Time‐varying extreme rainfall intensity‐duration‐frequency curves in a changing climate

Sarhadi, Ali; Soulis, E. D.

doi:10.1002/2016gl072201

Cited by 132 publications

(69 citation statements)

References 29 publications

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“…Nevertheless, the methodology to derive existing IDF curves has certain drawbacks, for example that the current IDF curves in Canada are based on the assumption of stationarity, which implies that statistical properties of hydroclimatic time series will remain the same over the period of time. However, the impact of urbanization and humaninduced climate change (IPCC SREX, 2012;Villarini et al, 2009a;Milly et al, 2009;Kunkel, 2003) raises the question of whether the stationarity assumption to derive IDF curves is still reliable for urban infrastructural planning (Sarhadi and Soulis, 2017;Cheng and AghaKouchak, 2014;Jakob, 2013;Yilmaz et al, 2014a;Yilmaz and Perera, 2013).…”

Section: Introductionmentioning

confidence: 99%

Does nonstationarity in rainfall require nonstationary intensity–duration–frequency curves?

Ganguli

Coulibaly

2017

Hydrol. Earth Syst. Sci.

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Abstract. In Canada, risk of flooding due to heavy rainfall has risen in recent decades; the most notable recent examples include the July 2013 storm in the Greater Toronto region and the May 2017 flood of the Toronto Islands. We investigate nonstationarity and trends in the short-duration precipitation extremes in selected urbanized locations in Southern Ontario, Canada, and evaluate the potential of nonstationary intensity-duration-frequency (IDF) curves, which form an input to civil infrastructural design. Despite apparent signals of nonstationarity in precipitation extremes in all locations, the stationary vs. nonstationary models do not exhibit any significant differences in the design storm intensity, especially for short recurrence intervals (up to 10 years). The signatures of nonstationarity in rainfall extremes do not necessarily imply the use of nonstationary IDFs for design considerations. When comparing the proposed IDFs with current design standards, for return periods (10 years or less) typical for urban drainage design, current design standards require an update of up to 7 %, whereas for longer recurrence intervals (50-100 years), ideal for critical civil infrastructural design, updates ranging between ∼ 2 and 44 % are suggested. We further emphasize that the above findings need re-evaluation in the light of climate change projections since the intensity and frequency of extreme precipitation are expected to intensify due to global warming.

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Section: Introductionmentioning

confidence: 99%

Does nonstationarity in rainfall require nonstationary intensity–duration–frequency curves?

Ganguli

Coulibaly

2017

Hydrol. Earth Syst. Sci.

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“…The RAMK test indicates that trends are 25 statistically positive for 15-, 30-, and 1440-minute durations. The lack of a clear signal in the direction of the trends has been previously reported for other regions (Sarhadi and Soulis, 2017) and might be linked to the weak power of statistical methods when the data are affected by high natural variability as is the case of precipitation (Renard et al, 2008).…”

Section: Trend Analysis Of Precipitation Extremesmentioning

confidence: 92%

“…In addition, positive increases in observed precipitation linked to a warmer atmosphere also bring into question the validity of the IDF curves developed under stationary assumptions and has prompted the development of new methods for determining return periods and risk that take 20 into account the effect of non-stationary in climate extremes (Bhatkoti et al, 2016;Condon et al, 2015;Du et al, 2015;Khaliq et al, 2006;Obeysekera and Salas, 2014;Salas and Obeysekera, 2014;Serinaldi and Kilsby, 2015). A few climate studies have shown that design storm estimates from stationary models are significantly lower than estimates from nonstationary models (Cheng and AghaKouchak, 2014;Sarhadi and Soulis, 2017;Wi et al, 2016). However, the lack of observed sub-daily precipitation limits the studies to using scaling factors to temporally disaggregate daily observations or 25 use merged radar-rain gauge data (Cheng and AghaKouchak, 2014;Yu et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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

Demaria

Goodrich

Keefer

2017

Preprint

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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)-10 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 15 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 20 storm design.

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“…For example, Cheng and AghaKouchak [78] employed a nonstationary GEV distribution with a time-varying location parameter to model a nonstationary IDF curve. They fitted the nonstationary GEV distribution for each duration examined, and their study provided an IDF curve for extreme rainfall events in the U.S. Sarhadi and Soulis [79] modeled a nonstationary IDF curve using the nonstationary GEV distribution with time-varying location and scale parameters. However, the temporal structure of the extreme rainfall events of South Korea change, although there is no trend in the mean of extreme rainfall events.…”

Section: Characteristics Of Spatial and Temporal Structure Of Extremementioning

confidence: 99%

The Spatial and Temporal Structure of Extreme Rainfall Trends in South Korea

Jung

Shin

Ahn

et al. 2017

Water

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Abstract:The spatial and temporal structures of extreme rainfall trends in South Korea are investigated in the current study. The trends in the annual maximum rainfall series are detected and their spatial distribution is analyzed. The scaling exponent is employed as an index representing the temporal structure. The temporal structure of the annual maximum series is calculated and spatially analyzed. Subsequently, the block bootstrap based Mann-Kendall test is employed detect the trend in the scaling exponent series subsampled by the annual maximum rainfalls using a moving window. Significant trends are detected in a small number of stations and there are no significant trends in many stations for the annual maximum rainfall series. There is a large variability in the temporal structures of the extreme rainfall events. Additionally, the variations of the scaling exponent estimates for each month within a rainy season are larger than the variation of the scaling exponent estimates on an annual basis. Significant trends in the temporal structures are observed at many stations unlike the trend test results of annual maximum rainfall series. Decreasing trends are observed at many stations located in the coastal area, while increasing trends are observed in the inland area.

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Time‐varying extreme rainfall intensity‐duration‐frequency curves in a changing climate

Cited by 132 publications

References 29 publications

Does nonstationarity in rainfall require nonstationary intensity–duration–frequency curves?

Does nonstationarity in rainfall require nonstationary intensity–duration–frequency curves?

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

The Spatial and Temporal Structure of Extreme Rainfall Trends in South Korea

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