Climate change impacts on the maximum daily discharge under conditions of uncertainty (Dinavar basin in Kermanshah)

Document Type : Complete scientific research article

Authors

Abstract

Background and Objectives: The phenomenon of climate change and its impact on water resources is of utmost importance that has been less investigated in our country.In this study, The meteorological variables in terms of predicted climate change and were compared with the present situation. The effect of this phenomenon on Dinavar Kermanshah discharge basin taking into account the uncertainty was evaluated.
Materials and Methods: To this end, results of 6 model coupled atmosphere - ocean general circulation of the atmosphere contains MPEH5, IPCM4, INCM3, HADCM3, GFCM21 and NCCCSM under scenarios of greenhouse gas emissions SRESS includes A1B, A2 and B1 were Downscaling using the LARS-WG software. To determine the accuracy of the models and scenarios, temperature and precipitation observational data were compared with temperature and precipitation available data on Canada base models and scenarios and weighted method was used to evaluate uncertainty models and scenarios. Then, base of scenario and models uncertainty, was predicted variables in coming period (2011-2034) and (2046-2069) compared with the base period (1987-2010). After the downscaling of climate variables, IHACRES rainfall-runoff models used to simulate runoff in future periods.
Results: Based on the results, it's expected that temperature will be increased respectively 1.72 ,1.55 and 1.39 ° C in 2011-2034 and 3.27, 2.88 and 2.26 ° C in 2046-2069, for A1B, A2 and B1 scenarios compared to the baseline in Dinavar basin. As well as precipitation changes respectively has been 15.22, 17.94 and 23.27 mm for A1B, A2 and B1 scenarios in 2011-2034, and -35.4, 7.97 and 2.58 mm for A1B, A2 and B1 scenarios in 2046-2069 compared to the baseline in this basin. The results showed that the amount of average flow and runoff volume has been increased in future periods except A1B scenario (2046-2069). But, flow regime of maximum daily discharges showed that it is adjust in future period. Flow - Frequency curve analysis with different probability showed that it is required to build large reservoirs to water supply in low flow seasons in future periods.
Conclusion: The results showed that the amount of average temperature and precipitation will be increased in future periods. So that the increase of temperature in the second period is more than the first period and increase of precipitation in the first period will be more than the second period. Also the amount of discharges in future period will be increased so that the increase in the first period will be more than the second period, and the volume of runoff in the first period will be more than the second period and in both periods were higher than the base period. But flow regime of maximum daily discharges showed the decreasing in future period, So that the maximum discharge rate decrease in the second period is more than the first period. Flow - Frequency curve analysis also showed that in the absence ofwater storage, agriculture andindustry and drinkingin the area faced withsupply problems.

Keywords


 1.Ashofteh, P. 2012. Climate change Impact on the crop water requirement using HadCM3
model in Aidoghmoush irrigation network. Iran. J. Irrig. Drain. 6: 3. 142-151. (In Persian)
2.Ashraf, B., Mousavi-Baygi, M., Kamali, G.A., and Davari, K. 2012. Evaluation of wheat and
Sugar beet water use Variation due to climate change effects in two Coming Decades in the
selected plains of Khorasan Razavi Province. Iran. J. Irrig. Drain. 6: 2. 105-117. (In Persian)
3.Booij, M.J., Tollenaar, D., van Beek, E., and Kwadijk, J.C. 2011. Simulating impacts of
climate change on river discharges in the Nile basin. Physics and Chemistry of the Earth,
Parts A/B/C. 36: 13. 696-709.
4.Carcano, E.C., Bartolini, P., Muselli, M., and Piroddi, L. 2008. Jordan recurrent neural
network versus IHACRES in modelling daily streamflows. J. Hydrol. 362: 3. 291-307.
5.COP21. 2015. UN climate change conference | Paris, http://www.cop21paris.org/about/cop21.
6.Dobler, C., Hagemann, S., Wilby, R.L., and Stötter, J. 2012. Quantifying different sources of
uncertainty in hydrological projections in an Alpine watershed. Hydrology and Earth System
Sciences. 16: 11. 4343-4360.
7.Ehteramian, K., Shahabfar, A., and Alizadeh, A. 2004. Evaluation ofthe ENSO phenomenonon
the precipitation regime in Khorasan province. J. Geograph. Reg. Dev. 3: 29-42.
8.Eslamian, S., Nosrati, K., and Shahbazi, A. 2004. Climate change impacts on the hydrological
drought. J. Agric. Tehran Univ. 6: 1. 49-56. (In Persian)
9.IPCC. 2014. Climate Change 2014: Impacts, Adaptation and Vulnerability. Contribution of
Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate
Change. Yokohama, Japan.
10.IPCC. 2007. Synthesis Report of the Forth Assessment Report. Cambridge University Press,
Cambridge.
11.Kabiri, R., Kanani, V., and Andrew, C. 2012. Climate Change Impacts on River Runoff in
Klang Watershed in West malasia. J. Clim. Res. 48: 57-71.
12.Kunreuther, H., Heal, G., Allen, M., Edenhofer, O., Field, C., and Yohe, G. 2013. Risk
management and climate change. Nature Climate Change. 3: 447-450.
13.Lee, H. 2015. The Climate System and Climate Change; Climate Change Biology. Chapter
2. (Second Edition), Pp: 13-53.
14.Nash, J.E., and Sutcliffe, J.V. 1970. River flow forecasting through conceptual models part IA discussion of principles. J. Hydrol. 10: 3. 282-290.
15.Phillips, J. 2010. Evaluating the level and nature of sustainable development for a
geothermal power plant. Renewable and sustainable energy reviews. 14: 8. 2414-2425.
16.Souvignet, M., Gaese, H., Ribbe, L., Kretschmer, N., and Oyarzun, R. 2008. Climate change
impacts on water availability in the Arid Elqui Valley, North Central Chile: a preliminary
assessment. In IWRA World Water Congress, Montpellier, France.
17.Teng, J., Vaze, J., Chiew, F.H., Wang, B., and Perraud, J.M. 2012. Estimating the relative
uncertainties sourced from GCMs and hydrological models in modeling climate change
impact on runoff. J. Hydrometeorol. 13: 1. 122-139.
18.Vaseghi, R., Massah, A.R., Meshkati, A.H., and Rahimzadeh, F. 2011. Investigation of
runoff impact of Ensembles scenarios AOGCM models, 4th Conference of Water Resources
Management of Iran, Tehran, Iran, Pp: 23-35. (In Persian)
19.Vaze, J., Post, D.A., Chiew, F.H.S., Perraud, J.M., Viney, N.R., and Teng, J. 2010. Climate
non-stationarity-validity of calibrated rainfall–runoff models for use in climate change
studies. J. Hydrol. 394: 3. 447-457.
20.Velazquez, D., Garrote, L., Andreu, J., Martin-Carrasco, F.J., and Iglesias, A. 2011. A
methodology to diagnose the effect of climate change and to identify adaptive strategies to
reduce its impacts in conjunctive-use systems at basin scale. J. Hydrol. 405: 1. 110-122.
21.Zhu, Q., Jiang, H., Peng, C., Liu, J., Fang, X., Wei, X., Liu, S., and Zhou, G. 2012. Effects of
future climate change, CO2 enrichment and vegetation structure variation on hydrological
processes in China. Global and Planetary Change. 80: 123-135.