Simulation of wheat water footprint using AquaCrop model under the climate change, case study in Qazvin plain

• Published in: Applied water science 2024-12, Vol.14 (12), p.264-18, Article 264
• Main Authors: Ahmadi, Mojgan, Etedali, Hadi Ramezani, Salem, Ali, Al-Mukhtar, Mustafa, Elbeltagi, Ahmed
• Format: Article
• Language: English
• Subjects: AquaCrop; Aquatic Pollution; Climate change; Climatic data; Comparative Law; Crop yield; Decision making; Earth and Environmental Science; Earth Sciences; Evapotranspiration; Food consumption; Food security; Footprint analysis; General circulation models; Hydrogeology; Industrial and Production Engineering; International & Foreign Law; Nanotechnology; Original Article; Private International Law; Spatial data; Sustainability; Sustainable development; Waste Water Technology; Water consumption; Water footprint; Water Industry/Water Technologies; Water Management; Water Pollution Control; Water use; Wheat; Winter wheat
• ISSN: 2190-5487; 2190-5495
• DOI: 10.1007/s13201-024-02305-0

Simulating crop water consumption has been introduced as a valuable decision tool in food security. Such a tool is typically used to support a better understanding of how to increase water-use efficiency to satisfy optimal water management and sustainability. However, climate change is one of the most important and influential factors that restrain sustainable development, agriculture, and food security. Wheat is one of the most important and strategic products in the world and Iran. Therefore, in this study, the impacts of future climate changes on winter wheat yield, water requirement (WR), evapotranspiration (ET), and water footprint (WF) were evaluated in Qazvin Plain, Iran. As such, the outputs from five general circulation models (EC-EARTH, GFDL-CM3, MPI-ESM-MR, MIROC5, and HADGEM2-ES) were fed into the LARS-WG model to get finer spatial climate data for four future periods (P1:2021–2040, P2:2041–2060, P3:2061–2080, P4:2081–2100) considering three emission scenarios (RCP2.6, RCP4.5, and RCP8.5). Thereafter, the projected climate change data were used in the FAO AquaCrop model to simulate the variability of wheat characteristics. The results proved the superiority of LARS-WG to model the maximum and minimum temperatures and precipitation (P) of the baseline scenario (1986–2015). Moreover, results revealed that the wheat WF will decrease in future periods. The modeling results showed that the average wheat yield and biomass will increase in future periods by 7.67 and 15.98 tons/ha, respectively, as compared to the baseline. The highest increase was recorded by the HadGEM2-ES model with RCP8.5 during 2081–2100. The average WR in the baseline was 127.14 mm, which was projected to decrease in future periods. The results show that ET will potentially increase in the period 2021–2040. As a consequence, the adapted methodology produced significantly superior outcomes and can aid in decision-making for both water managers and development planners.