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A Method for Assessment of Sub‐Daily Flow Alterations Using Wavelet Analysis for Regulated Rivers
Author(s) -
Ashraf Faisal Bin,
Haghighi Ali Torabi,
Riml Joakim,
Mathias Kondolf G.,
Kløve Bjørn,
Marttila Hannu
Publication year - 2022
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2021wr030421
Subject(s) - hydropower , environmental science , flexibility (engineering) , fluvial , wavelet , hydrology (agriculture) , streamflow , natural (archaeology) , flow (mathematics) , computer science , geography , geology , ecology , statistics , drainage basin , mathematics , cartography , geomorphology , structural basin , artificial intelligence , biology , geometry , geotechnical engineering , archaeology
New tools are needed to evaluate the impacts of short‐term hydropower regulation practices on downstream river systems and to progress towards sustainable river‐flow management. As hydropower is increasingly being used to balance the energy load deficit caused by other less flexible sources, sub‐daily flow conditions across many regulated river (RR) systems are changing. To address this, we used wavelet analyses to quantify the discharge variability in RRs and categorized the level of variability based on the conditions in natural free‐flowing rivers. The presented framework used the definition of fluvial connectivity (Grill et al., 2019) to identify free‐flowing rivers used in the study. We tested the developed framework in 12 different RRs in Finland and found higher overall averaged subdaily variations, with up to 20 times larger variability than natural conditions. A large, highly regulated Finnish river system was found to have the highest sub‐daily variations in winter, while smaller RRs with lower levels of regulation the highest variations in summer. The proposed framework offers a novel tool for sustainable river management and can be easily applied to various rivers and regions globally. It had flexibility to analyze sub‐daily variations in desired seasonal or other ecologically sensitive periods.