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Modeling of Water Resources Allocation and Water Quality Management for Supporting Regional Sustainability under Uncertainty in an Arid Region

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Abstract

In this study, a scenario-based interval-stochastic fraticle optimization with Laplace criterion (SISFL) method is developed for sustainable water resources allocation and water quality management (WAQM) under multiple uncertainties. SISFL can tackle uncertainties presented as interval parameters and probability distributions; meanwhile, it can also quantify artificial fuzziness such as risk-averse attitude in a decision-making issue. Besides, it can reflect random scenario occurrence under the supposition of no data available. The developed method is applied to a real case of water resources allocation and water quality management in the Kaidu-kongque River Basin, where encounter serve water deficit and water quality degradation simultaneously in Northwest China. Results of water allocation pattern, pollution mitigation scheme, and system benefit under various scenarios are analyzed. The tradeoff between economic activity and water-environment protection with interval necessity levels and Laplace criterions can support policymakers generating an effective and robust manner associated with risk control for WAQM under multiple uncertainties. These discoveries avail local policymakers gain insight into the capacity planning of water-environment to satisfy the basin’s integrity of socio-economic development and eco-environmental sustainability.

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Acknowledgements

This research was supported by the National Key Research Development Program of China (2016YFA0601502 and 2016YFC0502803). The authors are grateful to the editors and the anonymous reviewers for their insightful comments and suggestions.

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Authors and Affiliations

  1. Capital University of Economics and Business, Beijing, 10070, China

    X. T. Zeng

  2. University of Regina, Regina, Sask, S4S 0A2, Canada

    X. T. Zeng

  3. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China

    Y. P. Li

  4. Faculty of Engineering and Applied Sciences, University of Regina, Regina, Sask, S4S 0A2, Canada

    G. H. Huang

  5. Department of Environmental Engineering, Xiamen University of Technology, Xiamen, 361024, China

    J. Liu

Authors
  1. X. T. Zeng
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  2. Y. P. Li
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  3. G. H. Huang
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  4. J. Liu
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Corresponding author

Correspondence to Y. P. Li.

Appendix

Appendix

1.1 Subscript

j:

District: j = 1 Kuerle, j = 2 Yanqi, j = 3 Hejing, j = 4 Heshuo, j = 5 Bohu and j = 6 Yuli;

m:

Municipal sector: m = 1 Residential use, m = 2 Municipal services;

n:

Agriculture sector: n = 1 Cearl, n = 2 Cotton, n = 3 Oil plants, n = 4 Vegetable, n = 5 Fruit;

i:

Industrial sector: i = 1 Agricultural processing industry, i = 2 oil industry, i = 3 Chemical Industry;

k:

Ecological sector: k = 1 Forest, k = 2 Safe water level of river and reservoir.

h:

Water level: h = 1 Low, h = 2 Medium, h = 3 High;

1.2 Notation

f 1 :

system benefit without restricted policy (US $).

BM mj ,BA nj ,BI ij ,BE kj :

net benefit for municipality / agriculture / industry / ecology in district j per volume of water being delivered (US $/ m3).

WLM mj ,WLA nj ,WLI ij ,WLE kj :

water demand target for municipality / agriculture / industry / ecology in district j (m3).

WLM mjmax,WLA njmax,WLI ijmax :

the maximum water demand target for municipality / agriculture / industry in district j (m3).

POM mj :

the coefficient of waste water discharge per volume of water being used for municipality in district j.

ua nj :

The coefficient of water consumption per unit area for agriculture in district j (m3/ ha).

IRA nj :

the coefficient of pollution discharge of per volume of water being used for agriculture in district j.

IRI ij :

the coefficient of waste water discharge per volume of water being used for industry in district j.

p hj :

probability of random water availability \( {QR}_{ij}^{\pm } \) under level h(%).

α, η :

recycling ratio of municipality / industry in district j.

SLM mj ,SLA nj ,SLI ij ,SLE kj :

water shortage for municipality / agriculture / industry / ecology in district j (m3).

CM mj ,CA nj ,CI ij :

recycling cost for municipality / agriculture / industry in district j (US $/ m3).

QK jh :

water availability from river and underground of district j under probabilityp hj (m3).

QR jh :

water flow from river of district j in period t under probabilityp hj (m3).

E j :

evaporation and infiltration loss of water from river of district j (m3).

H j :

normal water requirement of watercourse of district j (m3).

QU j :

water availability from underground water of district j (m3).

CTM mj ,CTI ij :

maximum capacity of recycling for municipality / industry in district j.

dm COD ,dm TN ,dm TP :

the content of COD / TN / TP per volume of waste water for municipality in district j.

di COD ,di TN ,di TP :

the content of COD / TN / TP per volume of waste water for industry in district j.

dar TP ,dar TN :

dissolved TN /TP content of runoff corresponding to agricultural activity i in district j (%).

das TN ,das TP :

TN / TP content of soil corresponding to agricultural activity i in zone j (kg/t).

\( {SA}_{nj}^{\pm } \) :

soil loss from agricultural activity i in zone j (t/km2).

DCM mjh ,DNM mjh ,DPM mjh :

maximum allowable COD / TN / TP discharge for municipality in district j with probability p hj of occurrence under scenario h (ton).

DCI ijh ,DNI ijh ,DPI ijh :

maximum allowable COD / TN / TP discharge for industry in district j with probability p hj of occurrence under scenario h (ton).

DCA njh ,DNA njh ,DPA njh :

maximum allowable COD / TN / TP discharge for in district j with probability p hj of occurrence under scenario h (ton).

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Zeng, X.T., Li, Y.P., Huang, G.H. et al. Modeling of Water Resources Allocation and Water Quality Management for Supporting Regional Sustainability under Uncertainty in an Arid Region. Water Resour Manage 31, 3699–3721 (2017). https://doi.org/10.1007/s11269-017-1696-4

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