IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v30y2016i2d10.1007_s11269-015-1183-8.html
   My bibliography  Save this article

Fuzzy Conceptual Hydrological Model for Water Flow Prediction

Author

Listed:
  • Mustafa Erkan Turan

    (Celal Bayar University)

  • Mehmet Ali Yurdusev

    (Celal Bayar University)

Abstract

Reliability in flow prediction is key to designing water resources projects. Over prediction may result in overdesign whereas under prediction brings about insufficient capacity solutions. While the former means insufficient use of financial resources, the latter may result in some water demand unmet. Therefore, so many techniques have been developed and used to make better flow prediction. In this study, this traditional problem is revisited in an attempt to improve the modeling performance of long used conceptual hydrological models. This is attained by incorporating fuzzy systems into a presently used conceptual model. The fuzzy integration process is carried out through the replacement of the storage elements of conceptual model by fuzzy systems. The case study undertaken has proved that the fuzzy conceptual model developed is quite competitive with ordinary conceptual model and promises improved predictions.

Suggested Citation

  • Mustafa Erkan Turan & Mehmet Ali Yurdusev, 2016. "Fuzzy Conceptual Hydrological Model for Water Flow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 653-667, January.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:2:d:10.1007_s11269-015-1183-8
    DOI: 10.1007/s11269-015-1183-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-015-1183-8
    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/s11269-015-1183-8?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. Rong Zhang & Celso Santos & Madalena Moreira & Paula Freire & João Corte-Real, 2013. "Automatic Calibration of the SHETRAN Hydrological Modelling System Using MSCE," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(11), pages 4053-4068, September.
    2. Ye Tian & Yue-Ping Xu & Xu-Jie Zhang, 2013. "Assessment of Climate Change Impacts on River High Flows through Comparative Use of GR4J, HBV and Xinanjiang Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2871-2888, June.
    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. Kouao Laurent Kouadio & Jianxin Liu & Serge Kouamelan Kouamelan & Rong Liu, 2023. "Ensemble Learning Paradigms for Flow Rate Prediction Boosting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(11), pages 4413-4431, 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. Mustafa Turan & Mehmet Yurdusev, 2016. "Fuzzy Conceptual Hydrological Model for Water Flow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 653-667, January.
    2. Vesna Đukić & Zoran Radić, 2016. "Sensitivity Analysis of a Physically Based Distributed Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1669-1684, March.
    3. Vesna Đukić & Zoran Radić, 2014. "GIS Based Estimation of Sediment Discharge and Areas of Soil Erosion and Deposition for the Torrential Lukovska River Catchment in Serbia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4567-4581, October.
    4. Pao-Shan Yu & Tao-Chang Yang & Chen-Min Kuo & Yi-Tai Wang, 2014. "A Stochastic Approach for Seasonal Water-Shortage Probability Forecasting Based on Seasonal Weather Outlook," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 3905-3920, September.
    5. Jian Sha & Zeli Li & Dennis Swaney & Bongghi Hong & Wei Wang & Yuqiu Wang, 2014. "Application of a Bayesian Watershed Model Linking Multivariate Statistical Analysis to Support Watershed-Scale Nitrogen Management in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3681-3695, September.
    6. Hong Li & Chong-Yu Xu & Stein Beldring & Lena Merete Tallaksen & Sharad K. Jain, 2016. "Water Resources Under Climate Change in Himalayan Basins," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 843-859, January.
    7. Wei Li & Jianzhong Zhou & Huaiwei Sun & Kuaile Feng & Hairong Zhang & Muhammad Tayyab, 2017. "Impact of Distribution Type in Bayes Probability Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(3), pages 961-977, February.
    8. Moon-Hwan Lee & Deg-Hyo Bae & Eun-Soon Im, 2019. "Effect of the Horizontal Resolution of Climate Simulations on the Hydrological Representation of Extreme Low and High Flows," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(13), pages 4653-4666, October.
    9. Hadush Meresa & Yongqiang Zhang, 2021. "Contrasting Uncertainties in Estimating Floods and Low Flow Extremes," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(6), pages 1775-1795, April.
    10. David Werth & Kuo-Fu Chen, 2015. "The Application of a Statistical Downscaling Process to Derive 21st Century River Flow Predictions Using a Global Climate Simulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(3), pages 849-861, February.
    11. Adam P. Piotrowski & Jaroslaw J. Napiorkowski & Marzena Osuch, 2019. "Relationship Between Calibration Time and Final Performance of Conceptual Rainfall-Runoff Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 19-37, January.
    12. Chengcheng Huang & Guoqiang Wang & Xiaogu Zheng & Jingshan Yu & Xinyi Xu, 2015. "Simple Linear Modeling Approach for Linking Hydrological Model Parameters to the Physical Features of a River Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3265-3289, July.
    13. Vesna Đukić & Zoran Radić, 2016. "Sensitivity Analysis of a Physically Based Distributed Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1669-1684, March.
    14. Jian Sha & Zeli Li & Dennis P. Swaney & Bongghi Hong & Wei Wang & Yuqiu Wang, 2014. "Application of a Bayesian Watershed Model Linking Multivariate Statistical Analysis to Support Watershed-Scale Nitrogen Management in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3681-3695, September.
    15. Kai Duan & Yadong Mei, 2014. "Comparison of Meteorological, Hydrological and Agricultural Drought Responses to Climate Change and Uncertainty Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(14), pages 5039-5054, November.
    16. Jiang Wu & Jianzhong Zhou & Lu Chen & Lei Ye, 2015. "Coupling Forecast Methods of Multiple Rainfall–Runoff Models for Improving the Precision of Hydrological Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5091-5108, November.
    17. Hong Li & Chong-Yu Xu & Stein Beldring & Lena Tallaksen & Sharad Jain, 2016. "Water Resources Under Climate Change in Himalayan Basins," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 843-859, January.
    18. Sheng Sheng & Hua Chen & Fu-Qiang Guo & Jie Chen & Chong-Yu Xu & Sheng-lian Guo, 2020. "Transferability of a Conceptual Hydrological Model across Different Temporal Scales and Basin Sizes," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2953-2968, July.
    19. Tianxin Li & Yuxin Duan & Shanbo Guo & Linglong Meng & Matomela Nametso, 2020. "Study on Applicability of Distributed Hydrological Model under Different Terrain Conditions," Sustainability, MDPI, vol. 12(22), pages 1-18, November.

    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:30:y:2016:i:2:d:10.1007_s11269-015-1183-8. 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.