Year Established: 2018 Start Date: 2018-03-01 End Date: 2019-02-28
Total Federal Funds: $25,000 Total Non-Federal Funds: $50,000
Principal Investigators: Tyson Ochsner, Erik Krueger, Briana Wyatt, Eric Jones
Abstract: Rationale: Around the world the security and sustainability of surface water use are threatened by growing water demands and by changing and increasingly variable climate. These threats are difficult to address with current hydrologic forecasting systems, which can be unreliable, leaving water managers in a precarious situation. In a recent federal inter-agency needs assessment, water managers in the US identified as key needs making streamflow forecasts more reliable and expanding the geographic coverage of those forecasts. Nowhere in the US are these specific needs felt more urgently than in the Great Plains, where reservoirs rely on highly-variable seasonal inflows; inflows which have often failed in recent droughts causing substantial economic and ecological damage. In this region, operational forecasting systems for seasonal water supply are less skillful than the forecast systems available in the western US. This can be partly attributed to the fact that the Great Plains, unlike the western US, does not rely primarily on snowmelt runoff. As one Great Plains water manager noted, forecast[s] targeting seasonal periods are unreliable in our geographical areaIt is very difficult to provide water supply estimates One reason for this lack of reliability is that current forecasting systems do not incorporate soil moisture observations, even though their potential to improve seasonal streamflow forecasts has been known since the 1930s. Objectives: The overall objective of this multi-year project is to provide surface water managers with improved seasonal streamflow forecasts that are useful in making water management decisions. At the heart of these prediction systems will be calibrated and validated models of streamflow, which incorporate soil moisture data to produce probabilistic, quantitative forecasts of the potential streamflow totals for the upcoming season. We will pursue the following two specific aims: Year 1: Develop and evaluate streamflow forecasting methods informed by in situ soil moisture observations. Year 2 (subsequent funding cycle): Demonstrate the forecasts for water managers and researchers and refine the forecast delivery format to maximize usefulness for water management decisions. Methods: We propose an integrated plan of applied research leading to improved seasonal streamflow forecasting methods available to water managers, methods built upon existing, under-utilized soil moisture information. In year 1, we will incorporate soil moisture information into the mechanistic streamflow forecasting approach used by the National Weather Service (NWS) and the statistical streamflow forecasting used by the Natural Resources Conservation Service (NRCS). We will then evaluate the accuracy and document the strengths and weaknesses of these two contrasting approaches. Expected outcomes: If successful, this project will lay the foundation for implementation of the new forecast methods by the NWS and NRCS for the benefit of water managers in Oklahoma and across the nation. Our goal is that this project will serve as a seed and example and that, with other funding sources, we will be able to evaluate and refine these forecast methods for locations across the US. The resulting soil moisture-informed streamflow forecasts will assist water resource managers in making a wide array of management decisions such as water allocations and reservoir releases. The forecasts will also inform conservation and water rationing decisions for diverse municipal and industrial water users who rely on surface water sources.