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|Title:||HYDROMETRIC DATA BASED FLOOD FORECASTING USING MULTILINEAR ROUTING TECHNIQUE|
MULTILINEAR ROUTING TECHNIQUE
|Abstract:||The application of a multilinear hydrograph routing method for real-time flood forecasting at a river gauging site is demonstrated in this study. Adverse effects are experienced when high river flows occur in the form of floods causing loss of life and damage .to property which have to be mitigated by employing structural measures such as levees, flood walls and channel improvement. However, these types of measures cannot eliminate completely the hydraulic risk, given the impossibly of building larger structure to cope with extremely low probability events. Therefore, an important role remains for non-structural measures to be compared, evaluated and implemented in real time. Flood forecasting is an important non structural measure for flood damage reduction and for minimizing flood-related deaths and, hence, its implementation as an effective tool requires accurate forecasting with sufficient lead time. Therefore, it is essential that flood forecasting methods should be physically based, less data intensive and, over and above, should be physically based, less data intensive and, over and above, should be easily understood by the field engineers for troubleshooting of the problems related to these methods during real-time operation. Typically, the flood forecasting models have two components: The deterministic flow component and - the stochastic flow component. While the former is determined by the hydrologic/hydraulic model, the latter is determined based on the error series of the difference between the forecasted flow for a specified lead time and the corresponding observed one. The residual series reflects both the model error, due to the inability of the deterministic model to correctly reproduce the flow process, and the observational error while measuring the 'flow. It is imperative, therefore, to use an appropriate model to reduce the model error. The hydrometric data- based flood forecasting model studied here in employed for forecasting flood for a given lead-time at a gauging. The forecast error is estimated using a two-parameter linear autoregressive model with its parameters updated at every routing time interval of 30 minutes at which the observations are made. This hydrometric data-based forecast model is applied for forecasting floods at the downstream end of a 15 km reach of the Tiber River in Central Italy. vi|
|Appears in Collections:||MASTERS' DISSERTATIONS (Hydrology)|
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