Optimal operation of reservoirs with increasing water use efficiency: Climate change adaptation approach (case study: Jareh Dam)

Document Type : Research Article

Authors

1 Department of civil engineering, Jundi-Shapur university of Technology, Dezful

2 department of civil engineering, Jundi-Shapur university of technology, Dezful

Abstract

Impacts of climate change on water resources will force decision-makers to adopt climate change adaptation policies in order to reduce social-economic problems and difficulties resulting from it and water resource sustainable development. One of the adaptation methods is to increase water use efficiency in agriculture that will adjust climate change impacts include decreasing runoff and increasing water demands. In this study, the impact of water use efficiency as a climate change adaptation approach is assessed in the optimal operation of JAREH dam. Fifteen climate change scenarios were generated by using downscaling technique on CMIP5 data for the near (2020-2044) and far (2070-2094) future. Based on these scenarios, time series of reservoir inflow and downstream water demand were projected for both future periods. An optimization model is developed considering the water efficiency coefficient parameter in order to define four water use efficiency scenarios (0-S1, 0.1-S2, 0.3-S3, 0.5-S4). Results show that reservoir inflow decreases up to 18.8% and water agriculture demand increases up to 29%. The amount of water allocation would increase up to 18.7% in the future periods than in the baseline period under S1 scenario to supply the increased water demand, which may decrease reliability of reservoir system for water allocation. Increasing water use efficiency coefficient up to 0.5 in the future periods would increase system reliability up to 20% that will reduce social-economic problems caused by climate change impact in this study area.

Keywords

Main Subjects

References

[1] P.S. Ashofteh, O. Bozorg Haddad, H. Akbari-Alashti, M.A. Mari˜no, Determination of irrigation allocation policy under climate change by genetic programming, J. Irrig. Drain. Eng., 141(4) (2015) 04014059.
[2] IPCC, Climate Change 2014 Synthesis Report. Summary for Policymakers. Contribution of Working Group I, II and III to Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). In: R. Pachauri and L. Meyer (eds). Geneva, Switzerland, 2014.
[3] P.S. Ashofteh, O. Bozorg Haddad, M.A. Mari˜no, Climate change impact on reservoir performance indices in agricultural water supply, J. Irrig. Drain. 2013 139(2) (2013) 19434774.
[4] S. Khanjari Sadati, S. Speelman, M. Sabouhi, M. Gitizadeh, B. Ghahraman, Optimal irrigation water allocation using a genetic algorithm under various weather conditions, Water, 6 (10) (2014) 3068-3084.
[5] M. Chiyuan, D. Qingyun, S. Qiaohong, H. Yong, K. Dongxian, Y. Tiantian, Y. Aizhong, D. Zhenhua,  G. Wei, Assessment of CMIP5 climate models and coupled with singular spectrum analysis, Journal of Hydrology, 399 (2014) 394–409.
[6] A. Aghakhani, H. Hasanzadeh, Y. Besalatpour, M. Pourreza-Bilondi, Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways, Theoretical and applied climatology, 129 (1-2) (2017) 683-699.
[7] J. Rahimi, A. Malekian, A. Khalili, Climate change impacts in Iran: assessing our current knowledge, Theoretical and Applied Climatology, 135(1-2) (2019) 545–564.
[8] H. Akbari‐Alashti, A. Soncini, Y. Dinpashoh, A. FakheriFard, S. Talatahari, D. Bocchiola,  Operation of two major reservoirs of Iran under IPCC scenarios during the XXI Century, 32(12) (2018) 3254-3271.
[9] A. Sarhadi, D.H. Burn, F. Johnson, R. Mehrotra, A. Sharma, Water resources climate change projections using supervised nonlinear and multivariate soft computing techniques.  Journal of Hydrology, 536 (2016) 119–132.
[10] G.M. Bombelli,  A. Soncini , A. Bianchi, D. Bocchiola, 2019. Potentially modified hydropower production under climate change in the Italian Alps. Hydrological Processes, 10 (1-2) (2019) 13473.
[11] S.H. Moghadam, P.S. Ashofteh, H.A. Loáiciga, Application of climate projections and monte Carlo approach for assessment of future river flow: Khorramabad River Basin, Iran. journal of hydrologic engineering., 24(7) (2019) 5584.
[12] N.K. Nektarios, D. Zoi, P.K. George, Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: The example of a small Mediterranean agro-watershed. Journal of Environmental Management. 154 (2015) 86-101.
[13] J. Farajzadeh, A.F. Fard, Lotfi, S., Modeling of monthly rainfall and runoff of Urmia lake basin using “feedforward neural network” and “time series analysis” model, Water Resources and Industry, 7(8) (2014) 38–48.
[14] A. Sarkar, R. Kumar, Artificial Neural Networks for event based rainfall-runoff modeling. Journal of Water Resource and Protection, 4 (2012) 891-897.
[15] U. Surendran, C.M. Sushanth, G. Mammen, E.J. Joseph, Modelling the crop water requirement using FAOCROPWAT and assessment of water resources for sustainable water resource management: A case study in Palakkad district of humid tropical Kerala, India. Water Management (Agriculture) Division,Centre for Water Resources Development and Management, Kunnamangalam, 2015.
[16] T. Rezaiei, L.S. Pereira, Estimation of ETo with Hargreaves–Samani and FAO-PM temperature methods for a wide range of climates in Iran, Agricultural Water Management, 121 (2013) 1– 18.
[17] G. Stancalie, A. Marica, L. Toulios, Using earth observation data and CROPWAT model to estimate the actual crop evapotranspiration, Physics and Chemistry of the Earth, 35 (2012) 25–30.
[18] X. Wang, Q. Cui, S. Li, An optimal water allocation model based on water resources security assessment and its application in Zhangjiakou Region, northern China, Resources, Conservation and Recycling 69 (2012) 57– 65.
[19] M. Ehtram, H. Karami, S.F. Mousavi, A. ElShafie, Z. Amini, Optimizing dam and reservoirs operation based model utilizing shark algorithm approach. KnowledgeBased Systems, S0950-7051(17) (2017) 30039-4.
[20] T. Lafon, S. Dadson, G. Buys, C. Prudhomme, Bias correction of daily precipitation simulated by a regional climate model: a comparision of methods, International journal of climatology, 33 (2013) 1367-1381.
[21] F. Helfer, C. Lemckert, H. Zhang, Impacts of climate change on temperature and evaporation from a large reservoir in Australia. Journal of Hydrology, 475 (2012) 365–378.
[22] A. Hosseinizadeh, H. Zarei, A.M. Akhondali, H. Seyed kaboli, B. Farjad. Potential impacts of climate change on groundwater resources: A multi-regional modelling assessment. Journal of Earth System Science. 128(5) (2019) 355-365.
[23] E.T. Linacre, A simple formula for estimating evaporation rates in various climates, using temperature data alone, Agricultural Meteorology, 18 (1977) 409-424.
[24] A. Alizadeh, Optimization of the document of national water in agriculture water consumption, Khozestan province, Iran Meteorological Organization-Ministry of Agriculture-Jehad, Iran, 7 (2003) (In Persian).
[25] T.A. McMahon, J. Adebayo, Z. Sen-Lin, Understanding performance measures of reservoirs. Journal of Hydrology, 324 (2006) 359–382.
[26] P.S. Ashofteh, Evaluation of climatic-change impacts on multiobjective reservoir operation with multiobjective genetic programming, Journal of Water Resources Planning and Management, 141 (11) (2015) 04015030.
[27] D.P. Loucks, E. van Beek, Water resources systems planning and management, United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France, 2005.
[28] S. Sandoval-Solis, D.C. McKinney, D.P. Loucks, Sustainability index for water resources planning and management. Journal of Water Resources Planning and Management, 137(5) (2011) 381-390.
Amirkabir Journal of Civil Engineering
Volume 52, Issue 12
March 2021
Pages 3043-3058

Files

Share

How to cite

Statistics