Application of soil and water assessment tool model to estimate sediment yield in Kaw Lake

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Abstract

© 2014 The Alemayehu, D., R. Srinivasan and P. Daggupati. This open access article is distributed under a Creative Commons Attribution (CC-BY) 3.0 license. Kaw Lake is one of the reservoirs built by the Army Corps of Engineers in 1976 for the purpose of flood control, recreation, water supply, navigation and fish and wildlife conservation. The Arkansas River flows from Colorado and Kansas before reaching Oklahoma. As it passes through these states, the water carries various kinds of pollutants such as metals from mine waste discharge, salinity from the geology of the area, nutrients, pesticides and sediment from the agricultural fields and the surrounding watersheds. Sediment and other dissolved particles flow with the water and are deposited at the bottom of the Kaw Lake. These sediments may impede fish migration and act as bedding for nuisance aquatic species, decreasing the water quantity and quality affecting future development of many cities that depend on the water supply of Kaw Lake. The objective of this study was to assess the amount of sediment inflow through the Ark City and Winfield gauging stations into the Kaw Lake using the Soil and Water Assessment Tool (SWAT) model. The study found that SWAT model predicted 691 M tones a year of sediment flow through the two gauging stations into Kaw Lake with an average annual sediment rate of 1.75 M tons per year. SWAT is a good predictor of sediment yield in that the observed and predicted sediment values matched very well. Since the Arkansas River is impaired for sediment because of runoff from the surrounding area, a Total Maximum Daily Load (TMDL) be developed and Best Management Practices (BMP) carried out to protect, preserve an improve the aquatic habitat and natural resources of the watershed.

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Alemayehu, D., Srinivasan, R., & Daggupati, P. (2014). Application of soil and water assessment tool model to estimate sediment yield in Kaw Lake. American Journal of Environmental Sciences, 10(6), 530–545. https://doi.org/10.3844/ajessp.2014.530.545

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