Coupling the short-term global forecast system weather data with a variable source area hydrologic model

Abstract

Few current modeling tools are designed to predict short-term, high-risk runoff from hydrologically sensitive areas (HSAs) in watersheds. This study couples the Soil and Water Assessment Tool-Variable Source Area model with the Climate Forecast System Reanalysis model and the Global Forecast System-Model Output Statistics model short term weather forecast, to develop a HSA prediction tool designed to assist producers, landowners, and planners in identifying high-risk areas generating storm runoff and pollution. Short-term predictions for stream flow and soil moisture level were estimated in the South Fork of the Shenandoah river watershed. Daily volumetric flow forecasts were found to be satisfactory four days into the future, and distributed model predictions accurately captured sub-field scale HSAs. The model has the potential to provide valuable forecasts that can be used to improve the effectiveness of agricultural management practices and reduce the risk of non-point source pollution.

Phosphorus and the Chesapeake Bay: Lingering Issues and Emerging Concerns for Agriculture

“…End users have reported dissatisfaction with the general nature of nutrient management recommendations (Osmond et al, 2012), which often do not connect to specific best management practices and do not support daily, operational decisions that reflect antecedent conditions and weather (Buda et al, 2013). Persistent improvements to Chesapeake Bay state P indices (Sharpley et al, 2017), new conservation planning tools that target best management practices to vulnerable areas in watersheds (Tomer et al, 2015), and new decision support tools that use short‐term weather forecasts (Easton et al, 2017a; Sommerlot et al, 2017) all support improved assessment and management of P critical source areas.…”

Short‐term Forecasting Tools for Agricultural Nutrient Management

“…Corroboration of Virginia's Saturated Area Forecast Model Tool has primarily focused on hydrologic predictions. For instance, Sommerlot et al (2016) evaluated model performance in predicting streamflow and the extent of saturated areas within the South Fork of the Shenandoah River, a 2600‐km 2 mixed‐land‐use watershed in North‐Central Virginia. Field‐level hydrologic forecasts of saturated area extent (3‐m resolution) were compared with observed saturated areas mapped on two occasions in December 2015, with results demonstrating a true positive rate of 0.86 and a false positive rate of 0.25.…”

A Web Based Interface for Distributed Short-Term Soil Moisture Forecasts

“…Saturation excess runoff generation from soils with shallow restrictive layers at lower landscape positions (e.g., VSAs) accounts for the majority of surface runoff. This location was chosen as a proof of concept test bed based on the success of the short-term hydrologic forecast framework recently tested here [22]. Setup and calibration procedures are described in [22], resulting in a model which satisfactorily forecasted the streamflow response and distributed soil saturation classifications in the watershed [22,34].…”

“…SWAT-VSA is forced with dynamic meteorological forecasts to produce a 24-96 h distributed hydrologic forecast described in [22]. The DSS downloads and parses meteorological data from the GFS-MOS forecast dataset every six hours.…”

“…The model framework and development is described in detail by [22]. Briefly, the model links a VSA watershed model [23] with the National Oceanic and Atmospheric Association (NOAA)'s Global Forecast System-Model Output Statistics (GFS-MOS) forecast.…”