Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Stream-Reach Identification for New Run-of-River Hydropower Development through a Merit Matrix–Based Geospatial Algorithm
Even after a century of development, the total hydropower potential from undeveloped rivers is still considered to be abundant in the United States. However, unlike evaluating hydropower potential at existing hydropower plants or nonpowered dams, locating a feasible new hydropower plant involves many unknowns; hence, the total undeveloped potential is harder to quantify. In light of the rapid development of multiple national geospatial data sets for topography, hydrology, and environmental characteristics, a merit matrix–based geospatial algorithm is proposed to identify possible hydropower stream reaches for future development. These hydropower stream reaches—sections of natural streams with suitable head, flow, and slope for possible future development—are identified and compared by using three different scenarios. A case study was conducted in the Alabama-Coosa-Tallapoosa and Apalachicola-Chattahoochee-Flint hydrologic subregions. It was found that a merit matrix–based algorithm, which is based on the product of hydraulic head, annual mean flow, and average channel slope, can effectively identify stream reaches with high power density and small surface inundation. These identified stream reaches can then be evaluated for their potential environmental impact, land development cost, and other competing water usage in detailed feasibility studies. Given that the selected data sets are available nationally (at least within the conterminous U.S.), the proposed methodology will have wide applicability across the country.
Stream-Reach Identification for New Run-of-River Hydropower Development through a Merit Matrix–Based Geospatial Algorithm
Even after a century of development, the total hydropower potential from undeveloped rivers is still considered to be abundant in the United States. However, unlike evaluating hydropower potential at existing hydropower plants or nonpowered dams, locating a feasible new hydropower plant involves many unknowns; hence, the total undeveloped potential is harder to quantify. In light of the rapid development of multiple national geospatial data sets for topography, hydrology, and environmental characteristics, a merit matrix–based geospatial algorithm is proposed to identify possible hydropower stream reaches for future development. These hydropower stream reaches—sections of natural streams with suitable head, flow, and slope for possible future development—are identified and compared by using three different scenarios. A case study was conducted in the Alabama-Coosa-Tallapoosa and Apalachicola-Chattahoochee-Flint hydrologic subregions. It was found that a merit matrix–based algorithm, which is based on the product of hydraulic head, annual mean flow, and average channel slope, can effectively identify stream reaches with high power density and small surface inundation. These identified stream reaches can then be evaluated for their potential environmental impact, land development cost, and other competing water usage in detailed feasibility studies. Given that the selected data sets are available nationally (at least within the conterminous U.S.), the proposed methodology will have wide applicability across the country.
Stream-Reach Identification for New Run-of-River Hydropower Development through a Merit Matrix–Based Geospatial Algorithm
Pasha, M. Fayzul K. (Autor:in) / Yeasmin, Dilruba (Autor:in) / Kao, Shih-Chieh (Autor:in) / Hadjerioua, Boualem (Autor:in) / Wei, Yaxing (Autor:in) / Smith, Brennan T. (Autor:in)
28.12.2013
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
| British Library Online Contents | 2014
Uncertainty Analysis in Geospatial Merit Matrix–Based Hydropower Resource Assessment
| Online Contents | 2016
Uncertainty Analysis in Geospatial Merit Matrix-Based Hydropower Resource Assessment
| British Library Online Contents | 2016
Uncertainty Analysis in Geospatial Merit Matrix–Based Hydropower Resource Assessment
| Online Contents | 2016