摘要
感潮河口城市如上海、广州、天津,是经济发展的先驱、滨海城市的明珠。由于所处的特定地理位置、气候条件、地形特点,在尽享水资源带来的水土膏腴和舟楫之利的同时,亦深受水灾的威胁。一旦发生水灾,将给整个国民经济造成巨大损失。与大流域地区、内陆地区或其它城市的水灾相比,具有显著的复杂性和特殊性。在科学技术高速发展的今天,将现代信息技术应用于传统的减灾决策研究中,对于更好地制定减灾对策和措施、最大限度地减轻水灾损失和影响具有重要意义。目前,针对感潮河口城市的水灾减灾研究尚不多见,有效支撑其辅助决策的方法体系和关键技术有待进一步研究。
基于这样的认识,本文以感潮河口城市作为研究区域,以上海市为例,围绕如何为水灾减灾决策提供辅助支持,基于SDSS将水灾数据汇集、水灾过程动态模拟、信息网络联动共享等环节有机联系起来,搭建了实时动态、预测预警、分层联动的减灾辅助决策平台。论文从一个侧面对研究区域的水灾辅助决策的理论和方法、关键技术进行探讨,为相关研究提供技术借鉴和应用示范,也为国际化大都市上海最大限度地减轻水灾损失和影响提供决策依据。
论文首先结合大量历史资料,从水灾系统角度对研究区域的水灾复杂性进行剖析,进而基于SDSS理论和技术,提出水灾减灾辅助决策系统的总体框架。其次,针对市区暴雨积水、沿海沿江台风暴潮两种主要水灾,综合考虑天文潮、热带气旋、暴雨等因子,集成GIS、水文模型和数据库,对水灾过程进行动态模拟和预警。再次,论文基于WebGIS技术,对C/S模式的水灾减灾SDSS加以补充和拓展,探讨了水灾信息分层联动和网络共享。最后从实践应用层面构建了SDSS,为上海市水灾减灾决策提供科学依据,也对本文的方法和关键技术进行应用和验证。
论文主要有以下贡献:
1.针对感潮河口城市这一特定区域,基于SDSS将水灾数据汇集、水灾过程动态模拟、水灾信息网络联动共享等主要环节有机集成起来,提出了C/S和B/S结构相结合、实时动态、预测预警、分层联动特色的减灾辅助决策系统的理论框架和方法。研究区域水灾是在孕灾环境、致灾因子和承灾体等子系统相互作用、相互影响下形成的,水灾的发生往往是天文潮、热带气旋、暴雨、上游洪水、海平面上升、地面沉降、人类活动等综合作用的结果。针对信息难以共享和联动、预测
Large cities located at tidal estuaries such as Shanghai, Guangzhou and Tianjin are playing an important role in economy and society development in world. Because of the special geographical locations, climate and topography, those cities are threatened by flood, although meanwhile they benefit from abundant water resources and convenient transportation. Once flood happens, it will result in a huge loss in the national economy. Compared with those in large watersheds, inland area and other cities, the floods at urbanized tidal estuaries are very complicated and unique. However, very few researches have been done on flood-reduction for cities located at tidal estuaries in the past decades. Therefore, it is necessary and urgent to explore related methods and technologies, particularly the application of modern information technology.Based on the above discussion, the cities located at tidal estuaries are chosen as the study area, and Shanghai is taken as example in this thesis. The theories, methods and key technologies used in decision-making are discussed for the purpose of reducing flood disaster. A SDSS featured by real-time, dynamic, forecasting, early warning and layered-running is also established, by connecting a few key links such as data collecting, flood process forecasting and information sharing on the network, etc. This research not only gives an example of technology and application for other researches, but also provides scientific basis for reducing economic and social loss in shanghai city.First of all, this thesis analyzes the structure, characteristics, main disaster-causing factors and space-time distribution of flood disaster from the view of large complex system of flood disaster, based on plenty of historical data. A SDSS framework for reducing flood is then brought out on the basis of SDSS theory and technology. Next, the flood process is simulated by integrating GIS with hydrological model and database. Astronomical tide, typhoon and rainstorm are considered in this SDSS as well. Next, it is discussed how the information can be shared by city and county flood-control headquarters based on WebGIS, which extends SDSS applications of C/S mode. The SDSS is established, applied into the real problems and then verified, which provides a scientific basis for flood-reduction in Shanghai. Some solutions are also suggested in terms of the pitfalls of this system.This thesis has three main contributions:1. In terms of cities located at tidal estuaries, several key links including data collecting, flood process simulating and information sharing on the network are integrated based on SDSS, and a theoretical framework and constructing method
featured by integrating C/S and B/S modes, real-time, dynamic, forecasting and layered-running are brought out.The flood in the study area is a result from the interaction of disaster-breeding environment, disaster-causing factors and disaster-affected body. It is caused by astronomical tide, typhoon, rainstorm, flood upstream, sea level rise, ground subsidence and human activities. The current systems have quite a few pitfalls such as delayed information-sharing, inaccurate forecasting and warning, slow response to emergency, etc. This system is able to quickly gather data of weather, water regime, rain regime, hydraulic engineering, etc. It also can effectively simulate and forecast flood process by integrating GIS with hydrological models, and use WebGIS technology to publish information on Internet/Intranet.2. Using integrated hydrological models with GIS and database to simulate and forecast flood process dynamicly should also be considered an important contribution. The inherent mechanism of flood is also explored from the view of method.In terms of uban waterlogging caused by rainstorm and storm surge caused by typhoon, a system is established considering astronomical tide, typhoon, rainstorm, etc., based on the designed SDSS framework, the integrated GIS, hydrological model, database and middle-ware. This system can well simulate the process and space-time distri
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