Author(s): Chowdhary Archana, Shrivastava RK
Improved water management requires accurate scheduling of irrigation, which in turn requires an accurate estimation of crop evapotranspiration. Crop coefficients are used to estimate crop evapotranspiration from weather based reference evapotranspiration. Reference evapotranspiration is an important quantity for computing the irrigation demands for various crops. Monthly reference evapotranspiration are estimated by FAO Penman-Monteith method and irrigation requirements for the system are estimated based on the methodology suggested in FAO 24. Artificial Neural Network approach is found appropriate for the modeling of reference evapotranspiration for MRP command area. This study explores the potential of feedforward neural network (FFNN) for estimation and forecasting of monthly ETo valuesin MRP command area.