PairwiseIHA: A python toolkit to detect flow regime alterations for headwater rivers
The PairwiseIHA is an open-source toolkit written in Python that enables the user to quickly obtain the Indicators of Hydrologic Alteration (IHA) from inflow and outflow time series for headwater reservoirs. Specifically, the IHA metrics obtained from inflows (outflows) are considered as natural (re...
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Published in | Environmental modelling & software : with environment data news Vol. 154; p. 105427 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Elsevier Ltd
01.08.2022
Elsevier Science Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | The PairwiseIHA is an open-source toolkit written in Python that enables the user to quickly obtain the Indicators of Hydrologic Alteration (IHA) from inflow and outflow time series for headwater reservoirs. Specifically, the IHA metrics obtained from inflows (outflows) are considered as natural (regulated) and the differences are used to indicate how the magnitude, frequency, duration, timing and rate of change are altered by reservoir operation. It extends the functionality of the popular IHA software for analyzing concurrent inflows and outflows. The results of three case study reservoirs in California highlight that reservoir operation leads to considerable alterations in the five components of the flow regime. The findings on flow regime alteration are consistent across wet, normal and dry years. Overall, the PairwiseIHA can serve as an effective tool to investigate alterations in flow regime induced by human activities for water managers, scientists, natural resource agencies and water users.
•The PairwiseIHA toolkit was developed to investigate the hydrological regime.•The toolkit illustrated the flow regime alterations subject to reservoir operation.•The toolkit was shown to be effective for three case study reservoirs in California. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2022.105427 |