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Climate change impact of relative humidity on water resources in Marathwada region Jalna District, Maharashtra, India

Authors:

¹P. A. Mewade, ²Dr.G. K. Patil

¹Civil Engineering Department, Government College of Engineering Aurangabad, Chh. Sambhajinagar

²Associate Professor, Civil Engineering Department, Government College of Engineering Aurangabad,

Chh. Sambhajinagar, INDIA

Abstract: Climate change like relative humidity can cause various negative impacts on water resources system, ecosystem, etc. To deal with these effects, it is necessary to study the climate change. There are various ways to study climate change in which one of the ways is the study of downscaling. Downscaling is the procedure in which prediction of information is done for local scale area from the available information of a large-scale area. In the downscaling of climatic variables, General Circulation Model (GCM) plays an important role. GCM gives larger scale climatic variables. With the help of this downscaling, we can predict different climatic variables such as temperature, for future time period over the selected area. To perform this downscaling there are different ways, we can classify it as statistical downscaling and dynamical downscaling. In statistical downscaling, we can find relation between predictand and predictors and this statistical relation we use for the future prediction of the selected climatic variable. In dynamical downscaling, we use Regional Climatic Model (RCM), and with the help of this, we carry out downscaling procedure. In this study, statistical downscaling has studied for temperature parameter such as relative humidity by considering the basic equation given by Wilby in (Inter-research). The study area selected for this research is jalna district Maharashtra State, India (Latitude: 19° .8347r, Longitude: 75° .8816r). In this study, in the first step, statistical downscaling has been done with the help of statistical downscaling model (SDSM) software by using HadCM3 GCM with A2a and B2a scenarios for temperature parameter for the future time period up to 2099. In second step, the Statistical downscaling performed by using basic equation given by Wilby Temperature values predicted up to 2099. These results are considered with three different series such as 2020s, 2050s, and 2080s. Downscaled results of temperature parameter by “SDSM” model were compared for future series. After study of these results, it is concluded that SDSM gives higher value of temperature changes in jalna district marathwada region.

Key Words:  Climate change Impact, possible future series, SDSM, HadCM3, A2a, B2a, relative humidity