Abstract
Over the last few years, the operation of the Furnas Hydropower Plant (HPP) reservoir, located in the Grande River Basin, has been threatened due to a significant reduction in inflow. In the region, hydrological modelling tools are being used and tested to support decision making and water sustainability. In this study, the streamflow was modelled in the area of direct influence of the Furnas HPP reservoir, and the Soil andWater Assessment Tool (SWAT) model performance was verified for studies in the region. Analyses of sensitivity and uncertainty were undertaken using the Sequential Uncertainty Fitting algorithm (SUFI-2) with a Calibration Uncertainty Program (SWAT-CUP). The hydrological modelling, at a monthly scale, presented good results in the calibration (NS 0.86), with a slight reduction of the coefficient in the validation period (NS 0.64). The results suggested that this tool could be applied in future hydrological studies in the region of study. With the consideration that special attention should be given to the historical series used in the calibration and validation of the models. It is important to note that this region has high demands for water resources, primarily for agricultural use. Water demands must also be taken into account in future hydrological simulations. The validation of this methodology led to important contributions to the management of water resources in regions with tropical climates, whose climatological and geological reality resembles the one studied here.
Original language | English |
---|---|
Article number | 458 |
Journal | Water |
Volume | 10 |
Issue number | 4 |
DOIs | |
Publication status | Published - 11 Apr 2018 |
Keywords
- Hydroelectric reservoir
- Hydrological modelling
- Streamflow
- SWAT model
ASJC Scopus subject areas
- Biochemistry
- Geography, Planning and Development
- Aquatic Science
- Water Science and Technology
Fingerprint
Dive into the research topics of 'Historical streamflow series analysis applied to furnas HPP reservoir watershed using the SWAT model'. Together they form a unique fingerprint.Profiles
-
Gabriela M. Medero
- School of Energy, Geoscience, Infrastructure and Society, Institute for Infrastructure & Environment - Professor
- School of Energy, Geoscience, Infrastructure and Society - Professor
Person: Academic (Research & Teaching)