Estimation of Crop Irrigation Water Demand Using Climatic Data and Cropwat Model

Abstract
Objective: The agricultural sector is recognized as the largest consumer of water resources worldwide. Therefore, accurate estimation of water consumption plays a crucial role in long-term planning and policy-making. In the present study, the Cropwat model was employed to estimate the irrigation water demand of various agricultural crops in the Marun River Basin, located in Khuzestan Province, Iran, under a Representative Concentration Pathway (RCP) scenario for the future period of 2016–2040.
Method: To this end, the impacts of climate change on key climatic variables, namely temperature and precipitation, were first assessed using the GFDL-CM3 and MIROC5 climate models, respectively.
Results: The results indicate that, compared to the baseline period (1977–2001), temperature is projected to increase by 19%, while precipitation is expected to decrease by 5%. Furthermore, the Cropwat model results reveal that the total irrigation water demand for agricultural crops under the RCP 2.6 scenario will increase by approximately 39% relative to the baseline period.
Conclusion: Among all crops, forage crops and oilseeds exhibit the highest and lowest increases in water demand, with increases of 47% and 17%, respectively, compared to the baseline period.
 
 
 
English Extended Abstract
Introduction
The agricultural sector is recognized as the largest consumer of freshwater resources worldwide, accounting for a significant proportion of total water withdrawals. Consequently, accurate estimation of agricultural water consumption is of critical importance for effective water resources management and the development of long-term planning and policy-making strategies.
This issue becomes even more crucial under the impacts of climate change, which is expected to alter key climatic variables such as temperature and precipitation patterns, thereby affecting crop water requirements and irrigation demands. In arid and semi-arid regions, such as southwestern Iran, climate change may exacerbate existing water scarcity challenges and intensify pressure on limited water resources.
Therefore, assessing future agricultural water demand under climate change scenarios is essential to ensure sustainable water use, food security, and resilience of agricultural systems. The main objective of this study is to evaluate the future irrigation water requirements of major crops in the Marun Basin under climate change conditions using a reliable crop water demand model.
 
Method
In the present study, the Cropwat model has been used to estimate the irrigation water demand of various crops in the Marun basin, which is located in Khuzestan province, under the 2.6 Representative Concentration Pathway (RCP) scenario in the future time interval (2016-2040).
The Cropwat model developed by the Food and Agriculture Organization of the United Nations was used to estimate the irrigation water requirements of the crops in the Marun Basin. The inputs of this model include climate data and information on each agricultural crop.
First, different climate models were evaluated under the International Panel on Climate Change (IPCC) Fifth Assessment Report. The results showed that based on the error criteria, the two climate models, GFDL-CM3 and MIROC5 were proper for simulating the temperature and precipitation variables in the future time interval, respectively. In the next step, the Cropwat model has been used to estimate agricultural water irrigation demand.
In the present study, for the first time, the trends in changes in reference plant evapotranspiration, effective rainfall, irrigation water requirements for the crops, and agricultural water demand for each agricultural crop in the Marun basin were calculated using the Cropwat model under the RCP 2.6 climate scenario in the time interval (2016-2040). Final water demand for crops will increase in the future compared to the baseline.
Agricultural water demand for vegetables, forage crops, grain maize, oilseeds, wheat, barley, and pulses will increase by 38%, 47%, 33%, 17%, 19%, 20%, and 33%, respectively, under the RCP 2.6 scenario compared to the baseline interval. Overall, for all crops, agricultural water demand will be increased by 39% in the future time interval compared to the baseline period under the 2.6 RCP scenario.
 
Results
The results show that the climatic variable of temperature will increase by 19% and the rainfall variable will decrease by 5% compared to the baseline time interval (1977-2001). The Cropwat model showed the total long-term average monthly ET₀ will increase by 30% under the RCP 2.6 scenario compared to the baseline period and the effective precipitation in the future time interval will be increased by 7% compared to the base period under the 2.6 RCP scenario.
Among all agricultural crops, forage crops by 47% increase and oilseeds by 17% increasing compared to the baseline time interval have the largest and lowest increase in water demand compared to other agricultural crops, respectively.
 
Conclusion
The results of the present study provide important information to planners and policymakers of water and food resources so that, by identifying water-intensive agricultural products in the Marun basin in the future years under climate change impact, present sustainable strategies such as changing the cultivation pattern based on water and food security and prevent more severe stresses in the Marun River basin.