جستجوی مقالات مرتبط با کلیدواژه « climate variability » در نشریات گروه « آب و خاک »

Global warming has changed rainfall patterns and reduced snow sources. The main objective of this research was to investigate the impact of temperature increase on snowmelt and river runoff in hot months of the year along with analysis of climate variables in Tamar basin, Iran. For this purpose, the snow cover area was extracted from the daily images of Modis Satellite, based on elevation. Then, the study area was divided into four districts. Discharge flow measured data of Tamar hydrometric station, precipitation of Qarnaq and average temperature of Gidagh stations were used from 2013 to 2016 for calibration and from 2017 to 2019 for verification, to simulate snowmelt runoff. Snow cover extent, in calibration stage and january, reached the highest values of 28% and 28.8% in the third and fourth districts, respectively. Furthermore, in the verification stage, the third and fourth districts in February had the highest percentages of 45.8 and 30.2, respectively. Comparison of simulated and measured runoff data revealed that the portion of runoff due to snowmelt is significant by passing from February to April. So that the highest increase (from 1.8% to 39.1%) in runoff amount was corresponded to the water year of 2018-2019. The highest and the lowest percentages of snowmelt in water years of 2014-2015 and 2017-2018 were 19 and 3.3 percent, respectively. The results of sensitivity analysis of model parameters including temperature decrease rate, critical temperature, delay time, degree-day factor, X and Y coefficients, precipitation runoff coefficient and snow runoff coefficient showed that the rainfall coefficient and X parameters are the most effective parameters. The effect of temperature and rainfall on runoff process was varied in different months.

Climate change is crucially important in Iran given its arid and semiarid climate. It influences water resources, thereby affecting many activities and even threatening human life seriously. The assessment of the extent to which climate change can influence water use and resources can play a decisive role in macro-policymaking. Present study uses positive mathematical programming (PMP) in the context of four climatic scenarios (normal climate change, climate change, climate variability, and concurrent climate change) to explore impacts of these changes on agricultural water use and water resources of Iran in a 20-year period. The results showed that in the context of concurrent climate change and also climate change, in spite of the decrease in water use by the agricultural sector, water resources of Iran are reduced with much higher rate than that under other climatic conditions. According to results, average annual agricultural water use under four studied scenarios will be 35,103.65, 26,533.8, 35,216 and 26,510.69 million m3, and average rate of annual loss of water resources will be 4,422.2, 11,165.6, 4,438.24, and 11,267.45 million m3, respectively. Accordingly, changes should be applied in approach to water demand and supply management. Also, policies should be adopted to cope with climate change.