Spatio-temporal performance of large-scale Gezira Irrigation Scheme, Sudan

Information on irrigation indicators is needed to improve irrigation management. The objective of this paper is to assess the irrigation performance of the Gezira Scheme, Sudan. Data on climatic elements, irrigation water supply and crop yield for the period 1961–2010 integrated with remote sensing data from 2000 to 2014 are used. Crop evapotranspirations (ETc) are determined by FAO 56 reference evapotranspiration (ETo) with derived crop coefficients (kc) and the actual evapotranspiration (ETa) is estimated using FAO 33. Irrigation efficiency indicators, Relative Irrigation Supply (RIS) and Relative Water Supply (RWS), are calculated. Potential rainwater supply to crop is tested based on Moisture Availability Index (MAI) and Ratio of Moisture Availability (RMA). Furthermore, Water Use Efficiency (WUE) is used to assess the water productivity. For the spatial drought assessment, a modified Vegetation Condition Index (MVCI) derived from remotely-sensed data is used. The results of RIS and RWS show respectively that the irrigation efficiency has decreased since 1993/1994 from 1.40 and 1.70 to 2.23 and 2.60, respectively. MAI for cotton and sorghum presents moderate deficit values (0.4 to 0.68) in July and August. RMA has an average value of 0.67, 0.49 and 0.46 in July for cotton, groundnut and sorghum, respectively, indicating a promising rainfall contribution to irrigation. The Gezira Scheme achieves low WUE in comparison to many irrigation schemes of the globe. Based on the MVCI analysis, the northern part of the scheme experiences characteristic drought during the summer crop season whereas irrigation water is abundantly available during the winter. In conclusion, the overall water availability is higher than the demand; most likely the rain is not considered in irrigation scheduling. Low productivity is mainly due to poor distribution and irrigation mismanagement. Rain and drained irrigation water harvesting could be addressed in the scheme for balancing the demand and supply.

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