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Examination of changes in annual maximum gage height in the continental United States using quantile regression

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posted on 2017-09-07, 09:17 authored by Gabriele Villarini, Louise Slater
This study focuses on the detection of temporal changes in annual maximum gage height (GH) across the continental United States and their relationship to changes in short- and long-term precipitation. Analyses are based on 1805 U.S. Geological Survey records over the 1985-2015 period and are performed using quantile regression. Trends were significant only at a limited number of sites, with a higher number of detections at the tails of the distribution. Overall, we found only weak evidence that the annual maximum GH records have been changing over the continental United States during the past 30 years, possibly due to a weak signal of change, large variability, and limited record length. In addition to trend detection, we also assessed to what extent these changes can be attributed to storm total rainfall and long-term precipitation. Our findings indicate that temporal changes in GH maxima are largely driven by storm total rainfall across large areas of the continental United States (east of the 100th meridian, U.S. West Coast). Long-term precipitation accumulation, on the other hand, is a strong flood predictor in regions where snowmelt is an important flood generating mechanism (e.g., northern Great Plains, Rocky Mountains), and is overall a relatively less important predictor of extreme flood events.



  • Social Sciences


  • Geography and Environment

Published in

Journal of Hydrologic Engineering


VILLARINI, G. and SLATER, L., 2018. Examination of changes in annual maximum gage height in the continental United States using quantile regression. Journal of Hydrologic Engineering, 23(3): 0601701.


© American Society of Civil Engineers


  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

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This paper was accepted for publication in the journal Journal of Hydrologic Engineering and the definitive published version is available at https://doi.org/10.1061/(ASCE)HE.1943-5584.0001620




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