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Methodology for Estimating Streamflow by Water Balance and Rating Curve Methods Based on Logistic Regression

Author

Listed:
  • Tarcila Neves Generoso

    (Universidade Federal de Viçosa, University Campus)

  • Demetrius David Silva

    (Universidade Federal de Viçosa, University Campus)

  • Ricardo Santos Silva Amorim

    (Universidade Federal de Viçosa, University Campus)

  • Lineu Neiva Rodrigues

    (Universidade Federal de Viçosa, University Campus
    Brazilian Agricultural Research Corporation (EMPRAPA Cerrados))

  • Erli Pinto Santos

    (Universidade Federal de Viçosa, University Campus)

Abstract

Both water balance (WB) and rating curve (RC) are methods for estimating streamflow. The first is mostly used to estimate reservoir outflows, while the second is usually adopted in hydrometeorological network streamflow gauges. While WB uses hourly collected data, the RC estimates streamflow using current water level and extrapolation techniques. The objective of this study was to analyze variations in the reservoir’s hourly outflow at Queimado Hydroelectric Power Plant (HPP Queimado) and to propose a method to evaluate whether the estimate of the daily outflows, obtained by the WB method, is similar to the flow values obtained at a conventional station. The logistic regression (LR) model was used because it is a method that adopts binary, categorically dependent variables to identify the event of interest. The results showed that the values of streamflow, obtained from an average of two daily readings, were a good representation of the flows in the region. The LR was able to identify atypical data, especially in the rainy season. This means that data consistency analysis can be faster and safer, when adequately employed and considering the proposed conditions, contributing to both management policies and the management of water resources.

Suggested Citation

  • Tarcila Neves Generoso & Demetrius David Silva & Ricardo Santos Silva Amorim & Lineu Neiva Rodrigues & Erli Pinto Santos, 2022. "Methodology for Estimating Streamflow by Water Balance and Rating Curve Methods Based on Logistic Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4389-4402, September.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:11:d:10.1007_s11269-022-03259-1
    DOI: 10.1007/s11269-022-03259-1
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    References listed on IDEAS

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    1. Mohamed M. Fathi & Ayman G. Awadallah & Nabil A. Awadallah, 2021. "Estimation of Regional Sub-Daily Rainfall Ratios Using SKATER Algorithm and Logistic Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 555-571, January.
    2. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    3. King, Gary & Zeng, Langche, 2001. "Logistic Regression in Rare Events Data," Political Analysis, Cambridge University Press, vol. 9(2), pages 137-163, January.
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    1. Jingwei Huang & Hui Qin & Yongchuan Zhang & Dongkai Hou & Sipeng Zhu & Pingan Ren, 2023. "Short-term Prediction Method of Reservoir Downstream Water Level Under Complicated Hydraulic Influence," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(11), pages 4475-4490, September.

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