因应都市化之智能型水资源管理策略

Intelligent Water Resources Management Strategy under Urbanization

随着时代的变迁,台湾的桃园地区都市化发展迅速,由于人口膨胀、工商业发展蓬勃等因素,民生、工业用水需求日益增加。因此,在干旱发生的情形下,桃园地区的石门水库用水调度将是1个重大课题。面对日益增加的用水需求以及水文不确定性,本研究拟建置智能型水资源管理系统,期能于干旱时期透过灌溉用水弹性调度民生、工业用水方式,降低公共用水压力。本研究搜集2005~2014年桃园地区农业、工业以及人口发展等数据,透过系统动力模式推衍未来2015~2030年桃园地区需水情势,并参考1977、1984、2002年等干旱年之石门水库旬入流量及水库初始有效库容50%、40%、30%等情境,总共设定九种未来干旱供水可能状况,运用石门水库操作规则（M-5操作规线）模拟未来缺水严重程度,并透过非支配排序遗传算-Ⅱ（NSGA-Ⅱ）搜寻最大的平均有效蓄水率（RRS）及最小的修正缺水指标（MSI）等两个目标;透过NSGA-Ⅱ的搜寻,修正缺水指标（MSI）于各水文情境的表现最高达31.3%的改善率,各旬有效蓄水率最高达9.8%的改善率。我们期望所提出之智能型水资源管理系统能对未来永续水资源管理研究有所帮助。

Along with the changes over time, the urbanization of Taoyuan in Taiwan has progressed rapidly while the population growth and industrial development has led to a significant increase in the water demands in this area. Therefore, the water regulation of the Shimen Reservoir in Taoyuan is a critical issue, especially for drought periods. In response to increasing water demands and hydrological uncertainties, this study aims to build an intelligent water allocation system in order to suitably make water regulation with a flexible transfer of water from irrigation sectors to industrial and municipal sectors for reducing the water pressure in public sectors during drought periods. According to the analysis on the historical data collected from agricultural and industrial sectors as well as population statistics in Taoyuan during 2005 and 2014, this study first simulates the future water demands for the period of 2015 and 2030 in Taoyuan. We next design nine water supply scenarios in response to the possible drought periods in the future based on the ten-day inflow data collected from the Shimen Reservoir in three drought years and three initial storage capacities of the reservoir for these drought years. According to the simulation results of future water demand and supply, we analyze the water shortage conditions during 2015 and 2030 by using M-5 rule curves and the non-dominated sorting genetic algorithm-Ⅱ（NSGA-Ⅱ）. In search of the minimal modified shortage index（MSI） and the maximal ratio of effective reservoir storage capacity（RRS）, the results indicate that the largest improvement rates of the MSI and the averaged effective reservoir storage capacity ratio for ten-day periods can reach as high as 31.3% and 9.8%, respectively. We hope that the proposed intelligent water allocation system will pave the way to future research for sustaining water resources management.