Evaluation of the Best Management Practices at the Watershed Scale to Attenuate Peak Streamflow Under Climate Change Scenarios

Abdullah O. Dakhlalla () and Prem B. Parajuli
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Abdullah O. Dakhlalla: Mississippi State University
Prem B. Parajuli: Mississippi State University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 3, No 5, 963-982

Abstract: Abstract The objectives of this study are (1) to develop a calibrated and validated model for streamflow using the Soil and Water Assessment Tool (SWAT) for the Lower Pearl River Watershed (LPRW) located in southern Mississippi, and (2) to assess the performance of parallel terraces, grassed waterways, and detention pond BMPs at attenuating peakflows at the watershed-scale under changes in precipitation, temperature, and CO2 concentrations. The model was calibrated and validated for streamflow at 4 USGS gauge stations at the daily scale from 1994 to 2003 using the Sequential Uncertainty Fitting (SUFI-2) optimization algorithm in SWAT-CUP. The model demonstrated good to very good performance (R2 = 0.49 to 0.90 and NSE = 0.49 to 0.84) between the observed and simulated daily streamflows at all 4 USGS gauge stations. This study found that grassed waterways had the highest peak flow reduction (−8.4 %), followed by detention ponds (−6.0 %), and then parallel terraces (−3.1 %) during the baseline climate scenario. Combining the different BMPs yielded greater reduction in average peak flow compared to implementing each BMP individually in both the current and changing climate scenarios. This study also found that the effectiveness of BMPs to reduce peakflows decreases significantly when increased rainfall or increased CO2 concentrations are introduced in the watershed model. When increasing temperatures or decreasing rainfall is incorporated in the model, the peakflow reductions caused by BMPs generally does not change significantly.

Keywords: Watershed modeling; Streamflow; Climate change; BMPs; SWAT (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s11269-015-1202-9

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