Date of Award
Master of Science (MS)
J. Toby Minear
There is great need to quantify reservoir storage loss due to sediment. Less than 1% of reservoirs in the US have more than one volume survey. Due to the lack of frequent data collection, a constant rate sediment yield from year to year is often assumed. This study aims to explore the following questions: 1) Can hydrologically-forced sediment algorithms help us advance reservoir sedimentation estimates to improve future planning? 2) To which processes and inputs are reservoir sedimentation estimates most sensitive? 3) What can we learn from models that the linear sediment accumulation assumption fails to assess? It will address these questions through a Sobol Sensitivity analysis a hydrologically forced sediment algorithm ensemble, as well as an evaluation of differences between the hydrologically forced and linear sedimentation assumptions. The hydrologic model used are Variable Infiltration Capacity (VIC) which is coupled with sediment algorithms including the Modified Universal Soil Loss Equation (MUSLE), Hydrological Simulation Program—Fortran (HSPF) and Systeme Hydrologique European Sediment Model (SHE-SED) from within the Distributed Hydrology Soil Vegetation Model (DHSVM). Sediment accumulation will be modeled for Prineville Reservoir near Bend, Oregon.
Bensching, Leah Clare, "Diagnosing Drivers of Reservoir Sedimentation in the Western Us: a Case Study of Prineville Reservoir, Oregon" (2019). Civil Engineering Graduate Theses & Dissertations. 489.