Artikel ; Online: Estimation of water consumption and productivity for wheat using remote sensing and SEBAL model
Open Agriculture, Vol 8, Iss 1, Pp 3-
A case study from central clay plain Ecosystem in Sudan
2023 Band 14
Abstract: Remote sensing (RS) can efficiently support the quantification of crop water requirements and water productivity (WP) for evaluating the performance of agricultural production systems and provides relevant feedback for management. This research aimed to ... ...
Abstract | Remote sensing (RS) can efficiently support the quantification of crop water requirements and water productivity (WP) for evaluating the performance of agricultural production systems and provides relevant feedback for management. This research aimed to estimate winter wheat water consumption and WP in the central clay plain of Sudan by integrating remotely sensed images, climate data, and biophysical modelling. The wheat crop was cultivated under a centre-pivot irrigation system during the winter season of 2014/2015. The Landsat-8 satellite data were used to retrieve the required spectral data. The Surface Energy Balance Algorithm for Land (SEBAL) was supported with RS and climate data for estimating the Actual Evapotranspiration (ETa) and the WP for the wheat crop. The SEBAL outputs were validated using the FAO Penman–Monteith method coupled with field measurements and observation. The results showed that the seasonal ETa ranged from 400 to 600 mm. However, the WP was between 1.2 and 1.5 kg/m3 during the wheat cycle. The spatial ETa and WP maps produced by the SEBAL model and Landsat-8 images can improve water use efficiency at field scale environment and estimate the water balance over large agricultural areas. |
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Schlagwörter | actual evapotranspiration ; water productivity ; landsat-8 images ; sebal model ; water use efficiency ; Agriculture ; S ; Agriculture (General) ; S1-972 |
Thema/Rubrik (Code) | 550 |
Sprache | Englisch |
Erscheinungsdatum | 2023-11-01T00:00:00Z |
Verlag | De Gruyter |
Dokumenttyp | Artikel ; Online |
Datenquelle | BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl) |
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