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Drought mitigation through a hedging-based model of reservoir-farm systems considering climate and streamflow variations

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Abstract

For an effective reservoir operation during drought, the variations of both water supply and water demand which depend on hydrological and meteorological conditions need to be dealt with. This paper aimed to consider these variations in the Aharchay basin (Iran) by coupling a hedging rule (HR)-based reservoir operation model (HRROM) with a climate-based irrigation scheduling model (CBISM) at the farm level. Through the HRROM, optimal long-term decisions for Sattarkhan reservoir were made by considering the probable streamflow scenarios in the system. Given the variable agricultural demands (VAD) in the CBISM, the irrigation water was optimally allocated to the crops using several evapotranspiration (ET) scenarios. The CBISM employs three sub-models including linear programming (LP), nonlinear programming (NLP), and particle swarm optimization (PSO) to maximize the total income of the Aharchay agricultural network as a function of the climate factors and the supplied water. To this end, the daily weather and discharge data from 1990 to 2015 were used in this study. The standardized precipitation-evapotranspiration index (SPEI) and the streamflow drought index (SDI) were used to detect the meteorological and hydrological droughts, respectively. The SPEI was calculated based on the high-resolution-gridded datasets of the Climatic Research Unit (CRU). The findings demonstrated that the HRROM-CBISM generally managed to increase the time-based (αt) and volume-based (αv) reliability indices by 20% and 44%, respectively, compared with the conventional standard operation policy (SOP). For more investigations, the three major droughts of 2000–2002, 2004–2006, and 2008–2014 were separately analyzed. The average values of αt, αv, and vulnerability (V) for SOP were 0.33, 0.51, and 0.48, respectively. With the HRROM-CBISM, these values were about 0.5, 0.55, and 0.45, respectively. Among these indices, αt had the highest variations, while αv had the lowest variations in both the SOP and HRROM-CBISM approaches. The average water shortage for the mentioned droughts was significantly decreased from 89 (SOP) to 75 MCM (HRROM-CBISM).

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References

  • Adeloye AJ, Soundharajan BS, Ojha CS, Remesan R (2016) Effect of hedging-integrated rule curves on the performance of the pong reservoir (India) during scenario-neutral climate change perturbations. Water Resour Manag 30(2):445–470

    Article  Google Scholar 

  • Ahmad MI, Sinclair CD, Werritty A (1988) Log-logistic flood frequency analysis. J Hydrol 98(3-4):205–224

    Article  Google Scholar 

  • Akay B (2013) A study on particle swarm optimization and artificial bee colony algorithms for multilevel thresholding. Appl Soft Comput 13:3066–3091

    Article  Google Scholar 

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration – guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56, FAO, p 1998 ISBN 92-5-104219

    Google Scholar 

  • Anvari S, Mousavi SJ, Morid S (2014) Sampling/stochastic dynamic programming for optimal operation of multi-purpose reservoirs using artificial neural network-based ensemble streamflow predictions. J Hydroinf 16(4):907–921

    Article  Google Scholar 

  • Anvari S, Kim JH, Moghaddasi M (2019) The role of meteorological and hydrological uncertainties in the performance of optimal water allocation approaches. Irrig Drain 68(2):342–353

    Article  Google Scholar 

  • Bayazit M, Unal E (1990) Effects of hedging on reservoir performance. Water Resour Res 26(4):713–719

    Article  Google Scholar 

  • Chang J, Guo A, Wang Y, Ha Y, Zhang R, Xue L, Tu Z (2019) Reservoir operations to mitigate drought effects with a hedging policy triggered by the drought prevention limiting water level. Water Resour Res 55(2):904–922

    Article  Google Scholar 

  • Clarke D, Smith M, El-Askari K (2001) CropWat for Windows: user guide. IHE, Oak Brook, IL, USA

    Google Scholar 

  • Delavar M, Moghadasi M, Morid S (2012) Real-time model for optimal water allocation in irrigation systems during droughts. J Irrig Drain Eng 138(6):517–524

    Article  Google Scholar 

  • Draper AJ, Lund JR (2004) Optimal hedging and carryover storage value. J Water Resour Plan Manag 130(1):83–87

    Article  Google Scholar 

  • Eum H, Kim YO, Palmer R (2011) Optimal drought management using sampling stochastic dynamic programming with a hedging rule. J Water Resour Plan Manag 137(1):113–122

    Article  Google Scholar 

  • Ghodousi H, Sadaat Morsali S (2016) Application of linear programming for crop pattern optimization of Aharchay basin in existing and development conditions, pp 248–255

    Google Scholar 

  • Hashimoto T, Stedinger JR, Loucks DP (1982) Reliability, resilience, and vulnerability criteria for water resource system performance evaluation. Water Resour Res 18(1):14–20

    Article  Google Scholar 

  • Ji Y, Lei X, Cai S, Wang X (2016) Hedging rules for water supply reservoir based on the model of simulation and optimization. Water 8(6):249

    Article  Google Scholar 

  • Karamouz M, Imen S, Nazif S (2012) Development of a demand driven hydro-climatic model for drought planning. Water Resour Manag 26(2):329–357

    Article  Google Scholar 

  • Karamouz M, Ahmadi B, Zahmatkesh Z (2013) Developing an agricultural planning model in a watershed considering climate change impacts. J Water Resour Plan Manag 139(4):349–363

    Article  Google Scholar 

  • Kim YO, Eum H, Lee EG, Ko IH (2007) Optimizing operational policies of a Korean multi-reservoir system using sampling stochastic dynamic programming with ensemble streamflow prediction. J Water Resour Plan Manag 133(1):4–14

    Article  Google Scholar 

  • Kumar DN, Raju KS, Ashok B (2006) Optimal reservoir operation for irrigation of multiple crops using genetic algorithms. Journal of Irrigation and Drainage Engineering Engineering (ASCE) 132(2):123–129

    Article  Google Scholar 

  • Labadie JW (2004) Optimal operation of multi-reservoir systems: state-of-the-art review. J Water Resour Plan Manag 130(2):93–111

    Article  Google Scholar 

  • Lee S, Jin Y, Park J (2017) Comparison of hedging rule curves depending on available water and current storage in reservoir operation under droughts. European Water 60:227–232

    Google Scholar 

  • Loucks DP, Stedinger JR, Haith DA (1981) Water resources systems planning and analysis. Prentice-Hall, Englewood Cliffs, N. J.

    Google Scholar 

  • McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. American Meteorological Society. 8th Conference on Applied Climatology, 17–22 Janvier, Anaheim, California, Boston, MA: American, pp 179–184

    Google Scholar 

  • Men B, Wu Z, Li Y, Liu H (2019) Reservoir operation policy based on joint hedging rules. Water 11(3):419. https://doi.org/10.3390/w11030419

    Article  Google Scholar 

  • Moghaddasi M, Araghinejad S, Morid S (2010a) Long-term operation of irrigation dams considering variable demands: case study of Zayandeh-rud reservoir, Iran. J Irrig Drain Eng 136(5):309–316

    Article  Google Scholar 

  • Moghaddasi M, Morid S, Araghinejad S, Alikhani MA (2010b) Assessment of irrigation water allocation based on optimization and equitable water reduction approaches to reduce agricultural drought losses: the 1999 drought in the Zayandeh Rud irrigation system (Iran). Irrigation and drainage (ICID) 59(4):377–387

    Article  Google Scholar 

  • Moghaddasi M, Anvari S, Mohammadi T (2022b) Comparison of extreme value theory approaches in temperature frequency analysis (case study: Arak plain in Iran). Arab J Geosci 15(12):1–13

    Article  Google Scholar 

  • Mutti PR, Dubreuil V, Bezerra BG, Arvor D, de Oliveira CP, Santos e Silva, C. M. (2020) Assessment of gridded CRU TS data for long-term climatic water balance monitoring over the São Francisco Watershed. Brazil Atmosphere 11(11):1207

    Article  Google Scholar 

  • Naderi K, Moghaddasi M, shokri, A. (2022) Drought occurrence probability analysis using multivariate standardized drought index and copula function under climate change. Water Resour Manag 36:2865–2888. https://doi.org/10.1007/s11269-022-03186-1

    Article  Google Scholar 

  • Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23(5):881–897

    Article  Google Scholar 

  • Neelakantan TR, Pundarikanthan NV (1999) Hedging rule optimization for water supply reservoirs system. Water Resour Manag 13(6):409–426

  • Ranjbar N, Anvari S, Delavar M (2021) The application of harmony search and genetic algorithms for the simultaneous optimization of integrated reservoir–FARM systems (IRFS). https://doi.org/10.1002/ird.2567

    Book  Google Scholar 

  • Sasireka K, Neelakantan TR (2017) Optimization of hedging rules for hydropower reservoir operation. Scientia Iranica 24(5):2242–2252

    Google Scholar 

  • Shiau JT (2009) Optimization of reservoir hedging rules using multi-objective genetic algorithm. J Water Resour Plan Manag 135(5):355–363

    Article  Google Scholar 

  • Shih JS, ReVelle C (1994) Water-supply operations during drought: continuous hedging rule. J Water Resour Plan Manag 120(5):613–629

    Article  Google Scholar 

  • Soundharajan BS, Adeloye AJ, Remesan R (2016) Evaluating the variability in surface water reservoir planning characteristics during climate change impacts assessment. J Hydrol 538(10):625–639

    Article  Google Scholar 

  • Spiliotis M, Mediero L, Garrote L (2016) Optimization of hedging rules for reservoir operation during droughts based on particle swarm optimization. Water Resour Manag 30:5759–5778

    Article  Google Scholar 

  • Srinivasan K, Kumar K (2018) Multi-objective simulation-optimization model for long-term reservoir operation using piecewise linear hedging rule. Water Resour Manag 32:1901–1911

    Article  Google Scholar 

  • Srinivasan K, Philipose MC (1998) Effect of hedging on over-year reservoir performance. Water Resour Manag 12(2):95–120

    Article  Google Scholar 

  • Taghian M, Rosbjerg D, Haghighi A, Madsen H (2014) Optimization of conventional rule curves coupled with hedging rules for reservoir operation. J Water Resour Plan Manag 140(5):693–698

    Article  Google Scholar 

  • Vicente-Serrano SM, Begueria S, Lopez-Moreno JI (2010) A multi-scalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index - SPEI. J Clim 23:1696–1718. https://doi.org/10.1175/2009JCLI2909.1

    Article  Google Scholar 

  • Wurbs R (1993) Reservoir-system simulation and optimization models. J Water Resour Plan Manag 119(4):455–472

    Article  Google Scholar 

  • Yeh WWG (1985) Reservoir management and operations models: a state of-the-art review. Water Resour Res 21(12):1797–1818

    Article  Google Scholar 

  • Anvari S, Mousavi, S.J, Morid, S. (2017). Stochastic dynamic programming-based approach for optimal irrigation scheduling under restricted water availability conditions. Irrig Drain, 66(4), 492-500. https://doi.org/10.1002/ird.2130.

  • Doorenbos J, Kassam AH (1979) Yield response to water. In: Irrigation and Drainage. Paper 33. FAO, Rome. Italy

  • McKee TB, Doesken NJ, Kleist J (1995) Drought monitoring with multiple time scales. In: 482 9th Conference on Applied Climatology, American Meteorological Society 233-236

  • Moghaddasi M, Anvari S, Akhondi N (2022a) A trade-off analysis of adaptive and non-adaptive future optimized rule curves based on simulation algorithm and hedging rules. Theor Appl Climatol 148(65-78)

  • Shiau JT (2011) Analytical optimal hedging with explicit incorporation of reservoir release and carryover storage targets. Water Resour Res 47(1). https://doi.org/10.1029/2010WR009166

  • You JY, Cai X (2008a) Hedging rule for reservoir operations: 1. A theoretical analysis. Water Resour Res 44(1). https://doi.org/10.1029/2006WR005482

  • You JY, Cai X (2008b) Hedging rule for reservoir operations: 2. A numerical model. Water Resour Res 44(1). https://doi.org/10.1029/2006WR005481

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Acknowledgements

This research work was supported by the Graduate University of Advanced Technology (Institute of Science and High Technology and Environmental Science) (No. 97/2659). The authors gratefully acknowledge this help.

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The software used in this research will be available (by the corresponding author) upon reasonable request.

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Authors and Affiliations

  1. Department of Ecology, Institute of Science and High Technology and Environmental Science, Graduate University of Advanced Technology, Kerman, Iran

    Sedigheh Anvari

  2. Faculty of Agriculture and Environment, Department of Water Science and Engineering, Water Institute, Arak University, Arak, Iran

    Mahnoosh Moghaddasi

  3. Ph.D. Candidate in Water Resources Engineering and Management., Civil Engineering, University of Isfahan, Isfahan, Iran

    Mohammad Hossein Bagheri

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  1. Sedigheh Anvari
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Contributions

Sedigheh Anvari and Mahnoosh Moghaddasi: Conceptualization, methodology, technical investigation, writing, reviewing and editing, visualization, supervision, software, data curation, validation, editing. Mohammad Hossein Bagheri: Data collection

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Correspondence to Sedigheh Anvari.

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Anvari, S., Moghaddasi, M. & Bagheri, M.H. Drought mitigation through a hedging-based model of reservoir-farm systems considering climate and streamflow variations. Theor Appl Climatol 152, 723–737 (2023). https://doi.org/10.1007/s00704-023-04402-7

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