考虑水文非一致性变异的河道基本生态流量

Study of basic ecological instream flow considering hydrological alterations under non-stationary

  • 摘要: 考虑水文非一致性变异提出河道内基本生态流量阈值的计算方法与模型,并将其应用于湟水干流上游西宁断面进行例证。采用Mann-Kendal检验和滑动t检验进行水文非一致性变异综合诊断,经还原修正以水文变异前天然流量过程为基准,分别利用广义极值分布流量众值法、历时曲线法、改进年内同频率展布法计算河道内生态流量过程,取其外包线作为河道内基本生态流量阈值。结果表明,西宁站年径流量时间序列突变点是2000年,经还原修正,利用天然径流资料计算得到西宁站枯水期、平水期、丰水期的基本生态流量阈值下限均值分别是11.0、17.6和27.5 m3/s,阈值上限均值分别是17.0、35.6和56.0 m3/s。与已有结果对比,生态流量阈值计算方法具有一定的合理性,更加贴近具有季节性的湟水干流水文生态系统。

     

    Abstract: The calculation method and model of the basic ecological instream flow threshold were proposed considering hydrological alterations under non-stationary, and applied to the Xining section of the Huang River for illustration. Mann-Kendal test and sliding t test were used for comprehensive diagnosis of hydrological alterations under non-stationary. After restoration and correction, the natural flow process before hydrological alterations was used as the benchmark, and the Generalized Extreme Value Distribution (GEV) flow mode method, the diachronic curve method, and the improved equal frequency method within one year were used to calculate the ecological flow process in the river. The threshold of basic ecological flow in the river was the outsourcing line of the calculation results of the above method. The results show that the abrupt change point of the annual runoff time series of Xining Station is 2000. After reduction and correction, natural runoff data were used to calculate basic ecological flow threshold. Basic ecological flow lower threshold averages of Xining Station are 11.0 m3/s in drought period, 17.6 m3/s in common water period, and 27.5 m3/s in flood period, respectively. The upper threshold averages are 17.0 m3/s in drought period, 35.6 m3/s in common water period, and 56.0 m3/s in flood period, respectively. Comparing with the existing results, the calculation method of basic ecological flow threshold has a certain rationality, and it is closer to the hydrological ecosystem of the mainstream of the Huang River with seasonality.

     

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