Flood Risk Management Decision Analysis with Finite Historical Records and Highly Variable Climate Effects

Rehan, Balqis Mohamed

doi:10.1061/9780784413609.289

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…The power seems more important in such situations, as Vogel et al (2013) argued, because the power informs us about the likelihood of whether society is prepared to accommodate and respond to such trends. Delaying action should be made when designing flood control engineering if there are no sufficient historical data (Rehan and Hall, 2014).…”

Section: Evaluation Of the Power Of The Mk Testmentioning

confidence: 99%

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

et al. 2020

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The Mann-Kendall (MK) statistical test has been widely applied in the trend detection of the hydrometeorological time series. Previous studies have mainly focused on the null hypothesis of "no trend" or the "Type I Error." However, few studies address the capability of the MK test to successfully recognize the trends. In some cases, especially when the trend test is jointly applied with hydropower station design, flood risk assessment, and water quality evaluation, the "Type II error" is equally important and should not be neglected. To cope with this problem, we carry out Monte Carlo simulations and the results indicate that in addition to the significance level and the sample length, the MK test power has a close relationship with the sample variance and the magnitude of the trend. For a given time series with fixed length, the power of the MK test increases as the slope increases and declines with increasing sample variance. A deterministic relationship between the slope and the standard deviation of the white noise that can be used for evaluating the power of the MK test has also been detected. Furthermore, we find that a positive autocorrelation contained in the time series will increase both the Type I and the Type II errors due to the enlargement of the variance in the MK statistics. Finally, we recommend that researchers slightly increase the significance level and lengthen the time series sample to improve the power of the MK test in future studies.

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Section: Evaluation Of the Power Of The Mk Testmentioning

confidence: 99%

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

et al. 2020

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“…The probability distribution function for the risk calculations was based on the Generalised Extreme Value (GEV) distribution of the annual maxima series with the location, scale and shape parameters estimated by L‐moments as 260, 94.6 and 0.04, respectively (Rehan & Hall, 2014). The annual maxima series used to configure the GEV distribution were taken from Thames@Kingston station's peak flow data ranging from years 1890 to 2010.…”

Section: Applicationmentioning

confidence: 99%

A comparison of the cost effectiveness of property‐level adaptation and community‐scale flood defences in reducing flood risk

Rehan,

Hall,

Penning‐Rowsell

et al. 2023

J Flood Risk Management

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Adaptations to flood‐proof individual properties (referred to here as property‐level adaptation, PLA) provide a potential means of reducing flood risk at isolated properties, whilst conventional community‐scale flood protection (CSFP) is usually more economical in protecting high‐density urban spaces. This paper develops a risk‐based framework to identify the tipping point when PLA measures become more cost‐beneficial when compared to CSFP in different urban densities. The framework was demonstrated using a hypothetical case study based on a residential area in Teddington, London. Sensitivity analysis was performed by varying the building densities in the urban space. Results show that PLA can have a role to supplement CSFP even in dense urban areas if the CSFP standard of protection is low. However, adding some element of CSFP to PLA can be more cost‐effective than implementing a single higher protection standard of PLA. Given the unique flood risk condition of most urban spaces, and the sensitivity of cost‐effectiveness of flood adaptation measures such as those demonstrated in this work, this approach can provide additional information to assist decisions in finding a sensible portfolio of measures that match that risk condition.

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Data Analysis in Nonstationary State

Alashan

2018

Water Resour Manage

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Flood Risk Management Decision Analysis with Finite Historical Records and Highly Variable Climate Effects

Cited by 3 publications

References 16 publications

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

A comparison of the cost effectiveness of property‐level adaptation and community‐scale flood defences in reducing flood risk

Data Analysis in Nonstationary State

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