基于水平衡分析的干旱严重程度评价与预报方法

Ock-Jae Jang
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引用次数: 1

摘要

干旱是一种难以识别其发生和终止的自然灾害,也难以估计过去发生和预计在不久的将来发生的事件所造成的损害。虽然干旱指数或其频率在现有研究中被广泛应用于解释每种事件的严重程度,但由于不熟悉统计值的表达,决策者和利益相关者(公众)可能难以理解结果。因此,在本研究中,基于水平衡分析的缺水量来评估和预测干旱严重程度的方法被置于讨论的中心。首先,为了改进《国家水资源规划》中现有的干旱评价分析方法,提出了利用土地利用图估算各子流域需水量的替代方法,并在供水方面将水库和地下水纳入MODSIM-DSS模拟。利用决策树分析了研究区模拟缺水的干旱程度与SPEI值(SPEI 6 =冬季和春季6个月的估计值,SPEI 3 =夏季3个月的估计值)之间的关系。由于这一成果,每年春季结束时,对干旱严重程度的预测将得到定量估计的缺水情况,这将有助于在灾害发生前启动抗旱措施。
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Methodology for assessment and forecast of drought severity based on the water balance analysis
Drought is a natural disaster which is hard to recognize its onset and termination and to estimate the damage from the events which occurred in the past and are expected in near future. While the drought indices or their frequencies are widely applied to explain the severity of each event in the existing studies, decision-makers and stakeholders (the public) may have trouble in understanding the results due to the unfamiliar expression with statistical values. In this study, therefore, the methodology for assessment and forecast of drought severity based on the amount of water shortage from the water balance analysis was be placed at the center of the discussion. Firstly, in order to improve the existing analysis for drought assessment adopted in the National Water Resources Plan, alternative methods have been suggested to estimate the amount of water demand in each sub-basin using the land use map, and in an aspect of water supply, reservoirs and underground water are included in the simulation of MODSIM-DSS. The relationship between drought severity from the simulated water shortage in the study area and the values of SPEIs (SPEI 6 = estimated for 6 months winter and spring season, SPEI 3 = estimated for 3 months summer season) has been analyzed by the Decision tree. Due to this achievement, at the end of the spring season, every year the forecast for the drought severity will be available with the quantitatively estimated water shortage, and it will be helpful to activate the drought mitigation measures before the disaster occurs.
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