Rob Lamb

Calibration of a conceptual rainfall‐runoff model for flood frequency estimation by continuous simulation

An approach is described to the calibration of a conceptual rainfall-runoff model, the Probability Distributed Model (PDM), for estimating flood frequencies at gauged sites by continuous flow simulation. A first step was the estimation of routing store parameters by recession curve analysis. Uniform random sampling was then used to search for parameter sets that produced simulations achieving the best fit to observed, hourly flow data over a 2-year period. Goodness of fit was expressed in terms of four objective functions designed to give different degrees of weight to peaks in flow. Flood frequency results were improved, if necessary, by manual adjustment of parameters, with reference to peaks extracted from the entire hourly flow record. Although the primary aim was to reproduce observed peaks, consideration was also given to finding parameter sets capable of generating a realistic overall characterization of the flow regime. Examples are shown where the calibrated model generated simulations that reproduced well the magnitude and frequency distribution of peak flows. Factors affecting the acceptability of these simulations are discussed. For an example catchment, a sensitivity analysis shows that there may be more than one set of parameter values well suited to the simulation of peak flows.

Hyperresolution information and hyperresolution ignorance in modelling the hydrology of the land surface

There is a strong drive towards hyperresolution earth system models in order to resolve finer scales of motion in the atmosphere. The problem of obtaining more realistic representation of terrestrial fluxes of heat and water, however, is not just a problem of moving to hyperresolution grid scales. It is much more a question of a lack of knowledge about the parameterisation of processes at whatever grid scale is being used for a wider modelling problem. Hyperresolution grid scales cannot alone solve the problem of this hyperresolution ignorance. This paper discusses these issues in more detail with specific reference to land surface parameterisations and flood inundation models. The importance of making local hyperresolution model predictions available for evaluation by local stakeholders is stressed. It is expected that this will be a major driving force for improving model performance in the future.

Communicating uncertainty in flood inundation mapping: a case study

ABSTRACT An important issue in taking account of uncertainty in flood inundation mapping is the communication of the meaning of the outputs from an uncertainty analysis. In part this is because uncertainty estimation in this domain is not a simple statistical problem in that it involves knowledge uncertainties as well as statistical (aleatory) uncertainties in most of the important sources of uncertainty (estimated upstream discharges, effective roughness coefficients, flood plain and channel geometries and infrastructure, choice of model, fragility of defences, etc.). Thus, assumptions are required associated with the knowledge or lack of knowledge about these different sources of uncertainty. A framework has been developed in the form of a sequence of condition trees to help define these assumptions. Since stakeholders in the process can potentially be involved in making and recording decisions about those assumptions the framework also serves as a means of communicating the assumptions. Recording the decisions also serves to provide an audit trail for later evaluation of the decisions and hence the resulting analysis. Communication can also be helped in this type of spatial problem by effective visualization techniques and a visualization tool has been developed for both a web-based service using Google Maps™ and a desktop application using the Matlab™ numerical package.

A modelling framework for evaluation of the hydrological impacts of nature-based approaches to flood risk management, with application to in-channel interventions across a 29-km2 scale catchment in the United Kingdom

&NA; Nature‐based approaches to flood risk management are increasing in popularity. Evidence for the effectiveness at the catchment scale of such spatially distributed upstream measures is inconclusive. However, it also remains an open question whether, under certain conditions, the individual impacts of a collection of flood mitigation interventions could combine to produce a detrimental effect on runoff response. A modelling framework is presented for evaluation of the impacts of hillslope and in‐channel natural flood management interventions. It couples an existing semidistributed hydrological model with a new, spatially explicit, hydraulic channel network routing model. The model is applied to assess a potential flood mitigation scheme in an agricultural catchment in North Yorkshire, United Kingdom, comprising various configurations of a single variety of in‐channel feature. The hydrological model is used to generate subsurface and surface fluxes for a flood event in 2012. The network routing model is then applied to evaluate the response to the addition of up to 59 features. Additional channel and floodplain storage of approximately 70,000 m3 is seen with a reduction of around 11% in peak discharge. Although this might be sufficient to reduce flooding in moderate events, it is inadequate to prevent flooding in the double‐peaked storm of the magnitude that caused damage within the catchment in 2012. Some strategies using features specific to this catchment are suggested in order to improve the attenuation that could be achieved by applying a nature‐based approach.

The uncertainty cascade in model fusion

Abstract There are increasing demands in assessing the impacts of change on environmental systems to couple different model components together in a cascade, the outputs from one component providing the inputs to another with or without feedbacks in the coupling. Each model component will necessarily involve some uncertainty in its specification and simulations that can be conditioned using some observational data. Taking account of this uncertainty should result in more robust decision making and may change the nature of the decision made. The difficulty in environmental decision making is in making proper estimates of uncertainties when so many of the sources of uncertainty result from lack of knowledge (epistemic uncertainties) rather than uncertainty that can be treated as random variability (aleatory uncertainty). This is particularly the case for problems that involve cascades of model components. Examples are the use of UKCP09 climate scenarios in impact studies, flood risk assessment involving models of runoff generation and their impact on hydraulic models of flood plains, and integrated catchment management involving upstream to downstream surface and subsurface routing of water quality variables. The uncertainties are such that, even for relatively simple problems, they can result in wide ranges of potential outputs. This poses the questions that will be considered in this paper: how to take account of knowledge uncertainties in cascades of model components; and how to constrain the potential uncertainties for use in making decisions. In particular we highlight the difficulties of defining statistical likelihood functions that properly reflect the non-stationary uncertainty characteristics expected of epistemic sources of uncertainty.

Physical complexity to model morphological changes at a natural channel bend

This study developed a two-dimensional (2-D) depth-averaged model for morphological changes at natural bends by including a secondary flow correction. The model was tested in two laboratory-scale events. A field study was further adopted to demonstrate the capability of the model in predicting bed deformation at natural bends. Further, a series of scenarios with different setups of sediment-related parameters were tested to explore the possibility of a 2-D model to simulate morphological changes at a natural bend, and to investigate how much physical complexity is needed for reliable modeling. The results suggest that a 2-D depth-averaged model can reconstruct the hydrodynamic and morphological features at a bend reasonably provided that the model addresses a secondary flow correction, and reasonably parameterize grain-sizes within a channel in a pragmatic way. The factors, such as sediment transport formula and roughness height, have relatively less significance on the bed change pattern at a bend. The study reveals that the secondary flow effect and grain-size parameterization should be given a first priority among other parameters when modeling bed deformation at a natural bend using a 2-D model.