Abstract. The Gash Delta Spate Irrigation System (GDSIS), located in eastern Sudan with a net command area of 100 000 ha (an area currently equipped with irrigation structures), was established in 1924. The land is irrigated every 3 years (3-year rotation) or every 2 years (2-year rotation) so that about 33 000 or 50 000 ha respectively can be cultivated annually. This study deals with assessing the performance of the 3-and 2-year rotation systems using the Monte Carlo simulation. Reliability, which is a measure of how frequently the irrigation water supply satisfies the demand, and vulnerability, which is a measure of the magnitude of failure, were selected as the performance criteria. Combinations of five levels of intake ratio and five levels of irrigation efficiency for the irrigation water supply of each rotation system were analysed. Historical annual flow data of the Gash River for 107 years were fit to several frequency distributions. The Weibull distribution was the best on the basis of the Akaike information criteria and was used for simulating the ensembles of annual river flow. The reliabilities and vulnerabilities of both rotation systems were evaluated at typical values of intake ratio and irrigation efficiency. The results show that (i) the 3-year rotation is more reliable in water supply than the 2-year rotation, (ii) the vulnerability of the 3-year rotation is lower than that of the 2-year rotation and (iii) therefore the 3-year rotation is preferable in the GDSIS. The sensitivities of reliability and vulnerability to changes in intake ratio and irrigation efficiency were also examined.
Abstract:In this study, a simple methodology for mapping the seasonal cultivated area of the Gash Delta Spate Irrigation System based on satellite images was developed. The methodology combined information from multiple bands to characterize the land surface in terms of spectral indices (e.g., Normalized Difference Vegetation Index (NDVI), and surface temperature (Ts)). Visual interpretations of a conveniently selected image were undertaken to identify and select sample points of interest. The NDVI and Ts values (computed from multi-date images that represented the crop growing period) of the sample points were used to developed typical NDVI and Ts plots. By analyzing these plots and the cropping calendar, an NDVI and Ts threshold-based algorithm was developed to extract the cultivated area of a given season. Analysis of the developed algorithm showed that it was simple, easily modifiable, and had interpretable rules and threshold values. Comparing the extracted cultivated area with the field report area showed a promising application of the methodology to map and estimate the cultivated area from only remote sensing data.
The Gash Delta spate irrigation system (GDSIS) with a net command area of about 100,000 ha is the largest spate irrigation system in Sudan. Annually one third of the net command area is prepared before the flood season and irrigated during the flood period from July to September. The portion of the irrigated area, which is considered as well irrigated, is allocated to farmers for cultivation of crop and it depends on the moisture stored in the soil from the single irrigation. Classification of the irrigated area as well irrigated and poorly irrigated has been done based on experience. Hence, a scientific approach that can help in estimating the soil moisture is essential. This study deals with the estimation of soil moisture distribution based on remote sensing. A simple single-band and multiband indices at the end of flood period are used to show flooded area and the relationship between the flooded area and soil moisture distribution at the early cultivation period estimated by satellite-based Surface Energy Balance Algorithm for Land (SEBAL) is discussed. The result shows the flooded area can be used as a good index to specify well irrigated area.
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