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Water 2017, 9(8), 572; https://doi.org/10.3390/w9080572

Derivation of Flow Duration Curves to Estimate Hydropower Generation Potential in Data-Scarce Regions

Engineering Hydrology and Water Management, Technische Universität Darmstadt, Franziska-Braun-Str. 7, 64287 Darmstadt, Germany
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Received: 6 July 2017 / Revised: 24 July 2017 / Accepted: 26 July 2017 / Published: 31 July 2017
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Abstract

Small-scale hydropower is a robust and reliable form of sustainable energy supply in remote areas. On the one hand, the potential for hydropower generation depends on the specific climate in a given place, and precipitation above all. On the other hand, such potential also depends on the catchment’s characteristics, e.g., topography, land use, and soils. In the absence of discharge measurements, the available river flow for hydropower production can be estimated in the form of a flow duration curve based on these variables. In this study, the lumped rainfall-runoff method by Crawford and Thurin (1981) was modified to calculate a flow duration curve with a daily time step for an ungauged catchment in Nicaragua. Satisfactory results could be obtained by calibrating the method with the aid of a few discharge measurements. Best results were obtained with a parameter set for groundwater flow and recharge to groundwater from excess soil moisture of 0.014 and 0.6, respectively. Considering the climate and catchment characteristics of the study site, this parameterization can be physically reasoned. View Full-Text
Keywords: daily time steps; flow duration curve; lumped rainfall-runoff method; micro-hydropower; Nicaragua; ungauged catchments daily time steps; flow duration curve; lumped rainfall-runoff method; micro-hydropower; Nicaragua; ungauged catchments
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Reichl, F.; Hack, J. Derivation of Flow Duration Curves to Estimate Hydropower Generation Potential in Data-Scarce Regions. Water 2017, 9, 572.

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