paper.bib

@techreport{osti_1244193,
  author       = {O'Connor, Patrick W.},
  title        = {Hydropower Baseline Cost Modeling, Version 2},
  institution  = {Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)},
  annote       = {Recent resource assessments conducted by the United States Department of Energy have identified significant opportunities for expanding hydropower generation through the addition of power to non-powered dams and on undeveloped stream-reaches. Additional interest exists in the powering of existing water resource infrastructure such as conduits and canals, upgrading and expanding existing hydropower facilities, and the construction new pumped storage hydropower. Understanding the potential future role of these hydropower resources in the nation’s energy system requires an assessment of the environmental and techno-economic issues associated with expanding hydropower generation. To facilitate these assessments, this report seeks to fill the current gaps in publically available hydropower cost estimating tools that can support the national-scale evaluation of hydropower resources.},
  doi          = {10.2172/1244193},
  url          = {https://www.osti.gov/biblio/1244193},
  place        = {United States},
  year         = {2015},
  month        = {09}}



@misc{EIA_price,
    title = {Wholesale Electricity and Natural Gas Market Data},
    author = {{US Energy Information Administration}},
    year = {2025},
    url = {https://www.eia.gov/electricity/wholesale/},
    urldate      = {02/04/2025}
}

@misc{RETSCREEN,
    title = {RETSCREEN},
    url = {https://natural-resources.canada.ca/maps-tools-publications/tools-applications/retscreen},
    author = {Government of Canada},
    year = {2025},
    note = {Accessed on 02-18-2025}
}

@misc{irrigationviz,
    title = {irrigationviz},
    url = {https://irrigationviz.pnnl.gov/},
    author = {{Pacific Northwest National Laboratory}},
    year = {2024},
    note = {Accessed on 02-18-2025}
}

@misc{USGS,
    title = {dataretrieval (Python): a Python package for discovering and retrieving water data available from U.S. federal hydrologic web services: U.S. Geological Survey software release},
    url = {10.5066/P94I5TX3},
    author = {USGS},
    year = {2024},
    note = {Accessed on 02-18-2025}
}

@article{ALONSOTRISTAN20112729,
title = {Small hydropower plants in Spain: A case study},
journal = {Renewable and Sustainable Energy Reviews},
volume = {15},
number = {6},
pages = {2729-2735},
year = {2011},
issn = {1364-0321},
doi = {10.1016/j.rser.2011.03.029},
url = {https://www.sciencedirect.com/science/article/pii/S1364032111001328},
author = {C. Alonso-Tristán and D. González-Peña and M. Díez-Mediavilla and M. Rodríguez-Amigo and T. García-Calderón},
keywords = {Feasibility study, Small hydropower, RETScreen, Economic study},
abstract = {A small hydropower plant in Spain is studied from an energetic and economic perspective. The viability of the facility is examined using the freeware software RETScreen. Calculated and standard operational data are compared, thereby demonstrating the feasibility of the project from all points of view. The study highlights the growing interest in renewable energies.}
}

@BOOK{HPEH,
  TITLE = {Hydropower Engineering Handbook},
  SUBTITLE = {},
  AUTHOR = {Gulliver, John S. and Arndt, Roger E.A.},
  YEAR = {1991},
  PUBLISHER = {McGraw-Hill, Inc.},
}

@software{gillies_2025_14776272,
  author       = {Gillies, Sean and
                  van der Wel, Casper and
                  Van den Bossche, Joris and
                  Taves, Mike W. and
                  Arnott, Joshua and
                  Ward, Brendan C. and
                  others},
  title        = {Shapely},
  month        = jan,
  year         = 2025,
  publisher    = {Zenodo},
  version      = {2.0.7},
  doi          = {10.5281/zenodo.14776272},
  url          = {https://doi.org/10.5281/zenodo.14776272},
  swhid        = {swh:1:dir:9bc7da99727538708857e1e27ea6542920db0fd1
                   ;origin=https://doi.org/10.5281/zenodo.5597138;vis
                   it=swh:1:snp:44de75f53264cc3b455a9d033e92649a4e751
                   da6;anchor=swh:1:rel:455d78b22109c32af9ed7e0ed9f0a
                   71e0479fd3c;path=shapely-shapely-026c470
                  },
}

@article{NIEBUHR2019109240,
title = {A review of hydrokinetic turbines and enhancement techniques for canal installations: Technology, applicability and potential},
journal = {Renewable and Sustainable Energy Reviews},
volume = {113},
pages = {109240},
year = {2019},
issn = {1364-0321},
doi = {10.1016/j.rser.2019.06.047},
url = {https://www.sciencedirect.com/science/article/pii/S136403211930440X},
author = {C.M. Niebuhr and M. {van Dijk} and V.S. Neary and J.N. Bhagwan},
keywords = {Hydrokinetic energy conversion, Low head hydropower, Hydrokinetic technology, Hydrokinetic applicability, Hydrokinetic turbine},
abstract = {The hydrokinetic industry has advanced beyond its initial testing phase with full-scale projects being introduced, constructed and tested globally. However primary hurdles such as reducing the cost of these systems, optimizing individual systems and arrays and balancing energy extraction with environmental impact still requires attention prior to achieving commercial success. The present study addresses the advances and limitations of near-zero head hydrokinetic technologies and the possibility of increased potential and applicability when enhancement techniques within the design, implementation and operational phases are considered. Its goal is threefold: to review small-scale state-of-the-art near-zero hydrokinetic-current-energy-conversion-technologies, to assess barriers including gaps in knowledge, information and data as well as assess time and resource limitations of water-infrastructure owners and operators. A case study summarizes the design and implementation of the first permanent modern hydrokinetic installation in South Africa where improved outputs were achieved through optimization during each design and operation phase. An economic analysis validates a competitive levelized cost of energy and further emphasizes the broad potential that is relatively unexplored within existing water-infrastructure.}
}

@BOOK{BETZ,
  TITLE = {Introduction to the theory of flow machines},
  SUBTITLE = {},
  AUTHOR = {Albert Betz},
  YEAR = {2014},
  PUBLISHER = {Elsevier},
}

@article{BROWN,
title = {The History of the Darcy-Weisbach Equation for Pipe Flow Resistance},
journal = {Proceedings: Environmental and Water Resources History},
volume = {113},
pages = {109240},
year = {2019},
issn = {1364-0321},
doi = {10.1061/40650(2003)4},
url = {},
author = {Glenn O. Brown},
}

@BOOK{BARTER,
  TITLE = {Hanbook of Hydraulics},
  SUBTITLE = {7th edition},
  AUTHOR = {Brater, Ernest F. and King, Horace W. and Lindell, James E. and Wei, C. Y. },
  YEAR = {1996},
  PUBLISHER = {McGraw-Hill, Inc.},
}

@misc{osti_1968288,
  author       = {Harrison-Atlas, Dylan and Murphy, Caitlin and Grue, Nicholas and Gallego-Calderon, Juan and Elliott, Shiloh and Mosier, Thomas and USDOE Office of Energy Efficiency and Renewable Energy},
  title        = {Data on temporal complementarity of hybrid renewable energy systems [SWR-23-09]},
  annote       = {These datasets describe multiple facets of the temporal complementarity of co-located hybrid renewable energy systems throughout the United States. Several metrics characterizing the complementarity of generation profiles are provided on an annual and monthly basis (for both hourly and daily aggregations). These generation profiles are underpinned by hourly resource data (e.g., the WIND Toolkit and National Solar Radiation Database (NSRDB)) spanning the multi-year period 2007-2013. The data include complementarity results for greater than 1.76 million individual locations within the continental United States (CONUS). The data are intended to accompany two publications on the topic of temporal complementarity: 1) Harrison-Atlas, Dylan, Caitlin Murphy, Anna Schleifer, and Nicholas Grue. "Temporal complementarity and value of wind-PV hybrid systems across the United States." Renewable Energy 201 (2022): 111-123, doi:10.1016/j.renene.2022.10.060; and 2) Murphy, Caitlin, Harrison-Atlas, Dylan, Nicholas Grue, Vahan Gevorgian, Juan Gallego-Calderon, Shiloh Elliot and Thomas Mosier. “A Resource Assessment for FlexPower”. NREL Technical Report.},
  doi          = {10.11578/dc.20230405.2},
  url          = {https://www.osti.gov/biblio/1968288},
  place        = {United States},
  year         = {2023},
  month        = {01}}
  
@article{Arefiev,
title = {Development of Automated Approaches for Hydropower Potential Estimations and Prospective Hydropower Plants Siting},
journal = {Proceedings of the 10th International Scientific and Practical Conference},
volume = {2},
pages = {},
year = {2015},
issn = {},
doi = {10.17770/etr2015vol2.260},
url = {https://journals.ru.lv/index.php/ETR/article/view/260},
author = {Nikolay Arefiev and Olga Nikonova and Nikolay Badenko and Timofey Ivanov and Vyacheslav Oleshko},
}

@misc{HG,
title = {Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series},
author = {Mitra, Bhaskar and Gallego-Calderon, Juan F. and Elliott, Shiloh N and Mosier, Thomas M and Bastidas Pacheco, Camilo Jose and Nag, Soumyadeep and {USDOE Office of Energy Efficiency and Renewable Energy}},
abstractNote = {Hydropower is one of the most mature forms of renewable energy generation. The United States (US) has almost 103 GW of installed, with 80 GW of conventional generation and 23 GW of pumped hydropower [1]. Moreover, the potential for future development on Non-Powered Dams is up to 10 GW. With the US setting its goals to become carbon neutral [2], more renewable energy in the form of hydropower needs to be integrated with the grid. Currently, there are no publicly available tool that can estimate the hydropower potential for existing hydropower dams or other non-powered dams. The HydroGenerate is an open-source python library that has the capability of estimating hydropower generation based on flow rate either provided by the user or received from United States Geological Survey (USGS) water data services. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the “head” provided by the user.},
url = {https://www.osti.gov//servlets/purl/1829986},
doi = {10.11578/dc.20211112.1},
url = {https://www.osti.gov/biblio/1829986}, year = {2021},
month = {10},
note =
}

@misc{USGS_data,
    title = {National Water Information System: Web Interface},
    url = {https://waterdata.usgs.gov/nwis},
    author = {USGS},
    year = {2025},
    note = {Accessed on 04-01-2025}
}