Incorporation of Long Term Climate Changes in Hydrological Modelling
Roshini R1, P. N. Chandramouli2
1Roshini R, is pursuing M. Tech degree in Hydraulics, Department of Civil Engineering, National Institute of Engineering (NIE), Mysore, Karnataka, 570008, India.
2P. N. Chandramouli, is working as Professor in Department of Civil Engineering, National Institute of Engineering (NIE), Mysore, Karnataka, 570008, India.
Manuscript received on 01 August 2019 | Revised Manuscript received on 05 August 2019 | Manuscript published on 30 August 2019 | PP: 4521-4526 | Volume-8 Issue-10, August 2019 | Retrieval Number: I8904078919/19©BEIESP | DOI: 10.35940/ijitee.I8904.0881019
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: One of climate change’s most important concerns at the moment is its impact on hydrology as it has direct links with agriculture, vegetation, and livelihood. This study tries to analyze potential future climate change in the Kumaradhara river basin. This study involved three steps: (1) acquiring and using general circulation model (GCM) to project future global climate scenarios; (2) establishing statistical relationships between GCM data and observed data using Statistical Downscaling Model (SDSM); (3) downscaling the second-generation Canadian Earth system Model (CanESM2)GCM output based on the established statistical relationship. The statistical downscaling is carried out for three scenarios used in the fifth evaluation report of the recent Intergovernmental Panel on Climate Change (IPCC) viz., Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5. The statistical downscaling Model (SDSM) results showed that the mean annual daily precipitation is altered in the basin under all the scenarios but it will be different in different time periods depending on scenarios and the basin will experience the reduced precipitation levels in summer. Also the precipitation will marginally rise in all the time slices with reference to baseline data. We can conclude from the results that this region’s climate will affect future farming as the availability of water is bound to change. This study should, however, be followed up by a larger study incorporating multiple CMIP5 models such that changes in hydrological regimes can be examined appropriately.
Keywords: Climate Change Impacts; General Circulation Model; CanESM2; RCPs; Statistical downscaling; SDSM
Scope of the Article: Building Climate Systems