The study has been conducted to develop a data simulation model and irrigation schedules for the eastern Godavari delta irrigation system, Andhra Pradesh. It aims at analysis of various factors that influence the irrigation operations and development of appropriate mathematical models and associated computer programs.
Specifically the objectives are –
- To develop a suitable forecasting model to predict the evaporation from the crop fields, which can then be used for planning the irrigation schedules
- To develop the procedures for the management of irrigation system based on the forecasting models
The present system of scheduling in the study area is a traditional one and a more scientific scheduling method is proposed so as to result in water saving in irrigation. An Artificial Neural Network (ANN) model has been developed for forecasting the evaporation from rice fields. The performance of the model is evaluated by comparing the results with the observed data.
The output of the ANN model is then fed to the CROPWAT model, a program developed by FAO, to develop the irrigation schedule. The final output of the model is the amount of irrigation to be applied to each field and the time of each irrigation.
The water allocation to the canal is also computed after developing the schedule. The ANN model has been employed to assist irrigation managers to plan at the beginning of the season, where sufficient data is not available. But in real time the data has to be corrected depending on the actual weather, crop, water supply and difficulties of system operation.
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