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Erschienen in: Water Resources Management 11/2022

01.08.2022

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

verfasst von: Tarcila Neves Generoso, Demetrius David da Silva, Ricardo Santos Silva Amorim, Lineu Neiva Rodrigues, Erli Pinto dos Santos

Erschienen in: Water Resources Management | Ausgabe 11/2022

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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.

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Literatur
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Metadaten
Titel
Methodology for Estimating Streamflow by Water Balance and Rating Curve Methods Based on Logistic Regression
verfasst von
Tarcila Neves Generoso
Demetrius David da Silva
Ricardo Santos Silva Amorim
Lineu Neiva Rodrigues
Erli Pinto dos Santos
Publikationsdatum
01.08.2022
Verlag
Springer Netherlands
Erschienen in
Water Resources Management / Ausgabe 11/2022
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-022-03259-1

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