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Title: Using the Sacramento soil moisture accounting model to provide short-term forecasts of surface runoff for daily decision making in nutrient management

Author
item Buda, Anthony
item REED, SEANN - National Oceanic & Atmospheric Administration (NOAA)
item MOSER, CODY - National Oceanic & Atmospheric Administration (NOAA)
item Folmar, Gordon
item Kleinman, Peter
item Bryant, Ray
item KNIGHT, PAUL - Pennsylvania State University
item MILLER, DOUGLAS - Pennsylvania State University
item BILLS, BRIAN - Pennsylvania State University
item AHNERT, PETER - Pennsylvania State University
item DROHAN, PATRICK - Pennsylvania State University

Submitted to: American Water Resources Association Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 7/7/2014
Publication Date: 11/6/2014
Citation: Buda, A.R., Reed, S.M., Moser, C.L., Folmar, G.J., Kleinman, P.J., Bryant, R.B., Knight, P.G., Miller, D., Bills, B., Ahnert, P., Drohan, P. 2014. Using the Sacramento soil moisture accounting model to provide short-term forecasts of surface runoff for daily decision making in nutrient management. American Water Resources Association Conference Proceedings. P. 1.

Interpretive Summary: An interpretive summary is not required.

Technical Abstract: Managing the timing of fertilizer and manure application is critical to protecting water quality in agricultural watersheds. When fertilizers and manures are applied at inopportune times (e.g., just prior to a rainfall event that produces surface runoff) the risk of surface water contamination is unnecessarily increased. Therefore, timely forecasts on the likelihood of surface runoff occurrence may help farmers adjust when and where fertilizers are applied in order to mitigate water quality risk. This presentation draws upon research in the Mahantango Creek Experimental Watershed to develop a short-term decision support tool for nutrient management that provides forecasts of surface runoff occurrence over 24, 48, and 72 hour periods. The tool is underpinned by the Heat Transfer – Evapotranspiration (HTET) version of the Sacramento Soil Moisture Accounting Model (SAC-SMA), which is a high-resolution (2 × 2 km), fully distributed hydrologic simulation model used by National Weather Service River Forecast Centers to provide short-term guidance on flood risk for rivers and streams. For this study, we extracted time series of surface runoff and interflow predictions from SAC-HTET for a ten-year period (2002-2011) and compared them against observations of surface runoff occurrence at hillslope / field (0.04 km2), small watershed (0.1 km2), and large watershed (approximately 7 km2) scales within the Mahantango Creek watershed. We used the Gilbert Skill Score (GSS), also known as the Equitable Threat Score, to evaluate the skill of SAC-HTET in predicting surface runoff occurrence at each measurement scale. Results from the study showed that SAC-HTET could predict surface runoff occurrence with excellent skill at the small watershed scale (GSS = 0.70), while less skillful predictions were made at field / hillslope (GSS = 0.22) and large watershed (GSS = 0.28) scales. Preliminary findings from this work indicate that SAC-HTET holds great potential to forecast surface runoff occurrence in headwater agricultural basins, thus highlighting its applicability to support short-term decision support tools for nutrient management.