Stacey A. Archfield
Robert M. Hirsch
Richard M Vogel
Julie E. Kiang
Robert Dudley
Annalise G. Blum
2019
<div class="hlFld-Abstract"><div class="abstractSection abstractInFull"><p>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 7<i>Q</i>10, 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 7<i>Q</i>10 using the most recent 30 years of record when a trend is detected, reduces error and bias in 7<i>Q</i>10 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.</p></div></div>
application/pdf
10.1080/02626667.2019.1655148
en
Taylor and Francis
Updating estimates of low-streamflow statistics to account for possible trends
article