IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v32y2018i11d10.1007_s11269-018-2019-0.html
   My bibliography  Save this article

Modeling and Combined Application of Orthogonal Chaotic NSGA-II and Improved TOPSIS to Optimize a Conceptual Hydrological Model

Author

Listed:
  • Tian Peng

    (Huazhong University of Science and Technology
    Hubei Key Laboratory of Digital Valley Science and Technology)

  • Jianzhong Zhou

    (Huazhong University of Science and Technology
    Hubei Key Laboratory of Digital Valley Science and Technology)

  • Chu Zhang

    (Huazhong University of Science and Technology
    Hubei Key Laboratory of Digital Valley Science and Technology)

  • Na Sun

    (Huazhong University of Science and Technology
    Hubei Key Laboratory of Digital Valley Science and Technology)

Abstract

Conceptual rainfall-runoff modelling is a widely-used approach for rainfall-runoff simulation in streamflow forecasting. The objective of this paper is to introduce an improved non-dominated sorting genetic algorithm-II (NSGA-II) for multi-objective automatic calibration of a hydrologic model. The orthogonal design based initialization technique is exploited to produce a more uniformly-distributed initial population. At the same time, a chaotic crossover operator as well as a chaotic mutation operator are presented to avoid trapping into local minima and to obtain high quality solutions. Finally, a multi-criteria decision-making (MCDM) approach combing Shannon entropy weighting method and an improved technique for order preference by similarity to ideal solution (ITOPSIS) based on projection is introduced to prioritize the Pareto optimal solutions and select the comprehensive optimal solution as a follow-up step. Hydrological data from two river basins named the Leaf and Muma River basins are exploited to test the ability of the orthogonal chaotic NSGA-II (OCNSGA-II) for solving the multi-objective HYMOD (MO-HYMOD) problem. The results demonstrate that the OCNSGA-II can obtain better-distributed Pareto optimal front and thus can be exploited as an effective alternative approach for the multi-objective automatic calibration of hydrologic model.

Suggested Citation

  • Tian Peng & Jianzhong Zhou & Chu Zhang & Na Sun, 2018. "Modeling and Combined Application of Orthogonal Chaotic NSGA-II and Improved TOPSIS to Optimize a Conceptual Hydrological Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(11), pages 3781-3799, September.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:11:d:10.1007_s11269-018-2019-0
    DOI: 10.1007/s11269-018-2019-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-018-2019-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-018-2019-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jun Guo & Jianzhong Zhou & Qiang Zou & Yi Liu & Lixiang Song, 2013. "A Novel Multi-Objective Shuffled Complex Differential Evolution Algorithm with Application to Hydrological Model Parameter Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2923-2946, June.
    2. Junhong Zhang & Lu Chen & Vijay Singh & Hongwen Cao & Dangwei Wang, 2015. "Determination of the distribution of flood forecasting error," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(2), pages 1389-1402, January.
    3. Junhong Zhang & Lu Chen & Vijay Singh & Wenhong Cao & Dangwei Wang, 2015. "Erratum to: Determination of the distribution of flood forecasting error," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(2), pages 2065-2065, January.
    4. Feifei Zheng & Zhexian Qi & Weiwei Bi & Tuqiao Zhang & Tingchao Yu & Yu Shao, 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 Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1121-1138, March.
    5. Jianzhong Zhou & Shuo Ouyang & Xuemin Wang & Lei Ye & Hao Wang, 2014. "Multi-Objective Parameter Calibration and Multi-Attribute Decision-Making: An Application to Conceptual Hydrological Model Calibration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 767-783, February.
    6. Gift Dumedah & Aaron Berg & Mark Wineberg & Robert Collier, 2010. "Selecting Model Parameter Sets from a Trade-off Surface Generated from the Non-Dominated Sorting Genetic Algorithm-II," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4469-4489, December.
    7. Gift Dumedah, 2012. "Formulation of the Evolutionary-Based Data Assimilation, and its Implementation in Hydrological Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3853-3870, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shuai Zhou & Yimin Wang & Ziyan Li & Jianxia Chang & Aijun Guo, 2021. "Quantifying the Uncertainty Interaction Between the Model Input and Structure on Hydrological Processes," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 3915-3935, September.
    2. Tian Peng & Chu Zhang & Jianzhong Zhou & Xin Xia & Xiaoming Xue, 2019. "Multi-Objective Optimization for Flood Interval Prediction Based on Orthogonal Chaotic NSGA-II and Kernel Extreme Learning Machine," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4731-4748, November.
    3. Chu Zhang & Tian Peng & Chaoshun Li & Wenlong Fu & Xin Xia & Xiaoming Xue, 2019. "Multiobjective Optimization of a Fractional-Order PID Controller for Pumped Turbine Governing System Using an Improved NSGA-III Algorithm under Multiworking Conditions," Complexity, Hindawi, vol. 2019, pages 1-18, February.
    4. Babak Zolghadr-Asli & Omid Bozorg-Haddad & Maedeh Enayati & Xuefeng Chu, 2021. "A review of 20-year applications of multi-attribute decision-making in environmental and water resources planning and management," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 14379-14404, October.
    5. Peng, Tian & Zhang, Chu & Zhou, Jianzhong & Nazir, Muhammad Shahzad, 2020. "Negative correlation learning-based RELM ensemble model integrated with OVMD for multi-step ahead wind speed forecasting," Renewable Energy, Elsevier, vol. 156(C), pages 804-819.
    6. Adam P. Piotrowski & Marzena Osuch & Jarosław J. Napiorkowski, 2019. "Joint Optimization of Conceptual Rainfall-Runoff Model Parameters and Weights Attributed to Meteorological Stations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(13), pages 4509-4524, October.
    7. Tian Peng & Chu Zhang & Jianzhong Zhou, 2019. "Intra- and Inter-Annual Variability of Hydrometeorological Variables in the Jinsha River Basin, Southwest China," Sustainability, MDPI, vol. 11(19), pages 1-17, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Minglong Dai & Jianzhong Zhou & Xiang Liao, 2016. "Research on Combination Forecast Mode of Conceptual Hydrological Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4483-4499, October.
    2. Jianzhong Zhou & Shuo Ouyang & Xuemin Wang & Lei Ye & Hao Wang, 2014. "Multi-Objective Parameter Calibration and Multi-Attribute Decision-Making: An Application to Conceptual Hydrological Model Calibration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 767-783, February.
    3. Shirisha Pulukuri & Venkata Reddy Keesara & Pratap Deva, 2018. "Flow Forecasting in a Watershed using Autoregressive Updating Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(8), pages 2701-2716, June.
    4. Akshay Kadu & Basudev Biswal, 2022. "A Model Combination Approach for Improving Streamflow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 5945-5959, December.
    5. P. Shirisha & K. Venkata Reddy & Deva Pratap, 2019. "Real-Time Flow Forecasting in a Watershed Using Rainfall Forecasting Model and Updating Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4799-4820, November.
    6. Jun Guo & Jianzhong Zhou & Qiang Zou & Yi Liu & Lixiang Song, 2013. "A Novel Multi-Objective Shuffled Complex Differential Evolution Algorithm with Application to Hydrological Model Parameter Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2923-2946, June.
    7. Yawei Ning & Wei Ding & Guohua Liang & Bin He & Huicheng Zhou, 2021. "An Analytical Risk Analysis Method for Reservoir Flood Control Operation Considering Forecast Information," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2079-2099, May.
    8. He, Zhongzheng & Zhou, Jianzhong & Xie, Mengfei & Jia, Benjun & Bao, Zhengfeng & Qin, Hui & Zhang, Hairong, 2019. "Study on guaranteed output constraints in the long term joint optimal scheduling for the hydropower station group," Energy, Elsevier, vol. 185(C), pages 1210-1224.
    9. Shuo Ouyang & Jianzhong Zhou & Chunlong Li & Xiang Liao & Hao Wang, 2015. "Optimal Design for Flood Limit Water Level of Cascade Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(2), pages 445-457, January.
    10. Jiazheng Lu & Jun Guo & Li Yang & Xunjian Xu, 2017. "Research of reservoir watershed fine zoning and flood forecasting method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(3), pages 1291-1306, December.
    11. Seyedeh Hadis Moghadam & Parisa-Sadat Ashofteh & Hugo A. Loáiciga, 2022. "Optimal Water Allocation of Surface and Ground Water Resources Under Climate Change with WEAP and IWOA Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3181-3205, July.
    12. Tao Bai & Lianzhou Wu & Jian-xia Chang & Qiang Huang, 2015. "Multi-Objective Optimal Operation Model of Cascade Reservoirs and Its Application on Water and Sediment Regulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2751-2770, June.
    13. Zeinab Takbiri & Abbas Afshar, 2012. "Multi-Objective Optimization of Fusegates System under Hydrologic Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(8), pages 2323-2345, June.
    14. Jian Yin & Chesheng Zhan & Wen Ye, 2016. "An Experimental Study on Evapotranspiration Data Assimilation Based on the Hydrological Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5263-5279, November.
    15. Zhou, Jianzhong & Zhang, Yongchuan & Zhang, Rui & Ouyang, Shuo & Wang, Xuemin & Liao, Xiang, 2015. "Integrated optimization of hydroelectric energy in the upper and middle Yangtze River," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 481-512.
    16. Ahmad Sharafati & Siyamak Doroudi & Shamsuddin Shahid & Ali Moridi, 2021. "A Novel Stochastic Approach for Optimization of Diversion System Dimension by Considering Hydrological and Hydraulic Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3649-3677, September.
    17. Wen-jing Niu & Zhong-kai Feng & Yu-rong Li & Shuai Liu, 2021. "Cooperation Search Algorithm for Power Generation Production Operation Optimization of Cascade Hydropower Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2465-2485, June.
    18. Wen-jing Niu & Zhong-kai Feng & Shuai Liu & Yu-bin Chen & Yin-shan Xu & Jun Zhang, 2021. "Multiple Hydropower Reservoirs Operation by Hyperbolic Grey Wolf Optimizer Based on Elitism Selection and Adaptive Mutation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 573-591, January.
    19. Hairong Zhang & Jianzhong Zhou & Lei Ye & Xiaofan Zeng & Yufan Chen, 2015. "Lower Upper Bound Estimation Method Considering Symmetry for Construction of Prediction Intervals in Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5505-5519, December.
    20. Akbar Shirzad & Massoud Tabesh & Behzad Atayikia, 2017. "Multiobjective Optimization of Pressure Dependent Dynamic Design for Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2561-2578, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:32:y:2018:i:11:d:10.1007_s11269-018-2019-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.