In spite of the importance of Sudd (swamp) area estimation for any hydrological project in the southern Sudan, yet, no abroad agreement on its size, due to the inaccessibility and civil war. In this study, remote sensing techniques are used to estimate the Bahr El-Jebel flooded area. MODIS-Terra (Moderate Resolution Imaging Spectrora-5 diometer) level 1B satellite images are analyzed on basis of the unsupervised classification method. The annual mean of Bahr El-Jebel flooded area has been estimated at 20 400 km 2 , which is 96% of Sutcliffe and Park (1999) estimation on basis of water balance model prediction. And only, 53% of SEBAL (Surface Energy Balance Algorithm for Land) model estimation. The accuracy of the classification is 71%. The study also 10 found the swelling and shrinkage pattern of Sudd area throughout the year is following the trends of Lake Victoria outflow patterns. The study has used two evaporation methods (open water evaporation and SEBAL model) to estimate the annual storage volume of Bahr El-Jebel River by using a water balance model. Also the storage changes due time is generated throughout the study years.
15(Sudd is an Arabic word means the barrier), because of evaporation (Howell et al.,
Drought is a constraint upon development in Sudan. This paper attempts to understand drought and climate change in the central Sudan using the Silyaninov index (SI) because of its simplicity and its required datasets (monthly rainfall and temperature) are routinely collected in developing countries. Also, the ecoclimatological relationships for the natural vegetation cover were investigated using the normalized difference vegetation index (NDVI) and ancillary climatic data. The climate variability in the central Sudan is found to be highly generated by the variability in rainfall rather than temperature. Rainfall experienced a significant decreasing trend (≈ 3.5 mm per annum) coupled with a significant increasing trend in temperature (≈ 1.4 o C per annum) during the period 1960 to 2010. Accordingly, the aridity increased significantly at 50% of the studied stations. SI is found to be more effective in detecting drought than using rainfall dataset alone. However, when the temperature dataset is anomalies-free it could explain effectively most of the historical meteorological droughts witnessed in central Sudan. Using SI, the majority of the drought events were observed in 1970 to 1990, with the exception of Damazine (1998 to 2002) and Ed Duim stations (2000-2005). The common wetted years outweighed the common drought years, revealing the localized behavior of the rainfall. The analysis of NDVI showed that the vegetation cover experiences a decreasing pattern under the semi dry (Ed Duim station) and semi humid (Damazine station) climatic zones during the period 2000 to 2010. The relationships of NDVI-SI and NDVI-rainfall were found better than the NDVI-temperature.
Groundwater dominates the domestic water supply (85%) in the Gezira State, Central Sudan. Groundwater resources in Gezira are basically represented by two water-bearing geological formations: the Nubian Sandstone formation overlain by the Gezira formation and shallow quaternary to recent deposits in minor streams. This study aims at identifying the pattern distribution of selected aquifer characteristics of the Gezira geological formation. It applies empirical Driscoll's equation to generate the aquifer's transmissivity. Geospatial techniques in the Geographic Information System (GIS) accompanied with Digital Elevation Model (DEM) datasets were used in interpolation and map transmissivity. The obtained transmissivity of 7.44 to 875 m 2 a day were found to be conformable with those conventionally based values of 28 -824 m 2 a day. The spatial variation in the water table was extracted using the DEM data, resulting in a reliable potentiometric map (water table map) for the Gezira formation as compared with that traditionally produced. Potentiometric map was used effectively for mapping trends in the water levels and flow directions. The study showed a powerful example of using GIS and DEM techniques in studying groundwater aquifer characteristics, specifically the geospatially dependent variables.
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