A simple method for assessing available weather data quality for site specific nutrient management

Abstract:

Phosphorous (P) Indices are an assessment tool used to identifying agricultural fields most vulnerable to P losses. In the two decades since its introduction, the P Indexing concept has evolved, and there are now P Indices that serve as Best Management Practice (BMP) selection and targeting. While the use of observed P loss data under various management scenarios is the ideal way to assess the accuracy of the P Indices, water quality data, particularly at the field scale, are not widely available and can require years of costly field research to generate. In place of in-situ water quality measurements, the use of locally relevant and corroborated water quality models is a more expedient option to conduct index assessments in the short time required for new standards.

The input forcing data required by these models include precipitation and temperature. Unfortunately obtaining representative meteorological data for watershed-scale hydrological modelling can be difficult and time consuming. Land-based weather stations do not always adequately represent the weather occurring over a watershed because they can be far from the watershed of interest and can have gaps in their data series, or recent data are not available. Fuka et al. (2013) has shown that readily available short term forecasting data can match the accuracy of using traditional weather gauging stations, especially when the closest stations are more than 10km from the watershed. In this study we demonstrate a methodology to ascertain the most representative openly accessible weather forcing data for running water quality models in any location in the US. For this P-Index assessment, nine representative project watersheds from the three regional consortiums--Heartland, Chesapeake Bay, and Southern Regions--are used to demonstrate this method of determining what is the most representative weather forcing data for any location within the regions.