نوع مقاله : مقالات پژوهشی
نویسندگان
گروه علوم و مهندسی آّب، دانشکده کشاورزی و منابع طبیعی، دانشگاه بینالمللی امام خمینی)ره(، قزوین، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Introduction
Climate change is one of the most important issues in the world in the 21st century which affects various sectors of agriculture, forestry, water and financial markets, and has serious economic consequences (Reidsma et al., 2009). In recent years, the management of agricultural water consumption has always been considered as one of the important issues in water resources management. Koochaki and colleagues (Koochaki and Kamali, 2006) by evaluating the climatic indicators of Iran's agriculture showed that during the next 20 years, the average monthly temperature will increase in almost all regions of the country, and the increase in evaporation and transpiration is one of the most important consequences of this warming. Simulated climate parameters can be obtained through different general GCM atmospheric models. Due to the low spatial resolution of these models, its output should be downscaled using dynamic or statistical methods.
Materials and Methods
The LARS-WG model predicts meteorological variables for a period of time in the future by using a series of basic and fine-scale meteorological data, output of one of the GCM models. Research has shown that the LARS-WG model has the necessary accuracy for this task. Calculating the amount of evapotranspiration and yield of very complex plants are time-consuming and dependent on spending a lot of money and limited to the tests performed, the shortness of the test time and also the limitation in the number of scenarios that are checked by the test. Therefore, plant models are considered and evaluated by researchers. The AquaCrop model has demonstrated commendable accuracy in various regions of Iran and globally for forecasting plant growth, water consumption efficiency, and evapotranspiration requirements. These predictions hold significant potential for optimizing irrigation strategies across different agricultural settings. AquaCrop is one of the applied agricultural models that was obtained from the modification and revision of FAO publication No. 33 by prominent experts from all over the world. In this study, the values of green water footprint of winter wheat plant (Pishgam) were estimated in climatic conditions obtained from LARS-WG model and DKRZ database under scenarios 4.5 and 8.5 and at different planting dates (15 October, 1 November, 15 November, 30 November and 15 December), in the next 4 periods (2021-2040, 2041-2060, 2061-2080 and 2081-2100) and by Aquacrop model.
Results and Discussion
The results showed that if planting date is on October 15, in the climatic conditions obtained from the LARS-WG model and under scenarios 4.5 and 8.5, in all future periods, the footprint of green water will increase compared to its value in the base period, and if planting is the rest of the dates, in each of the next 4 periods, the average green water footprint will decrease compared to its value in the base period. The results obtained for the DKRZ database show that the green water footprint attained for the dates of cultivation and periods investigated in scenarios 4.5 and 8.5 does not have a particular trend. On the planting dates of October 15 and November 1 for the periods of 2061-2080 and 2081-2100, the green water footprint will decrease and on the other three dates (15 November, 30 November, and 1 November) for these periods, there will be an increasing trend. On 15 December, for the DKRZ database, in both scenarios defined for all periods, an increase in green water footprint compared to the base period is reported. However, in the period of 2081-2100 in scenario 8.5, a decrease compared to the base period will be observed. The highest amount of green water footprint in all these periods and models for the period 2041-2060 under the climatic conditions of the DKRZ database in scenario 4.5, if the planting date is 15 October, it is estimated that the amount of water consumed is equal to 4272 cubic meters per ton with a standard deviation of 5018 cubic meters per ton is predicted. The lowest footprint of green water for the period 2081-2100 under the climatic conditions obtained from the LARS-WG model in scenario 8.5, if the planting date is on 15 December, is reported to be 232 tons per hectare with a standard deviation of 52.3 tons per hectare.
کلیدواژهها [English]
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