建立了流域水安全评价指标体系和评价标准,用基于加速遗传算法的模糊层次分析法筛选指标、确定各指标和子系统的权重,用集对分析方法建立了基于联系数的流域水安全评价模型(CN—AM)。CN—AM可从指标、子系统和样本3个层次定量地分析流域水安全的复杂状态,既可测度流域水安全整体状态的高低程度,又可识别影响流域水安全状态的重要指标和重要子系统。CN—AM在巢湖流域中的应用结果表明,基于联系数的均分原则评判方法与属性数学的置信度准则评判方法具有一致性和互补性,联合应用可保障CN—AM评价结果的可靠性。巢湖流域水安全系统处于临界安全状态,应提升流域的经济和科技发展水平、推广节水技术、加快城市化进程和控制人口增长,以提高该流域水安全的保障程度。
On the basis of theoretical analysis, expert consultant and on-site investigation, an index system for assessing the water security of watershed under uncertain environment was established. The accelerating genetic algorithm based fuzzy analytic hierarchy process was used to screen the index system and to determine the weights of both indexes and subsystems of water security assessment system. The index connection numbers, subsystem connection numbers and sample connection numbers between assessed samples and evaluation grading standards were established by using set pair analysis method. Then, a connection number based quantitative assessment model for watershed water security, named connection number assessment model (CN-AM), was established. The application of this model to assess the water security of Chaohu Lake watershed shows that the joint application of judgment method based on principle of equally sharing connection coefficient with method according to confidence criterion of attribute mathematics in CN-AM can improve the reliability of the assessment result. The water security in Chaohu Lake watershed is in a critical security state, the economy, science and technology development level must be further heightened, the water saving technology must be popularized, the urbanization process must be accelerated and the population growth must be controlled in order to heighten the safeguard degree of the watershed water security.