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  • 1
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    Non-stationarity in annual and seasonal series of peak flow and precipitation in the UK (2013)
    Copernicus
    Details
    Publication Date: 2013-10-14
    Description: When designing or maintaining an hydraulic structure, an estimate of the frequency and magnitude of extreme events is required. The most common methods to obtain such estimates rely on the assumption of stationarity, i.e. the assumption that the process under study is not changing. The public perception and worry of a changing climate have led to a wide debate on the validity of this assumption. In this work trends for annual and seasonal maxima in peak river flow and catchment-average daily rainfall are explored. Assuming a 2-parameters log-normal distribution, a linear regression model is applied, allowing the mean of the distribution to vary with time. For the river flow data, the linear model is extended to include an additional variable, the 99th percentile of the daily rainfall for a year. From the fitted models, dimensionless magnification factors are estimated and plotted on a map, shedding light on whether or not geographical coherence can be found in the significant changes. The implications of the identified trends from a decision making perspective are then discussed, in particular with regard to the Type I and Type II error probabilities. One striking feature of the estimated trends is that the high variability found in the data leads to very inconclusive test results. Indeed, for most stations it is impossible to make a statement regarding whether or not the current design standards for the 2085 horizon can be considered precautionary. The power of tests on trends is further discussed in the light of statistical power analysis and sample size calculations.
    Electronic ISSN: 2195-9269
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 2
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    Reassessing flood frequency For the Sussex Ouse, Lewes: the Inclusion of historical Flood Information since AD 1650 (2013)
    Copernicus
    Details
    Publication Date: 2013-12-19
    Description: The application of historical flood information as a tool for augmenting instrumental flood data is increasingly recognised as a valuable tool; most previous studies have focused on large catchments with historic settlements, this paper applies the approach to the smaller lowland system of the Sussex Ouse in Southeast England. The reassessment of flood risk on the Sussex Ouse is pertinent in light of severe flooding in October 2000 and heightened concerns of a perceived increase in flooding nationally. Systematic flood level readings from 1960 and accounts detailing past flood events within the catchment are compiled back to c.1750. This extended flood record provides an opportunity to reassess estimates of flood frequency over a timescale not normally possible within flood frequency analysis. This paper re-evaluates flood frequency at Lewes on the Sussex Ouse downstream of the confluence of the Sussex Ouse and River Uck. The paper considers the strengths and weaknesses in estimates resulting from contrasting methods of analysis and their corresponding data: (i) single site analysis of gauged annual maxima; (ii) combined analysis of systematic annual maxima augmented with historical peaks of estimated magnitude; (iii) combined analysis of systematic annual maxima augmented with historical peaks of estimated magnitude exceeding a known threshold, and (iv) sensitivity analysis including only the very largest historical flood events. Use of the historical information was found to yield much tighter confidence intervals of risk estimates, with uncertainty reduced by up to 40% for the 100 yr return frequency event when historical information was added to the gauged data.
    Electronic ISSN: 2195-9269
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 3
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    Reassessing flood frequency for the Sussex Ouse, Lewes: the inclusion of historical flood information since AD 1650 (2014)
    Copernicus
    Details
    Publication Date: 2014-10-30
    Description: The application of historical flood information as a tool for augmenting instrumental flood data is increasingly recognised as a valuable tool. Most previous studies have focused on large catchments with historic settlements, this paper applies the approach to the smaller lowland system of the Sussex Ouse in southeast England. The reassessment of flood risk on the Sussex Ouse is pertinent in light of the severe flooding in October 2000 and heightened concerns of a perceived increase in flooding nationally. Systematic flood level readings from 1960 and accounts detailing past flood events within the catchment are compiled back to ca. 1750. This extended flood record provides an opportunity to reassess estimates of flood frequency over a timescale not normally possible within flood frequency analysis. This paper re-evaluates flood frequency at Lewes on the Sussex Ouse downstream of the confluence of the Sussex Ouse and River Uck. The paper considers the strengths and weaknesses in estimates resulting from contrasting methods of analysis and their corresponding data: (i) single site analysis of gauged annual maxima; (ii) combined analysis of systematic annual maxima augmented with historical peaks of estimated magnitude; (iii) combined analysis of systematic annual maxima augmented with historical peaks of estimated magnitude exceeding a known threshold, and (iv) sensitivity analysis including only the very largest historical flood events. Use of the historical information was found to yield much tighter confidence intervals of risk estimates, with uncertainty reduced by up to 40% for the 100-year return frequency event when historical information was added to the gauged data.
    Print ISSN: 1561-8633
    Electronic ISSN: 1684-9981
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 4
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    Non-stationarity in annual and seasonal series of peak flow and precipitation in the UK (2014)
    Copernicus
    Details
    Publication Date: 2014-05-16
    Description: When designing or maintaining an hydraulic structure, an estimate of the frequency and magnitude of extreme events is required. The most common methods to obtain such estimates rely on the assumption of stationarity, i.e. the assumption that the stochastic process under study is not changing. The public perception and worry of a changing climate have led to a wide debate on the validity of this assumption. In this work trends for annual and seasonal maxima in peak river flow and catchment-average daily rainfall are explored. Assuming a two-parameter log-normal distribution, a linear regression model is applied, allowing the mean of the distribution to vary with time. For the river flow data, the linear model is extended to include an additional variable, the 99th percentile of the daily rainfall for a year. From the fitted models, dimensionless magnification factors are estimated and plotted on a map, shedding light on whether or not geographical coherence can be found in the significant changes. The implications of the identified trends from a decision-making perspective are then discussed, in particular with regard to the Type I and Type II error probabilities. One striking feature of the estimated trends is that the high variability found in the data leads to very inconclusive test results. Indeed, for most stations it is impossible to make a statement regarding whether or not the current design standards for the 2085 horizon can be considered precautionary. The power of tests on trends is further discussed in the light of statistical power analysis and sample size calculations. Given the observed variability in the data, sample sizes of some hundreds of years would be needed to confirm or negate the current safety margins when using at-site analysis.
    Print ISSN: 1561-8633
    Electronic ISSN: 1684-9981
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 5
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    CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological use (2015)
    Copernicus
    Details
    Publication Date: 2015-01-27
    Description: The Centre for Ecology & Hydrology – Gridded Estimates of Areal Rainfall (CEH-GEAR) dataset was developed to provide reliable 1 km gridded estimates of daily and monthly rainfall for Great Britain (GB) and Northern Ireland (NI) (together with approximately 3500 km2 of catchment in the Republic of Ireland) from 1890 onwards. The dataset was primarily required to support hydrological modelling. The rainfall estimates are derived from the Met Office collated historical weather observations for the UK which include a national database of raingauge observations. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall, was used to generate the daily and monthly rainfall grids. To derive the monthly estimates, rainfall totals from monthly and daily (when complete month available) read raingauges were used in order to obtain maximum information from the raingauge network. The daily grids were adjusted so that the monthly grids are fully consistent with the daily grids. The CEH-GEAR dataset was developed according to the guidance provided by the British Standards Institution. The CEH-GEAR dataset contains 1 km grids of daily and monthly rainfall estimates for GB and NI for the period 1890–2012. For each day and month, CEH-GEAR includes a secondary grid of distance to the nearest operational raingauge. This may be used as an indicator of the quality of the estimates. When this distance is greater than 100 km, the estimates are not calculated due to high uncertainty. CEH-GEAR is available free of charge for commercial and non-commercial use subject to licensing terms and conditions. doi:10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e
    Electronic ISSN: 1866-3591
    Topics: Geosciences
    Published by Copernicus
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  • 6
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    CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological and other applications (2015)
    Copernicus
    Details
    Publication Date: 2015-06-29
    Description: The Centre for Ecology & Hydrology – Gridded Estimates of Areal Rainfall (CEH-GEAR) data set was developed to provide reliable 1 km gridded estimates of daily and monthly rainfall for Great Britain (GB) and Northern Ireland (NI) (together with approximately 3500 km2 of catchment in the Republic of Ireland) from 1890 onwards. The data set was primarily required to support hydrological modelling. The rainfall estimates are derived from the Met Office collated historical weather observations for the UK which include a national database of rain gauge observations. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall (AAR), was used to generate the daily and monthly rainfall grids. To derive the monthly estimates, rainfall totals from monthly and daily (when complete month available) rain gauges were used in order to obtain maximum information from the rain gauge network. The daily grids were adjusted so that the monthly grids are fully consistent with the daily grids. The CEH-GEAR data set was developed according to the guidance provided by the British Standards Institution. The CEH-GEAR data set contains 1 km grids of daily and monthly rainfall estimates for GB and NI for the period 1890–2012. For each day and month, CEH-GEAR includes a secondary grid of distance to the nearest operational rain gauge. This may be used as an indicator of the quality of the estimates. When this distance is greater than 100 km, the estimates are not calculated due to high uncertainty. CEH-GEAR is available from doi:10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e and is free of charge for commercial and non-commercial use subject to licensing terms and conditions.
    Print ISSN: 1866-3508
    Electronic ISSN: 1866-3516
    Topics: Geosciences
    Published by Copernicus
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  • 7
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    Assessing the element of surprise of record-breaking flood events (2016)
    Wiley
    Details
    Publication Date: 2016-08-08
    Electronic ISSN: 1753-318X
    Topics: Architecture, Civil Engineering, Surveying , Geosciences
    Published by Wiley
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  • 8
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    Using R in hydrology: a review of recent developments and future directions (2019)
    In:  Hydrology and Earth System Sciences
    Details
    Publication Date: 2021-02-03
    Description: The open-source programming language R has gained a central place in the hydrological sciences over the last decade, driven by the availability of diverse hydro-meteorological data archives and the development of open-source computational tools. The growth of R's usage in hydrology is reflected in the number of newly published hydrological packages, the strengthening of online user communities, and the popularity of training courses and events. In this paper, we explore the benefits and advantages of R's usage in hydrology, such as the democratization of data science and numerical literacy, the enhancement of reproducible research and open science, the access to statistical tools, the ease of connecting R to and from other languages, and the support provided by a growing community. This paper provides an overview of a typical hydrological workflow based on reproducible principles and packages for retrieval of hydro-meteorological data, spatial analysis, hydrological modelling, statistics, and the design of static and dynamic visualizations and documents. We discuss some of the challenges that arise when using R in hydrology and useful tools to overcome them, including the use of hydrological libraries, documentation, and vignettes (long-form guides that illustrate how to use packages); the role of integrated development environments (IDEs); and the challenges of big data and parallel computing in hydrology. Lastly, this paper provides a roadmap for R's future within hydrology, with R packages as a driver of progress in the hydrological sciences, application programming interfaces (APIs) providing new avenues for data acquisition and provision, enhanced teaching of hydrology in R, and the continued growth of the community via short courses and events.
    Type: info:eu-repo/semantics/article
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