Comparison of Meteoric Water Lines at Different Temporal Scales and Regression Methods in Inland Monsoon Region, Northwest China.
PubMed(2023)
摘要
The local meteoric water line (LMWL) is an important basis for tracing the regional hydrological processes with stable isotopes. The establishment of LMWL, which can represent the overall characteristics of stable isotopes of local precipitation, is crucial for accurately revealing the hydrological processes. The influences of different temporal scales and regression methods on the established LMWL were analyzed and compared based on nine years of stable isotopic data of precipitation in Changwu Tableland, a typical area of the inland monsoon region of Northwest China. The results showed that, for different regression methods, the LMWL established by stable isotopes of annual precipitation was basically stable, whereas the LWML established by each precipitation event and the monthly precipitation data showed significant differences with different regression methods. The LMWL from the ordinary least squares regression (OLSR), major axis regression (MA) and reduced major axis regression (RMA) methods were significantly different based on the data of precipitation event, monthly precipitation data, and annual precipitation data, respectively. Only when OLSR, MA and RMA considering precipitation weighting were used, the LMWL established by these scale data was relatively close. This suggested that special attention should be paid to the selection of precipitation stable isotope data scale and regression method when LMWL was established in areas with temporal heterogeneity of precipitation and stable isotopic characteristics. For regions where stable isotope observations of precipitation were difficult and data were limited, the precipitation weighted major axis regression or reduced major axis regression methods are recommended during the establishment of representative LMWL.
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关键词
meteoric water line,northwest inland monsoon region,regression method,stable isotope,time scale
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