Remote sensing

An algorithm is developed that can accurately predict and forecast farm-scale regional daily out to 3 days. Daily ET forecast (3 days) model based on random forest (RF) has R2 and RMSE of 0.72 mm and 0.76mm respectively while recurrent neural network (RNN) ensemble forecast model was able to forecast 3 days ET with R2 and RMSE of 0.71 mm and 0.78 mm respectively.

We can better quantify evapotranspiration (ET) to improve our understanding of the Central Sands water cycle and improve irrigation demand forecasting.