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Evaluation of a Two-Stage SVM and Spatial Statistics Methods for Modeling Monthly River Suspended Sediment Load

Author

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  • Vahid Nourani
  • Farhad Alizadeh
  • Kiyoumars Roushangar

Abstract

This study is aimed on successful modeling of Ajichay River Suspended Sediment Load (SSL) which is significant object in watershed planning and management. Therefore, a two-stage modeling strategy was proposed in order to handle spatio-temporal variation of SSL. At temporal stage, Support Vector Machine (SVM) was utilized for three stations located on the Ajichay River to find the non-linear relationship of SSL in time domain. Different input sets were examined for the SVM via sensitivity analysis. Results of temporal modeling stage were used in spatial modeling. In spatial modeling stage, firstly semi-variogram of monthly SSL data was calculated and then theoretical semi-variogram model was fitted to the empirical variogram. It was found that Gaussian model is the best fitted model for the study case. The obtained results of semi-variogram were imported into Geostatistic tool for spatial estimation of SSL in sites where there is not any measurement. Results of temporal modeling stage demonstrated that input data as combination of SSL and discharges at 1 month and 12 monthes ago employing RBF based SVM could lead to the best performance for each station. Spatial modeling performance was improved relatively using streamflow dataset. The obtained results show that the hybrid of SVM and Spatial statistics methods could predict and simulated SSL appropriately by enjoying unique features of both approaches. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • Vahid Nourani & Farhad Alizadeh & Kiyoumars Roushangar, 2016. "Evaluation of a Two-Stage SVM and Spatial Statistics Methods for Modeling Monthly River Suspended Sediment Load," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 393-407, January.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:1:p:393-407
    DOI: 10.1007/s11269-015-1168-7
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    Citations

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    Cited by:

    1. Asli Ulke & Gokmen Tayfur & Sevinc Ozkul, 2017. "Investigating a Suitable Empirical Model and Performing Regional Analysis for the Suspended Sediment Load Prediction in Major Rivers of the Aegean Region, Turkey," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(3), pages 739-764, February.
    2. Vahid Nourani & Mohammad Taghi Sattari & Amir Molajou, 2017. "Threshold-Based Hybrid Data Mining Method for Long-Term Maximum Precipitation Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2645-2658, July.
    3. Mingxiang Yang & Hao Wang & Yunzhong Jiang & Xing Lu & Zhao Xu & Guangdong Sun, 2020. "GECA Proposed Ensemble–KNN Method for Improved Monthly Runoff Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 849-863, January.
    4. Bing-Chen Jhong & Hsi-Ting Fang & Cheng-Chia Huang, 2021. "Assessment of Effective Monitoring Sites in a Reservoir Watershed by Support Vector Machine Coupled with Multi-Objective Genetic Algorithm for Sediment Flux Prediction during Typhoons," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2387-2408, June.
    5. 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.

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