Regional modeling of winter wheat yield and water productivity under water-saving irrigation scenarios

• Published in: Journal of water and climate change 2022-10, Vol.13 (10), p.3547-3565
• Main Authors: Ahmadi, Seyed Hamid, Jorenush, Mohammad Hadi, Boroomand Nasab, Saeed
• Format: Article
• Language: English
• Subjects: Accuracy; Agricultural production; Agriculture; aquacrop; Biomass; Canopies; Canopy; Climate change; Climatic conditions; Crop growth; Crop production; Crop yield; Crops; Cultivars; Decision making; deficit irrigation; Farming systems; Field tests; Grain; Growing season; Growth models; Irrigation; Irrigation water; Major elements; Modelling; Moisture content; Parameterization; Plant cover; Planting; Productivity; Provinces; Regions; Simulation; Soil; Soil water; sowing date; Triticum aestivum; Water conservation; Water content; water productivity; Wheat; wheat grain yield; Wheat yield; Winter; Winter wheat
• ISSN: 2040-2244; 2408-9354
• DOI: 10.2166/wcc.2022.170

Wheat is the major agricultural crop in Iran. Using reliable tools to estimate wheat grain yield may help the regional planners and stakeholders to employ proper cultivation approaches to increase grain yield in different regions. The process-based crop growth models are the essential analytical tools for representing the main interactions between the environment, crop, resources, and yield production. For these reasons, the crop growth models have been used as an important component in productive farming systems for assessing and improving the crop production at field and regional scales. In this study, the parameterized AquaCrop model was employed to simulate the four major elements that affect the crop growth process, such as soil water content, canopy cover, biomass, and grain yield, of three irrigated winter wheat cultivars. The field experiments were conducted in four locations with different climatic conditions in the south and southwest of Iran during three consecutive growing seasons of 2016–2017, 2017–2018, and 2018–2019. Results showed that AquaCrop had reliable simulation of soil water content with normalized root mean squared error (NRMSE) and Nash–Sutcliffe coefficient (CNS) ranging from 0.05 to 0.15 and 0.69 to 0.85, respectively, for the four study locations. The NRMSE and CNS ranged from 0.10 to 0.21 and 0.83 to 0.97 for canopy cover, respectively. The NRMSE and CNS values were 0.11–0.26 and 0.80–0.97 for biomass, respectively. These results indicate that the parameterized AquaCrop model has high skill in the simulation of soil water content, canopy cover, biomass, and grain yield of different winter wheat cultivars in the vast regions in the southern part of Iran. The model was then used to simulate wheat grain yield and irrigation water productivity (WP) for 324 scenarios, including nine sowing dates, three irrigation levels, and three climatic conditions. AquaCrop showed that it was skillful to simulate grain yield and WP of different irrigated winter wheat cultivars in different regional climatic conditions, deficit irrigation levels, and sowing dates. Overall, the AquaCrop model could be used as a reliable decision-making tool for the field managers and stakeholders.