A Method of Modelling Flood Event
Zeqian Chen · Geo-information Science · 2015
Flood is a frequently occurred disaster and it causes great harm in China. In order to effectively prevent, reduce and relief disaster, it is necessary to establish a flood event information model to represent and share flood information. By far, many scholars have studied a variety of event information models. However, the existed event information models mainly represent static information, and they are lack of the capability to handle dynamic process information. To solve this problem, a flood event model is proposed in this paper based on the flood emergence management stages and the dynamic process from the perspective of observation. To build up the model, this paper firstly describes the modelling considerations, including flood phases, observation, and ten types of primary elements for modeling. Then, we construct the flood event model as a ten tuple model based on MOF modelling framework with four layers, and encode the model with a method that maps the elements of the model to elements of the Event Pattern Markup Language(EML). Finally, we simulated an experiment for a flood case occurred in the Liangzi Lake in 2010 as an example to test the proposed model. In the experiment, the building pr ocess and the r esults of the pr oposed model at differ ent emer gence management stages ar e detailed. The exper iment r esults show that the pr oposed model has following char acter istics:(1) it establishes a model fr om the per spective of obser vation, since obser vation plays a decisive r ole in r eal-time disaster infor mation acquisition.(2) The flood model was established by four emer gence management stages, and the main tasks of each stage ar e differ ent.(3) The flood model was modelled dynamically. The pr oposed ten tuple model itself is not dynamic, but the establishing pr ocess and its r epr esented infor mation ar e dynamic. The modelling pr ocess is modelled on r eal-time data str eams, and it dynamically updates time-ser ies data. The time ser ies data in this model ar e gener ally the latest obser vations, which r eveal the dynamic infor mation of cur r ent flood.(4) The model is extensible and adaptable to ensur e the suitability. As a conclusion, the model can r epr esent flooding events and model dynamic flood infor mation effectively, as well as provide a good approach to represent and share flood information.