Streamflow Regionalization Considering Water Balance with Actual Evapotranspiration Estimated from Remote Sensing
Publication: Journal of Hydrologic Engineering
Volume 27, Issue 8
Abstract
Streamflow regionalization is a technique used in areas where hydrological data are scarce or nonexistent. Although numerous studies have been conducted with the aim of improving this technique, unsatisfactory results are still evident. This study, therefore, aims to propose and evaluate the performance of a new explanatory variable for regionalization, which represents the streamflow formation process and considers the actual evapotranspiration (ETR) obtained from remote sensing products. For this purpose, the regional regression method was used to estimate long-term mean streamflow and minimum flow with 90% of permanence in time. The explanatory variables were the precipitated volume (), precipitated volume minus the empirical value of 750 mm (), water balance for each segment of the water course (), and water balance for each hydrologically homogenous region (). These variables were obtained using a combination of drainage area, precipitation, and ETR. The ETR was estimated using two remote sensing products: MOD16 and Global Land Evaporation Amsterdam Model. The models of streamflow regionalization were evaluated by statistical, physical, and risk analyses. The study was applied for Grande River basin. All the variables, with the exception of , presented good statistical performance, good representativeness of regionalized streamflows, and safe estimates for the planning and management of water resources. The was the most recommended variable for streamflow regionalization in Grande River basin, because it considers variations in edaphoclimatic and vegetative conditions along the basin. This work contributes to improving the predictive capacity of the streamflow through a method that is potentially applicable to other areas of study, allows easy physical interpretation, utilizes easily obtained variables, and represents the streamflow formation process.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This study was partially financed by the National Council for Scientific and Technological Development (CNPq) and Coordination for the Improvement of Higher Education Personnel (CAPES), CAPES–Financing Code 001.
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Journal of Hydrologic Engineering
Volume 27 • Issue 8 • August 2022
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© 2022 American Society of Civil Engineers.
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Received: Jun 21, 2021
Accepted: Mar 24, 2022
Published online: May 27, 2022
Published in print: Aug 1, 2022
Discussion open until: Oct 27, 2022
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