The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Influence of hydrologically based environmental flow methods on flow alteration and energy production in a run-of-river hydropower plant
Abstract
Abstract Increasing demand for renewable energy has led to a massive expansion of the small-scale hydropower plants and particularly those of run-of-river type. Meanwhile, the awareness concerning river conservation and restoration is being continually increasing. This study focuses on the assessment of environmental flows releases and energy production considering eight hydrological based environmental flows methods. The main goal of this study is to propose a practical approach that allows for quick estimation of the environmental flows releases and alteration due to water diversion for energy production, in the case of run-of-river hydropower plants. For this purpose, the indicators of hydrological alteration approach was applied to characterise flow alteration, and three economic metrics were used to assess the impact on energy production. Downstream Diversion Index was proposed to characterise the degree of water diversion due to energy production. Also, five new simplified indexes derived from indicators of hydrologic alteration approach were proposed to simplify flow alteration characterisation. The results of this study showed that a minor reduction of energy production could significantly improve environmental flows releases for the riverine ecosystem needs. Particularly, proportional dynamic approaches maximise energy production and imposes relatively less flow alteration. Also, it was concluded that following flow parameters: frequency, timing, duration and rates, can be maintained close to the natural regime without necessarily reducing the energy production by choosing the right environmental flows method. Finally, the methodology developed in this study can be a useful decision-making tool to help water managers, by including other relevant information also (i.e., biological, water supply, irrigation, and social) to choose the most appropriate method for the environmental flows determination in the case of run-of-river hydropower plants.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Brisbane Declaration and Global Action Agenda on Environmental Flows (2018)
Arthington, A. H., Bhaduri, A., Bunn, S. E., Jackson, S. E., Tharme, R. E., Tickner, D., Young, B., Acreman, M., Baker, N., Capon, S., et al. (2018) · Frontiers in Environmental Science · doi:10.3389/fenvs.2018.00045 · Cited by 473
Cited by
Kuriqi, A., Pinheiro, A. N., Sordo-Ward, A., Bejarano, M. D., & Garrote, L. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.110833 · Cited by 555
Self-citationMayer, M. J., Szilágyi, A., & Gróf, G. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115058 · Cited by 401
Farrell, C. C., Osman, A. I., Doherty, R., Saad, M., Zhang, X., Murphy, A., Harrison, J., Vennard, A. S. M., Kumaravel, V., Al-Muhtaseb, A. H., et al. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.109911 · Cited by 326
Kuriqi, A., Pinheiro, A. N., Sordo-Ward, A., & Garrote, L. (2019) · Applied Energy · doi:10.1016/j.apenergy.2019.113980 · Cited by 281
Self-citationKang, Y., Yang, Q., Bartocci, P., Wei, H., Liu, S. S., Wu, Z., Zhou, H., Yang, H., Fantozzi, F., & Chen, H. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.109842 · Cited by 268
Metadata
- Authors
- Kuriqi, A., Pinheiro, A. N., Sordo-Ward, A., & Garrote, L.
- Venue
- Journal of Cleaner Production
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 232
- Pages
- 1028-1042
- ISSN
- 0959-6526 (ISSN-L)
- OpenAlex
- W2947064583
- Cited by
- 350
- References
- 1
- FWCI
- 41.00
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Influence of hydrologically based environmental flow methods on flow alteration and energy production in a run-of-river hydropower plant. https://app.cochat.ai/papers/10.1016/j.jclepro.2019.05.358
- The paper
- Kuriqi, A., Pinheiro, A. N., Sordo-Ward, A., & Garrote, L. (2019). Influence of hydrologically based environmental flow methods on flow alteration and energy production in a run-of-river hydropower plant. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2019.05.358
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.