A Manifesto for the Equifinality Thesis.

This essay discusses some of the issues involved in the identification and predictions of hydrological models given some calibration data. The reasons for the incompleteness of traditional calibration methods are discussed. The argument is made that the potential for multiple acceptable models as representations of hydrological and other environmental systems (the equifinality thesis) should be given more serious consideration than hitherto. It proposes some techniques for an extended GLUE methodology to make it more rigorous and outlines some of the research issues still to be resolved

Distributed lag models for hydrological data

The distributed lag model (DLM), used most prominently in air pollution studies, finds application wherever the effect of a covariate is delayed and distributed through time. We explore the use of modified formulations of DLMs to provide flexible varying-coeficient models with smoothness constraints, applicable in any setting in which lagged covariates are regressed on a time-dependent response. The models are applied to simulated flow and rainfall data and to flow data from a Scottish mountain river, with particular emphasis on approximating the relationship between environmental covariates and flow regimes in order to detect the influence of unobserved processes. It was found that under certain rainfall conditions some of the variability in the influence of rainfall on flow arises through a complex interaction between antecedent ground wetness and the time-delay in rainfall. The models are able to identify subtle changes in rainfall response, particularly in the location of peak influence in the lag structure and offer a computationally attractive approach for fitting DLMs

How far can we go in distributed hydrological modelling?

International audienceThis paper considers distributed hydrological models in hydrology as an expression of a pragmatic realism. Some of the problems of distributed modelling are discussed including the problem of nonlinearity, the problem of scale, the problem of equifinality, the problem of uniqueness and the problem of uncertainty. A structure for the application of distributed modelling is suggested based on an uncertain or fuzzy landscape space to model space mapping. This is suggested as the basis for an Alternative Blueprint for distributed modelling in the form of an application methodology. This Alternative Blueprint is scientific in that it allows for the formulation of testable hypotheses. It focuses attention on the prior evaluation of models in terms of physical realism and on the value of data in model rejection. Finally, some unresolved questions that distributed modelling must address in the future are outlined, together with a vision for distributed modelling as a means of learning about places

Fuzzy set approach to calibrating distributed flood inundation models using remote sensing observations

The paper presents a methodology for the estimation of uncertainty of inundation extent, which takes account of the uncertainty in the observed spatially distributed information and implements a fuzzy evaluation methodology. The Generalised Likelihood Uncertainty Estimation (GLUE) technique and the 2-D LISFLOOD-FP model were applied to derive the set of uncertain inundation realisations and resulting flood inundation maps. Conditioning of the inundation maps on fuzzified Synthetic Aperture Radar (SAR) images results in much more realistic inundation risk maps which can better depict the variable pattern of inundation extent than previously used methods. It has been shown that the evaluation methodology compares well to traditional approaches and can produce flood hazard maps that reflect the uncertainties in model evaluation

Using a Grid-Enabled Wireless Sensor Network for Flood Management

Flooding is becoming an increasing problem. As a result there is a need to deploy more sophisticated sensor networks to detect and react to flooding. This paper outlines a demonstration that illustrates our proposed solution to this problem involving embedded wireless hardware, component based middleware and overlay networks

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. Keith BEVEN, Hannah CLOKE, Florian PAPPENBERGER, Rob LAMB, Neil HUNTE

Flood frequency estimation by continuous simulation under climate change (with uncertainty)

International audienceThis paper explores the potential for assessing the impacts of climate change upon flood frequency for the gauged, upland Wye catchment at Plynlimon, Wales, UK, while taking account of uncertainty in modelling rainfall-runoff processes under current conditions. A continuous simulation methodology which uses a stochastic rainfall model to drive the rainfall-runoff model TOPMODEL is utilised. Behavioural parameter sets for both the rainfall model and TOPMODEL are identified prior to the climate change runs using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. The "medium-high" UKCIP98 climate change scenario, obtained from the HadCM2 GCM simulations, is used as a starting point for a variety of different scenarios at the catchment scale. It is demonstrated that while the scenarios have only a small impact upon the likelihood weighted flood frequency uncertainty bounds in comparison with the current condition scenario, the risk of a given discharge as an element in the distribution of T year floods is changed. This underlines the need to account explicitly for uncertainty within hydrological modelling, especially in estimating the impacts of climate change. Keywords: Climate change; Floods; Frequency; TOPMODEL</p