Showing papers by "Thomas Kjeldsen published in 2007"

An investigation of site-similarity approaches to generalisation of a rainfall–runoff model

Abstract: . This paper investigates a new approach to spatial generalisation of rainfall–runoff model parameters – site-similarity with pooling groups – for use in flood frequency estimation at ungauged sites using continuous simulation. The method is developed for the generalisation of a simple conceptual model, the Probability Distributed Model, with four parameters which require specific estimation. The study is based on a relatively large sample of catchments in Great Britain. Various options are investigated within the approach. In the final version, the pooling group comprises the 10 calibrated catchments closest, in catchment property space, to the target site, where the catchment properties used to define the space differ for each parameter of the model. An analysis that, explicitly, takes account of calibration uncertainty as a source of error enables the uncertainty associated with generalised parameter values to be reduced, justifiably. The approach uses calibration uncertainty estimated through jack-knifing and employs a weighting scheme within pooling groups that uses weights which vary both with distance in the catchment property space and with the calibration uncertainty. Models using generalised values from this approach perform relatively well compared with direct calibration. Although performance appears to be better in some areas of the country than others, there are no obvious relationships between catchment properties and performance.

The revitalised FSR/FEH rainfall-runoff method

Abstract: User name Dr Rob Sweet Catchment name Date/time modelled 15-May-2008 09:44 Company name Scott Wilson Ltd Catchment easting 329850 Version 1.3 Project name D118674 Llanshay Farm Track C tchment northing 271950 Catchment area 0.51 Summary of model setup Design rainfall parameters Loss model parameters Routing model parameters Baseflow model parameters Return period (yr) 100 Cmax (mm) 523 Tp (hr) 0.67 BL (hr) 28.7 Duration (hr) 1.3 Cini (mm) 96 Up 0.65 BR 2.05

Estimation of an index flood using data transfer in the UK

Abstract: An important part of the statistical procedure for flood frequency analysis in the UK outlined in the Flood Estimation Handbook (FEH) is concerned with estimation of an index flood at an ungauged site. This is carried out through application of a multivariate regression model linking the index flood, defined as the median annual maximum flood, to a set of catchment descriptors. The FEH then emphasises the importance of data transfer from nearby gauged (donor) sites, or from catchments considered to be hydrologically similar but located anywhere in the UK (analogue sites). This paper considers the suggested methods for estimating the index flood at ungauged sites and develops a new and improved data transfer scheme. A study of 728 gauged catchments located in the UK found that the new data transfer method performs better than both using the FEH regression model only and the FEH data transfer method.

Recursive estimation of a hydrological regression model

Abstract: The use of the generalised least square (GLS) technique for estimation of hydrological regression models has become good practi ce in hydrology. Through a regression model, a simple link between a part icular hydrological variable and a set of catchment descriptors can be established. The regression residuals can be treated as the sum of sampling errors in the hydrological variable and errors in the regression model. This paper presents a recursive metho d for estimating a parameterised form of the cross correlation between the regression model errors, the variance of these errors and the regression model parameters . A re -weighted set of regression residuals can be defined such that the covariance of these residuals is essentially similar to that of the model error. The cross products of the re -weighted regression residuals, pooled within bins, can be used to identify a structure and to fit a parameterised form for the cross -correlations of the regression e rrors. The procedure has been tested successfully on annual maximum flow data from 602 catchments located throughout the UK.

Statistical modelling of flood risk at ungauged sites

Abstract: The use of multivariable regression models which provide linkage between a particular hydrological variable and a set of physical catchment descriptors is a long established practice in applied hydrology. This paper focuses on the modelling and prediction of the median annual maximum index flood at gauged and ungauged sites through the use of regression modelling and on data transfer from gauged to ungauged catchments as outlined in the Flood Estimation Handbook (FEH). Through an extension of the commonly used regression model to include, in addition to cross correlation of sampling errors, non-zero cross correlation of model errors, it is possible to establish a more formal relationship between the regression model and the use of data transfer from a gauged (donor) catchment to an ungauged catchment. By explicitly considering the correlation between the regression model errors, a revised data transfer scheme has been developed, which was found to perform better in terms of predictive error than the established FEH scheme and the case where only the regression model is used. In fact, the automated version of the original FEH data transfer scheme used in this study was found to give estimates of the index flood with higher prediction variance than estimates obtained using regression only.