Description
Dams and reservoirs are vital for generating electricity and solving regional water problems. By storing and releasing water according operating rules, large reservoirs and dams can dramatically reform a hydrograph generated from large storm events. To model these systems, hydrodynamic models that include reservoir routing are needed. The Hillslope River Routing Model (HRR) is a hydrologic-hydraulic model, which simulates excess rainfall and routes surface and subsurface runoff, separately, using kinematic wave and channel flows using diffusion wave methodologies. As part of this research, the Green-Ampt infiltration and reservoir routing are incorporated into the HRR model. Although many reservoir routing models are available, they commonly require stage-discharge or storage-discharge relationships, which are difficult to obtain without in-situ data. The model developed here is intended to be parameterized using remote sensing to provide water surface elevations and surface areas (i.e., storage changes) measured from NASA's Surface Water and Ocean Topography (SWOT) mission which is tentatively scheduled to launch in 2019 and will measure reservoir areas ≥1 ha and water surface elevations to ± 10 cm with repeat sampling period varying from approximately 1 day to 2 weeks depending on the reservoir location. A case study for the May 2010 Nashville flood, which includes 8 reservoirs, is presented. To assess the impacts of potential repeat sampling on the reservoir routing model, 11 effective storage series are developed using the actual daily data plus 5 potential repeat cycles: 1-, 7-, 14-, 21-, and 28-days for two sampling period: 2000-2010 and 2000-2009 (i.e., with and without the May 2010 flood event). Using the measured storage changes, generalized storage patterns are developed and used to modulate daily reservoir storage. The results suggest that the modeling approach is effective for flood modeling but only for the 1-day sampling period, with simulated mean reservoir storage and outflow errors of -30 to 300%, respectively.
