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CLIMATE CHANGE IMPACT OF RELATIVE HUMIDITY ON WATER RESOURCES IN MARATHWADA REGION JALNA DISTRICT,MAHARASHTRA, INDIA

AUTHORS:
P. A. Mewade
Mentor
Dr.G. K. Patil
Affiliation
Civil Engineering Department, Government College of Engineering Aurangabad, Chh. Sambhajinagar
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.
Keywords
Climate change Impact possible future series SDSM HadCM3 A2a B2a relative humidity
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Mewade, P. A. (2026). Climate Change Impact of Relative Humidity on Water Resources in Marathwada Region Jalna District,Maharashtra, India. International Journal of Science, Strategic Management and Technology, Volume 10(01). https://doi.org/10.55041/ijsmt.v2i2.128

Mewade, P.. "Climate Change Impact of Relative Humidity on Water Resources in Marathwada Region Jalna District,Maharashtra, India." International Journal of Science, Strategic Management and Technology, vol. Volume 10, no. 01, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i2.128.

Mewade, P.. "Climate Change Impact of Relative Humidity on Water Resources in Marathwada Region Jalna District,Maharashtra, India." International Journal of Science, Strategic Management and Technology Volume 10, no. 01 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i2.128.

References
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[2]Chu,J.,Xia,J.,Xu,C.Y.,Singh,V.,2010.Statistical downscaling of daily mean temperature ,pan evaporation and precipitation for climate change scenarios in Haihe River, China. Theory .Application Climatol. 99(1),149–161. http://dx.doi.org/ 10.1007/s00704-009-0129-6

[3] Goyal, M.K., Ojha, C.S.P. and Burn, D.H. (2012) Nonparametric Statistical Downscaling of Temperature, Precipitation and Evaporation in Semiarid Region in India. Journal of Hydrologic Engineering ASCE, 17, 615-627

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[6] Wilby RL, Dawson CW, Barrow EM (2002) SDSM—a decision support tool for the assessment of regional climate change impacts. Environ Model Software 17:147–159

[7]Castillo, J. E.; Weibel, J. A.; and Garimella, S V., "The Effect of Relative Humidity on Dropwise Condensation Dynamics" (2015). CTRC Research Publications. Paper 244. http://dx.doi.org/http://dx.doi.org/10.1016/j.ijheatmasstransfer.2014.09.080.

[8] Michael Geruso and Dean Spears NBER Working Paper No. 24870 July 2018 JEL No. H23, I1, J1, O1, Q5, Q54, Q56.

[9] Nikolaos Nikolaou, Laurens M. Bouwer, Marco Dallavalle, Mahyar Valizadeh, Massimo Stogie, Annette Peters, Kathrin Wolf, and Alexandra Schneide Effects of cold weather on mortality: results from15 European cities within the PHEWE project. Am. J. Epidemiol. 168 (12), 1397–140https://doi.org/10.1093/aje/kwn266.

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