The parametrisation of statistical models of change in extremes and its impact on the description of change

2020 ◽  
Author(s):  
Ilaria Prosdocimi ◽  
Thomas Kjeldsen
Keyword(s):  
River Flow ◽  
Location Parameter ◽  
Mathematical Structure ◽  
Quantile Function ◽  
Scaling Properties ◽  
Environmental Extremes ◽  
Distribution Parameters ◽  
Change Metrics ◽  
The Uk ◽  
The Impact

<p>The impact of climate change on environmental extremes such as high flows or rainfall, is routinely investigated by fitting non-stationary extreme value distributions to long-term observational records. These investigations often use regression models in which one or more distribution parameters is allowed to change as a function of time or some other preocess-related covariate. The changes in quantiles implied by different regression model are quantified in this study using different quantile change metrics. We expose the mathematical structure of these change metrics for various commonly used non-stationary models, showing how for most commonly used models the resulting changes in the estimated quantiles are a non-intuitive function of the distribution parameters, leading to results which are difficult to interpret and therefore of little practical use in engineering design. Further, it is posited that the most commonly used non-stationary models do not preserve fundamental scaling properties of environmental extremes. </p><p>A new (parsimonious) model is proposed which results in changes in the quantile function that are easy to interpret, and for which the scaling properties are maintained, so that when the location parameter is allowed to change so is the scale. The proposed parameterization is applicable within a range of commonly used distributions (e.g. GEV, GLO, Kappa, ...) and is better suited for investigating changes in environmental extremes as it provides more interpretable description of changes in design events under a non-stationary model. The empirical behaviour of the quantile change metrics under different modelling frameworks when applied to river flow data in the UK is investigated to showcase the usefulness of the proposed model. </p>

Understanding change in hydrometeorological extremes with statistical models - the importance of model parametrization

2021 ◽  
Author(s):  
Ilaria Prosdocimi ◽  
Thomas Kjeldsen
Keyword(s):  
Coefficient Of Variation ◽  
Constant Coefficient ◽  
River Flow ◽  
Extreme Value ◽  
Flow Measurements ◽  
Scaling Properties ◽  
Distribution Parameters ◽  
Quantile Estimates ◽  
Constant Coefficient Of Variation ◽  
The Impact

<p>The potential for changes in hydrometeorological extremes is routinely investigated by fitting change-permitting extreme value models to long-term observations, allowing one or more distribution parameters to change as a function of time or some physically-motivated covariate. In most practical extreme value analyses, the main quantity of interest though is the upper quantiles of the distribution, rather than the parameters' values. This study focuses on the changes in quantile estimates under different change-permitting models. First, metrics which measure the impact of changes in parameters on changes in quantiles are introduced. The mathematical structure of these change metrics is investigated for several models based on the Generalised Extreme Value (GEV) distribution. It is shown that for the most commonly used models, the predicted changes in the quantiles are a non-intuitive function of the distribution parameters, leading to results which are difficult to interpret. Next, it is posited that commonly used change-permitting GEV models do not preserve a constant coefficient of variation, a property that is typically assumed to hold and that is related to the scaling properties of extremes. To address these shortcomings a new (parsimonious) model is proposed: the model assumes a constant coefficient of variation, allowing the location and scale parameters to change simultaneously. The proposed model results in more interpretable changes in the quantile function. The consequences of the different modelling choices on quantile estimates are exemplified using a dataset of extreme peak river flow measurements.</p>

scholarly journals Parametrisation of change-permitting extreme value models and its impact on the description of change

2020 ◽  
Author(s):  
Ilaria Prosdocimi ◽  
Thomas Kjeldsen
Keyword(s):  
Coefficient Of Variation ◽  
Constant Coefficient ◽  
River Flow ◽  
Extreme Value ◽  
Flow Measurements ◽  
Environmental Extremes ◽  
Distribution Parameters ◽  
Quantile Estimates ◽  
Constant Coefficient Of Variation ◽  
The Impact

AbstractThe potential for changes in environmental extremes is routinely investigated by fitting change-permitting extreme value models to long-term observations, allowing one or more distribution parameters to change as a function of time or some other covariate. In most extreme value analyses, the main quantity of interest is typically the upper quantiles of the distribution, which are often needed for practical applications such as engineering design. This study focuses on the changes in quantile estimates under different change-permitting models. First, metrics which measure the impact of changes in parameters on changes in quantiles are introduced. The mathematical structure of these change metrics is investigated for several change-permitting models based on the Generalised Extreme Value (GEV) distribution. It is shown that for the most commonly used models, the predicted changes in the quantiles are a non-intuitive function of the distribution parameters, leading to results which are difficult to interpret. Next, it is posited that commonly used change-permitting GEV models do not preserve a constant coefficient of variation, a property that is typically assumed to hold for environmental extremes. To address these shortcomings a new (parsimonious) model is proposed: the model assumes a constant coefficient of variation, allowing the location and scale parameters to change simultaneously. The proposed model results in changes in the quantile function that are easier to interpret. Finally, the consequences of the different modelling choices on quantile estimates are exemplified using a dataset of extreme peak river flow measurements in Massachusetts, USA. It is argued that the decision on which model structure to adopt to describe change in extremes should also take into consideration any requirements on the behaviour of the quantiles of interest.

scholarly journals Development of a high resolution grid-based river flow model for use with regional climate model output

2007 ◽  
Vol 11 (1) ◽  
pp. 532-549 ◽  
Author(s):  
V. A. Bell ◽  
A. L. Kay ◽  
R. G. Jones ◽  
R. J. Moore
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
River Flow ◽  
Climate Model ◽  
Regional Climate ◽  
Flow Routing ◽  
The Uk ◽  
The Impact ◽  
Runoff Production ◽  
Grid Based

Abstract. A grid-based approach to river flow modelling has been developed for regional assessments of the impact of environmental change on hydrologically sensitive systems. The approach also provides a means of assessing, and providing feedback on, the hydrological performance of the land-surface component of a regional climate model (RCM). When combined with information on the evolution of climate, the model can give estimates of the impact of future climate change on river flows and flooding. The high-resolution flow routing and runoff-production model is designed for use with RCM-derived rainfall and potential evaporation (PE), although other sources of gridded rainfall and PE can be employed. Called the "Grid-to-Grid Model", or G2G, it can be configured on grids of different resolution and coverage (a 1 km grid over the UK is used here). The model can simulate flow on an area-wide basis as well as providing estimates of fluvial discharges for input to shelf-sea and ocean models. Configuration of the flow routing model on a relatively high resolution 1 km grid allows modelled river flows to be compared with gauged observations for a variety of catchments across the UK. Modelled flows are also compared with those obtained from a catchment-based model, a parameter-generalised form of the Probability-Distributed Model (PDM) developed for assessing flood frequency. Using RCM re-analysis rainfall and PE as input, the G2G model performs well compared with measured flows at a daily time-step, particularly for high relief catchments. It performs less well for low-relief and groundwater-dominated regions because the dominant model control on runoff production is topography.

scholarly journals Modelling the impact of urbanization on flood frequency relationships in the UK

2010 ◽  
Vol 41 (5) ◽  
pp. 391-405 ◽  
Author(s):  
Thomas R. Kjeldsen
Keyword(s):  
Flood Frequency ◽  
Ungauged Sites ◽  
Index Flood ◽  
Adjustment Factors ◽  
Distribution Parameters ◽  
Urban Catchments ◽  
Impact Of Urbanization ◽  
The Uk ◽  
Leave One Out ◽  
The Impact

This paper investigates the effect of urbanization on the three key statistics used to establish flood frequency curves when combining the index flood method with the method of L-moments for estimating distribution parameters, i.e. the median annual maximum peak flow (the index flood), and the high-order L-moment ratios L-CV and L-SKEW. An existing procedure employing catchment descriptors was used to estimate the three statistics at ungauged sites in the UK. As-rural estimates of the three statistics were obtained in 200 urban catchments and compared to the corresponding values obtained from observed data. The (log) differences of these estimates were related to catchment descriptors relevant to the urbanization process using linear regression. The results show that urbanization leads to a reduction in L-CV but an increase in L-SKEW. A jack-knife leave-one-out experiment showed that the adjustment factors developed were generally better at predicting the effect of urbanization on the flood frequency curve than the existing adjustment factor currently used in the UK.

The Film World’s Cooperative Store: Institutions and Films of the 1930s and 1940s

2018 ◽  
Author(s):  
C. Claire Thomson
Keyword(s):  
World War Ii ◽  
Meat Products ◽  
Public Information ◽  
Early History ◽  
World War ◽  
International Context ◽  
German Occupation ◽  
History Of ◽  
The Uk ◽  
The Impact

This chapter traces the early history of state-sponsored informational filmmaking in Denmark, emphasising its organisation as a ‘cooperative’ of organisations and government agencies. After an account of the establishment and early development of the agency Dansk Kulturfilm in the 1930s, the chapter considers two of its earliest productions, both process films documenting the manufacture of bricks and meat products. The broader context of documentary in Denmark is fleshed out with an account of the production and reception of Poul Henningsen’s seminal film Danmark (1935), and the international context is accounted for with an overview of the development of state-supported filmmaking in the UK, Italy and Germany. Developments in the funding and output of Dansk Kulturfilm up to World War II are outlined, followed by an account of the impact of the German Occupation of Denmark on domestic informational film. The establishment of the Danish Government Film Committee or Ministeriernes Filmudvalg kick-started aprofessionalisation of state-sponsored filmmaking, and two wartime public information films are briefly analysed as examples of its early output. The chapter concludes with an account of the relations between the Danish Resistance and an emerging generation of documentarists.

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