Evaluation of Climate Change Effects on the Entering Runoff the Makhmalkoh Dam Using the IHACRES Model

Document Type : Research Paper


1 Department of Water Engineering, Faculty of Agriculture, Lorestan University, Khorramabad, Iran.

2 Department of Water Engineering, Faculty of Agriculture, Lorestan University, Khorramabad, Iran.‎

3 Water Structures Engineering, Faculty of Agriculture, Lorestan University, Khorramabad, Iran.‎

4 Renewable Energies and Environment, University of Tehran, Tehran, Iran.



In this study, the entering runoff to Makhmalkooh Dam; in Lorestan province; was studied under climate change scenarios. For this using, the data of precipitation, maximum and minimum temperature and sunshine for the study area in the basic time of 1980-2014 were downscaled with LARS-WG6 model and after choosing the IPSL-CM6A-LR-INCA model as the most compatible model with the study area among the 26 models in the sixth IPCC report, precipitation, minimum and maximum temperature and sunshine were estimated for Kakareza station in three times of 2026-2050, 2051-2075 and 2076-2100 under SSP scenarios. After that, the entering runoff to Makhmalkooh dam was estimated in the future periods under the SSP scenarios using the IHACRES model and the results obtained from the previous step. The results of this study showed that the entering runoff the studied dam will decrease on monthly and seasonal scale in all future periods under SSP climate scenarios. The highest runoff in the monthly scale was predicted in October under the SSP5-8.5 scenario, and the lowest decrease was predicted in May under the SSP1-2.6 scenario. On seasonal scale, the highest amount of reduction in entering runoff to the dam was estimated in the autumn season under the SSP5-8.5 scenario, and the lowest amount of reduction was estimated in the spring season under the SSP1-2.6 scenario. The results of this study also showed that the climate change will have significant effect on entering runoff to Makhmalkooh dam and therefore, the impacts of this phenomenon should be considered in water resources development plans to reduce its damages for posterity.


Main Subjects

  1. Adgolign, T. B., Rao, G. S., & Abbulu, Y. (2016). WEAP modeling of surface water resources allocation in Didessa Sub-Basin, West Ethiopia. Sustainable Water Resources Management, 2, 55-70. DOI 10.1007/s40899-015-0041-4.
  2. Adib, A., Mirsalari, S. B., & Ashrafi, S. M. (2018). Prediction of meteorological and hydrological phenomena by different climatic scenarios in the Karkheh watershed (south west of Iran). Scientia Iranica.
  3. Basile, S.M.L., Tognetti, J.A., Gandini, M. L., & Rogers, W. L. (2022). Climate change in the temperature and precipitation at two contrasting sites of the Argentinean wheat region. Theoretical and Applied Climatology, 148, 237-254.https://doi.org/10.1007/s00704-022-03936-6
  4. Bekele, D., Alamirew, T., Kebede, A., Zeleke, G., & Melesse, A. M. (2019). Modeling climate change impact on the hydrology of Keleta watershed in the Awash River Basin, Ethiopia. Environmental Modeling & Assessment. 24 (1), 95–107.
  5. Dobriyal, P., Badola, R., Tuboi, C., & Hussain, S.A. (2017). A review of methods for monitoring streamflow for sustainable water resource management. Application Water Science, 7, 2617-2628. doi:10.1007/s13201-016-0488-y.
  6. Emami, F., & Koch, M. (2019), Modeling the Impact of Climate Change on Water Availability in the Zarrine River Basin and Inflow to the Boukan Dam, Iran. Climate, 7, 51. doi:10.3390/cli7040051.
  7. Salahi, B., Fatemi Nia, F.S., & Hosseini, S.M. (2015). Assessment of future climate change in Isfahan province using BCM2 & HADCM3 models by lars-wg downscaling model. Journal of Arid Region Geography Studies, 5(16), 55-71.
  8. Feng, S., Hu, Q., Huang, W., Ho, C. H., Li, R., & Tang, Z. (2014). Projected climate regime shift under future global warming from multi-model, multi-scenario CMIP5 simulations. Global and Planetary Change, 112, 41-52.
  9. Ghorbani, Kh., Sohrabian, E., Salarijazi, M., & Abdolhoseini, M. (2016). Prediction of climate change impact on monthly river discharge trend using IHACRES hydrological model (case study: Galikesh watershed). Journal of water and soil resources conservation, 5(4), 18-34. (In Persian).
  10. Hosseini, S.H., Ghorbani, M.A., & Massahbavani A.R. (2015). Rainfall-Runoff Modelling under the Climate Change Condition in Order to Project Future Streamflow of Sufichay Watershed. Journal of Watershed Management Resources, 6 (11), 1-14 (In Persian).
  11. House, A.R., Thompson, J.R., & Acreman, M.C. (2016). Projecting impacts of climate change on hydrological conditions and biotic responses in a chalk valley riparian wetland. Journal of Hydrology, 534, 178-192. doi:10.1016/ j. journal of hydrology. 2016.01.004.
  12. Information of Kakareza transfer project. (2014). Abdan Faraz adviser engineers.
  13. (2021). Climate Change 2021. Human Influence on global warming is unequivocal. The physical science basis. Intergovernmental panel on climate change, Cambridge University Press, https://www.livescience.com/ipcc-climate-report-2021.html.
  14. Irwin, S.E. et al. (2012). Assessment of Climatic Vulnerability in the Upper Thames River Basin: Downscaling with LARS-WG. Water Resources Research Report. The University of Western Ontario, Department of Civil and Environmental Engineering.
  15. Jahangir, M.H., Haghighi, P., & Danehkar, Sh. (2022). Downscaling climate parameters in Fars province, using models of the fifth report and RCP scenarios. Ecological Informatics, 68, (101558), 1-12. Journal homepage: elsevier.com/locate/ecolinf.
  16. Jakeman, A.J. and Hornberger, G.M. (1993). How Much Complexity Is Warranted in a Rainfall-Runoff Model? Water Resources Research 29 (8), 2637-2649.
  17. Jiang, L., & O’Neill, B.C. (2017). Global urbanization projections for the shared socioeconomic pathways, Global Environ. Change, 42, 193-199, https://doi. org/10.1016/j.gloenvcha.2015.03.008.
  18. Jones, B., & O’Neill, B.C. (2016) Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways, Res. Lett, 11, 1-10. https:// doi.org/10.1088/1748-9326/11/8/084003.
  19. Kuriqi, A., Pinheiro, A.N., Sordo-Ward, A., Bejarano, M.D., & Garrote, L. (2021). Ecological impacts of run-of-river hydropower plants-Current status and future prospects on the brink of energy transition. Renew. Sustain. Energy Rev. 2021. doi:10.1016/ j. rser .2021.110833.
  20. Majdai, F., Hosseini. S. A., Karbalaee, A., Kaseri, M., & Marjanian, M. (2022). Future projection of precipitation and temperature changes in the Middle East and North Africa (MENA) region based on CMIP6. Theoretical and Applied Climatology, 147, 1249-1262.
  21. Mwabumba, M., Yadav, B.K., Mwemezi, J.R., Larbi, I., Dotse, S.Q., Limantol, A.M., Sarpong, S., & Kewawuvi, D. (2022). Rainfall and temperature changes under different climate scenarios at the watersheds surrounding the Ngorongoro Conservation Area in Tanzania. Environmental Challenges, 7, 100446.
  22. Riahi, K., D.P., van Vuuren, E., Kriegler, J., Edmonds, B.C., O’Neill, S., Fujimori, N., Bauer, K., Calvin, R., Dellink, O., Fricko, W., Lutz, A., Popp, J.C., Cuaresma, S. Kc. M., Leimbach, L., Jiang, T., Kram, S., Rao, J., Emmerling, K., Ebi, T., Hasegawa, P., Havlik, F., Humpen¨oder, L.A., da Silva, S., Smith, E., Stehfest, V., Bosetti, J., Eom, D., Gernaat, T., Masui, J., Rogelj, J., Strefler, L., Drouet, V., Krey, G., Luderer, M., Harmsen, K., Takahashi, L., Baumstark, J.C., Doelman, M., Kainuma, Z., Klimont, G., Marangoni, H., Lotze-Campen, M., Obersteiner, A., Tabeau, M., Tavoni, (2017). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: an overview, Global Environ. Change, 42, 153-168, https:// doi.org/10.1016/j.gloenvcha.2016.05.009.
  23. Sanikhani, H., Gohardoust, MR., & Sadeghi, M. (2016). The Impacts of Climate Change on Runoff of Ghareh-Chay Basin in Markazi Province, Iran. Journal of Watershed Management Research, 13(7), 12-22. (In Persian).
  24. Samir, K., & Wolfgang, L. (2017). The human core of the shared socioeconomic pathways: population scenarios by age, sex and level of education for all countries to 2100, Global Environ. Change, 42, 181-192. https://doi.org/10.1016/j. gloenvcha.2014.06.004.
  25. Thomas, T., Goyal, S., Goyal, V. C., & Kale, R. V. (2019). Water availability under changing climate scenario in Ur river basin. In: Climate Change Impacts. Springer, Singapore, 213-229.
  26. Toosi, A. S., Calbimonte, G. H., Nouri, H., & Alaghmand, S. (2019). River basin-scale flood hazard assessment using a modified multi-criteria decision analysis approach: a case study. Journal of Hydrology, 574, 660-671.
  27. Try, S., Tanaka, S., Tanaka, K., Sayama, T., Khujanazarov, T., & Oeurng, C. (2022). Comparison of CMIP5 and CMIP6 GCM performance for flood projections in the Mekong River Basin. Journal of Hydrology: Regional Studies, 40, 101035.
  28. Westin, L.G.F., Conceição, L.R., Bortoni, E.C., Marcato, A.L.M., Ribeiro, C.B.D.M., & Honório, L.D.M. (2021). Evaluating the Impact of Streamflow Rating Curve Precision on Firm Energy of Hydropower Plants. Water Journal, 13, 1016. https://doi.org/10.3390/w13081016.
  29. Yue, Y., Yan, D., Yue, Q., Ji, G., & Wang, Zh. (2021). Future changes in precipitation and temperature over the Yangtze River Basin in China based on CMIP6 GCMs, Atmospheric Research,
  30. You, Q., Cai, Z., Wu, F., Jiang, Z., Pepin, N., & Shen, S.P. (2021). Temperature dataset of CMIP6 models over China evaluation, trend and uncertainty. Climatology Dynamics, 57, 17-35.