Izadfard, A., Sarmadian, F., Jahansooz, M. R., Asadi Oskouie, E. (2021). Optimum Cropping Pattern Based on Irrigation Water Productivity Using AquaCrop Simulation Model. , 23(5), 1163-1178.
A. Izadfard; F. Sarmadian; M. R. Jahansooz; E. Asadi Oskouie. "Optimum Cropping Pattern Based on Irrigation Water Productivity Using AquaCrop Simulation Model". , 23, 5, 2021, 1163-1178.
Izadfard, A., Sarmadian, F., Jahansooz, M. R., Asadi Oskouie, E. (2021). 'Optimum Cropping Pattern Based on Irrigation Water Productivity Using AquaCrop Simulation Model', , 23(5), pp. 1163-1178.
Izadfard, A., Sarmadian, F., Jahansooz, M. R., Asadi Oskouie, E. Optimum Cropping Pattern Based on Irrigation Water Productivity Using AquaCrop Simulation Model. , 2021; 23(5): 1163-1178.

Optimum Cropping Pattern Based on Irrigation Water Productivity Using AquaCrop Simulation Model

Journal of Agricultural Science and Technology
Article 15, Volume 23, Issue 5, 2021, Pages 1163-1178    PDF (738.95 K)
Document Type: Original Research
Authors
A. Izadfard* 1; F. Sarmadian2; M. R. Jahansooz3; E. Asadi Oskouie4
1Department of Hybrid Seed Production, Iranian Company for Maize Development, Tehran, Islamic Republic of Iran.
2Department of Soil Science, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Islamic Republic of Iran.
3Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences and Engineering, College of Agriculture and Natural Resources, University of Tehran, Islamic Republic of Iran.
4Atmospheric Science and Meteorological Research Center, Islamic Republic of Iran.
Abstract
Optimum cropping pattern increases productivity where input resources are limited. An optimized cropping pattern was developed for a region in Moghan Plain, located in the northwestern Iran, to help water supplier in pre-season decision making on water and land allocation. AquaCrop simulation model was calibrated and executed for yield predictions for 11 different crops and 13 diverse soil types. Evaluation of AquaCrop model showed great robustness for a broad range of crops, even for the crops like canola and alfalfa that were undefined for the model. The precise generated crop water functions revealed the ideal conditions for water allocation by considering the impact of the existing limitation in monthly water availability on optimum cropping pattern without imposing any manipulation. Optimum cropping pattern based on water productivity (OCPWP) was identified by LINGO software. Integrating AquaCrop model and LINGO optimization problem solver created a Decision Support System (DSS) for technical analysis at the regional level. The created DSS is able to support the OCPWP in terms of the complex regional crop-mixture acreage. The ecological considerations introduced diverse winter crops to benefit from autumn precipitations. This strategy decreases irrigation requirement and saves some water for spring/summer high water-demanding crops like alfalfa and cotton, which generally enhances the system resiliency. The generated DSS revealed that 8,762 m3 water ha-1 was required for optimum cropping pattern, which is 8% lower than the maximum and 3% more than the average available water.
Keywords
Crop per drop index; Decision support system; System resiliency
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