2016
DOI: 10.1590/1809-4430-eng.agric.v36n5p830-838/2016
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Extrapolation of regionalization equations for long-term average flow

Abstract: Knowledge about long-term average flow is essential for planning and managing water resources because it represents the potential water availability. One technique used to determine streamflow is regionalization, but because most gauge stations normally are associated with large drainage areas, the extrapolation of regionalization equations does not accurately represent the water availability; therefore, this method is not recommended. The main objective of the present paper is to propose a new method of estim… Show more

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Cited by 8 publications
(5 citation statements)
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“…Costa's (2020) [19] methodology shows two results within the limit, whereas PERH's (2015) [18] and Honório's (2020) [8] methodologies show six results each, within the limit. Results on RE are according to the ones found by Araújo et al (2018) [30] (between 0.2% and 83.8%) for the "Piquiri river" basin (Paraná, Brazil), with areas between 274.3 km 2 and 20,943 km 2 , and also in the range of values from −19.1% to 62.9% found by Pruski et al (2016) [31] for the "Corrente river" basin (34.253 km 2 ). However, there are significant differences in RE values for the three methodologies in the hydrographic basin of the "Retiro stream", where the errors ranged from −167.32% (RE-Costa) to −15,693.32% (RE-PERH), and in the hydrographic basin of the "Sucuapara stream", where the errors ranged from −485.87% (RE-Costa) to −1331.88% (RE-Honório).…”
Section: Comparative Analysis Between Estimated and Observed Flowssupporting
confidence: 62%
See 1 more Smart Citation
“…Costa's (2020) [19] methodology shows two results within the limit, whereas PERH's (2015) [18] and Honório's (2020) [8] methodologies show six results each, within the limit. Results on RE are according to the ones found by Araújo et al (2018) [30] (between 0.2% and 83.8%) for the "Piquiri river" basin (Paraná, Brazil), with areas between 274.3 km 2 and 20,943 km 2 , and also in the range of values from −19.1% to 62.9% found by Pruski et al (2016) [31] for the "Corrente river" basin (34.253 km 2 ). However, there are significant differences in RE values for the three methodologies in the hydrographic basin of the "Retiro stream", where the errors ranged from −167.32% (RE-Costa) to −15,693.32% (RE-PERH), and in the hydrographic basin of the "Sucuapara stream", where the errors ranged from −485.87% (RE-Costa) to −1331.88% (RE-Honório).…”
Section: Comparative Analysis Between Estimated and Observed Flowssupporting
confidence: 62%
“…The use of regression equations is not recommended for regions with limits higher than the measurement station interval [31], which makes water resource management a complex and difficult task. In this research, about 38% (eight basins) of the 21 hydrographic basins are considered small, with drainage areas ranging from 0.15 km 2 to 150.75 km 2 .…”
Section: Comparative Analysis Between Estimated and Observed Flowsmentioning
confidence: 99%
“…Temporal distributions, as well as runoff generation rates, can be extrapolated to neighboring basins that have similar morphoclimatic characteristics (Lopes et al, 2017), considering the lack of hydrological data in Brazil (Pontes et al, 2016). This knowledge can compose a database on long-term flows, essential for planning and managing regional water resources (Pruski et al, 2016).…”
Section: Resultsmentioning
confidence: 99%
“…Regarding the statistical parameters, the quotient model showed the best performance for the two regions. Pruski, Rodriguez, Pruski, Nunes and Rego (2016), when regionalizing Q mlt for the São Francisco River sub-basins, obtained models with R² coefficients equal to 0.898 and 0.893, using the drainage area and the mean annual precipitation as explanatory variables for each model, respectively. Thus, because the results obtained in the present study are comparable, it is considered that the models proposed for the Araguaia River sub-basins are parsimonious and can be considered effective and efficient for estimating Q mlt .…”
mentioning
confidence: 99%