Intra- and Inter-Annual Variability of Hydrometeorological Variables in the Jinsha River Basin, Southwest China

• Main Authors: Tian Peng, Chu Zhang, Jianzhong Zhou
• Format: Article
• Language: English
• Published: MDPI AG 2019-09-01
• Series: Sustainability
• Subjects: Jinsha River Basin; intra- and inter-annual variability; hydrometeorological variables; Mann–Kendall trend detection; correlation analysis
• Online Access: https://www.mdpi.com/2071-1050/11/19/5142

In this study, the intra- and inter-annual variability of three major elements in the water system, temperature, precipitation and streamflow, from 1974 to 2010 in the Jinsha River Basin, China, were analyzed. An exploratory data analysis method, namely, moving average over shifting horizon (MASH), was introduced and combined with the Mann–Kendall (MK) test and Sen’s slope estimation to analyze the intra- and inter-annual variations. The combination of MASH with the MK test and Sen’s slope estimation demonstrated that the annual temperature, precipitation and streamflow from 1974 to 2010 showed, on average, an increasing trend. The highest change in temperature was detected in early January, 0.8 ℃, that of precipitation was detected in late June, 0.4 mm/day, and that of streamflow was detected mid-August, 138 mm/day. Sensitivity analysis of the smoothing parameters on estimated trends demonstrated that <i>Y</i> parameters smaller than 2 and <i>w</i> parameters smaller than 6 were not suitable for trend detection when applying the MASH method. The correlation between the smoothed data was generally greater than that between the original hydrometeorological data, which demonstrated that the application of MASH could eliminate the influence of periodicity and random fluctuations on hydrometeorological time series and could facilitate regularity and the detection of trends.