IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v22y2008i1p1-22.html
   My bibliography  Save this article

Runoff Analysis for a Small Watershed of Tono Area Japan by Back Propagation Artificial Neural Network with Seasonal Data

Author

Listed:
  • A. Sohail
  • K. Watanabe
  • S. Takeuchi

Abstract

The rainfall runoff (R-R) process was studied for two small sub-basins having different sizes in a mountainous catchment of Tono area Japan. The runoff and other meterological data have been collected in this catchment for the last 14 years. The major objective of this study was to construct numerical models for these sub-basins to predict runoff after 1/2 and 1 h. The effects of season and the size of the catchment on R-R process were also investigated. The hydrogeological conditions of the catchment were studied prior to the analyses. The data obtained for summer (rainy) and winter (dry) seasons were treated separately in order to study the seasonal effects on the model development. The back propagation artificial neural network technique (BPANN) and the multivariate autoregressive and moving average models (ARMA) were adopted for the analysis. It was found that for very small catchments the seasonal effects are dominant and therefore separate models should be developed for each season to obtain better forecasting estimates. It was also found that the predictions by BPANN models were better than multivariate ARMA models for intense rains having complex R-R relationships in summer. On the other hand, both the modelling techniques yielded almost similar results for smaller rains in winter. It was also found clearly that the accuracy of prediction decreased with the increase of the time period for prediction. Copyright Springer Science+Business Media, Inc. 2008

Suggested Citation

  • A. Sohail & K. Watanabe & S. Takeuchi, 2008. "Runoff Analysis for a Small Watershed of Tono Area Japan by Back Propagation Artificial Neural Network with Seasonal Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(1), pages 1-22, January.
    • Handle: RePEc:spr:waterr:v:22:y:2008:i:1:p:1-22
    DOI: 10.1007/s11269-006-9141-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-006-9141-0
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11269-006-9141-0?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. Dooge, James C. I., 1973. "Linear Theory of Hydrologic Systems," Technical Bulletins 160041, United States Department of Agriculture, Economic Research Service.
    2. Avinash Agarwal & R. Singh, 2004. "Runoff Modelling Through Back Propagation Artificial Neural Network With Variable Rainfall-Runoff Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(3), pages 285-300, 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. Krishna Singh & Mahesh Pal & V. Singh, 2010. "Estimation of Mean Annual Flood in Indian Catchments Using Backpropagation Neural Network and M5 Model Tree," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(10), pages 2007-2019, August.
    2. Arash Malekian & Ali Azarnivand, 2016. "Application of Integrated Shannon’s Entropy and VIKOR Techniques in Prioritization of Flood Risk in the Shemshak Watershed, Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 409-425, January.
    3. Shin-Jen Cheng, 2010. "Generation of Runoff Components from Exponential Expressions of Serial Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(13), pages 3561-3590, October.
    4. Ferhat Gökbulak & Kamil Şengönül & Yusuf Serengil & İbrahim Yurtseven & Süleyman Özhan & Hikmet Cigizoglu & Betül Uygur, 2015. "Comparison of Rainfall-Runoff Relationship Modeling using Different Methods in a Forested Watershed," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(12), pages 4229-4239, September.
    5. Arash Malekian & Ali Azarnivand, 2016. "Application of Integrated Shannon’s Entropy and VIKOR Techniques in Prioritization of Flood Risk in the Shemshak Watershed, Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 409-425, January.
    6. Desalegn Edossa & Mukand Babel, 2011. "Application of ANN-Based Streamflow Forecasting Model for Agricultural Water Management in the Awash River Basin, Ethiopia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(6), pages 1759-1773, April.
    7. Manish Goyal & C. Ojha, 2011. "Estimation of Scour Downstream of a Ski-Jump Bucket Using Support Vector and M5 Model Tree," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(9), pages 2177-2195, July.

    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. Bhabagrahi Sahoo, 2013. "Field Application of the Multilinear Muskingum Discharge Routing Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1193-1205, March.
    2. Maria Diamantopoulou & Vassilis Antonopoulos & Dimitris Papamichail, 2007. "Cascade Correlation Artificial Neural Networks for Estimating Missing Monthly Values of Water Quality Parameters in Rivers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(3), pages 649-662, March.
    3. Jia Liu & Jianhua Wang & Shibing Pan & Kewang Tang & Chuanzhe Li & Dawei Han, 2015. "A real-time flood forecasting system with dual updating of the NWP rainfall and the river flow," 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. 77(2), pages 1161-1182, June.
    4. R. Rai & S. Sarkar & Alka Upadhyay & V. Singh, 2010. "Efficacy of Nakagami-m Distribution Function for Deriving Unit Hydrograph," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(3), pages 563-575, February.
    5. R. Rai & S. Sarkar & V. Singh, 2009. "Evaluation of the Adequacy of Statistical Distribution Functions for Deriving Unit Hydrograph," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(5), pages 899-929, March.
    6. Marijana Hadzima-Nyarko & Anamarija Rabi & Marija Šperac, 2014. "Implementation of Artificial Neural Networks in Modeling the Water-Air Temperature Relationship of the River Drava," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(5), pages 1379-1394, March.
    7. Abdüsselam Altunkaynak, 2007. "Forecasting Surface Water Level Fluctuations of Lake Van by Artificial Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(2), pages 399-408, February.
    8. Avinash Agarwal & R. Singh, 2004. "Runoff Modelling Through Back Propagation Artificial Neural Network With Variable Rainfall-Runoff Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(3), pages 285-300, June.
    9. Qiang Fu & Long-Bin Lu & Jin-Bai Huang, 2014. "Numerical Analysis of Surface Runoff for the Liudaogou Drainage Basin in the North Loess Plateau, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4809-4822, October.
    10. Raveendra Rai & B. Mathur, 2008. "Event-based Sediment Yield Modeling using Artificial Neural Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(4), pages 423-441, April.
    11. Rajib Bhattacharjya & Sandeep Chaurasia, 2013. "Geomorphology Based Semi-Distributed Approach for Modelling Rainfall-Runoff Process," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(2), pages 567-579, January.
    12. Zaw Latt, 2015. "Application of Feedforward Artificial Neural Network in Muskingum Flood Routing: a Black-Box Forecasting Approach for a Natural River System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 4995-5014, November.
    13. Muhammad Sulaiman & Ahmed El-Shafie & Othman Karim & Hassan Basri, 2011. "Improved Water Level Forecasting Performance by Using Optimal Steepness Coefficients in an Artificial Neural Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(10), pages 2525-2541, August.
    14. Maryam Ghashghaei & Ali Bagheri & Saeed Morid, 2013. "Rainfall-runoff Modeling in a Watershed Scale Using an Object Oriented Approach Based on the Concepts of System Dynamics," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5119-5141, December.
    15. R. Rai & M. Jain & S. Mishra & C. Ojha & V. Singh, 2007. "Another Look at Z-transform Technique for Deriving Unit Impulse Response Function," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(11), pages 1829-1848, 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:22:y:2008:i:1:p:1-22. 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.