Presentation Title

Estimating Erosion and Validating Sediment Yield Models in the Magdalena River Basin, Colombia

Authors' Names

Luke Fisher

Presentation Type

Oral Presentation

Abstract/Artist Statement

The Magdalena river basin (MRB) occupies 24% of Colombia’s national territory and is home to 77% of its people and the 80% of the nation’s GDP. Colombia’s geography in the northern Andes combines steep mountains with ample precipitation, creating an environment that is, on the one hand, ideal for hydroelectric development, but on the other hand leads to intensely eroded landscapes and sediment-rich rivers. The dams and reservoirs associated with hydroelectric development interrupt the natural flow of large rivers and block passage of sediment, causing loss of aquatic habitat, incision of the river bed, and other downstream environmental impacts.

Colombia’s electricity demand is increasing. With numerous hydropower projects currently planned or under construction across the MRB, there is a need to gain a greater understanding of how sediment moves through the basin. One important element that has yet to be explored in depth is the amount of sediment generated by erosion that will eventually reach the river and be exported from river basins (i.e., sediment yield).

Because field data on landscape and river processes in the MRB are limited, modeling to estimate erosion and sediment yield is needed. In the MRB modeling techniques can be applied to estimate sediment yield on a range of scales using existing geospatial data and other parameters derived from the literature. These modeling techniques are built on statistical methods linking observable characteristics of the landscape to sediment yields at a specific location in the basin. This level of specificity allows the user to investigate how erosion varies across the basin and how specific factors may influence sediment yield.

This project tests two existing sediment-yield models. Inputs to these models are derived from publicly available geospatial data including digital elevation models (DEM), geologic maps, climate data, remote sensing and published characteristics of large reservoirs in the river network. These models will be used to estimate sediment yield in the Sogamoso, Saldaña and Alto Magdalena sub-basins of the broader MRB. These basins either have existing hydropower projects or have hydropower potential. Comparisons will be made between modeling results to quantify how sediment yield and erosion varies across the broader MRB and the quality of each model in predicting sediment yield. Validations of both models will be made with data from gauging stations in all three study areas as well as geochemically derived erosion rates in the Sogamoso basin.

A study evaluating the applicability of established models has not been published for the MRB. The results of this work are valuable in constraining values for sediment yield in the basin. Additionally, evaluating the efficacy of these models is valuable in developing tools and methodologies that will help us gain a greater understanding of how rivers work in mountainous tropical basins.

Mentor Name

Andrew Wilcox

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Estimating Erosion and Validating Sediment Yield Models in the Magdalena River Basin, Colombia

UC 330

The Magdalena river basin (MRB) occupies 24% of Colombia’s national territory and is home to 77% of its people and the 80% of the nation’s GDP. Colombia’s geography in the northern Andes combines steep mountains with ample precipitation, creating an environment that is, on the one hand, ideal for hydroelectric development, but on the other hand leads to intensely eroded landscapes and sediment-rich rivers. The dams and reservoirs associated with hydroelectric development interrupt the natural flow of large rivers and block passage of sediment, causing loss of aquatic habitat, incision of the river bed, and other downstream environmental impacts.

Colombia’s electricity demand is increasing. With numerous hydropower projects currently planned or under construction across the MRB, there is a need to gain a greater understanding of how sediment moves through the basin. One important element that has yet to be explored in depth is the amount of sediment generated by erosion that will eventually reach the river and be exported from river basins (i.e., sediment yield).

Because field data on landscape and river processes in the MRB are limited, modeling to estimate erosion and sediment yield is needed. In the MRB modeling techniques can be applied to estimate sediment yield on a range of scales using existing geospatial data and other parameters derived from the literature. These modeling techniques are built on statistical methods linking observable characteristics of the landscape to sediment yields at a specific location in the basin. This level of specificity allows the user to investigate how erosion varies across the basin and how specific factors may influence sediment yield.

This project tests two existing sediment-yield models. Inputs to these models are derived from publicly available geospatial data including digital elevation models (DEM), geologic maps, climate data, remote sensing and published characteristics of large reservoirs in the river network. These models will be used to estimate sediment yield in the Sogamoso, Saldaña and Alto Magdalena sub-basins of the broader MRB. These basins either have existing hydropower projects or have hydropower potential. Comparisons will be made between modeling results to quantify how sediment yield and erosion varies across the broader MRB and the quality of each model in predicting sediment yield. Validations of both models will be made with data from gauging stations in all three study areas as well as geochemically derived erosion rates in the Sogamoso basin.

A study evaluating the applicability of established models has not been published for the MRB. The results of this work are valuable in constraining values for sediment yield in the basin. Additionally, evaluating the efficacy of these models is valuable in developing tools and methodologies that will help us gain a greater understanding of how rivers work in mountainous tropical basins.