Future Climate Conditions and Trend Analysis of Precipitation and Temperature in Bar Watershed, Iran

Abstract

Aims: Climate change is one of the most important challenges for human society, which will affect ecological, social and economical systems. Because of water scarcity issues, studying the potential climate change and its impacts on climate variables and water resources is necessary. The study of climate variables and predict their changes in policy and planning is so vital. Between climatic variables, changes in precipitation and temperature patterns have important influences on the quantity and quality of water resources, especially in arid regions. Therefore, evaluating the trend of their values is one of the most important issues in the hydro climate studies. Place and Duration of Study: Trend of maximum and minimum temperature and precipitation for observation period (1971-2010) and future periods (2010-2039, 2040-2069 and 2070-2099) has been studied by nonparametric Mann-Kendall test in Nayshabour Bar watershed, Iran. Methodology: In this investigation the output of Hadcm3 and CGCM1 models under A1, A2 and B2 scenarios were downscaled by using Statistical downscaling model (SDSM). Then trend of these climate variables by using nonparametric Mann-Kendall test was analyzed. Results: The results of the statistical parameters evaluating showed that the outputs of Hadcm3 model under A2 scenario are more compatible with the study area. The results of Mann-Kendall test showed that during the observation period, the trend of precipitation and minimum temperature was decreasing. On the other hand, the trend of average and maximum temperature was increasing, but the trend of these variables at 95% confidence level was not significant. During the future periods, the trend of precipitation was decreasing, and the trend of average, maximum and minimum temperature was increasing that was not significant at 95% confidence level too. Conclusion: Statistical downscale model is powerful tools for downscale climate variables. Also trend analyses of climate variable can help to mitigation and adaptation global warming issue.