Impact of climate change on hydrology of Manjalar sub basin of river Vaigai in Tamil Nadu, India
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Abstract
This study evaluates the impacts of possible future climate change scenarios on the hydrology of the catchment area of the Manjalar sub basin of River Vaigai, Tamil Nadu, India carried out at the department of Soil and Water Conservation Engineering, Tamil Nadu Agricultural University during the period of 2011-2014 using Soil
and Water Assessment Tool (SWAT). For the climate impact assessment the hydrological model was driven with output of bias corrected Earth System Models of the Coupled Model Intercomparison Project Phase 5 (CMIP5): HadGEM2. Climate scenarios were downscaled to a grid resolution of 0.22° x 0.22°. In this study RCP 4.5 and RCP 8.5 were included for future assessment with three future periods: 2012–2039, 2040–2069, and 2070–2098. The projected increase in maximum and minimum temperature for RCP 4.5 scenario is 0.8 to 2.3 ºC and 0.7 to 1.6 ºC and for RCP 8.5 scenario is 1.1 to 4.0 ºC and 1.0 to 3.1 ºC, respectively. Rainfall is projected to an increase between 9.2 to 15.2 per cent for RCP 4.5 scenario and an increase of 13.6 to 18.8 per cent for RCP 8.5 scenario during 21st century. The soil water storage and stream flow contribution to ground water are likely to increase in RCP 4.5 scenario and it would again decline for RCP 8.5 scenario during 21st century. The increase in annual rainfall evapotranspiration and surface runoff would be more in RCP 8.5 scenario compared to RCP 4.5 scenario. The possible changes projected by the study provide a useful input to effective planning of water resources of the study area.
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Climate change impacts, Hydrologic model, RCP 4.5 and RCP 8.5 scenario, Surface runoff
Arnell, N and Lloyd-Hughes B. (2014). The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios. Climate Change 122 :127–40.
Arnold,J.G., Srinivasan, R., Muttiah ,R.S. and. Williams, J. R. (1998). Large area hydrologic modeling and assessment Part I: Model development. Journal of the American Water Resources Association, 34(1): 73-89.
Dibike, Y.B. and Coulibaly P. (2005). Hydrologic impact of climate change in the Saguenay watershed: comparison of downscaling methods and hydrologic models. Journal of Hydrology 307(1–4): 145–163.
Fengge Su, Xiaolan Duan, Deliang Chen, Zhenchun Hao and Lan Cuo. (2013). Evaluation of the Global Climate Models in the CMIP5 over the Tibetan Plateau. Journal of Climate, 26: 3187-3208.
Gerten D, Lucht W, Ostberg S, Heinke J, Kowarsch M, Kreft H, Wkundzewicz Z, Rastgooy J, Warren R and Schellnhuber H J. (2013). Asynchronous exposure to global warming: freshwater resources and terrestrial ecosystems. Environmental Research Letter 8 :034032.
Gosain, A. K., Sandhya Rao and Anamika Arora. (2011). Climate change impact assessment of water resources of India. Current Science 101(3): 356-371.
Gosling S and Arnell N (2013). A global assessment of the impact of climate change on water scarcity. Climate Change: 1–15
Hirabayashi Y, Mahendran R, Koirala S, Konoshima L, Yamazaki D, Watanabe S, Kim H and Kanae S. (2013).Global flood risk under climate change. Nature Climate Change 3: 816–21.
IPCC (2014) Climate Change: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge: Cambridge University Press)
IPCC. (2000). Emission scenarios. In: A special report of IPCC Working Group III, Cambridge University Press, Cambridge, UK.
Karl, T.R., Wang, W.C., Schlesinger, M.E., Knight, R.W. and Portman, D.(1990). A method of relating general circulation model simulated climate to observed local climate. Part I: Seasonal statistics. Journal of Climate. 3, 1053-1079.
Kumar, C. P. (2012). Climate Change and Its Impact on Groundwater Resources. International Journal of Engineering and Science Vol. 1, Issue 5, PP 43-60.
Lampert, R. J., Groves, D. G, Popper S. W and Bankes. S. C. (2006). A general, analytic method for generating robust strategies and narrative scenarios. Management Science, 52(4) : 514-528
Liu, H. (2011). Impact of climate change on groundwater recharge in dry areas: An ecohydrology approach. Journal of Hydrology, 407(1-4): 175-183.
Martin Jung, Markus Reichstein, Philippe Ciais and Sonia I. (2010). Seneviratne Recent decline in the global land evapotranspiration trend due to limited moisture supply. Nature (467): 951-954.
Moriasi, D. N, Arnold, J. G, Van Liew, M. W, Bingner, R. L, Harmel R. D. and Veith T. L..(2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the American Society of Agricultural Engineer 50(3): 885?900.
Moss, R. H., Edmonds J. A and Hibbard K. A. (2010). The next generation of scenarios for climate change research and assessment. Nature, 463: 747-756.
Rajiv Kumar,C., Joshi, J, Jayaraman M, Bala G and Ravindranath. N. H. (2012). Multi-model climate change projections for India under representative concentration Pathways. Current. Science.103: 791-802.
Rupakumar, K.,. Sahai, A. K, Krishna Kumar, K., Patwardhan, S. K., Mishra, P. K., Revadekar, J. V., Kamala K. and G. B. Pant. (2006). High-resolution climate change scenarios for India for the 21st century. Current Science, 90: 334-345.
Rupakumar, K., K. Kumar, V. Prasanna, K. Kamala, N. R. Desphnade, S. K. Patwardhan and G.B. Pant. (2003). Future climate scenario. In: Climate Change and Indian Vulnerability Assessment and Adaptation. Universities Press (India) Pvt. Ltd, Hyderabad. 462pp.
Santhi, C., J. G. Arnold, J. R. Williams, W. A. Dugas, R. Srinivasan and L. M. Hauck. (2001). Validation of the SWAT model on a large river basin with point and nonpoint sources. J. American Water Resources Association, 37(5): 1169-1188.
Saxton, K. E. and W. J. Rawls. (2006). Soil water characteristic estimates by Texture and organic matter for hydrologic solutions. Soil Science Society of America Journal, 70: 1569–1578.
Stoll, S., H. J. H. Franssen, R. Barthel and W. Kinzelbach. (2011). What can we learn from long-term groundwater data to improve climate change impact studies. Hydrology and Earth System Sciences, 15(12): 3861-3875.
Stott, P. A., N. P. Gillett, G. C. Hegerl, D. J. Karoly, D. A. Stone, X. Zhang and F. Zwiers. (2010). Detection and attribution of climate change: a regional perspective. Wiley Interdisciplinary Reviews-Climate Change, 1(2): 192-211.
Taylor, R. G., B. Scanlon, P. Döll, M. Rodell, R. van Beek, Y. Wada, L. Longuevergne, M. Leblanc, J. S. Famiglietti, M. Edmunds, L. Konikow, T. R. Green, J. Chen, M. Taniguchi, M. F. P. Bierkens, A. MacDonald, Y. Fan, R. M. Maxwell, Y. Yechieli, J. J. Gurdak, D. M. Allen, M. Shamsudduha, K. Hiscock, P. J. F. Yeh, I. Holman and H. Treidel. (2013). Ground water and climate change. Nature Climate Change, 3(4): 322-329.
Tripathi, S., Srinivas, V.V., and Nanjundiah, R. S. (2006). Downscaling of precipitation for climate change scenarios: A support vector machine approach. Journal of Hydrology. 330, 621-640.
USGS. (2014). Why Is This House Wearing Stilts?. Retrieved from Impervious Surfaces and Urban Flooding: USGS Water-Science School: http://water.usgs.gov/edu/impervious.html
Van Liew, M. W and J. Garbrecht. 2003. Hydrologic simulation of the Little Washita River experimental watershed using SWAT. Journal of American Water Resource. Association 39(2): 413-426.
Van Vuuren DP, Stehfest E, Den Elzen MGJ, Deetman S, Hof A, Isaac M, Klein Goldewijk K, Kram T, Mendoza Beltran A, Oostenrijk R .(2011a). RCP2.6: Exploring the possibility to keep global mean temperature change below 2°C. Climatic Change. doi: 10.1007/s10584-011-0152-3
Xu ZX, Zhao FF, Li JY. (2009). Response of streamflow to climate change in the headwater catchment of the Yellow River basin. Quaternary International 208: 62–75.
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