A Feedback System to Optimize Crop Water Use Estimates in Irrigation Scheduling

This paper deals with errors in estimation of soil water depletion inirrigation management. Such errors can reduce net economic returns to water, increase economic risk and motivate risk averse farm managers to adopt less profitable strategies. Two common methods of estimating depletion are discussed, one based on cumulative ET the other on soil moisture measurements. Both are characterized by significant uncertainty. It is common practice to rely on one or the other of these estimators for irrigation scheduling. This paper proposes an alternative approach that utilizes both estimators in combination. Rather than treating them as deterministic quantities, they are treated as random variables. The probability distributions of each are combined in a Bayesian analysis to derive a probability distribution of depletion, which then provides a better basis for irrigation decisions.