Intrinsic Cross-Correlation Analysis of Hydro-Meteorological Data in the Loess Plateau, China

作者：Xiaowei Wei, Hongbo Zhang, Xinghui Gong, Xingchen Wei, Chiheng Dang, Tong Zhi · 发表于：International Journal of Environmental Research and Public Health · 年份：2020 · DOI：10.3390/ijerph17072410 · 被引用次数：9 · 研究领域：Hydrological Forecasting Using AI、Hydrology and Watershed Management Studies、Climate variability and models

The purpose of this study is to illustrate intrinsic correlations and their temporal evolution between hydro-meteorological elements by building three-element-composed system, including precipitation (P), runoff (R), air temperature (T), evaporation (pan evaporation, E), and sunshine duration (SD) in the Wuding River Basin (WRB) in Loess Plateau, China, and to provide regional experience to correlational research of global hydro-meteorological data. In analysis, detrended partial cross-correlation analysis (DPCCA) and temporal evolution of detrended partial-cross-correlation analysis (TDPCCA) were employed to demonstrate the intrinsic correlation, and detrended cross-correlation analysis (DCCA) coefficient was used as comparative method to serve for performance tests of DPCCA. In addition, a novel way was proposed to estimate the contribution of a variable to the change of correlation between other two variables, namely impact assessment of correlation change (IACC). The analysis results in the WRB indicated that (1) DPCCA can analyze the intrinsic correlations between two hydro-meteorological elements by removing potential influences of the relevant third one in a complex system, providing insights on interaction mechanisms among elements under changing environment; (2) the interaction among P, R, and E was most strong in all three-element-composed systems. In elements, there was an intrinsic and stable correlation between P and R, as well as E and T, not depending on time s...