Journal
HYDROLOGICAL SCIENCES JOURNAL
Volume 64, Issue 12, Pages 1404-1414Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/02626667.2019.1655148
Keywords
low-streamflow; trends; Monte Carlo experiments; statistical hydrology; frequency statistics
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Funding
- United States National Science Foundation [DGE-1144081, EEC1444926]
- EPA Interagency Agreement [DW-14-92433201]
- Glenadore and Howard L. Pim Postdoctoral Fellowship
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Accurate estimators of streamflow statistics are critical to the design, planning, and management of water resources. Given increasing evidence of trends in low-streamflow, new approaches to estimating low-streamflow statistics are needed. Here we investigate simple approaches to select a recent subset of the low-flow record to update the commonly used statistic of 7Q10, the annual minimum 7-day streamflow exceeded in 9 out of 10 years on average. Informed by low-streamflow records at 174 US Geological Survey streamgages, Monte Carlo simulation experiments evaluate competing approaches. We find that a strategy which estimates 7Q10 using the most recent 30 years of record when a trend is detected, reduces error and bias in 7Q10 estimators compared to use of the full record. This simple rule-based approach has potential as the basis for a framework for updating frequency-based statistics in the context of possible trends.
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