Flood warning systems have been researched and discussed for several decades and there is a high degree of consensus in the literature that the most effective structure for a flood warning system is that of an integrated system. Experience suggests however, that few, if any, operational systems are designed in an integrated way and that few practitioners fully appreciate the benefits of integration. Through an analysis of arrangements in the Thames Basin, this research addresses this issue by identifying the necessary criteria and actions required to introduce an integrated system. The limited number of models that attempt to conceptualise flood warning systems in an integrated way have been critically examined and have found to focus too narrowly on selective integrative criteria. It is concluded that there is a need for a wider and multidimensional perspective. This study rectifies this deficiency by presenting a conceptual model that is derived from a more comprehensive assessment of the most relevant integrative factors. A two-staged process is adopted with an initial identification of a wide range of issues and variables, leading to a more focused set of factors presented under four main headings that are used to structure the substantive chapters of this thesis. These integrative factors can be conceptualised as crosscutting strands running through and drawing together the main components of a flood warning system (detection, forecasting, dissemination and response) that help ensure that these components work together collaboratively towards a common aim. Few of the integrative factors identified in this research were found in operational flood warning practices in England and Wales prior to 1996. A number of improvements were made with the establishment of the Environment Agency as the lead authority in both flood forecasting and flood warning dissemination, but a number of weakness still prevail. Through the use of case studies the plausibility of introducing a fully integrated approach to future arrangements has been tested and found to be both practical and feasible.

A major area targeted for hydrometeorological forecast service improvements is in flash flood forecasting. Verification data show that general public service products of flash flood forecasts do not provide enough lead time in order for the public to make effective response. Sophisticated users of flash flood forecasts could use forecast probabilities of flash flooding in order to make decisions in preparation for the predicted event. To this end, a systematic probabilistic approach to flash flood forecasting is presented. The work first describes a deterministic system which serves as a conceptual basis for the probability system. The approach uses accumulated rainfall plus potential rainfall over a specified area and time period, and assesses this amount against the water holding capacity of the affected basin. These parameters are modeled as random variables in the probabilistic approach. The effects of uncertain measurements of rainfall and forecasts of precipitation from multiple information sources within a time period and moving forward in time are resolved through the use of Bayes' Theorem. The effect of uncertain inflows and outflows of atmospheric moisture on the states of the system, the transformation of variables, is resolved by use of convolution. Requirements for probability distributions to satisfy Bayes' Theorem are discussed in terms of the types and physical basis of meteorological data needed. The feasibility of obtaining the data is evaluated. Two alternatives for calculating the soil moisture deficit are presented--one, an online automatic rainfall/runoff model, the other an approximation. Using the soil moisture approximation, a software program was developed to test the probabilistic approach. A storm event was simulated and compared against an actual flash flood event. Results of the simulation improved forecast lead time by 3-5 hours over the actual forecasts issued at the time of the event.

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