Review of rainfall frequency estimation methods

Svensson, Cecilia; Jones, David A.

doi:10.1111/j.1753-318x.2010.01079.x

Cited by 92 publications

(59 citation statements)

References 23 publications

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“…In the UK, the industry standard for flood event return period analysis follows the Flood Estimation Handbook (FEH) flood frequency curve approach which is based on fitting a Generalised Extreme Value (GEV) or Generalised Logistic (GL) function [22] to annual maximum (AM) flow series. However, other popular methods include the Generalised Pareto (GP) distribution function which is fitted on peak-over-threshold (POT) series [23][24][25]. Methods based on AM or POT series have well-known advantages and disadvantages.…”

Section: Extreme Values Assessment and Automating Approachesmentioning

confidence: 99%

Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain

Collet

Beevers

Prudhomme

2017

Water

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Floods are the most common and widely distributed natural risk, causing over £1 billion of damage per year in the UK as a result of recent events. Climatic projections predict an increase in flood risk; it becomes urgent to assess climate change impact on extreme flows, and evaluate uncertainties related to these projections. This paper aims to assess the changes in extreme runoff for the 1:100 year return period across Great Britain as a result of climate change using the Future Flows Hydrology database. The Generalised Extreme Value (GEV) and Generalised Pareto (GP) models are automatically fitted for 11-member ensemble flow series available for the baseline and the 2080s. The analysis evaluates the uncertainty related to the Extreme Value (EV) and climate model parameters. Results suggest that GP and GEV give similar runoff estimates and uncertainties. From the baseline to the 2080s, increasing estimate and uncertainties is evident in east England. With the GEV the uncertainty attributed to the climate model parameters is greater than for the GP (around 60% and 40% of the total uncertainty, respectively). This shows that when fitting both EV models, the uncertainty related to their parameters has to be accounted for to assess extreme runoffs.

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Section: Extreme Values Assessment and Automating Approachesmentioning

confidence: 99%

Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain

Collet

Beevers

Prudhomme

2017

Water

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“…The IDF curves are based on fitting a theoretical probability distribution to shortduration (sub-hourly, hourly, and daily) annual maximum precipitation (AMP). The approach can be implemented both locally (at site) or regionally (Svensson and Jones, 2010; regional frequency analysis (RFA) or pooled). The RFA is used when available record lengths are short or at locations where no observed data are available (Castellarin et al, 2012;Komi et al, 2016).…”

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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“…They find that the ratio scale/location σ/µ, and, as a consequence, the coefficient of variation, increase with decreasing duration, concluding that a simple scaling formula cannot hold. In other works (Borga et al, 2005;Svensson and Jones, 2010), 5. Maps of the estimated GEV parameters ε (location, left) α (scale, centre) and ξ (shape, right), all dimensionless.…”

Section: Depth-duration-frequency Curves and Scale Invariancementioning

confidence: 99%

“…Most methods are based on parameter estimation of Gumbel or GEV distribution and make use of a growth curve to relate a statistical rainfall index to a design rainfall/flood estimate (indexflood method). What is of interest for the present work is that many methods reviewed by Svensson and Jones (2010) make use of some form of regionalisation, either by spatially interpolating the distribution parameters after estimation at station points, or by using together data from homogeneous areas, either defined by geographical boundaries, or centred around a location of interest.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Svensson and Jones (2010) have reviewed methods applied in 9 countries worldwide to characterise rainfall and flood return periods relevant for dam design. Most methods are based on parameter estimation of Gumbel or GEV distribution and make use of a growth curve to relate a statistical rainfall index to a design rainfall/flood estimate (indexflood method).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A spatial bootstrap technique for parameter estimation of rainfall annual maxima distribution

Uboldi¹,

Sulis

Lussana

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Estimation of extreme event distributions and depth-duration-frequency (DDF) curves is achieved at any target site by repeated sampling among all available raingauge data in the surrounding area. The estimate is computed over a gridded domain in Northern Italy, using precipitation time series from 1929 to 2011, including data from historical analog stations and from the present-day automatic observational network. The presented local regionalisation naturally overcomes traditional station-point methods, with their demand of long historical series and their sensitivity to very rare events occurring at very few stations, possibly causing unrealistic spatial gradients in DDF relations. At the same time, the presented approach allows for spatial dependence, necessary in a geographical domain such as Lombardy, complex for both its topography and its climatology. The bootstrap technique enables evaluating uncertainty maps for all estimated parameters and for rainfall depths at assigned return periods.

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Review of rainfall frequency estimation methods

Abstract: This review outlines nationwide methods for point rainfall frequency estimation currently in use in nine different countries:

Cited by 92 publications

References 23 publications

Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain

Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain

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

A spatial bootstrap technique for parameter estimation of rainfall annual maxima distribution

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