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Abstract:An extensive sediment monitoring network was established within the LOIS programme, involving 10 of the main tributaries of the River Humber (UK). Its primary purpose was to measure the¯ux of suspended sediment to the estuary. A turbidity monitoring system was developed to provide a continuous record of suspended sediment concentration in the rivers, from which the¯uxes were calculated. Linear relationships were established between suspended sediment concentration and turbidity (with slopes varying from 0 . 89 to 1 . 69) to enable the conversion of nephelometric turbidity [NTU] to suspended sediment concentration [mg l À1 ]. Potential uncertainties were identi®ed and quanti®ed. The suspended sediment¯ux to the Humber (November 1994±October 1997) was calculated to be 699 861 t, equivalent to a yield of 15 t km À2 yr À1 . Large temporal and spatial variations in the¯ux were measured during the monitoring period, in response to factors such as climate, land use, catchment scale, deposition and reservoir trapment. The particle size composition of the suspended sediment was measured and found to vary little, except at very high discharges, when it coarsened. The organic content of the sediment was found to be directly related to the discharge of sewage euent to the rivers.

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Keith Beven was amongst the first to propose and demonstrate a combination of conceptual rainfall-runoff modelling and stochastically-generated rainfall data in what is known as the "continuous simulation" approach for flood frequency analysis. The motivations included the potential to establish better links with physical processes and to avoid restrictive assumptions inherent in existing methods applied in design flood studies. Subsequently attempts have been made to establish continuous simulation as a routine method for flood frequency analysis, particularly in the UK. The approach has not been adopted universally, but numerous studies have benefitted from applications of continuous simulation methods. This paper asks whether industry has yet realised the vision of the pioneering research by Beven and others. It reviews the generic methodology and illustrates applications of the original vision for a more physically-realistic approach to flood frequency analysis through a set of practical case studies, highlighting why continuous simulation was useful and appropriate in each case. The case studies illustrate how continuous simulation has helped to offer users of flood frequency analysis more confidence about model results by avoiding (or exposing) bad assumptions relating to catchment heterogeneity, inappropriateness of assumptions made in (UK) industry-standard design event flood estimation methods and the representation of engineered or natural dynamic controls on flood flows. By implementing the vision for physically-realistic analysis of flood frequency through continuous simulation, each of these examples illustrates how more relevant and improved information was provided for flood risk decision-making than would have been possible using standard methods. They further demonstrate that integrating engineered infrastructure into flood frequency analysis, and assessment of environmental change are also significant motivations for adopting the continuous simulation approach in practice.This article is protected by copyright. All rights reserved. IntroductionBuilding on advances in hydrological modelling made in the 1970s, in particular the physically-based TOPMODEL concepts (Beven and Kirkby, 1979), Keith Beven (1986, 1987 was amongst the first hydrologists to demonstrate what is now described as a "continuous simulation" (CS) approach for flood frequency analysis. This paper examines how the original vision to "provide more physically-based techniques for prediction of flood frequency characteristics" (Beven, 1987) has been realised, and what lessons can be learned from applications in practice.Probabilistic methods have underpinned the design and economic analysis of flood mitigation measures for over 50 years (Benson, 1968). In a flood frequency analysis, peak river flows are regarded as a random variable, Y, and the probability of the flow not exceeding a given where g Y (y) is a probability density function describing Y. The temporal scale is usually defined such that G Y (y) represents the annu...