated African catchment, Tanzania en_US
dc.type Article en_US
dc.url https://doi.org/10.1016/j.pce.2019.03.009 en_US


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