scholarly journals Reservoir Sediment Management Practices in Sudan: A Case Study of Khashm El-Girba Dam

2021 ◽  
pp. 455-471
Author(s):  
Elhadi Adam ◽  
Mohammed Suleiman
Keyword(s):  
Management Practices ◽  
Water Storage ◽  
River System ◽  
Sediment Management ◽  
Nile River ◽  
Sediment Source ◽  
Flood Period ◽  
Multipurpose Dam ◽  
Eastern Sudan

AbstractThe sedimentation problem is a hot issue currently affecting the operations of reservoirs and irrigation networks in Sudan. Most of the rivers that cross Sudanese borders come from the Eastern African Plateau, which acts as a sediment source for the Nile River and its tributaries. Khashm el-Girba Dam (KEGD), which crosses the Atbara River in Eastern Sudan, is a multipurpose dam that was constructed in 1964. The Atbara River is a branch of the Nile River system, and the river carries a large amount of sediment during the flood period. Seven years after construction, in 1970, the dam faced a critical problem that could have led to a disaster; it was discovered that, due to sediment deposition, the water storage was not enough to satisfy the downstream requirements. This study discusses the sediment management practices used in KEGD and their impacts on maintaining the reservoir capacity. Practices including operation policy (OP), trap efficiency (TE), sluicing, sediment sluicing, and flushing operation (FO) were discussed. The adopted management practices succeeded in removing a considerable amount of silt and maintaining the lifetime of the reservoir.

scholarly journals Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Regression Models ◽  
Meteorological Data ◽  
Water Storage ◽  
Model Performance ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

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