Attribution Analysis of Long-Term Trends of Aridity Index in the Huai River Basin, Eastern China

Abstract

This paper aims to combinedly investigate the spatiotemporal trends of precipitation (Pre), reference evapotranspiration (ET0), and aridity index (AI) by employing nonparametric methods based on daily datasets from 137 meteorological stations during 1961–2014 in the Huai River Basin (HRB). The dominant factors influencing ET0 and AI trends were also explored using the detrended and differential equation methods. Results show that (1) Pre, ET0, and AI were much larger in summer than in other seasons, and AI had a nonsignificant increasing trend in annual time scale, while Pre and ET0 exhibited decreasing trends, but AI showed a downward trend in spring and autumn (becoming drier) and an upward trend during summer and winter due to increased Pre (becoming wetter); (2) lower AI values were identified in north and higher in south, and lower ET0 was identified in south and higher in north in annual time scale, growing season and spring, while ET0 decreased from west to east in summer and winter, the spatial distribution of Pre was similar to that of AI; (3) for ET0 trends, in general, wind speed at two-meter height (u2) was the dominant factor in spring, autumn, winter, and annual time scale, while in other seasons, solar radiation (Rs) played a dominant role; (4) for AI trends, AI was mostly contributed by Pre in spring, autumn, and winter, the Rs contributed the most to AI trend in growing season and summer, then in annual time scale, u2 was the dominant factor; (5) overall, the contribution of Pre to AI trends was much larger than that of ET0 in spring, autumn, and winter, while AI was mostly contributed by ET0 in annual time scale, growing season and summer. The outcomes of the study may improve our scientific understanding of recent climate change effects on dry–wet variations in the HRB; moreover, this information may be utilized in other climatic regions for comparison analyses.