Comparing 1-D sediment transport modeling with field observations: Simkins Dam removal case study. Issue 2 (3rd April 2019)

• Record Type: Journal Article
• Authors: Cui, Yantao; Collins, Mathias J.; Andrews, Mary; Boardman, Graham C.; Wooster, John K.; Melchior, Marty; McClain, Serena
• Is Part Of: International journal of river basin management. Volume 17:Issue 2(2019)
• Page Start: 185
• Page End: 197
• Publication Date: 2019-04-03
• Subjects: Dam removal -- sediment transport -- modeling -- field data collection; Watershed management -- Periodicals; Water resources development -- Periodicals; Hydraulic engineering -- Periodicals; Watershed hydrology -- Periodicals; Water resources development; Watershed management; Watersheds; Periodicals; 551.483
• DOI: 10.1080/15715124.2018.1508024
• Languages: English
• ISSNs: 1814-2060

Abstract

ABSTRACT: We present a sediment transport modelling study for the 2010 removal of the 3.3-m tall Simkins Dam on the Patapsco River, MD that released more than 56, 000 m 3 of sediment downstream. Our objectives are to validate the pre-removal model forecasts with detailed post-removal monitoring data, and through hindcast modelling, examine the effects of using approximate channel geometry data or more accurate data on model results. Comparisons of DREAM-1 model predictions using approximate data and field observations indicate that reach-scale model predictions were generally accurate, but some discrepancies between predicted and observed magnitudes of sediment deposition at specific locations occurred. A refined model, developed post-dam removal with more accurate channel geometry as model input, produced slightly improved results in reaches where input data were significantly improved. However, more accurate input data did not change the general conclusions nor substantially improve the model performance for the entire study reach. In conjunction with two previous studies, our results support a simplified data collection approach that enables timely predictions for decision making and minimizes study costs.