基于两种多元干旱指数构建的综合方法的机制研究。
On the mechanisms of two composite methods for construction of multivariate drought indices.
机构信息
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China; School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China.
College of Hydrometeorology, Nanjing University of Information Science & Technology, Nanjing 210044, China.
出版信息
Sci Total Environ. 2019 Jan 10;647:981-991. doi: 10.1016/j.scitotenv.2018.07.273. Epub 2018 Jul 31.
Droughts are comprehensive and complex issues that need to be characterized from a multivariate perspective. In recent years, a number of composite indices have been proposed for drought characterization. However, rare studies have systematically compared similarities and dissimilarities of these indices, and they have provided little insights into the combination mechanisms. To address this issue, two widely used combination approaches, namely the principal component analysis (PCA) and copula based joint probability distribution were employed, with the corresponding integrated product denoted as the Aggregate Drought Index (ADI) and Joint Drought Deficit Index (JDI). Five constituents for constructing ADI and JDI were derived from the variable infiltration capacity model (VIC) monthly simulations over the Yellow River basin (YRB), China, including precipitation (P), actual evapotranspiration (ET), soil moisture of top two layers, and runoff (during 1961-2012). Results showed that the behavioral patterns of ADI and JDI may not be easily influenced by the variation of one single element, and they represented comprehensive moisture status well. A further comparison between these two composite indices suggested that ADI and JDI behaved similarly in most areas of YRB, with some dissimilarities in the source region. The particular behavior of ET was responsible for the inconsistency. Comparing to other regions, an enhanced role of potential evapotranspiration (PET) was imposed on ET in the source region, leading to a poor relationship of ET with P and other hydrological variables. Accordingly, when constructing composite drought indices, the drought information indicated by ET was more easily abandoned by ADI but reserved in JDI. This study clearly demonstrates the mechanisms of two common integrated approaches in blending different drought information, which has significant implications for composite drought indices construction and application, and potentially provides some valuable references for the improvement of monitoring techniques in future drought related researches.
干旱是一个综合性和复杂性的问题，需要从多个角度进行描述。近年来，提出了许多综合指标来描述干旱。然而，很少有研究系统地比较这些指标的相似性和差异性，也没有深入了解它们的组合机制。为了解决这个问题，本文采用了两种广泛使用的组合方法，即主成分分析（PCA）和基于 copula 的联合概率分布，对应的综合产品分别表示为综合干旱指数（ADI）和联合干旱亏缺指数（JDI）。从中国黄河流域（YRB）的可变渗透能力模型（VIC）月模拟中得出了构建 ADI 和 JDI 的五个组成部分，包括降水（P）、实际蒸散（ET）、前两层土壤水分和径流（1961-2012 年）。结果表明，ADI 和 JDI 的行为模式可能不容易受到单一元素变化的影响，并且它们很好地代表了综合湿度状况。对这两个综合指数的进一步比较表明，ADI 和 JDI 在 YRB 的大部分地区表现相似，在源区存在一些差异。ET 的特殊行为是造成这种不一致的原因。与其他地区相比，源区潜在蒸散（PET）对 ET 的作用增强，导致 ET 与 P 和其他水文变量的关系较差。因此，在构建综合干旱指数时，ADI 更容易忽略 ET 所表示的干旱信息，而 JDI 则保留了这些信息。本研究清楚地展示了两种常见综合方法在融合不同干旱信息方面的机制，这对综合干旱指数的构建和应用具有重要意义，并为未来干旱相关研究中监测技术的改进提供了一些有价值的参考。
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