IAHR副主席、悉尼科技大学James Ball教授:The importance of field monitoring urban catchments

发布日期:2018-05-30访问次数: 字号:[ ]

IAHR副主席、悉尼科技大学James Ball教授做《The importance of field monitoring urban catchments》学术报告

河海大学副校长郑金海为James Ball教授颁发证书

Abstract: Management of storm runoff in urban catchments remains an ongoing problem.  Data is a fundamental need for this management. This data can be obtained from monitoring of catchments or from application of catchment modelling systems; both catchment modelling systems and catchment monitoring generate data. Rather than being competitive forms of data generation, it will be shown how catchment monitoring and catchment modelling are symbiotic and are complementary.

Philosophically, the purpose of a catchment modelling system is the reproduction of flows and associated variables that would have been recorded if a monitoring system was implemented at that location for the simulated storm event and catchment conditions. This poses the question of how is the data generated by catchment modelling systems to be assessed as adequate reproductions of the catchment response. This question becomes more important if common applications of catchment modelling systems in urban environments are considered; these typical applications are for events larger in magnitude than previously seen or for catchment conditions not yet in place. In other words, one of the uses for catchment modelling systems is the extrapolation of likely catchment response to different management scenarios or unrecorded events.

For reliable and robust predictions to be obtained from the catchment modelling system, calibration of the model is an important component. This can be achieved only through consideration of data generated through monitoring of the catchment.  While the process of calibration has the aim of minimising the prediction errors from the model, the methodology of minimising the prediction errors requires a comparison of the prediction flow conditions from the model with the flow conditions from the catchment monitoring data and hence errors in the monitored data can be reflected in the model calibration and predictions of flow conditions.

Reliable and robust data from catchment monitoring, therefore, is a fundamental component of modelling urban catchments. Presented will be a discussion of likely errors in monitoring of urban catchments and potential mitigation measures and the implications of these errors in modelling urban catchments.

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