Hydrologic Response of North Karun Basin to Increase in Minimum Air Temperature

Document Type : Full length article


1 Associate Professor of Climatology, University of Isfahan, Isfahan, Iran

2 PhD Candidate in Climatology, Faculty of Geography, University of Isfahan, Iran


The climate change and global warming is a widespread problem in the world.  Increase in the greenhouse gases is the reason of this climate change (Dettinger et al, 2004, 2). According to IPPC report, average annual temperature of the earth has been raised from 0.3º to 0.6º as a result of spreading the greenhouse gases and this value will increase from 1 to 3.5º by 2100. The main effects of the phenomenon are drought, extreme flood, snowmelting, storms and increasing air temperature in different regions. These phonemes are in the whole world but they are different from each other. Climate change is an important environmental challenge in recent years.
In the north Karun basin,  higher than 2500 m in altitude, is covered mainly by snow. Therefore, the snowmelt water supply plays an important role in Karun River. We will analyze the effects of minimum air temperature on snow cover and discharge changes in Karun River. In this basin, snowfall supply of water is more than precipitation rate to whole basin.  
According to previous studies in different regions in the world, annual rainfall has downward trend but heavy rains have upward trend. Average air temperature, maximum air temperature, minimum air temperature and evaporation have upper ward trend. In addition, flooding has an increasing trend. However, these parameters have caused decrease in water resources.        
The global effects including temperature increase, melting of polarized ice, and global sea level rise are the main results of that the climate changes. Among the negative effects are Non-uniformly distributed rainfall, increase and continuity of the droughts and finally on water resources in all over the world.  
Materials and Methods
North Karun watershed is 2300 km2 in area in south west Iran. This is  one of the important basins in supplying water resources in southwest Iran. The volume water as resources is almost 10billion m3 in North Karun basin.
The hydrologic data were recorded by power ministry and meteorological organization in 1984-2014. These data are including air minimum temperature, ice daily, snow cover and river discharge.
Results and Discussion
In this research for change assessment, simulation and forecasting the minimum temperature, we have used meteorological data from 4 synoptic stations in the North Karun Basin. We have divided research period in the stations into 2 parts: 30 and 25 years. Therefore, the purpose of this research is to evaluate changes of minimum temperature in the past and to forecast it in the future. We have used CMIP5 for future climate change projections over the HNZ under a very-low forcing scenarios (RCP2.6), a medium stabilization scenarios (RCP4.5) and a very high baseline emission scenarios (RCP8.5). CMIP5 data were interpolated to the spatial scale (0.4˚×0.4˚). We have also made a downscaling by MATLAB software (0.2˚ ×0.2˚). In the following, correction model is used in accordance with the equation:



We have also used indexes Bias, RMSE and R for assessment models to apply them for forecasting data in North Karun basin. The models of CMIP5 under, RCP4.5 and RCP8.5 have been utilized in this study. The output CMIP5 and scenarios RCP4.5 and 8.5 is comparedwith CMIP5 and MNA-44_ICHEC-EC, RCP4.5 scenariochoice for simulation and forecasting.
Eventually temperature changes were evaluated.  In addition, we have used to change snow cover of MODIS TERRA and Aqua satellite Image monthly for 2000-2014. An aspect of technical analysis is to predict the future movement of a stock based on past data. Trend analysis is based on the idea that what happened in the past gives an idea of what will happen in the future. A trend can be considered as the general movement over time of a statistically detectable change. The MK test is usually used to assess the trend of a time-series. The purpose of Mann-Kendall (MK) test is to assess if there is a monotonic upward or downward trend of the variables of interest over time. A monotonic upward (downward) trend means that the variable consistently increases (decreases) through time, but the trend may or may not be linear. The MK can be employed instead of a parametric linear regression analysis to test if the slope of the estimated linear regression line is different from zero. The following equation can be used:













The climate change can cause water stress. The increase in air temperature, drought and decrease in water are the signs of climate change in the whole world. The results indicate that there are changes in minimum air temperature, snow cover and discharge in North Karun Basin. The results show that minimum air temperature has upper ward trend at 95% and it is increasing between 0.1Cº to 4.4Cº in particular at cold season (November, December, January, February). In addition, snow cover, ice daily and discharge have decreasing trend. The results of simulator by GCM represent that air temperature trend will perpetuate in this basin at future period. Therefore, the increase in air temperature minimum, decrease in snow cover and discharge can cause water stress in North Karun Basin and Karun River. The results show that increased minimum temperature of air cause decreasing water resources and hydro-electric supply in the feature.    


Main Subjects

بذرافشان، ج.؛ خلیلی، ع.؛ هورفر، ع. ح.؛ ترابی، ص. و حجام، س. (1388). بررسی و مقایسة عملکرد دو مدل (LARS-WG و ClimGen) در شبیه‏سازی فراسنج‏های هواشناسی در شرایط مختلف اقلیمی، تحقیقات منابع آب ایران، 5(1):44ـ57.
خزانه‏داری، ل.؛ کوهی، م.؛ قندهاری، ش. و آسیایی، م. (1387). تغییر اقلیم علل، اثرات، و راه‏حل‏ها، هاردی، جان تی، برگردان، انتشارات پاپلی.
خلیلی، ن.؛ خداشناس، س.‏ر. و داوری، ک. (1385). پیش‏بینی بارش با استفاده از شبکه‏های عصبی مصنوعی، دومین کنفرانس مدیریت منابع آب، دانشگاه صنعتی اصفهان.
جاماب (1388). بازنگری مطالعات جامع آب کشور حوضة کارون، وزارت نیرو.
قربان‏زاده خرازی، ح.؛ صادقی، ح.؛ ثقفیان، ب. و پورهمت، ج. (1388). بررسی اثر تغییر اقلیم بر توزیع زمانی جریان رواناب ناشی از ذوب برف در حوضة کارون، مجلة علوم و مهندسی آبخیزداری، 45ـ50.
ذهبیون، ب.؛ گودرزی، م.ر. و مساح بوانی، ع.‏ر. (1389). کاربرد مدل SWAT در تخمین رواناب حوضه در دوره‏های آتی تحت تأثیر تغییر اقلیم، نشریة پژوهش‏های اقلیم‏شناسی، 1(3 و 4): 43ـ58.
رحیمی، د. (1385). برآورد حداکثر بارش و سیلاب محتمل در حوضة کارون شمالی، دانشکدة علوم جغرافیایی، دانشگاه اصفهان، رسالة دکتری.
رئیسیان، ر. و پورهمت، ج. (1392). بررسی میزان و تغییرات زمانی انباشت و عمق آب معادل برف در حوضة کارون شمالی (مطالعة موردی گردنة چری)، فصل‏نامة مهندسی آبیاری و آب، 90ـ101.
سبحانی، ب. و فاطمی‏نیا، ف.س. (1393). مدل‏سازی فراسنج‏‏های اقلیمی استان خراسان جنوبی، مجلة پژوهش‏های جغرافیای طبیعی، 46(3):  311ـ332.
کابلی، ح.؛ آخوند علی، ع.‏م.؛ مساح بوانی، ع.ر. و رادمنش، ف. (1391). ارائة ریزمقیاس‏نمایی داده‏های اقلیمی بر اساس روش ناپارامتریک نزدیک‏ترین همسایگی (K-NN)، نشریة آب و خاک، 26(4): 779ـ808.
کاویانی، م.ر. و علیجانی، ب. (1386). مبانی آب و هواشناسی، تهران: سمت.
گودرزی، ا.؛ مساح بوانی، ع.ر.؛ دستورانی، م.ت. و طالب، ع. (1389). شبیه‏سازی رواناب و بررسی تغییرات هیدرولوژیکی حوضة رودخانة اعظم هرات- یزد تحت تأثیر تغییر اقلیم، چهارمین کنفرانس منطقه‏ای تغییر اقلیم، ص 531ـ537.
مساح بوانی، ع.ر. و مرید، س. (1384). اثرات تغییر اقلیم بر منابع آب و تولید محصولات کشاورزی (مطالعة موردی: حوضة زاینده‏رود)، مجلة تحقیقات منابع آب ایران، 1(47): 1ـ40.
مساح بوانی، ع.ر. (1385). ارزیابی ریسک تغییر اقلیم و تأثیر آن بر منابع آب (مطالعة موردی: حوضة زاینده‏رود اصفهان)، رسالة دکتری، گروه مهندسی سازه‏های آبی، دانشگاه تربیت مدرس.
هاشمی‏نسب، س.؛ عطایی، ه. و صادقی، ف. (1394). بررسی و تحلیل روند حداکثر دما در حوضة آبخیز دریاچة نمک، مجلة اکوسیستم بیابان، 4(6): 1ـ14.
Alcamo, J.; Henrichs, T. and Rosch, T. (2000). World Water 2025: Global Modeling and Scenario Analysis for the World Commission on Water for 21st Century, Kassel University Press, World Water Series, Technical Report, Center of Environmental Systems Research University of Kassel, Germany.
Bazrafshan, J.; Khalili, A.; Hoorfar, A.; Torabi, S. and Hajjam, S. (2009). Comparison of the Performance of ClimGem and LARS-WG Models in Simulating the Weather Factors for Diverse Climates of Iran, Journal Iran-Water Resources Research, 5(13):44-57.
Dettinger, M.D.; Cayan, D.R.; Meyer, M. and Jeton A.E. (2004). Simulated Hydrologic Responses to Climate Variations and Change in the Merced, Carson, and American Riverbasins, Sierra Nevada, California, 1900-2099. Climatic Change, 62(1-3).
Dracup, J.A. and Viccuman, S. (2005). An Overviwo of Hydrology and Water Resources Studies on Climate Change: the California Experience, Proc.EWRI2005: Impacts of Global Climate Change.
Ezber, Y.; Lutfi Sen, O.; Kindap, T. and Karaca, M. (2007). Climate effects of urbanization in Istanbul: a statistical and modeling analysis, International Journal of Climatology, 27: 667- 679.
Goodarzi, E.; Masah Bavani, A.R.; Dastoorati, M.T. and Taleb, A. (2010). Grand River watershed runoff simulation and hydrological changes under the impact of climate change Yazd Heart, 4thRegional Conference Climate Change, 531-537.
Ghorbanizadeh Kharazi, H.; Sedghi, H.; Saghafian, B. and Porhemmat, J. (2010). Study on the Effect of Climate Change on Snowmelt Runoff Timing in Karoon Basin, Iran-Watershed Management Science & Engineering, 3(9): 45-50.
Hardi, J.T. (2008). Climate Change: Causes, Effects, and Solutions, Translate by Khazanehdari, Kuhi, Ghandehari, and Asiyaie, Papoli Press, Tehran.
Hasheminasab, S.; Ataei, H. and Sadeghi, F. (2015). Analyzed and Survey of Maximum Temperature Trend in Daryache-e-Namak Basin, Journal Desert Ecosystem Engineering, 4(6): 1-14.
IPCC. (2007). Climate change 2007: synthesis report. Intergovernmental Panel on Climate Change, Cambridge
IPCC. (2008). IPCC workshop on Describing Scientific Uncertainties in Climate Change to Support Group Colorado, USA.
IWRMC. (2012). Water Planning Office macro Iran, Ministry of Power.
Jamieson, J.; Porter, R. and Wilson., D.R. (1991). A test of the computer simulation model ARCWHEAT1 on wheat crops grow in New Zealand, Field Crops Research, 27: 337-350.
Khazanedari, L.; Koohi, M.; Ghandehari, Sh. and Asiaei, M. (2008). Climate Change, Causes, effects and solutions, Hadrdi, J.T., Publishers.Papoli
Kalili, N.; Khodashenas, S.R. and Davari, K. (2006). Forecast Precipetation by using Artificial Neural networks, th2 water resourse management, Isfahan University of technology.
Kaboli, S.H.; Akhondali, A.M.; Massah Bavani, A.R. and Radmanesh, F. (2012). A Downscaling Model Based on K-Nearest Neighbor (K-NN)Non-Parametric Method, Journal of Water and Soil(Agricultural Science and Technilogy, 26(4):799-808.
Kavyani, M.R. and Alijani, B. (2006). The Foundations of Climatology, Samt Publishers, Tehran.
Kendall, MG. (1975). Rank Correlation Methods, 4th edn, Griffin: London, 202.
Leavesley, G.H.; Restrepo, P.; Stannard, L.G. and Dixon, M. (1983). Precipitation-Runoff Modeling System: User Manual, Water Resour.Invest.Rpt.83-4238.USDept. Interior, Geological Survey.
Lisa, V.A. and Julie, M.A. (2009). Assessing trends in observed and modelled climate extremes over Australia in relation to future projections, International Journal of Climatology, 29: 417-435.
Man, HB. (1945). Nonparametric tests against trend, Econometrica, 13: 245-259.
Mansouri, B.; Ahmadzadeh, H.; Massah Bavani, A.R.; Morid, S.; Delavar, M. and Lotfi, S. )2014(. Change Impacts on Water Resources in Zarrinehrud Basin Using SWAT Model, Journal of Water and Soil, 28(6):1191-1203.
Martinez, M.; Serra, D.; Burgueno, C. and Lana, X. (2010). Time trends of daily maximum and minimum temperatures in Catalonia (ne Spain) for the period 1975–2004, International Journal of Climatology, 30: 267-290.
Massah Bavani, A.R. and Morid, S. (2005). The Effects of Climate Change on Water Resources and Agricultural Production Case Study: Zayandehrood basin, Journal Water Resources Research Iran, 47: 1-40.
Massah Bavani, A.R. (2006). Assessing the Risks of Climate Change and its Impact on Water Resources Case Study: Zayanderud Basin, PhD thesis, Department of Water Structures, Tarbiat Modarres University.
Ouyang, F.; Zhu, Y.; Fu, G.; Lu¨, H.; Zhang, A.; Yu, Zh. and Chen, Xi. (2015). Impacts of climate change under CMIP5 RCP scenarios on streamflow in the Huangnizhuang catchmen, Stoch Environ Res Risk Assess, 29: 1781-1795.
Rahimi, D. (2006). Probable maximum precipitation and flooding in the basin of Northern Karun, PhD thesis, Department geography, Isfahan University.
Riahi, K.; Rao, Sh.; Krey, V.; Cho, Ch. and et al. (2011). RCP 8.5—A scenario of comparatively high greenhouse gas emissions,Climate Change, 109: 33-57.
Raesiyan, R. and porhemmat, J. (2014). An Investigation on Temporal Variation of Snow Accumulated Depth and Snow Water Equivalent in Northern Karoon Basin (Case Study: Col Cheri), Journal Irrigation science and Engineering, 13: 90-101.
Rohrer, M.B. and Braun, L.N. (1994). Long-term records of the Snow Cover Water Equivalent in the Swiss Alps-2, Simulation .Nordic Hydrology., 25(1-2): 65-78.
Carlos A. C. dos Santos ,Christopher M. U. Neale ,Tantravahi V. R. Rao ,Bernardo B. da Silva,. (2011). Trends in indices for extremes in daily temperature and precipitation over Utah, USA. International Journal of Climatology, DOI: 10.1002/joc.2205.
Schlunzen, K.H.; Hoffmann, P.; Rosenhagen, G. and Riecke, W. (2010). Long-term changes and regional differences in temperature and precipitation in the metropolitan area of Hamburg, International Journal of Climatology, 30: 1121-1136.
Serrano, A.; Mateos, V.L. and Garcia, J.A. (1999). Trend analysis of monthly precipitation over the iberian peninsula for the period 1921–1995, Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere,  24(1-2): 85-90.
Singh, P. and Singh, V.P. (2001). Snow and Glacier Hydrology, Dordrecht: Kluwer Academic Publishers
Steele-Dunne, S.; Lynch, P.; McGrath, R.; Semmler, T.; Wang, S.; Hanafin, J. and  PaulNolan  (2008). The Impacts of Climate Change on Hydrology in Ireland, Journal of Hydrology, 356: 28-45.
Vuuren, D.V.; Edmonds, J.; Kainuma, M.; Riahi, K. and Weyant, J. (2011). A special issue on the RCPs, Climate Change, 109: 1-4
Vuuren, D.V.; Edmonds, J.; Kainuma, M.; Riahi, K. and et al. (2011). The representative concentration pathways: an overview, Climate Change, 109: 5-31.
Yang, X.L; Xu, L.R.; Liu, K.K; Li, CH; HU, J. and Xia, XH. (2012). Trends in Temperature and Precipitation in the Zhangweinan River Basin during the last 53 Years, Procedia Environmental Sciences, 13: 1966-1974.
Zahabiyoun, B.; Goodarzi, M.R. and Massh Bavani, A.R. (2011). Application of the SWAT Model in the Ghare sou River Basin Under Climate Change, Journal Climate Research, 1(3-4): 45-60.
Zulkarnain, H.; Supiah, Sh. and Sobri, H. (2014). Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature, Journal Theoretical and Applied Climatology, 116: 243-257.
Volume 50, Issue 1
April 2018
Pages 1-17
  • Receive Date: 11 March 2017
  • Revise Date: 15 July 2017
  • Accept Date: 27 August 2017
  • First Publish Date: 21 March 2018