大坝下游人口增长引起的溃坝风险等级变化

Gagah Guntur Aribowo, P. Juwono, E. Suhartanto, R. Asmaranto
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引用次数: 0

摘要

本研究旨在评估大坝下游人口数量增长率对溃坝风险等级的影响。大坝下游地区的人口增长率决定了受灾害风险影响的人口数量。在本研究中,根据种群增长率的增加数量对溃坝进行了危险等级的划分。在本研究中,根据人口增长率的增长对溃坝进行了分类。该方法从数据收集开始,例如用于分析大坝溃坝的PMF设计洪水,获得大坝下游地区的洪水边界,用于了解大坝下游地区地形的数字高程模型地图,从BPS获得的人口数据,用于了解人口增长率,从而可以预测人口数量,直到水库寿命;而土地利用数据则是为了了解下游坝区的人口增长率,从而了解到水库寿命期间的居住发展情况。然后根据风险人群的数量进行评价和评估。结果表明:滨塘巴诺坝、罗蒂克洛特坝、纳蓬盖特坝、洛拉克坝、库威尔坝、潘度杜里坝等6座大坝下游破坏程度危险性极高,分级评价极值;然而,其他四座大坝也显示出非常高的危险水平,但在大坝的评估分类中是高的(不是极端的),如Batu Nampar, Kengkang, Sepit和Jangkih Jawa大坝。以期对水库全寿命期溃坝危险性分级进行预测。此外,还可以为决策者确定溃坝风险等级提供参考。此外,它还可以作为建立溃坝风险分类模型的输入之一。
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The Risk-Level Change of Dam Break Due to the Population Growth in the Dam Downstream
This research intends to evaluate the risk-level change of dam break due to the number of population growth rates in the dam downstream. The number of population growth rates in the dam downstream area causes the number of populations that is impacted by disaster risk. In this research, there is conducted the danger class classification of dam failure based on the increasing number of population growth rates. In this research, there is conducted a class classification about the dam failure based on the increasing of population growth rate. The methodology is started from data collecting such as PMF design flood that is used for analyzing the dam break to be obtained the flood boundary of the dam downstream area, Map of the Digital Elevation Model that is for knowing the topography of the dam downstream area, population data which is obtained from BPS that is for knowing the population growth rate so it can predict the population number until the life time of the reservoir, and the land use data that is for knowing the population growth rate in the downstream dam area so it can be known the development of residence until the life time of reservoir. Then there is carried out the evaluation and assessment, which is based on the number of risk populations. The result show that there are 6 dams with very high danger level of the downstream damage level and the classification assessment of dams is extreme such as the dams of Bintang Bano, Rotiklot, Napungette, Lolak, Kuwil, and Pandanduri. However, the other four dams also show a very high danger level but in the assessment classification of dam is high (not extreme) such as the dams of Batu Nampar, Kengkang, Sepit, and Jangkih Jawa. The result is hoped can predict the danger classification of dam failure during the life time of the reservoir. Additionally, it can give input to the policymaker in determining the risk classification of dam failure. Moreover, it can be as one of the inputs in developing the risk classification model of dam failure.
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