Intelligent algorithms applied to weather radar based flood forecasting system

Zhang, L

Abstract

The UK weather radar network and telemetry system for the raingauges and river level gauges provided the solid physical base which produce the large amount of data in real time and a large variety of operational flood forecasting models were supplied from SW Region of the Environment Agency. Data processing, the selection of a suitable model, model calibration and parameters updating have played a more and more important role in real time forecasting and this thesis focuses on many of the key issues involved in the emerging area. Within this context, surface fitting, interpolation and cluster analysis were used for adjustment of the weather radar data and comparison between the raingauge data and radar data. As the core of the forecasting system the rainfall runoff model and river routing model were investigated in a wide-ranging manner, the key model utilised is the Transfer Function model. Potential misinterpretation of the TF model was explained by distinguishing between the "Black Box" model and the "White Box" model. The physically based Genetic Cascade Transfer Function (GCTF) model was introduced and shown to be consistent with the Gamma function and Muskingum model which were based upon the three common assumptions: linear, time-invariant and Single Input Single Output (SISO) system. The calculation formula for the moment parameters and the geometry coefficients (t-peak time, volume parameter) create the initial model and a genetic algorithm provides the basic tool to global search for the parameters. An expert system plus the genetic algorithm are combined to provide a real time updating capability. A dentritic model composed of the SISO rainfall runoff model at several tributaries and the Multi-Input Single Output (MISO) routing model in the mainstream were developed and applied to the Bristol Avon catchment. As a Weather Radar Information Processor, WRIP(II) was extended and implemented on a SPARC 10 workstation and communions at Environment Agency South West Region (Exeter) with a graphical user interface based on X/Motif.

Citation

Zhang, L. Intelligent algorithms applied to weather radar based flood forecasting system. (Thesis). University of Salford

• Thesis Type: Thesis
• Deposit Date: Jul 13, 2017
• Publisher URL: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314065
• Related Public URLs: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314065
• Award Date: Jan 1, 1999