Investigating the role of downscaling and reference evapotranspiration estimation method in analysis of the impact of climate change on water resources

Document Type : Research Paper

Authors

Department of Water Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

Abstract

Climate change could largely affect the surface water and groundwater sources. This impact should be simulated using appropriate models. In the present study, using LARS-WG and SDSM statistical models, the output of HADCM3 general circulation model under four emission scenarios was downscaled in the Hablehroud Basin in the period of 2018-2047. The SWAT model was calibrated in the basin and utilized to simulate the discharge, groundwater recharge, and soil water content in the mentioned period. Three different methods including Hargreaves, Penman-Monteith and Priestley-Taylor in the SWAT model were used to estimate reference evapotranspiration. Different combinations of the factors effecting the uncertainty, including downscaling model, emission scenario, and evapotranspiration estimation method were used. The results showed that the method used in downscaling the output of the general circulation model is the most effective factor affecting the uncertainty of the output of the SWAT model. It was also observed that the different combinations produce more outliers in simulating groundwater recharge, in comparison with simulating the discharge and soil water content. The median of the annual discharges simulated using all combinations was calculated to be 13.32 cms. The results showed that the combinations of downscaling model, emission scenario, and evapotranspiration estimation method that simulate values less than 13.32 cms have less uncertainty than other combinations. In the case of groundwater recharge (with a median of 2.07 mm/ year) and soil water content (with a median of 112.4), same results were observed.

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Abbaspour, K. C., Faramarzi, M., Ghasemi, S. S. and Yang, H. (2009). Assessing the impact of climate change on water resources in Iran. Water Resources Research. 1-16, 45.
Abbaspour, K. C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., Zobrist, J. and Srinivasan, R. (2007). Modelling hydrology and water qualityin the pre-Alpine/Alpine Thur watershed using SWAT. Journal of Hydrology. 413-430, 333.
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. 73-89, 34(a1).
Bae, D. H., Jung, I. W. and Lettenmaier, D. (2011). Hydrologic uncertainties in climate change from IPCC AR4 GCM simulations of the Chungju Basin, Korea. Journal of Hydrology. 90-105, 401.
Bastola, S., Murphy, C. and Sweeney, J. (2011). The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments. Water Resources Research. 562-576, 34.
Bosshard, T., Carambia, M., Goergen, K., Kotlarski, S., Krahe, P., Zappa, M. and Schar, C. (2013). Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections. Water Resources Research. 1523-1536, 49.
Devkota, L. P. and Gyawali, D. R. (2015). Impacts of climate change on hydrological regime and water resources management of the Koshi River Basin, Nepal. Journal of Hydrology. 502-515, 4.
Faramarzi, M., Abbaspour, K. C., Schulin, R. and Yang, H. (2009). Modeling blue and green water availability in Iran. Hydrological Processes. 486-501, 23(3).
Faramarzi, M., Abbaspour, K. C., Vaghefi, S. A., Farzaneh, M. R., Zehnder, A. J. B. and Yang, H. (2013). Modelling impacts of climate change on freshwater availability in Africa. Journal of Hydrology. 1-14, 250.
IPCC. (2013). Summary for policymakers. In T. F. Stocker, D. Qin, G. K. Plattner, M. Tignor, S. K. Allen and J. Boschung (Eds.), Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.
Mahmood, R. and Babel M. S. (2014). Future changes in extreme temperature events using the statistical downscaling model (SDSM) in the trans-boundary region of the Jhelum river basin. Weather and Climate Extremes. 56-66, 5-6.
Najafi, M. R., Moradkhani, H. and Wherry, S. A. (2011). Statistical downscaling of precipitation using machine learning with optimal predictor selection. Journal of Hydrologic Engineering. 650-664, 16(8).
Palazzoli, I., Maskey, S., Uhlenbrook, S., Nana, E. and Bocchiola, D. (2015). Impact of prospective climate change on water resources and crop yields in the Indrawati basin, Nepal. Agricultural Systems. 143-157, 133.       
Rostamian, R., Jaleh, A., Afyuni, M., Mousavi, S. F., Heidarpour, M., Jalalian, A. and Abbaspour, K. C. (2008). Application of a SWAT model for estimating runoff and sediment in two mountainous basins in central Iran. Hydrological Sciences Journal. 977-988, 53(5).
Xu, X., Wang, Y. C., Kalcic, M., Muenich, R. L., Yang, Y. C. E. and Scavia, D. (2017). Evaluating the impact of climate change on fluvial flood risk in a mixed-used watershed. Environmental Modelling & Software. In Press.
Yang, J., Reichert, P., Abbaspour, K. C., Xia, J. and Yang, H. (2008). Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China. Journal of Hydrology. 1-23, 358.