• Title/Summary/Keyword: Climate Risk

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The 50th Anniversary of the UNESCO World Heritage Convention: present status and challenges (유네스코 세계유산 협약 50주년, 현재 및 과제)

  • LEE Hyunkyung ;YOO Heejun ;NAM Sumi
    • Korean Journal of Heritage: History & Science
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    • v.56 no.2
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    • pp.264-279
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    • 2023
  • The 50th anniversary of the UNESCO World Heritage Convention was in 2022. In order to reflect on the present and future of the meaning of World Heritage, this paper examines the development and changes of the UNESCO World Heritage system. After promulgating the convention in 1972, the UNESCO World Heritage system prioritized the protection of heritage sites in the world that were at risk due to armed conflicts and natural disasters to bequeath heritage to the next generation. In addition, the UNESCO World Heritage's emphasis on Outstanding Universal Value represents the particular culture of human beings formed during a certain period of time, and acts as a significant source of soft power in public diplomacy. The UNESCO World Heritage might be perceived as a shared heritage that has not only become a channel to understand various national values, but also an effective medium to convey one of UNESCO's main principles, that is, peacebuilding. However, the UNESCO World Heritage is now at the center of conflicts of heritage interpretation between many stakeholders related to invisible wars, such as cultural wars, memory wars, and history wars as the social, political, and cultural contexts concerning World Heritage have dramatically shifted with the passing of time. Paying attention to such changing contexts, this paper seeks to understand the main developments in UNESCO World Heritage's discourse concerning changes to the World Heritage Operation Guidelines and heritage experts' meetings by dividing its 50-year history into five phases. Next, this paper analyzes the main shifts in keywords related to UNESCO World Heritage through UNESDOC, which is a platform on which all UNESCO publications are available. Finally, this paper discusses three main changes of UNESCO World Heritage: 1) changes in focus in World Heritage inscriptions, 2) changes in perception of World Heritage protection, and 3) changes of view on the role of the stakeholders in World Heritage. It suggests new emerging issues regarding heritage interpretation and ethics, climate change, and human rights.

Case study on flood water level prediction accuracy of LSTM model according to condition of reference hydrological station combination (참조 수문관측소 구성 조건에 따른 LSTM 모형 홍수위예측 정확도 검토 사례 연구)

  • Lee, Seungho;Kim, Sooyoung;Jung, Jaewon;Yoon, Kwang Seok
    • Journal of Korea Water Resources Association
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    • v.56 no.12
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    • pp.981-992
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    • 2023
  • Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.