Skip to main content

Advertisement

SpringerLink
Log in

Optimal Water Allocation of Surface and Ground Water Resources Under Climate Change with WEAP and IWOA Modeling

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

The water evaluation and planning (WEAP) approach and the invasive weed optimization algorithm (IWOA) are herein employed to determine the optimal operating policies in conjunctive (surface water/groundwater) systems for water supply in agricultural municipal/industrial (M&I) sectors under climate change. Climatic variables are simulated with atmospheric-ocean general circulation models (AOGCMs) under emission scenarios A2 and B2 during the baseline period 1971–2000 and the future periods 2040–2069 and 2070–2099 in the Khorramabad basin, Iran. The Hadley Centre Coupled Model, version 3 (HadCM3), and the Canadian Global Coupled Model, version 2 (CGCM2), produced superior temperature and rainfall projections, respectively, than other climate models. Under both emissions scenarios and during each future period, this study indicates an increase in temperature and a decrease in rainfall. Simulations of surface water with the IHACRES (Identification of unit Hydrographs And Component flows from Rainfall, Evaporation and Streamflow data) calibrated model shows a decrease in the future runoff. The Groundwater Modeling System (GMS) calibrated software projects a decrease in water level and a decrease in recharge under climate change scenarios. Simulation results from IHACRES and GMS are input to the Water Evaluation and Planning (WEAP) system to develop operational policies for the combined use of water resources., The water-allocation reliability of the system is estimated with the WEAP system for 24 scenarios reflecting climate change scenarios assuming increases in water demand, ranging from 10 to 60% in agriculture and from 20 to 30% in the municipal and industrial (M&I) sector. The IWOA is applied to optimize the conjunctive system of water resources (i.e., surface water and groundwater). The objective function is to maximize the system's water allocation reliability. The range of optimal water-allocation reliability changes is between 3 and 16%, with the lowest increase corresponding to the baseline period for agricultural water demand, and the highest rise corresponding to an increase of 50% in water demand under the B2 emissions scenario in 2040–2069 for the M&I water sector.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Availability of Data and Materials

Authors have no restrictions on sharing data.

References

  • Alamanos A, Latinopoulos D, Loukas A, Mylopoulos N (2020) Comparing two hydro-economic approaches for multi-objective agricultural water resources planning. Water Resour Manage 34:4511–4526. https://doi.org/10.1007/s11269-020-02690-6

    Article  Google Scholar 

  • Asgari HR, Bozorg-Haddad O, Pazoki M, Loáiciga HA (2016) Weed optimization algorithm for optimal reservoir operation. J Irrig Drain Eng 142(2). https://doi.org/10.1061/(ASCE)IR.1943-4774.0000963

  • Azadi F, Ashofteh P-S, Shokri A, Loáiciga HA (2021) Simulation-optimization of reservoir water quality under climate change. J Water Resour Plan Manag 147(9)

  • Azari A, Hamzeh S, Naderi S (2018) Multi-objective optimization of the reservoir system operation by using the hedging policy. Water Resour Manage 32(6):2061–2078. https://doi.org/10.1007/s11269-018-1917-5

    Article  Google Scholar 

  • Chen H-T, Wang W-C, Chau K-W, Xu L, He J (2021) Flood control operation of reservoir group using Yin-Yang Firefly Algorithm. Water Resour Manage 35(15):5325–5345

    Article  Google Scholar 

  • Golfam P, Ashofteh P-S, Loáiciga HA (2019) Evaluation of the VIKOR and FOWA multi-criteria decision making methods for climate-change adaptation of agricultural water supply. Water Resour Manage 33(8):2867–2884. https://doi.org/10.1007/s11269-019-02274-z

    Article  Google Scholar 

  • Golfam P, Ashofteh P-S, Loáiciga HA (2021) Modeling adaptation policies to increase the synergies of water-climate-agriculture nexus under climate change. Environmental Development 37:100612. https://doi.org/10.1016/j.envdev.2021.100612

    Article  Google Scholar 

  • IPCC-TGCIA (1999) Guidelines on the use of scenario data for climate impact and adaptation assessment. (eds) Carter TR, Hulme M, Lal M, Version 1, 69pp. Intergovernmental Panel on Climate Change, Task Group on Scenarios for Climate Impact Assessment

  • IPCC (2007) Summary for Policymakers. In: Climate Chang 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, USA, pp 18

  • Jakemann AJ, Hornberger GM (1993) How much complexity is warranted in a rainfall-runoff model? Water Resour Res 29(8):2637–2649. https://doi.org/10.1029/93WR00877

    Article  Google Scholar 

  • Jones PD, Hulme M (1996) Calculating regional climatic time series for temperature and precipitation: Methods and illustrations. Int J Climatol 16(4):361–377

    Article  Google Scholar 

  • Lane ME, Kirshen PH, Vogel RM (1999) Indicators of impact of global climate change on U.S. water resources. J Water Resour Plan Manag 125(4):194–204. https://doi.org/10.1061/(ASCE)0733-9496(1999)125:4(194)

  • Li X, Wang X, Guo H, Ma W (2020) Multi-water resources optimal allocation based on multi-objective uncertain chance-constrained programming model. Water Resour Manage 34:4881–4899. https://doi.org/10.1007/s11269-020-02697-z

    Article  Google Scholar 

  • Majedi H, Fathian H, Nikbakht-Shahbazi A, Zohrabi N, Hassani F (2021) Multi-objective optimization of integrated surface and groundwater resources under the clean development mechanism. Water Resour Manage 35:2685–2704. https://doi.org/10.1007/s11269-021-02860-0

    Article  Google Scholar 

  • Mehrabian AR, Lucas C (2006) A novel numerical optimization algorithm inspired from weed colonization. Eco Inform 1(4):355–366. https://doi.org/10.1016/j.ecoinf.2006.07.003

    Article  Google Scholar 

  • Mitchell TD (2003) Pattern scaling: An examination of the accuracy of the technique for describing future climates. Clim Change 60(3):217–242

    Article  Google Scholar 

  • Mousavi SJ, Rafiee Anzab N, Asl-Rousta B, Kim JH (2017) Multi-objective optimization-simulation for reliability-based inter-basin water allocation. Water Resour Manage 31(11):3445–3464. https://doi.org/10.1007/s11269-017-1678-6

    Article  Google Scholar 

  • Moutsopoulos KN, Papaspyros JNE, Tsihrintzis VA (2017) Management of groundwater resources using surface pumps: Optimization using genetic algorithms and the tabu search method. KSCE J Civ Eng 21(7):2968–2976. https://doi.org/10.1007/s12205-017-1013-z

    Article  Google Scholar 

  • Pyne D (2005) Aquifer Storage Recovery. ASR Systems LLC, Gainesville, Florida

  • Safavi HR, Enteshari S (2016) Conjunctive use of surface and ground water resources using the antsystem optimization. Agric Water Manag 173:23–34. https://doi.org/10.1016/j.agwat.2016.05.001

    Article  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 33:2123–2137. https://doi.org/10.1007/s11269-019-02229-4

    Article  Google Scholar 

  • Tabari MMR, Soltani J (2013) Multi-objective optimal model for conjunctive use management using SGAs and NSGA-II models. Water Resour Manage 27(1):37–53. https://doi.org/10.1007/s11269-012-0153-7

    Article  Google Scholar 

  • Taormina R, Chau K-W (2015) ANN-based interval forecasting of streamflow discharges using the LUBE method and MOFIPS. Eng Appl Artif Intell 45:429–440

    Article  Google Scholar 

  • van der Voorn T, Svenfelt Å, Björnberg KE, Fauré E, Milestad R (2020) Envisioning carbon-free land use futures for Sweden: a scenario study on conflicts and synergies between environmental policy goals. Reg Environ Chang 20(35). https://doi.org/10.1007/s10113-020-01618-5

  • Wang W-C, Du Y-J, Chau K-W, Xu D-M, Liu C-J, Ma Q (2021) An ensemble hybrid forecasting model for annual runoff based on sample entropy, secondary decomposition, and long short-term memory neural network. Water Resour Manage 35(14):4695–4726

    Article  Google Scholar 

  • Wilby RL, Harris I (2006) A framework for assessing uncertainties in climate change impacts: Low flow scenarios for the River Thames, UK. Water Resour Res 42(2):W02419. https://doi.org/10.1029/2005WR004065

    Article  Google Scholar 

  • Wu X, Zheng Y, Wu B, Tian Y, Han F, Chunmiao Zh (2016) Optimizing conjunctive use of surface water and groundwater for irrigation to address human-nature water conflicts: A surrogate modeling approach. Agric Water Manag 163:380–392. https://doi.org/10.1016/j.agwat.2015.08.022

    Article  Google Scholar 

  • Wu CL, Chau K-W (2013) Prediction of rainfall time series using modular soft computing methods. Eng Appl Artif Intell 26(3):997–1007

    Article  Google Scholar 

  • Xie H, Randall M, Chau K-W (2022) Green roof hydrological modelling with GRU and LSTM networks. Water Resour Manage 36(3):1107–1122

    Article  Google Scholar 

  • Yang C-C, Chang L-C, Chen CS, Yeh MS (2009) Multi-objective planning for conjunctive use of surface and subsurface water using genetic algorithm and dynamics programming. Water Resour Manage 23(3):417–437. https://doi.org/10.1007/s11269-008-9281-5

    Article  Google Scholar 

  • Zheng F, Qi Zh, Zhange T, Yu T, Shao Y (2017) Improved Understanding on the Searching Behavior of NSGA-II Operators Using Run-Time Measure Metrics with Application to Water Distribution System Design Problems. Water Resour Manage 31(4):1121–1138

    Article  Google Scholar 

Download references

Funding

Not applicable.

Author information

Authors and Affiliations

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

    Seyedeh Hadis Moghadam & Parisa-Sadat Ashofteh

  2. Department of Geography, University of California, Santa Barbara, CA, 93016-4060, USA

    Hugo A. Loáiciga

Authors
  1. Seyedeh Hadis Moghadam
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Parisa-Sadat Ashofteh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hugo A. Loáiciga
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Seyedeh Hadis Moghadam developed the theory and performed the computations. Parisa-Sadat Ashofteh verified the analytical methods and encouraged Seyedeh Hadis Moghadam to investigate a specific aspect. Parisa-Sadat Ashofteh supervised the findings of this work. All authors discussed the results and contributed to the final manuscript. Seyedeh Hadis Moghadam wrote the manuscript with support from Parisa-Sadat Ashofteh, and especially Loáiciga. Parisa-Sadat Ashofteh conceived the original idea.

Corresponding author

Correspondence to Parisa-Sadat Ashofteh.

Ethics declarations

Conflict of Interest

None.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moghadam, S.H., Ashofteh, PS. & Loáiciga, H.A. Optimal Water Allocation of Surface and Ground Water Resources Under Climate Change with WEAP and IWOA Modeling. Water Resour Manage 36, 3181–3205 (2022). https://doi.org/10.1007/s11269-022-03195-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-022-03195-0

Keywords

Search

Navigation