Evaluation of Sediment Yield Predicting Models of Ghana

Authors

  • John Manyimadin Kusimi Dept. of Geography & Resource Development, University of Ghana, Legon, Accra, Ghana
  • Bertha Ansaah Kusimi Institute of Environment and Sanitation Studies, University of Ghana, Legon, Accra, Ghana
  • Barnabas A. Amisigo Water Research Institute, Council for Scientific & Industrial Research, P.O. Box AH.38, Accra, Ghana

DOI:

https://doi.org/10.30564/jgr.v4i1.2596

Abstract

Fluvial sediment transport data is a very important data for effective water resource management. However, acquiring this data is expensive and tedious hence sediment yield modeling has become an alternative approach in estimating river sediment yields. In Ghana, several sediment yield predicting models have been developed to estimate the sediment yields of ungauged rivers including the Pra River Basin. In this paper, 10 months sediment yield data of the Pra River Basin was used to evaluate the existing sediment yield predicting models of Ghana. A regression analysis between predicted sediment yield data derived from the models and the observed suspended sediment yields of the Pra Basin was done to determine the extent of estimation of observed sediment yields. The prediction of suspended sediment yield was done for 4 out of 5 existing sediment yield predicting models in Ghana. There were variations in sediment yield between observed and predicted suspended sediments. All predicted sediment yields were lower than observed data except for equation 3 where the results were mixed. All models were found to be good estimators of fluvial sediments with the best model being equation 4. Sediment yield tends to increase with drainage basin area. 

Keywords:

Pra River, Regression analysis, Sediment transport, Sediment yield, Sediment yield modeling, Ghana

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How to Cite

Kusimi, J. M., Kusimi, B. A., & Amisigo, B. A. (2021). Evaluation of Sediment Yield Predicting Models of Ghana. Journal of Geographical Research, 4(1), 37–47. https://doi.org/10.30564/jgr.v4i1.2596

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