An integrated approach for agricultural water resources management under drought with consideration of multiple uncertainties.

Interactions across meteorological drought, agricultural drought and irrigation enlarge complexities of simulating and forecasting crop yield under droughts. Besides, contradictory relationships amid multiple objectives considering respective critical thresholds aggravate difficulties in agricultural water resources optimization. To address the above problems, this paper developed a framework of random forest based multi-objective multi-critical control programming with fuzzy boundary intervals (RFMOMCCPFBI) model for agricultural water resources optimization. The MOMCCP is established based on the MOP approach, and it improves upon the MOP in giving lower and upper thresholds of each objective, promising achievement of subjectivities of managers. Moreover, the model enhances the advantages of MCCP in reflecting multiple variations and uncertainties of thresholds by introducing fuzzy boundary intervals. In addition, the crop yield is simulated by random forest approach, which improves calculation efficiency as well as reflect influences of multiple interactive drought and irrigation on crop yield. The RFMOMCCPFBI model is used to Yingke irrigation district to allocate water resources to multiple crops at different growth stages to verify its applications. The results disclose that frequencies of meteorological drought are around 27%, 19% at five growth stages, higher than agricultural drought in future year 2022 to year 2047. Meteorological drought has many times of abrupt changes without significance. Agricultural water-saving potential increases about 20% considering demands of acceptable thresholds of objectives. Water saving potential enlarges with increase of tolerance levels of objective deviations. The model can provide alternatives for managers based on their preferences on objectives. [ABSTRACT FROM AUTHOR]