River Flow Modelling for Sustainable Operation Of Hydroelectric Power Plant in the Taludaa-Gorontalo Watershed

https://doi.org/10.22146/ijg.64627

Sardi Salim(1*), Muchlis Polin(2)

(1) Electrical Engineering Department, Universitas Negeri Gorontalo, Gorontalo, Indonesia
(2) Information Systems Department, Universitas Negeri Gorontalo, Gorontalo, Indonesia
(*) Corresponding Author

Abstract


River flow discharge is generally measured by multiplying the cross-sectional river area at the measurement point with the flow velocity. However, this approach cannot be used for planning needs which involves knowing the changes in discharge values at all times, which are directly affected by the variations in weather conditions and catchment area systems. This is necessary because planning errors usually lead to unsustainable and interrupted operations. It is possible to determine the changes in the river discharge values using the rainfall-runoff modelling technique through the hydrograph output of the model. Therefore, this study used hydrological modelling techniques to obtain a watershed's spatial and temporal river flow discharge. This involved using parameters such as watershed area, curve number representing land use and soil type, time lag as the delay between maximum rainfall and the occurrence of peak discharge, and the initial abstraction that considers all the losses before the runoff occurred. Moreover, rainfall data were obtained from an ARR station installed around the watershed area, while water level data were retrieved through an AWLR station installed in the river at the debit measurement point. The model was analyzed using HEC-HMS software, while the dependable discharge for power plants was analyzed using the flow duration curve method. The results showed that the rainfall-runoff hydrological modelling technique applied to the Taludaa-Gorontalo sub-watershed could ensure the continuous and sustainable operation of the hydroelectric power plant.


Keywords


Modeling, Hydrology;Discharge;Watershed;electric_power

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DOI: https://doi.org/10.22146/ijg.64627

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