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Developing an optimized groundwater exploitation prediction model based on the Harris hawk optimization algorithm for conjunctive use of surface water and groundwater resources

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Abstract

Due to the lack of surface water and groundwater resources, especially in the agricultural parts, the simultaneous and sustainable use of water resources to supply water demands is essential. In this study, a conjunctive use optimization model is developed to minimize the shortage of water demand. This model is implemented for the Mahabad study area in northwestern Iran to improve the conditions of surface water and groundwater resources and the reclamation of Urmia Lake. For this purpose, the current research is accomplished in three parts. At first, the Mahabad aquifer is numerically simulated to investigate the aquifer conditions. In the second part, the optimized model of conjunctive use obtained by the Harris hawk optimization (HHO) algorithm is investigated over a 20-year period in the study area. In the last part of this research, seven scenarios are developed to predict the optimized groundwater exploitation (OGE) using the results of HHO, meteorological data, and some input information on the dam reservoir. Then, the OGE values are predicted using the artificial neural network (ANN) and ANN-HHO machine learning models for the scenarios. The results showed that the scenario that includes all input variables and the ANN-HHO model outperformed other models. Furthermore, the HHO algorithm provides suitable allocation of the surface water and groundwater resources in optimized conjunctive use and also improves the performance of ANN in predicting the OGE values. The findings of this study also show that groundwater resources can be more applied to supply water demand, and in contrast, surface water resources can be used for supplying downstream environmental demands and reclamation of Urmia Lake.

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References

  • Afshar A, Khosravi M, Ostadrahimi L, Afshar A (2020) Reliability-based multi-objective optimum design of nonlinear conjunctive use problem; cyclic storage system approach. J Hydrol 588:125109

    Article  Google Scholar 

  • Ahmadzadeh H, Morid S, Delavar M, Srinivasan R (2016) Using the SWAT model to assess the impacts of changing irrigation from surface to pressurized systems on water productivity and water saving in the Zarrineh Rud catchment. Agric Water Manag 175:15–28

    Article  Google Scholar 

  • Al-qaness MAA, Ewees AA, Fan H, Abualigah L, Elaziz MA (2022a) Boosted ANFIS model using augmented marine predator algorithm with mutation operators for wind power forecasting. Appl Energy 314:118851

    Article  Google Scholar 

  • Al-qaness MAA, Ewees AA, Fan H, AlRassas AM, Elaziz MA (2022b) Modified Aquila optimizer for forecasting oil production. Geo-Spatial Inf Sci. https://doi.org/10.1080/10095020.2022.2068385

    Article  Google Scholar 

  • AlRassas AM, Al-qaness MAA, Ewees AA, Ren S, Sun R, Pan L, Elaziz MA (2022) Advance artificial time series forecasting model for oil production using neuro fuzzy-based slime mould algorithm. J Pet Explor Prod Technol 12:383–395

    Article  Google Scholar 

  • Anderson JA (1995) An introduction to neural networks. MIT Press, Cambridge, MA. https://doi.org/10.7551/mitpress/3905.001.0001

  • Arthington AH (2022) Environmental flows: history of assessment methods, ecosystem frameworks and global uptake. Treatise on Geomorphology (Second Edition) 6.2:1277–1295. https://doi.org/10.1016/B978-0-12-409548-9.12450-9

  • Arya Azar N, Kardan N, Ghordoyee Milan S (2021) Developing the artificial neural network–evolutionary algorithms hybrid models (ANN–EA) to predict the daily evaporation from dam reservoirs. Eng Comput. https://doi.org/10.1007/s00366-021-01523-3

  • Arya Azar N, Kayhomayoon Z, Ghordoyee Milan S, Zarif Sanayei H, Berndtsson R, Nematollahi Z (2022) A hybrid approach based on simulation, optimization, and estimation of conjunctive use of surface water and groundwater resources. Environ Sci Pollut Res 29:56828–56844

  • Barlow PM, Ahlfeld DP, Dickerman DC (2003) Conjunctive-management models for sustained yield of stream-aquifer systems. J Water Resour Plan Manag 129(1):35–48

    Article  Google Scholar 

  • Bui DT, Moayedi H, Kalantar B, Osouli A, Pradhan B, Nguyen H, Rashid ASA (2019) A novel swarm intelligence—Harris hawks optimization for spatial assessment of landslide susceptibility. Sensors 19(16):3590

    Article  Google Scholar 

  • Chang LC, Chu HJ, Chen YW (2013) A fuzzy inference system for the conjunctive use of surface and subsurface water. Adv Fuzzy Syst 2013:128393

  • Chen YW, Chang LC, Huang CW, Chu HJ (2013) Applying genetic algorithm and neural network to the conjunctive use of surface and subsurface water. Water Resour Manage 27(14):4731–4757

    Article  Google Scholar 

  • Dawadi S, Ahmad S (2013) Evaluating the impact of demand-side management on water resources under changing climatic conditions and increasing population. J Environ Manage 114:261–275

    Article  Google Scholar 

  • Dehghanipour AH, Schoups G, Zahabiyoun B, Babazadeh H (2020) Meeting agricultural and environmental water demand in endorheic irrigated river basins: a simulation-optimization approach applied to the Urmia Lake basin in Iran. Agric Water Manag 241:106353

    Article  Google Scholar 

  • Forte A, Trobia F, Gualtieri F, Lamis DA, Cardamone G, Giallonardo V, Pompili M (2018) Suicide risk among immigrants and ethnic minorities: a literature overview. Int J Environ Res Public Health 15(7):1438

    Article  Google Scholar 

  • Gleick PH, Palaniappan M (2010) Peak water limits to freshwater withdrawal and use. Proc Natl Acad Sci 107(25):11155–11162

    Article  CAS  Google Scholar 

  • Harbaugh AW, Banta ER, Hill MC, McDonald MG (2000) Modflow-2000, the U.S. geological survey modular groundwater model-user guide to modularization concepts and the groundwater flow process. Open-file report. U. S. Geological Survey 92:134

  • Hasanzadeh SK, Saadatpour M, Afshar A (2020) A fuzzy equilibrium strategy for sustainable water quality management in river-reservoir system. J Hydrol 586:124892

    Article  CAS  Google Scholar 

  • Haykin S, Nie J, Currie B (1999) Neural network-based receiver for wireless communications. Electron Lett 35(3):203–205

    Article  Google Scholar 

  • Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris hawks optimization: algorithm and applications. Futur Gener Comput Syst 97:849–872

    Article  Google Scholar 

  • Joodavi A, Izady A, Maroof MTK, Majidi M, Rossetto R (2020) Deriving optimal operational policies for off-stream man-made reservoir considering conjunctive use of surface-and groundwater at the Bar dam reservoir (Iran). J Hydrol Reg Stud 31:100725

    Article  Google Scholar 

  • Karamouz M, Tabari MMR, Kerachian R (2007) Application of genetic algorithms and artificial neural networks in conjunctive use of surface and groundwater resources. Water Int 32:163–176

    Article  Google Scholar 

  • Kayhomayoon Z, Milan SG, Arya Azar N, Bettinger P, Babaian F, Jaafari A (2022) A simulation-optimization modeling approach for conjunctive water use management in a semi-arid region of Iran. Sustainability 14(5):2691

    Article  Google Scholar 

  • Khosravi M, Afshar A, Molajou A (2022) Decision tree-based conditional operation rules for optimal conjunctive use of surface and groundwater. Water Resour Manage 36(6):2013–2025

    Article  Google Scholar 

  • Madani K, Dinar A (2012) Non-cooperative institutions for sustainable common pool resource management: application to groundwater. Ecol Econ 74:34–45

    Article  Google Scholar 

  • Mehra P, Wah BW (1991) Learning load-balancing strategies using artificial neural networks. In: Dagli CH, Kumara SRT, Shin YC (eds) Intelligent engineering systems through artificial neural networks. ASME Press, New York, pp 855–860

  • Milan SG, Roozbahani A, Azar NA, Javadi S (2021) Development of adaptive neuro fuzzy inference system–evolutionary algorithms hybrid models (ANFIS-EA) for prediction of optimal groundwater exploitation. J Hydrol 598:126258

    Article  Google Scholar 

  • Milan SG, Roozbahani A, Banihabib ME (2018) Fuzzy optimization model and fuzzy inference system for conjunctive use of surface and groundwater resources. J Hydrol 566:421–434

    Article  Google Scholar 

  • Mirzaie N, Banihabib ME, Randhir TO (2021) Fuzzy particle swarm optimization for conjunctive use of groundwater and reclaimed wastewater under uncertainty. Agric Water Manag 256:107116

    Article  Google Scholar 

  • Moayedi H, Gör M, Lyu Z, Bui DT (2020) Herding behaviors of grasshopper and Harris hawk for hybridizing the neural network in predicting the soil compression coefficient. Measurement 152:107389

    Article  Google Scholar 

  • Montazar A, Riazi H, Behbahani SM (2010) Conjunctive water use planning in an irrigation command area. Water Resour Manage 24(3):577–596

    Article  Google Scholar 

  • Morid S, Smakhtin V, Moghaddasi M (2006) Comparison of seven meteorological indices for drought monitoring in Iran. Int J Climatol 26(7):971–985

    Article  Google Scholar 

  • Parsapour-Moghaddam P, Abed-Elmdoust A, Kerachian R (2015) A heuristic evolutionary game theoretic methodology for conjunctive use of surface and groundwater resources. Water Resour Manage 29(11):3905–3918

    Article  Google Scholar 

  • Peralta RC (2001) Simulation/optimization applications and software for optimal groundwater and conjunctive water management. Int Ground Water Model Center 691–694

  • Portoghese I, Giannoccaro G, Giordano R, Pagano A (2021) Modeling the impacts of volumetric water pricing in irrigation districts with conjunctive use of surface and groundwater resources. Agric Water Manag 244:106561

    Article  Google Scholar 

  • Rafipour Langeroudi M, Kerachian R, Bazargan-Lari MR (2014) Developing operating rules for conjunctive use of surface and groundwater considering the water quality issues. KSCE J Civ Eng 18(2):454–461

    Article  Google Scholar 

  • Rezaei F, Safavi HR, Mirchi A, Madani K (2017) F-MOPSO: an alternative multi-objective PSO algorithm for conjunctive water use management. J Hydro-Environ Res 14:1–18

    Article  Google Scholar 

  • Safavi HR, Alijanian MA (2011) Optimal crop planning and conjunctive use of surface water and groundwater resources using fuzzy dynamic programming. J Irrig Drain Eng 137:383–397

    Article  Google Scholar 

  • Safavi HR, Enteshari S (2016) Conjunctive use of surface and ground water resources using the ant system optimization. Agric Water Manag 173:23–34

    Article  Google Scholar 

  • Safavi HR, Esfahani MK, Zamani AR (2014) Integrated index for assessment of vulnerability to drought, case study: Zayandehrood River Basin, Iran. Water Resour Manag 28(6):1671–1688

    Article  Google Scholar 

  • Safavi HR, Esmikhani M (2013) Conjunctive use of surface water and groundwater: application of support vector machines (SVMs) and genetic algorithms. Water Resour Manage 27(7):2623–2644

    Article  Google Scholar 

  • Safavi HR, Rezaei F (2015) Conjunctive use of surface and ground water using fuzzy neural network and genetic algorithm. Iran J Sci Technol Trans Civ Eng 39(C2):365–377

    Google Scholar 

  • Sammen SS, Ghorbani MA, Malik A, Tikhamarine Y, AmirRahmani M, Al-Ansari N, Chau KW (2020) Enhanced artificial neural network with Harris hawks optimization for predicting scour depth downstream of ski-jump spillway. Appl Sci 10(15):5160

    Article  CAS  Google Scholar 

  • Sepahvand R, Safavi HR, Rezaei F (2019) Multi-objective planning for conjunctive use of surface and ground water resources using genetic programming. Water Resour Manage 33(6):2123–2137

    Article  Google Scholar 

  • Song J, Yang Y, Sun X, Lin J, Wu M, Wu J, Wu J (2020) Basin-scale multi-objective simulation-optimization modeling for conjunctive use of surface water and groundwater in northwest China. Hydrol Earth Syst Sci 24(5):2323–2341

    Article  Google Scholar 

  • Tabari MMR (2015) Conjunctive use management under uncertainty conditions in aquifer parameters. Water Resour Manage 29(8):2967–2986

    Article  Google Scholar 

  • Tabari MMR, Yazdi A (2014) Conjunctive use of surface and groundwater with inter-basin transfer approach: case study Piranshahr. Water Resour Manage 28(7):1887–1906

    Article  Google Scholar 

  • Tikhamarine Y, Souag-Gamane D, Ahmed AN, Sammen SS, Kisi O, Huang YF, El-Shafie A (2020) Rainfall-runoff modelling using improved machine learning methods: Harris hawks optimizer vs. particle swarm optimization. J Hydrol 589:125133

  • Wang CX, Li YP, Zhuang XW (2018) Conjunctive water management under multiple uncertainties: a centroid-based type-2 fuzzy-probabilistic programming approach. Eng Appl Artif Intell 72:437–448

    Article  Google Scholar 

  • Yasi M, Ashori M (2017) Environmental flow contributions from in-basin rivers and dams for saving Urmia Lake. Iran J Sci Technol Trans Civ Eng 41(1):55–64

    Article  Google Scholar 

  • Yousefi M, Banihabib ME, Soltani J, Roozbahani A (2018) Multi-objective particle swarm optimization model for conjunctive use of treated wastewater and groundwater. Agric Water Manag 208:224–231

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Civil Engineering, Shahrekord University, Shahrekord, Iran

    Zahra Nematollahi & Hamed Reza Zarif Sanayei

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  1. Zahra Nematollahi
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  2. Hamed Reza Zarif Sanayei
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Zahra Nematollahi and Hamed Reza Zarif Sanayei contributed equally to this work, and they take responsibility for it.

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Correspondence to Hamed Reza Zarif Sanayei.

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Nematollahi, Z., Sanayei, H.R.Z. Developing an optimized groundwater exploitation prediction model based on the Harris hawk optimization algorithm for conjunctive use of surface water and groundwater resources. Environ Sci Pollut Res 30, 16120–16139 (2023). https://doi.org/10.1007/s11356-022-23224-0

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