Preprints
https://doi.org/10.5194/hess-2017-247
https://doi.org/10.5194/hess-2017-247
09 May 2017
 | 09 May 2017
Status: this discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.

Frequency Analysis of Extreme Sub-Daily Precipitation under Stationary and Non-Stationary Conditions across Two Contrasting Hydroclimatic Environments

Eleonora M. C. Demaria, David Goodrich, and Timothy Keefer

Abstract. Observed sub-daily precipitation intensities from contrasting hydroclimatic environments in the USA are used to evaluate temporal trends and to develop Intensity-Duration-Frequency (IDF) curves under stationary and non-stationary climatic conditions. Analyses are based on observations from two United States Department of Agriculture (USDA)-Agricultural Research Service (ARS) experimental watersheds located in a semi-arid and a temperate environment. We use an Annual Maximum Series (AMS) and a Partial Duration Series (PDS) approach to identify temporal trends in maximum intensities for durations ranging from 5- to 1440-minutes. A Bayesian approach with Monte Carlo techniques is used to incorporate the effect of non-stationary climatic assumptions in the IDF curves. The results show increasing trends in observed AMS sub-daily intensities in both watersheds whereas trends in the PDS observations are mostly positive in the semi-arid site and a mix of positive and negative in the temperate site. Stationary climate assumptions lead to much lower estimated sub-daily intensities than those under non-stationary assumptions with larger absolute differences found for shorter durations and smaller return periods. The risk of failure (R) of a hydraulic structure is increased for non-stationary effects over those of stationary effects, with absolute differences of 25 % for a 100-year return period (T) and a project life (n) of 100 years. The study highlights the importance of considering non-stationarity, due to natural variability or to climate change, in storm design.

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Eleonora M. C. Demaria, David Goodrich, and Timothy Keefer
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Eleonora M. C. Demaria, David Goodrich, and Timothy Keefer
Eleonora M. C. Demaria, David Goodrich, and Timothy Keefer

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Latest update: 22 Jun 2024
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Short summary
Infrastructure design is commonly based on the assumption that historical precipitation intensities have stayed stationary in time, i.e. its statistical properties are constant. However, recently observed increasing trends in precipitation make this assumption invalid and prompt the need for new design storms. Using observed maximum precipitation, we find that design storms are underestimated under stationary assumptions which entails a larger risk of structural failure.