基于主成分分析法的河流水文改变指标优选

    Optimization of hydrological alteration indicators based on principal component analysis

    • 摘要: 为了克服传统水文改变指标法(IHA)在评价河流水文情势变化特征时各指标间相关性和数据冗余造成整体评价偏差的问题,收集了金沙江流域华弹水文站1952~2017年的日径流数据,运用主成分分析法(PCA),从IHA的32个指标中优选出7个能够较为全面评价水文情势变化的代表性指标:30 d最小流量、基流指数、落水率、涨水率、最大流量日、高流脉冲次数和最小流量日,进行了合理性分析。结果发现:①这7个代表性指标间相关性较弱,用其对河流水文情势变化进行评价的结果与传统IHA法的结果基本一致;②优选出的指标能够提供较为全面合理的水文情势变化评价。研究成果对河流水资源管理有着重要的参考价值和借鉴意义。

       

      Abstract: There is evaluation deviation in quantifying the river hydrological regime characteristic variation by the IHA method,which is caused by inter-correlations between indicators and data redundancy. Therefore, in this paper we selected a set of representative indicators from 32 IHA indicators by principal component analysis on the basis of the daily runoff data from1952 to 2017 obtained from Huatan hydrological station. The preferred indexes were 30-day minimum flow, base flow index, water fall rate, water rise rate, date of maximum flow, high pulse count and date of minimum flow. The results showed that:① there were weak correlations between 7 representative indicators,and the evaluation results by 7 representative indicators were basically the same as the results by IHA method. ② the selected representative indicators could provide more comprehensive and reasonable hydrological regime evaluation results, which was significant for water resources management.

       

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