Changing characteristics and attribution analysis of potential evapotranspiration in the Huang–Huai–Hai River Basin, China

• Published in: Meteorology and atmospheric physics 2021-02, Vol.133 (1), p.97-108
• Main Authors: Guan, Xiaoxiang, Zhang, Jianyun, Yang, Qinli, Wang, Guoqing
• Format: Article
• Language: English
• Subjects: Air temperature; Aquatic Pollution; Atmospheric Sciences; Climate change; Earth and Environmental Science; Earth Sciences; Elasticity; Evapotranspiration; Gauges; Hydrologic cycle; Hydrological cycle; Hydrology; Industrial development; Math. Appl. in Environmental Science; Meteorology; Net radiation; Original Paper; Potential evapotranspiration; Radiation; Radiation balance; Regression analysis; Relative humidity; River basins; Rivers; Terrestrial Pollution; Waste Water Technology; Water consumption; Water Management; Water Pollution Control; Water shortages; Wind speed
• ISSN: 0177-7971; 1436-5065
• DOI: 10.1007/s00703-020-00741-6

Evapotranspiration is a key component of the hydrological cycle. It is important to understand the features of the variation of potential evapotranspiration and the impacts of its drivers to estimate regional water consumption. The Huang–Huai–Hai (HHH) River Basin is comprised of three major rivers (the Yellow, Huai and Hai) and has been threatened by water shortages and huge consumption of water for agricultural and industrial development. In this study of the Huang–Huai–Hai (HHH) River Basin, potential evapotranspiration ( E 0 ) across the basin was calculated using the Penman–Monteith model, and their changing characteristics were detected by using the Mann–Kendall test. The test was based on the daily climatic variables from 1965 to 2014 at 175 meteorological gauges. In addition, the influential effect of net radiation ( R n ), relative humidity (RHU), wind speed (WIN), mean, maximum and minimum air temperature ( T a , T max and T min ) on E 0 were analyzed by using the climate elasticity method, with their relative contribution to the changes of E 0 quantitatively revealed by using the multiple linear regression method. The results showed that R n , WIN, RHU and T a are the predominant climatic predictors that are more influential to E 0 while T max and T min have the least impact. The increase in annual E 0 in the period of 1985–2014 in the HHH River Basin was mainly attributed to the significantly increasing T a , which may greatly offset the effect of decreasing WIN and R n . The decrease of annual E 0 in the period of 1965–2014 in the middle area of the basin was mainly attributed to the falling WIN and R n .