Using Ensemble-based Forecasts as an Irrigation Planning Aid
This leads to the motivation for this study, which is to produce a forecast tool that will enable producers to make more efficient irrigation management decisions. First, we will calculate the forecast error associated with ensemble-based forecasts (here the ECMWF model) for a portion of the agricultural region in southern Georgia. We will calculate errors based on observations from the Georgia Automated Environmental Monitoring Network (www.georgiaweather.net). Once the errors have been calculated, we will apply a q-to-q bias correction technique to the data in an effort to improve the precipitation forecasts over the selected region. Once we have applied the bias corrections, then we will use the check-book method of irrigation scheduling to determine the probability of receiving the required amount of rainfall for each week of the growing season. Once established, this tool will allow producers to make more informed decisions concerning irrigation water use. The techniques used here suggest how probabilistic forecasts may be used to optimize agricultural practices in a very general sense.