Abstract. The availability of the actual water use from agricultural crops is considered as the key factor for irrigation water management, water resources planning, and water allocation. Traditionally, evapotranspiration (ET) has been calculated in the Gezira scheme as the point of reference with evapotranspiration (ET o ) and crop coefficients (k c ) being derived from actual measurements of soil-water balance. Recently developed, advanced energy balance models assisted in estimating the ET through the remotely sensed data. In this study Enhanced Thematic Mapper Plus (ETM+) and MODerate Resolution Imaging Spectroradiometer (MODIS) images were used to estimate the spatial distribution of the daily, monthly and seasonal ET for irrigated sorghum in the Gezira scheme, Sudan. The daily ET maps were also used to estimate k c over time and space. Results of the energy balance, based on being remotely sensed, were compared to actual measurements conducted during 2004/05 season. The seasonal actual ET values, obtained from the seven MODIS images for irrigated sorghum, were estimated at 579 mm. The values for remotely sensed k c , derived during the initial mid-season and late-season crop development stages, were 0.62, 0.85, 1.15, and 0.48, respectively. On the other hand, the values for the experimental k c during the pervious mention stages were 0.55, 0.94, 1.21 and 0.65, respectively. The estimated seasonal ET of the sorghum, derived by remotely sensed k c , was 674 mm. The Landsat data and the Free MODIS provided reliable, exhaustive, and consistent information on the water use, relevant for decision support in the Gezira scheme.

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Abstract:Stream-flow recessions are commonly characterized by the exponential equation or in the alternative power form equation of a single linear reservoir. The most common measure of recession is the recession constant K, which relates to the power function form of the recession equation for a linear reservoir. However, in reality it can be seen that the groundwater dynamics of even the simplest of aquifers may behave in a non-linear fashion. In this study three different storage-outflow algorithms; single linear, non-linear and multiple linear reservoir were considered to model the stream-flow recession of the upper Blue Nile. The recession parameters for the linear and non-linear models were derived by the use of least-squares regression procedures. Whereas, for the multiple linear reservoir model, a second-order autoregressive AR (2) model was applied first in order to determine the parameters by the least-squares method. The modelling of the upper Blue Nile recession flow performed shortly after the wet season, when interflow and bank storage may be contributing considerably to the river flow, showed that the non-linear reservoir model simulates well with the observed counterparts. The variation related to preceding flow on a recession parameter of the non-linear reservoir remains significant, which was obtained by stratification of the recession curves. Although a similar stratification did not show any systematic variation on the recession parameters for the linear and multiple linear reservoir models.

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Abstract:Estimates of the amount of recession flow can be derived from streamflow records. Such estimates are critical in the assessment of low flow characteristics for the Blue Nile River, from which about two-thirds of the irrigation requirements in Sudan are satisfied. The recession flow hydrograph can be estimated by fitting the conceptual nonlinear storage outflow model using an iterative algorithm. An analytical model to forecast the Blue Nile recession flow is developed and the performance of the model is compared to the previous Blue Nile recession flow model. In the proposed model, a simple linear regression equation is introduced to illustrate the effect of antecedent flow on the recession parameter. Results indicate that the model can provide a simple and reliable method to predict the recession flow of the Blue Nile River.