Location: Watershed Management Research
Project Number: 2052-13610-012-29-I
Project Type: Interagency Reimbursable Agreement
Start Date: Sep 10, 2018
End Date: Sep 30, 2019
To apply isnobal for water supply forecasting, and to test and develop new and more effective simulation models that can be used by the National Water and Climate Center (NRCS) for water supply forecasting.
Work cooperatively with NRCS to address issues, needs, and problems as they arise each year. With NRCS guidance, ARS will develop a research plan, including objectives, milestones and deliverables for each year of the project. ARS will provide the site, technical support, data management and analysis, and will publish findings as appropriate. NRCS will participate in project planning, analysis and publication of results. 1) Statistical Forecasting: Run iSnobal for the Reynolds Creek Basin generating model output like snow water equivalent (SWE) for approximately 31 years (water years 1984 through 2014). With the model output, develop new statistical relationships between the spatial model results and the seasonal streamflow volume. Compare the new relationships with the current NRCS models to evaluate and analyze the differences. The results of the analysis would form the basis of a water volume forecast based on iSnobal model results. 2) Data development: The most important and time-consuming step of running iSnobal requires carefully quality controlling the meteorological input data. When developing a long-term data set to run a 15-year simulation over multiple basins, quality control will consume more time than running the model. Therefore, working with the staff at NWCC, ARS will evaluate how to improve the data development workflow. This will include evaluating how sensitive iSnobal model outputs are to different levels of quality control schemes. 3) Assess process of setting up iSnobal in new basin: Initiate the process of setting up iSnobal in a basin with different instrumentation and data availability. Show “proof of concept”, determining costs of model set up and data assimilation, overall level of effort, addressing obstacles and pinch points. Through understanding the model setup, we can evaluate the operational feasibility of applying iSnobal to new basins in order to prioritize forecast development.