Simulating streamflow on regulated rivers using characteristic reservoir storage patterns derived from synthetic remote sensing data

This study presents a method to estimate streamflow in rivers regulated by lakes or reservoirs using synthetic satellite remote sensing data. To illustrate the approach, the new reservoir routing method is integrated into the Hillslope River Routing model, and a case study is presented for the highly regulated river in the Cumberland River basin (46,400km(2)). The study period is April-May 2000, which contains a significant flood event that occurred in 1-2 May 2000. The model is shown to capture storage/release characterises in eight reservoirs with a mean normalized root mean square error (NRMSE) of 20% for entire simulation period and 27% for the May flood event. These errors are 69 and 75%, respectively, less than the NRMSE if reservoirs are not included in the model. Given the limitations of satellite missions, the impacts of the revisit cycles and operational periods are quantified. We used 26 observation sets of satellite altimetry over Cumberland River basin that are generated by considering both repeat cycles and satellite operation periods. For the revisit cycles, increasing the interval of repeat cycle leads to a corresponding increase of mean NRMSE from 27 to 59% as a result of sampling fewer flood events and smoothing of the change in storage signal as a result of longer intervals between visits. For the operation periods, the impact of data periods is limited because of the strong seasonal pattern of reservoir operations. Overall, the results suggest that the generalized routing model derived from reservoir stage observations can be used to simulate reservoir operating conditions, which can be used in forecasting hydrologic impacts of land cover or climate change. Copyright (c) 2014 John Wiley & Sons, Ltd.