基于ITD与信息熵的区域蒸发时序复杂性分析

蒸发序列复杂性分析对揭示区域水文系统非稳态与不确定性具有重要现实意义。以中国黑龙江省哈尔滨市为例,将本征时间尺度分解(Intrinsic time-scale decomposition,ITD)算法引入水文系统复杂性测度中,将其与信息熵(Information entropy,IE)结合,探讨逐月蒸发序列复杂性特征。结果表明,研究区月蒸发复杂性呈西高东低基本格局,哈尔滨市蒸发时序复杂性与海拔高度呈正相关,与水田面积、旱田面积、工业产值呈负相关,而人口密度对哈尔滨市蒸发复杂性影响较小;相较于小波熵与样本熵研究提出ITD-IE蒸发时序复杂性测度组合算法表现出更优异鲁棒性。研究成果提高水文序列复杂性测度结果准确性,揭示蒸发序列复杂性变异规律,可为哈尔滨市科学合理利用水资源与指导农业生产实践等提供理论支撑。

Complexity analysis on regional evaporation timing based on ITD and information entropy

Evaporation sequence complexity analysis has important practical significance for revealing the unsteady state and uncertainty of regional hydrological systems. Taking the example of Harbin City, Heilongjiang Province, China, the intrinsic time-scale decomposition(ITD) algorithm was introduced into the hydrological system complexity measure, and it was combined with information entropy(IE) to explore the complexity of the monthly evaporation sequence. The results showed that the complexity of monthly evaporation in the study area was the basic pattern of west high and east low.The complexity of evaporation time series in Harbin City was positively correlated with altitude and negatively correlated with paddy field area, dry land area and industrial output value, while population density was negative. The influence of evaporation complexity in Harbin City was small; compared with wavelet entropy and sample entropy, the ITD-IE evaporative timing complexity measure combination algorithm proposed in this paper showed better robustness. The research results improved the accuracy of hydrological sequence complexity measurement results, revealed the complexity variation law of evaporation sequence in Harbin City, and provided ascientific support for Harbin scientific and rational use of water resources and guiding agricultural production practices.