Year Established: 2017 Start Date: 2017-03-01 End Date: 2018-02-28
Total Federal Funds: $4,999 Total Non-Federal Funds: Not available
Principal Investigators: Ben Livneh
Abstract: The reliability of streamflow observations is foundational for developing and testing forecasts. The expectation is that meteorological data can be used to predict streamflow. However, this relationship can be obscured by external physical forcings, such as changes in land use, land cover, upstream reservoir operations and inconsistent gauging protocols. To date, these have not been well accounted for in streamflow forecasts. Errors in streamflow forecasts are often attributed to model insufficiencies, whereas part of the error is likely due to external forcings that have not been accounted for. A variety of studies have examined the impacts of external forcings in individual watersheds and regions, but a large scale systematic analysis has not been conducted. The goal for this award would be to help support critical first steps and provide seed research towards a large scale analysis of the impacts of single and multiple forcings on streamflow from a variety of western U.S. watersheds. Knowing the presence and magnitude of these signals will improve model development and water resource planning efforts that rely on forecast information. For Colorado this is especially important given the over allocation of water resources. The effects of external forcings will be quantified by comparing differences between model-based datasets that simulate conditions without external forcings (e.g. Livneh et al., 2015; Newman et al., 2015) to streamflow observation data from USGS National Water Information System. The primary goal is to identify times when external forcings influence streamflow and develop a disturbance severity index for the gauged HUC08 rivers in Colorado.