skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed

Abstract

Changes in extreme precipitation events may require revisions of civil engineering standards to prevent water infrastructures from performing below the designated guidelines. Climate change may invalidate the intensity-duration-frequency (IDF) computation that is based on the assumption of data stationarity. Efforts in evaluating non-stationarity in the annual maxima series are inadequate, mostly due to the lack of long data records and convenient methods for detecting trends in the higher moments. In this study, using downscaled high resolution climate simulations of the historical and future periods under different carbon emission scenarios, we tested two solutions to obtain reliable IDFs under non-stationarity: (1) identify quasi-stationary time windows from the time series of interest to compute the IDF curves using data for the corresponding time windows; (2) introduce a parameter representing the trend in the means of the extreme value distributions. Focusing on a mountainous site, the Walker Watershed, the spatial heterogeneity and variability of IDFs or extremes are evaluated, particularly in terms of the terrain and elevation impacts. We compared observations-based IDFs that use the stationarity assumption with the two approaches that consider non-stationarity. The IDFs directly estimated based on the traditional stationarity assumption may underestimate the 100-year 24-h events by 10% tomore » 60% towards the end of the century at most grids, resulting in significant under-designing of the engineering infrastructure at the study site. Strong spatial heterogeneity and variability in the IDF estimates suggest a preference for using high resolution simulation data for the reliable estimation of exceedance probability over data from sparsely distributed weather stations. Discrepancies among the three IDFs analyses due to non-stationarity are comparable to the spatial variability of the IDFs, underscoring a need to use an ensemble of non-stationary approaches to achieve unbiased and comprehensive IDF estimates.« less

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1529550
Report Number(s):
PNNL-SA-141612
Journal ID: ISSN 2073-4441; WATEGH
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Water (Basel)
Additional Journal Information:
Journal Name: Water (Basel); Journal Volume: 11; Journal Issue: 6; Journal ID: ISSN 2073-4441
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; IDF; heterogeneity; non-stationarity; extreme precipitation; high-resolution and bias-corrected regional simulations; climate change

Citation Formats

Ren, Huiying, Hou, Zhangshuan Jason, Wigmosta, Mark S., Liu, Ying, and Leung, Lai-Yung Ruby. Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed. United States: N. p., 2019. Web. doi:10.3390/w11061296.
Ren, Huiying, Hou, Zhangshuan Jason, Wigmosta, Mark S., Liu, Ying, & Leung, Lai-Yung Ruby. Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed. United States. doi:10.3390/w11061296.
Ren, Huiying, Hou, Zhangshuan Jason, Wigmosta, Mark S., Liu, Ying, and Leung, Lai-Yung Ruby. Fri . "Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed". United States. doi:10.3390/w11061296. https://www.osti.gov/servlets/purl/1529550.
@article{osti_1529550,
title = {Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed},
author = {Ren, Huiying and Hou, Zhangshuan Jason and Wigmosta, Mark S. and Liu, Ying and Leung, Lai-Yung Ruby},
abstractNote = {Changes in extreme precipitation events may require revisions of civil engineering standards to prevent water infrastructures from performing below the designated guidelines. Climate change may invalidate the intensity-duration-frequency (IDF) computation that is based on the assumption of data stationarity. Efforts in evaluating non-stationarity in the annual maxima series are inadequate, mostly due to the lack of long data records and convenient methods for detecting trends in the higher moments. In this study, using downscaled high resolution climate simulations of the historical and future periods under different carbon emission scenarios, we tested two solutions to obtain reliable IDFs under non-stationarity: (1) identify quasi-stationary time windows from the time series of interest to compute the IDF curves using data for the corresponding time windows; (2) introduce a parameter representing the trend in the means of the extreme value distributions. Focusing on a mountainous site, the Walker Watershed, the spatial heterogeneity and variability of IDFs or extremes are evaluated, particularly in terms of the terrain and elevation impacts. We compared observations-based IDFs that use the stationarity assumption with the two approaches that consider non-stationarity. The IDFs directly estimated based on the traditional stationarity assumption may underestimate the 100-year 24-h events by 10% to 60% towards the end of the century at most grids, resulting in significant under-designing of the engineering infrastructure at the study site. Strong spatial heterogeneity and variability in the IDF estimates suggest a preference for using high resolution simulation data for the reliable estimation of exceedance probability over data from sparsely distributed weather stations. Discrepancies among the three IDFs analyses due to non-stationarity are comparable to the spatial variability of the IDFs, underscoring a need to use an ensemble of non-stationary approaches to achieve unbiased and comprehensive IDF estimates.},
doi = {10.3390/w11061296},
journal = {Water (Basel)},
number = 6,
volume = 11,
place = {United States},
year = {2019},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 1 work
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

Critical review of the evolution of the design storm event concept
journal, February 2013

  • Watt, Ed; Marsalek, Jiri
  • Canadian Journal of Civil Engineering, Vol. 40, Issue 2
  • DOI: 10.1139/cjce-2011-0594

Generating robust rainfall intensity–duration–frequency estimates with short-record satellite data
journal, June 2009


Flood frequency analysis based on simulated peak discharges
journal, November 2013


Dynamics of flood frequency
journal, August 1972


CMIP5 multimodel ensemble projection of storm track change under global warming: CMIP5 MODEL-PROJECTED STORM TRACK CHANGE
journal, December 2012

  • Chang, Edmund K. M.; Guo, Yanjuan; Xia, Xiaoming
  • Journal of Geophysical Research: Atmospheres, Vol. 117, Issue D23
  • DOI: 10.1029/2012JD018578

Intensification of Northern Hemisphere subtropical highs in a warming climate
journal, September 2012

  • Li, Wenhong; Li, Laifang; Ting, Mingfang
  • Nature Geoscience, Vol. 5, Issue 11
  • DOI: 10.1038/ngeo1590

Rainfall Intensity Duration Frequency Curves Under Climate Change: City of London, Ontario, Canada
journal, January 2012

  • Peck, Angela; Prodanovic, Predrag; Simonovic, Slobodan P. P.
  • Canadian Water Resources Journal / Revue canadienne des ressources hydriques, Vol. 37, Issue 3
  • DOI: 10.4296/cwrj2011-935

Future changes to the intensity and frequency of short-duration extreme rainfall: FUTURE INTENSITY OF SUB-DAILY RAINFALL
journal, August 2014

  • Westra, S.; Fowler, H. J.; Evans, J. P.
  • Reviews of Geophysics, Vol. 52, Issue 3
  • DOI: 10.1002/2014RG000464

Time‐varying extreme rainfall intensity‐duration‐frequency curves in a changing climate
journal, March 2017

  • Sarhadi, Ali; Soulis, Eric D.
  • Geophysical Research Letters, Vol. 44, Issue 5
  • DOI: 10.1002/2016GL072201

Assessment of future change in intensity–duration–frequency (IDF) curves for Southern Quebec using the Canadian Regional Climate Model (CRCM)
journal, December 2007


Non-stationary frequency analysis of extreme daily rainfall in Sao Paulo, Brazil
journal, July 2009

  • Sugahara, Shigetoshi; da Rocha, Rosmeri Porfírio; Silveira, Reinaldo
  • International Journal of Climatology, Vol. 29, Issue 9
  • DOI: 10.1002/joc.1760

A Bayesian beta distribution model for estimating rainfall IDF curves in a changing climate
journal, September 2016


Modeling non-stationarity in intensity, duration and frequency of extreme rainfall over India
journal, February 2015


Intensity-Duration-Frequency (IDF) rainfall curves, for data series and climate projection in African cities
journal, January 2014


A nonstationary flood frequency analysis method to adjust for future climate change and urbanization
journal, January 2012


Climate Change Impacts in the Design of Drainage Systems: Case Study of Portugal
journal, February 2015

  • Modesto Gonzalez Pereira, Mário Jorge; Sanches Fernandes, Luís Filipe; Barros Macário, Eduarda Maria
  • Journal of Irrigation and Drainage Engineering, Vol. 141, Issue 2
  • DOI: 10.1061/(ASCE)IR.1943-4774.0000788

Influence of Climate Change on the Design of Retention Basins in Northeastern Portugal
journal, June 2018

  • Sanches Fernandes, Luis; Pereira, Mário; Morgado, Sónia
  • Water, Vol. 10, Issue 6
  • DOI: 10.3390/w10060743

Negligent killing of scientific concepts: the stationarity case
journal, June 2015


Stationary and Non-Stationary Frameworks for Extreme Rainfall Time Series in Southern Italy
journal, October 2018


Stationarity is undead: Uncertainty dominates the distribution of extremes
journal, March 2015


The Value of High-Resolution Met Office Regional Climate Models in the Simulation of Multihourly Precipitation Extremes
journal, August 2014

  • Chan, Steven C.; Kendon, Elizabeth J.; Fowler, Hayley J.
  • Journal of Climate, Vol. 27, Issue 16
  • DOI: 10.1175/JCLI-D-13-00723.1

Robust spring drying in the southwestern U.S. and seasonal migration of wet/dry patterns in a warmer climate: FUTURE WATER AVAILABILITY CHANGES
journal, March 2014

  • Gao, Yang; Leung, L. Ruby; Lu, Jian
  • Geophysical Research Letters, Vol. 41, Issue 5
  • DOI: 10.1002/2014GL059562

The Community Climate System Model Version 4
journal, October 2011

  • Gent, Peter R.; Danabasoglu, Gokhan; Donner, Leo J.
  • Journal of Climate, Vol. 24, Issue 19
  • DOI: 10.1175/2011JCLI4083.1

An Overview of CMIP5 and the Experiment Design
journal, April 2012

  • Taylor, Karl E.; Stouffer, Ronald J.; Meehl, Gerald A.
  • Bulletin of the American Meteorological Society, Vol. 93, Issue 4
  • DOI: 10.1175/BAMS-D-11-00094.1

Nonparametric Tests Against Trend
journal, July 1945


Trends of precipitation in Beijiang River Basin, Guangdong Province, China
journal, January 2008

  • Luo, Yan; Liu, Shen; Fu, ShengLei
  • Hydrological Processes, Vol. 22, Issue 13
  • DOI: 10.1002/hyp.6801

Monte Carlo Experiments on the Detection of Trends in Extreme Values
journal, May 2004


Detecting rainfall trends in twentieth century (1871–2006) over Orissa State, India
journal, August 2011


Recent changes in rainfall and rainy days in Ethiopia
journal, June 2004

  • Seleshi, Yilma; Zanke, Ulrich
  • International Journal of Climatology, Vol. 24, Issue 8
  • DOI: 10.1002/joc.1052

Extreme Rainfall Nonstationarity Investigation and Intensity–Frequency–Duration Relationship
journal, June 2014


Estimates of the Regression Coefficient Based on Kendall's Tau
journal, December 1968


Rainfall and river flow trends using Mann–Kendall and Sen’s slope estimator statistical tests in the Cobres River basin
journal, February 2015

  • da Silva, Richarde Marques; Santos, Celso A. G.; Moreira, Madalena
  • Natural Hazards, Vol. 77, Issue 2
  • DOI: 10.1007/s11069-015-1644-7

Trend analysis in Turkish precipitation data
journal, January 2006

  • Partal, Turgay; Kahya, Ercan
  • Hydrological Processes, Vol. 20, Issue 9
  • DOI: 10.1002/hyp.5993

More extreme precipitation in the world’s dry and wet regions
journal, March 2016

  • Donat, Markus G.; Lowry, Andrew L.; Alexander, Lisa V.
  • Nature Climate Change, Vol. 6, Issue 5
  • DOI: 10.1038/nclimate2941

Adaptive sequential segmentation of piecewise stationary time series
journal, February 1983


Weather Regimes: Recurrence and Quasi Stationarity
journal, April 1995


Nonstationary Precipitation Intensity-Duration-Frequency Curves for Infrastructure Design in a Changing Climate
journal, November 2014

  • Cheng, Linyin; AghaKouchak, Amir
  • Scientific Reports, Vol. 4, Issue 1
  • DOI: 10.1038/srep07093

Non-stationary extreme value analysis in a changing climate
journal, September 2014


Statistics of extremes in hydrology
journal, August 2002


New Software to Analyze How Extremes Change Over Time
journal, January 2011

  • Gilleland, Eric; Katz, Richard W.
  • Eos, Transactions American Geophysical Union, Vol. 92, Issue 2
  • DOI: 10.1029/2011EO020001

Flood Frequency Analysis Using Gumbel's Distribution Method: A Case Study of Lower Mahi Basin, India
journal, January 2017


Statistics of extremes in climate change
journal, May 2010


Quantifying Changes in Future Intensity‐Duration‐Frequency Curves Using Multimodel Ensemble Simulations
journal, March 2018

  • Ragno, Elisa; AghaKouchak, Amir; Love, Charlotte A.
  • Water Resources Research, Vol. 54, Issue 3
  • DOI: 10.1002/2017WR021975

Differential Evolution Markov Chain with snooker updater and fewer chains
journal, October 2008


Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling
journal, January 2009

  • Vrugt, J. A.; ter Braak, C. J. F.; Diks, C. G. H.
  • International Journal of Nonlinear Sciences and Numerical Simulation, Vol. 10, Issue 3
  • DOI: 10.1515/IJNSNS.2009.10.3.273