|REED, SEANN - National Weather Service|
|MILLER, DOUGLAS - Pennsylvania State University|
|DROHAN, PATRICK - Pennsylvania State University|
Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/1/2022
Publication Date: 6/13/2022
Citation: Buda, A.R., Reed, S.M., Folmar, G.J., Kennedy, C.D., Millar, D.J., Kleinman, P.J., Miller, D.A., Drohan, P.J. 2022. Applying the NWS’s distributed hydrologic model to short-range forecasting of quickflow in the Mahantango Creek watershed. Journal of Hydrometeorology. https://doi.org/10.1175/JHM-D-21-0189.1.
Interpretive Summary: Agricultural producers need accurate and reliable runoff forecasts to decide when fertilizers and manures should be applied in order to protect water quality. In this study, we used runoff monitoring data from a large agricultural watershed and one of its headwater tributaries to evaluate the quality of short-term runoff forecasts (1 to 3 days ahead) that were generated by a National Weather Service watershed model. Results showed that the accuracy and reliability of runoff forecasts generally improved in both watersheds as lead times increased from 1 to 3 days. Findings highlight the potential for National Weather Service models to provide useful short-term runoff forecasts that can inform operational decision making in agriculture.
Technical Abstract: Accurate and reliable forecasts of quickflow, including interflow and overland flow, are necessary to provide early warnings of rainfall-runoff events that can wash off recently-applied agricultural nutrients. Accordingly, this study examined whether a gridded version of the Sacramento Soil Moisture Accounting model with Heat Transfer (SAC-HT) could simulate and forecast quickflow in two agricultural watersheds in east-central PA. Briefly, we used the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) software, which incorporates SAC-HT, to conduct a 15-year (2003–2017) simulation of quickflow in the 420-km2 Mahantango Creek watershed and in WE-38, a 7.3-km2 headwater interior basin. A modest hydrologic calibration was applied to the Mahantango Creek outlet, while all grid cells within Mahantango Creek, including WE-38, were calibrated indirectly using scalar multipliers derived from the basin outlet calibration. Using the calibrated model, we then assessed the quality of deterministic quickflow forecasts in both watersheds from July 2017–October 2019 for lead times of 24–72 hr. We found that quickflow was well-simulated by HL-RDHM at the basin outlet, with low biases and strong agreement between observations and simulations. At the headwater scale, HL-RDHM overestimated the amount and variability of quickflow to a greater degree, but quickflow simulations were generally satisfactory based on hydrologic performance metrics. When applied to quickflow forecasting, HL-RDHM produced skillful forecasts at all lead times and significantly outperformed persistence reference forecasts, especially at lead times of 48–72 hr. As such, short- to medium-range quickflow forecasts by HL-RDHM offer great potential to inform operational decision making in agriculture.