In this paper, an innovative framework is developed for simulating the water distribution in agricultural lands considering existing constraints related to soil, water, atmosphere and plant. Some nonlinear operating rules are formulated for the irrigation planning and groundwater management in Shahrekord plain in Iran. Evapotranspiration values are estimated based on a real-time modeling. Groundwater exploitations are limited for each irrigated area by considering its actual water requirement and soil moisture balance with daily time steps at the root zone. Moreover, this work introduces an approach for taking into account the uncertainty of available water. For this purpose, the membership functions of fuzzy inputs are discretized into five levels and then a multiobjective optimization model is developed to find the extreme values of economic efficiency of irrigation water for different levels. The results show that under limited water conditions, the economic productivity could be further improved when water, soil, atmosphere and crop relationships are simultaneously considered. In the proposed cropping pattern, the net annual return was increased by more than 43% comparing to the existing cropping pattern. Furthermore, different efficiency criteria for crops with higher values of yield production (e.g., potato, maize, sugar beet and alfalfa) are more affected by the existing uncertainties.
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This research has been supported by Iran National Science Foundation (INSF) under Grant Number 95000151.
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Lalehzari, R., Kerachian, R. An Integrated Framework for Optimal Irrigation Planning Under Uncertainty: Application of Soil, Water, Atmosphere and Plant Modeling. Iran J Sci Technol Trans Civ Eng 45, 429–442 (2021). https://doi.org/10.1007/s40996-020-00442-5
- Uncertainty analysis
- Cropping pattern
- Water use efficiency
- Fuzzy set theory
- Shahrekord plain