IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v28y2014i7p1991-2003.html
   My bibliography  Save this article

Modeling of Sediment Yield Prediction Using M5 Model Tree Algorithm and Wavelet Regression

Author

Listed:
  • Manish Goyal

Abstract

The forecast of the sediment yield generated within a watershed is an important input in the water resources planning and management. The methods for the estimation of sediment yield based on the properties of flow and sediment have limitations attributed to the simplification of important parameters and boundary conditions. Under such circumstances, soft computing approaches have proven to be an efficient tool in modelling the sediment yield. The focus of present study is to deal with the development of decision tree based M5 Model Tree and wavelet regression models for modeling sediment yield in Nagwa watershed in India. A comparison is also performed with the artificial neural network (ANN) model for streamflow forecasting. The root mean square errors (RMSE), Nash-Sutcliff efficiency index (N-S Index), and correlation coefficient (R) statistics are used for the statistical criteria. A comparative evaluation of the performance of M5 Model Tree and wavelet regression versus ANN clearly shows that M5 Model Tree and wavelet regression can prove more useful than ANN models in estimation of sediment yield. Further, M5 model tree offers explicit expressions for use by design engineers. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Manish Goyal, 2014. "Modeling of Sediment Yield Prediction Using M5 Model Tree Algorithm and Wavelet Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 1991-2003, May.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:7:p:1991-2003
    DOI: 10.1007/s11269-014-0590-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-014-0590-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11269-014-0590-6?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. A. kumar & Manish Goyal & C. Ojha & R. Singh & P. Swamee & R. Nema, 2013. "Application of ANN, Fuzzy Logic and Decision Tree Algorithms for the Development of Reservoir Operating Rules," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 911-925, February.
    2. Ozgur Kisi, 2011. "Wavelet Regression Model as an Alternative to Neural Networks for River Stage Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(2), pages 579-600, January.
    3. Hui-cheng Zhou & Yong Peng & Guo-hua Liang, 2008. "The Research of Monthly Discharge Predictor-corrector Model Based on Wavelet Decomposition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(2), pages 217-227, February.
    4. 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.
    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. Ayoub Zeroual & Mohamed Meddi & Ali A. Assani, 2016. "Artificial Neural Network Rainfall-Discharge Model Assessment Under Rating Curve Uncertainty and Monthly Discharge Volume Predictions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 3191-3205, July.
    2. Pankaj Bhardwaj & Tejpal Sharma & Omvir Singh, 2021. "Impact evaluation of watershed management programmes in Siwalik Himalayas of Haryana, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 5251-5276, April.
    3. Hai Tao & Behrooz Keshtegar & Zaher Mundher Yaseen, 2019. "The Feasibility of Integrative Radial Basis M5Tree Predictive Model for River Suspended Sediment Load Simulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(13), pages 4471-4490, October.
    4. Granata, Francesco, 2019. "Evapotranspiration evaluation models based on machine learning algorithms—A comparative study," Agricultural Water Management, Elsevier, vol. 217(C), pages 303-315.
    5. Rana Muhammad Adnan & Kulwinder Singh Parmar & Salim Heddam & Shamsuddin Shahid & Ozgur Kisi, 2021. "Suspended Sediment Modeling Using a Heuristic Regression Method Hybridized with Kmeans Clustering," Sustainability, MDPI, vol. 13(9), pages 1-21, April.
    6. Meral Buyukyildiz & Serife Yurdagul Kumcu, 2017. "An Estimation of the Suspended Sediment Load Using Adaptive Network Based Fuzzy Inference System, Support Vector Machine and Artificial Neural Network Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1343-1359, March.
    7. Zhenfang He & Yaonan Zhang & Qingchun Guo & Xueru Zhao, 2014. "Comparative Study of Artificial Neural Networks and Wavelet Artificial Neural Networks for Groundwater Depth Data Forecasting with Various Curve Fractal Dimensions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5297-5317, December.
    8. Rana Muhammad Adnan & Xiaohui Yuan & Ozgur Kisi & Muhammad Adnan & Asif Mehmood, 2018. "Stream Flow Forecasting of Poorly Gauged Mountainous Watershed by Least Square Support Vector Machine, Fuzzy Genetic Algorithm and M5 Model Tree Using Climatic Data from Nearby Station," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4469-4486, November.
    9. Anas Mahmood Al-Juboori, 2019. "Generating Monthly Stream Flow Using Nearest River Data: Assessing Different Trees Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3257-3270, July.
    10. Vahid Nourani & Amir Molajou & Ali Davanlou Tajbakhsh & Hessam Najafi, 2019. "A Wavelet Based Data Mining Technique for Suspended Sediment Load Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(5), pages 1769-1784, March.

    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. Vinit Sehgal & Rajeev Sahay & Chandranath Chatterjee, 2014. "Effect of Utilization of Discrete Wavelet Components on Flood Forecasting Performance of Wavelet Based ANFIS Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1733-1749, April.
    2. A. Agarwal & R. Maheswaran & J Kurths & R. Khosa, 2016. "Wavelet Spectrum and Self-Organizing Maps-Based Approach for Hydrologic Regionalization -a Case Study in the Western United States," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4399-4413, September.
    3. Jaydip Makwana & Mukesh Tiwari, 2014. "Intermittent Streamflow Forecasting and Extreme Event Modelling using Wavelet based Artificial Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4857-4873, October.
    4. Asmadi Ahmad & Siti Fatin Mohd Razali & Zawawi Samba Mohamed & Ahmed El-shafie, 2016. "The Application of Artificial Bee Colony and Gravitational Search Algorithm in Reservoir Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2497-2516, May.
    5. Maryam Shafaei & Ozgur Kisi, 2016. "Lake Level Forecasting Using Wavelet-SVR, Wavelet-ANFIS and Wavelet-ARMA Conjunction Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 79-97, January.
    6. Chunlong Li & Jianzhong Zhou & Shuo Ouyang & Chao Wang & Yi Liu, 2015. "Water Resources Optimal Allocation Based on Large-scale Reservoirs in the Upper Reaches of Yangtze River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2171-2187, May.
    7. Dimitrios Myronidis & Konstantinos Ioannou & Dimitrios Fotakis & Gerald Dörflinger, 2018. "Streamflow and Hydrological Drought Trend Analysis and Forecasting in Cyprus," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1759-1776, March.
    8. Chang-ming Ji & Ting Zhou & Hai-tao Huang, 2014. "Operating Rules Derivation of Jinsha Reservoirs System with Parameter Calibrated Support Vector Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(9), pages 2435-2451, July.
    9. Vahid Nourani & Mehdi Komasi & Akira Mano, 2009. "A Multivariate ANN-Wavelet Approach for Rainfall–Runoff Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(14), pages 2877-2894, November.
    10. Hadi Sanikhani & Ozgur Kisi, 2012. "River Flow Estimation and Forecasting by Using Two Different Adaptive Neuro-Fuzzy Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(6), pages 1715-1729, April.
    11. Nazak Rouzegari & Yousef Hassanzadeh & Mohammad Taghi Sattari, 2019. "Using the Hybrid Simulated Annealing-M5 Tree Algorithms to Extract the If-Then Operation Rules in a Single Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3655-3672, August.
    12. Mahmoud Mohammad Rezapour Tabari & Mohsen Mazak Mari, 2016. "The Integrated Approach of Simulation and Optimization in Determining the Optimum Dimensions of Canal for Seepage Control," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1271-1292, February.
    13. Liping Li & Pan Liu & David Rheinheimer & Chao Deng & Yanlai Zhou, 2014. "Identifying Explicit Formulation of Operating Rules for Multi-Reservoir Systems Using Genetic Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1545-1565, April.
    14. Sanjeet Kumar & Mukesh Tiwari & Chandranath Chatterjee & Ashok Mishra, 2015. "Reservoir Inflow Forecasting Using Ensemble Models Based on Neural Networks, Wavelet Analysis and Bootstrap Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4863-4883, October.
    15. Liang Zhu & Christine Lim & Wenjun Xie & Yuan Wu, 2017. "Analysis of tourism demand serial dependence structure for forecasting," Tourism Economics, , vol. 23(7), pages 1419-1436, November.
    16. Gokmen Tayfur & Luca Brocca, 2015. "Fuzzy Logic for Rainfall-Runoff Modelling Considering Soil Moisture," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3519-3533, August.
    17. Manish Pandey & Masoud Karbasi & Mehdi Jamei & Anurag Malik & Jaan H. Pu, 2023. "A Comprehensive Experimental and Computational Investigation on Estimation of Scour Depth at Bridge Abutment: Emerging Ensemble Intelligent Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3745-3767, July.
    18. Mohammad Rezaie-Balf & Zahra Zahmatkesh & Sungwon Kim, 2017. "Soft Computing Techniques for Rainfall-Runoff Simulation: Local Non–Parametric Paradigm vs. Model Classification Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(12), pages 3843-3865, September.
    19. Sajjad Abdollahi & Jalil Raeisi & Mohammadreza Khalilianpour & Farshad Ahmadi & Ozgur Kisi, 2017. "Daily Mean Streamflow Prediction in Perennial and Non-Perennial Rivers Using Four Data Driven Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4855-4874, December.
    20. Manish Kumar & Ahmed Elbeltagi & Chaitanya B. Pande & Ali Najah Ahmed & Ming Fai Chow & Quoc Bao Pham & Anuradha Kumari & Deepak Kumar, 2022. "Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2201-2221, May.

    More about this item

    Keywords

    Streamflow; M5 model tree; Discrete wavelet transform; Regression; Forecast;
    All these keywords.

    JEL classification:

    • M5 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics

    Statistics

    Access and download statistics

    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:28:y:2014:i:7:p:1991-2003. 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.