Impact of cmip5 climate change model in Jamishan dam reservoir simulation under cropping pattern change scenario

Document Type : Original Article

Authors

1 Master Student of Water Resources, Department of Water Science and Engineering, Faculty of Agriculture, Razi University, Kermanshah, Iran

2 Assistant professor, Department of Water Science and Engineering, Faculty of Agriculture, Razi University, Kermanshah, Iran.

Abstract

In this research, monthly temperature, precipitation and discharge values of Jamishan Dam in 1988-2017 have been considered as the base period. Simulation of resources and uses of Dam-d-Gomishan basin in WEAP model with existing cropping patterns in the region was investigated. To evaluate the effect of climate change on precipitation and temperature parameters in this region, the outputs of the RCP8.5 scenario of the HADGEM2_ES models were used from the cmip5 fifth report series and the output of these models was downscaled for the desired area. In this study, using the method of change factor downscaling the climatic model and monthly temperature and precipitation parameters of Jamishan Dam for the period 2021-2050 were generated. In order to investigate the runoff of the area due to climate change, SVM, GEP and IHACRES models were investigated and compared. The results of the climatic model show an average temperature increase of 1.5 °C and an increase in precipitation of 5%. In general, results of discharge forecasting in all three models indicate a decrease in runoff that the highest runoff reduction was related to SVM with 21.6% and the lowest runoff reduction was related to IHACRES with 4%. In this study, IHACRES and GEP models have more favorable accuracy than SVR method. Simulation of different cropping patterns in WEAP shows that the highest supply is equal to 74.9% in GEP model and the lowest supply is equal to 70% in SVR model which is related to cropping pattern 1 and cropping pattern 3, respectively.

Keywords

Main Subjects

References

Ahmadi, F., Radmanesh, F., & Mirabbasi, R. (2016). Comparison of the performance of support vector machine methods and business networks in predicting daily river flow (Case study: Barandozchay River). Journal of Soil and Water Conservation Research, 22 (6), 186-171. https://dorl.net/dor/20.1001.1.23222069.1394.22.6.10.2 [In Persian]
Avaz yar, M., Ahmadpour Borazjani, M., & zyaei, S. (2018). Determine optimal crop pattern with an emphasis on increasing the irrigation efficiency in lands of Mollasadra Dam in Fars province. Water Resources Engineering, 11(36), 21-32. https://dorl.net/dor/20.1001.1.20086377.1397.11.36.3.4 [In In Persian]
Dibike, Y.B., Velickov, S., Solomatine, D.P., & Abbott, M.B. (2001). Model induction with support vector machines: introduction and applications. Journal of Computing in Civil Engineering. 15(3), 208-216. https://dx.doi.org/10.1061/(ASCE)0887-3801(2001)15:3(208)
Fatemi, S.E., Bahramloo, ali & Adebrad, M.H. (2016). Studying the Structural and Non-structural Solutions for Sustainable Water Resources Management of Hamedan-Bahar Plainn. Geography and Environmental Sustainability, 6(3), 55-67. https://ges.razi.ac.ir/article_631.html [In Persian]
General Department of Water Affairs of Kermanshah Province. (2004). Study of the first stage of Jamishan reservoir dam. Needs, water resources planning and dam and network improvement, Ministry of Energy, Western Regional Water. [In Persian]
Hafezparast, M., Bafkar, A., & Panahi, E. (2016). Assessing the uncertainty of climate change and its effects on the likelihood of frequent flooding of the entrance to the Jamishan Dam. Journal of Water and Soil Conservation, 6(3), 19-42. https://dorl.net/dor/20.1001.1.22517480.1396.6.3.2.3 [In Persian]
He, Z., Wen, X., Liu, H., & Du, J. (2014). A comparative study of artificial neural network, adaptive neuro fuzzy inference system and support vector machine for forecasting river flow in the semiarid mountain region. Journal of Hydrology, 509, 379–386.                  http://dx.doi.org/10.1016/j.jhydrol.2013.11.054
IPCC. (2001). The Scientific Basis of Climate Change. Contribution of Working Grop I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge.
Jakeman, A.J., & Hornberger, G.M. (1993). How much complexity is warranted in a rainfall-runoff model. Water Resources Research. 29(8), 2637-2649. https://doi.org/10.1029/93WR00877
Karmaoui, A., Minucci, G., Messouli, M., Khebiza, M. Y., Ifaadassan, I., & Babqiqi, A., (2019). Climate Change Impacts on Water Supply System of the Middle Draa Valley in South Morocco.  Published in Climate Change, Food Security and Natural Resource Management, Springer.
Kalbali, E., Ziaee, S., Mardani Najafabadi, M., & Zakerinia, M. (2019). Assessment of Climate Change Impacts on Optimum Cropping Pattern: A Case Study of Ghareso Basin in Golestan Province. Iran-Water Resources Research, 15(3), 251-271. https://dorl.net/dor/20.1001.1.17352347.1398.15.3.20.1 [In Persian]
Lotfirad, M., Adib, A., & Haghighi, A. (2018). Estimation of daily runoff using of the semi- conceptual rainfall-runoff IHACRES model in the Navrood watershed (a watershed in the Gilan province. Iranian journal of Ecohydrology, 5(2), 449-460. https://dx.doi.org/10.22059/ije.2017.234237.614 [In Persian]
Mansouri, A., Aminnejad, B., & Ahmadi, H. (2018). Investigating the Effect of Climate Change on Inflow Runoff into the Karun-4 Dam Based on IPCC's Fourth and Fifth Report. JWSS, 22 (2) ,345-359. http://dx.doi.org/10.29252/jstnar.22.2.345 [In Persian]
Mohammadi, H., Sargazi, A., & Sarani, V. (2019). Studying Impact of Increase in Water Usage Efficiency on Cropping Pattern Change with Emphasis on the Policy Makers and Environmental Objectives in Fars Province. Journal of Environmental Science and Technology, 21(10), 147-160. http://dx.doi.org/10.22034/JEST.2019.15616 [In Persian]
Mohie, E. D. O., & Moussa. A. (2016) Water Management in Egypt for Facing the Future Challenges. Advanced Research, 7(3), 403-412. https://doi.org/10.1016/j.jare.2016.02.005
Momblanch, A., Beevers, L., Srinivasalu, P., & Kulkarni, A. (2020). Enhancing production and flow of freshwater ecosystsm services in a managed Himalayan river system under uncertain future climate. Climatic change, 162, 343-361. https://doi.org/10.1007/s10584-020-02795-2
Nabizadeh, M., Mosaedi, A., & Dehghani, A. (2012). Intelligent estimation of stream flow by Adaptive Neuro-Fuzzy Inference System. Water and Irrigation Management, 2(1), 69-80. https://dx.doi.org/10.22059/jwim.2012.25093 [In Persian]
Panahi, E. (2015). Integrated water resources management of the catchment area in terms of climate change (B. SC. Thesis), Faculty of Agriculture, Department of Water Science and Engineering, Razi University, Kermanshah, Iran. [In Persian]
Pourkheirolah, Z., Hafezparast, M. & Fatemi, S.A. (2017). Changes in the parameters of precipitation, temperature and Dubai under the radiation scenario caused the radiation (study area: Dehloran city). In: Second National Conference on Hydrology of Iran. Shahrekord University, Shahrekord, Iran. https://civilica.com/doc/661416 [In Persian]
Pourmohamadi, S., Dastourani, M., Mesahbovani, A. & Jafari, H. (2015). Investigating the effects of climate change and cloud fertility on river runoff (Case study: Qolqol River River Tuyserkan catchment area). 10th International River Engineering Seminar, Chamran University, Ahvaz, Iran. https://civilica.com/doc/677149 [In Persian]
Rahimi, B., Hafezparast Mavaddat, M. (2020). Comparison of SVM, GEP and IHACRES Models in Prediction of Runoff Changes Due to Climate Change (Case Study: Jamishan Dam). Iranian Journal of Soil and Water Research, 51(10), 2483-2499.                          https://dx.doi.org/10.22059/ijswr.2020.303779.668640 [In Persian]
Rahimi, B., & Hafezparast, M. (2021). Investigation of IHACRES Model in Predicting Runoff Due To Climatic Models Fifth Report (Case Study: Jamishan Dam). The first national conference on applied research in the water and electricity industry. Kermanshah. Iran. https://civilica.com/doc/1202087 [In Persian]
Salimi masteali, F., Hafezparast, M., & Sargordi, F. (2020). Simulation and Optimization of Dam Operation under Changing Cultivation Pattern Scenario (Case Study: Harsin Dam). Iranian Journal of Soil and Water Research, 51(1), 1-12. https://dx.doi.org/10.22059/ijswr.2019.282440.668221 [In Persian]
Sambou, D., Weihrauch, D., Hellwing, V., Diekkruger, B., Hollermann, B., & Gaye, A. (2015) Assessment of Water Availability and Demand in Lake Guiers, Senegal. American Geophysical Union Fall meeting, San Francisco.                                       https://ui.adsabs.harvard.edu/abs/2015AGUFMGC43B1191S/abstract
Solgi, A., Zarei, H., Shehnidarabi, M. & Alidadi, S. (2017). Predict monthly precipitation using gene expression expression models and support vector machines. Journal of Applied Research in Geographical Sciences. 18(50), 91-103. http://dx.doi.org/10.29252/jgs.18.50.91 [In Persian]
Xue, L., Yue, Z., Chunli, Sh., Jian, Sh., Zhong Ling, W., & Yuqia, W. (2015) Application of Water Evaluation and Planning (WEAP) Model for Water Resources Management Strategy Estimation in Coastal Binhai New Area, China, Ocean & Coastal Management, 106, 97-109.  https://doi.org/10.1016/j.ocecoaman.2015.01.016
Advanced Technologies in Water Efficiency
Volume 1, Issue 1
December 2022
Pages 1-23

Files

History

  • Receive Date: 20 June 2021
  • Revise Date: 09 July 2021
  • Accept Date: 18 July 2021

Share

How to cite

Statistics