Fuzzy State Reservoir Operation Model for Irrigation with Gridded Rainfall Forecasts

Abstract:

This paper presents development and application of a fuzzy state dynamic programming model for irrigation of multiple crops. A fuzzy stochastic dynamic programming (FSDP) model is developed in which the reservoir storage and soil moisture of the crops are considered as fuzzy numbers, and the reservoir inflow is considered as a stochastic variable. The reservoir operation model is integrated with a daily water allocation model which results in daily variations of allocated water, soil moisture, and crop evapotranspiration (ET) deficits.

A short term real time operation model is also developed for irrigation of multiple crops with the following distinguishing features with respect to the FSDP model: a) Apart from inclusion of fuzziness in reservoir storage and in soil moisture of crops, spatial variations in rainfall and soil moisture of crops are included in the model by considering gridded command area with a grid size of 0.5 degree latitude by 0.5 degree longitude, b) The water allocation model and soil moisture balance equations are integrated with the real time operation model with consideration of ponding water depth for Paddy crop, and c) The release policy is developed using forecasted daily rainfall data of each grid and is implemented for the current time period using actual 10-day inflow and actual daily rainfall of each grid.

A case study of an existing Bhadra Reservoir in Karnataka, India is chosen for the model application. The results are found to be more acceptable for the case study than those of the classical stochastic dynamic model and the standard operating policy model, in terms of ten-day releases from the reservoir and evapotranspiration deficit. Consideration of irrigation decisions on a daily basis and the gridded command area are shown to result in a better performance of the reservoir operation models.