UC Davis

In the northeastern United States (U.S.), watersheds and ecosystems are impacted by nonpoint source pollution (NPS) from agricultural activity. Where agricultural fields coincide with runoff-producing areas-so called hydrologically sensitive areas (HSA)-there is a potential risk of NPS contaminant transport to streams during rainfall events. Although improvements have been made, water management practices implemented to reduce NPS pollution generally do not account for the highly variable, spatiotemporal dynamics of HSAs and the associated dynamics in NPS pollution risks. This paper presents a prototype for a web-based HSA prediction tool developed for the Salmon Creek watershed in upstate New York to assist producers and planners in quickly identifying areas at high risk of generating storm runoff. These predictions can be used to prioritize potentially polluting activities to parts of the landscape with low risks of generating storm runoff. The tool uses real-time measured data and 24-48 h weather forecasts so that locations and the timing of storm runoff generation are accurately predicted based o present-day and future moisture conditions. Analysis of HSA predictions in Salmon Creek show that 71% of the largest storm events between 2006 and 2009 were correctly predicted based on 48 h forecasted weather data. Real-time forecast of HSAs represents an important paradigm shift for the management of NPS in the northeastern U.S. © 2013 by the authors.