Updating <scp>intensity–duration–frequency</scp> curves for urban infrastructure design under a changing environment

Yan, Lei; Xiong, Lihua; Jiang, Cong; Zhang, Mengjie; Wang, Dong; Xu, Chong‐Yu

doi:10.1002/wat2.1519

Cited by 42 publications

(23 citation statements)

References 140 publications

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“…In future studies, we plan to include spatial covariates into the estimation of the newly proposed d-GEV parameters, including intensity offset, in order to use data from different locations more efficiently. Also, the concept of non-stationary precipitation with respect to IDF curves is important to consider (see Cheng and AghaKouchak, 2014;Ganguli and Coulibaly, 2017;Yan et al, 2021) since extremes are expected to vary due to climate change. For example, Benestad et al (2021) found a model that enables downscaling of 24 h measurement data to shorter durations without assuming stationarity.…”

Section: Discussionmentioning

confidence: 99%

Flexible and consistent quantile estimation for intensity–duration–frequency curves

Fauer¹,

Ulrich²,

Jurado³

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. Assessing the relationship between the intensity, duration, and frequency (IDF) of extreme precipitation is required for the design of water management systems. However, when modeling sub-daily precipitation extremes, there are commonly only short observation time series available. This problem can be overcome by applying the duration-dependent formulation of the generalized extreme value (GEV) distribution which fits an IDF model with a range of durations simultaneously. The originally proposed duration-dependent GEV model exhibits a power-law-like behavior of the quantiles and takes care of a deviation from this scaling relation (curvature) for sub-hourly durations (Koutsoyiannis et al., 1998). We suggest that a more flexible model might be required to model a wide range of durations (1 min to 5 d). Therefore, we extend the model with the following two features: (i) different slopes for different quantiles (multiscaling) and (ii) the deviation from the power law for large durations (flattening), which is newly introduced in this study. Based on the quantile skill score, we investigate the performance of the resulting flexible model with respect to the benefit of the individual features (curvature, multiscaling, and flattening) with simulated and empirical data. We provide detailed information on the duration and probability ranges for which specific features or a systematic combination of features leads to improvements for stations in a case study area in the Wupper catchment (Germany). Our results show that allowing curvature or multiscaling improves the model only for very short or long durations, respectively, but leads to disadvantages in modeling the other duration ranges. In contrast, allowing flattening on average leads to an improvement for medium durations between 1 h and 1 d, without affecting other duration regimes. Overall, the new parametric form offers a flexible and enhanced performance model for consistently describing IDF relations over a wide range of durations, which has not been done before as most existing studies focus on durations longer than 1 h or day and do not address the deviation from the power law for very long durations (2–5 d).

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Section: Discussionmentioning

confidence: 99%

Flexible and consistent quantile estimation for intensity–duration–frequency curves

Fauer¹,

Ulrich²,

Jurado³

et al. 2021

Hydrol. Earth Syst. Sci.

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“…We can affirm that most existing stormwater runoff infrastructures are ill-adapted, and design strategies, including climate change adaptation, need to be implemented (Lopez-Cantu and Samaras 2018;Myhre et al 2019). IDF curves are a critical part of the design process and require updating to account for an evolving climate and reduce infrastructure vulnerability (ASCE 2018;Watt and Marsalek 2013;Yan et al 2021).…”

Section: Introductionmentioning

confidence: 98%

Climate Change and Rainfall Intensity–Duration–Frequency Curves: Overview of Science and Guidelines for Adaptation

et al. 2021

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One of the most important impacts of a future warmer climate is the projected increase in the frequency and intensity of extreme rainfall events. This increasing trend in extreme rainfall is seen in both the observational record and climate model projections. However, a thorough review of the recent scientific literature paints a complex picture in which the intensification of rainfall extremes depends on a multitude of factors. While some projected rainfall indices follow the Clausius-Clapeyron relationship scaling of an ∼7% increase in rainfall per 1°C of warming, there is substantial evidence that this scaling depends on rainfall extremes frequency, with longer return period events seeing larger increases, leading to super Clausius-Clapeyron scaling in some cases. The intensification of extreme rainfall events is now well documented at the daily scale but is less clear at the subdaily scale. In recent years, climate model simulations at a finer spatial and temporal resolution, including convection-permitting models, have provided more reliable projections of subdaily rainfall. Recent analyses indicate that rainfall scaling may also increase as a function of duration, such that shorter-duration, longer return period events will likely see the largest rainfall increases in a warmer climate. This has broad implications on the design and the use of rainfall intensity-duration-frequency (IDF) curves, for which both an overall increase in magnitude and a steepening can now be predicted. This paper also presents an overview of measures that have been adopted by various governing bodies to adapt IDF curves to the changing climate. Current measures vary from multiplying historical design rainfall by a simple constant percentage to modulating correction factors based on return periods and to scaling them to the Clausius-Clapeyron relationship based on projected temperature increases. All of these current measures fail to recognize a possible super Clausius-Clapeyron scaling of extreme rainfall and, perhaps more importantly, the increasing scaling toward shorter-duration rainfall and the most extreme rainfall events that will significantly impact stormwater runoff in cities and in small rural catchments. This paper discusses the remaining scientific gaps and offers technical recommendations for practitioners on how to adapt IDF curves to improve climate resilience.

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“…It is now recognized that these changes are responsible for higher frequency and/or intensity of extreme rainfall (Ganguli and Coulibaly, 2017;Agilan and Umamahesh, 2016). Rainfall extremes and their statistical properties are important for proper estimations of design values in numerous engineering infrastructures such as urban drainage systems, bridges, railways, highways, rain harvesting systems and road culverts can be designed more economically when the frequency of extreme rainfall is known (Yan et al, 2021;Lakatos et al, 2020;Onderka et al, 2020;Bara et al, 2009;Faško et al, 2000). Rainfall extremes can studied at a range of spatial and temporal scales (AghaKouchak et al, 2013;Diffenbaugh and Giorgi, 2012;Jakob, 2013;Kharin et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Observations from the Western Carpathians and Pannonian Plain show that rainfall return levels need to be adjusted to account for rising dew-point temperature

Onderka¹,

Pecho²

2022

AHS

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Rainfall records from a total of 526 rain gauges located in the western part of the Carpathian Mountains and the adjacent Pannonian Plain were analyzed. Estimation of extreme rainfall totals with various return periods is essential for reliable design of hydraulic infrastructure. The ongoing climate change brings additional challenges to the estimation of rainfall return levels. In this paper, we compared stationary vs. non-stationary generalized extreme value distributions (GEV) for 2-, 5-, 10-, 25-, 50-, and 100-year return levels of 24-h rainfall determined from annual maxima series. The fundamental question we seek to answer in this paper is whether the stationarity-based design concept is adequate under changing climate conditions because the statistical parameters of probability distribution become dependent on dew-point temperature. Our analyses revealed that the projected return levels tend to increase with decreasing return periods. For instance, the 100-year return levels need an adjustment by ~6.64% (CI: -1.03% +14.95%), while the stationary 5-year return periods of 24-h precipitation totals need to be adjusted by up to ~10.5% (CI: -3.61% +21.24%). Our investigations showed that in ~60% of the analyzed sites the current return levels might need an adjustment to account for the rising dew-point temperature. The presented results may have implication for regional water management planning and flood risk assessment.

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Updating intensity–duration–frequency curves for urban infrastructure design under a changing environment

Cited by 42 publications

References 140 publications

Flexible and consistent quantile estimation for intensity–duration–frequency curves

Flexible and consistent quantile estimation for intensity–duration–frequency curves

Climate Change and Rainfall Intensity–Duration–Frequency Curves: Overview of Science and Guidelines for Adaptation

Observations from the Western Carpathians and Pannonian Plain show that rainfall return levels need to be adjusted to account for rising dew-point temperature

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