کسب دانش به منظور طراحی و مدیریت سیستم اطلاعات سیل: حوضه رودخانه چی در تایلند
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|7565||2013||6 صفحه PDF||9 صفحه WORD|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Procedia - Social and Behavioral Sciences, Volume 73, 27 February 2013, Pages 109–114
روش اجرای پژوهش
قلمرو دانش مدیریت سیل
Thai people living along the Chi River Basin (CRB), an important river for economic and social development of the Northeast of Thailand, have long been affected by both flood and drought. These problems have not yet been solved due to a lack of knowledge sharing between responsible organizations and researchers who are the experts on CRB to monitor and control the water condition. The knowledge owned by these experts has not been captured, classified and integrated into an information system for decision making. This paper is a part of the research on the development of knowledge-based DSS for water resources management of CRB. It aimed to develop the knowledge domain and to design knowledge-based DSS architecture. The research methods included document analysis and qualitative methods by adopting Liou (1990)’s
Freshwater resources are an essential component of the Earth's hydrosphere and an indispensable part of all terrestrial ecosystems. The freshwater environment is characterized by the hydrological cycle, including floods and droughts, which in some regions have become more extreme and dramatic in their consequences . The OECD Environmental Outlook to 2030 has identified water as one of the four critical environmental priorities for the coming two decades. On current trends high water stress in 2030, and the Millennium Development Goals on water and sanitation will not be met . Water resource decision-making can ultimately affect land use practices and resource allocation, and can identify a need for additional data collection. Scientific data and information have always been important for making decisions related to water resource management. Increasing demands for water have elevated the importance of reliable input data. The confidence with which the outputs of scientific assessments can be used in decision-making is directly related to the availability and quality of the data used . It was found that earlier studies on water resources management system had rather emphasized on using classical approach based on mathematical formulae and models, so as the study of Mikulecky. However, Mikulecky  noted that the system based on mathematical models and simulations was useful but merely playing a supporting role relating to knowledge application. As an ultimate goal, the system should be a complex knowledge-based system, accumulating the most important if not all the necessary that knowledge-based related to the water resources management. Such a system should be able to support the decision making process of river operators intensively, leaving just small margins for erroneous decision
نتیجه گیری انگلیسی
The results of this research were the knowledge domain and the knowledge-based DSS architecture. The knowledge domain was structured by following three processes of disaster management cycle, consisting of 9 domains of forecasting, 10 domains of response, 9 domains of recovery, 16 domains of Historical, 30 domains of GeoInformatic, and 6 domains of Government policy and land use (see example of knowledge domain in Fig 1).