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ABSTRACT Potential evapotranspiration represents the maximum evaporative capacity for a region, which underscores the importance of analysing its changes and attribution to provide information for water resource management. This study focused on the northern Loess Plateau of China, investigated the changes in potential evapotranspiration ( ET0) using data from 34 stations during 1960-2013 and conducted its temporal and spatial attribution through the differentiation equation method. The results show that the annual mean ET0 is 1004.9 mm with a decreasing trend at the rate of 0.33 mm year−1. The lowest values were found in the northeast and southwest regions, while the greatest ET0 was in the northwest region. An 'evaporation paradox' existed as a whole, but not obviously. The ET0 was most sensitive to actual vapour pressure ( ea), followed by solar radiation ( Rs), mean temperature ( Tmean) and wind speed ( U2). The inter-annual variation in the sensitivity of ET0 in relation to climatic factors showed that ET0 became more sensitive to U2 and Tmean but less sensitive to Rs and ea from 1960 to 2013. Temporally, the increasing Tmean resulted in the increase of ET0; while its effect was weakened by the other three factors, especially by decreasing U2. The contributions of climatic factors to the ET0 spatial variation trends were also analysed along two transects, but the dominant factors were different for each transect. Furthermore, the possible impacts of human activities on ET0 changes were also discussed. [ABSTRACT FROM AUTHOR]

• Interactions between factors impacting ET varies at different time scales. • Interannual change of vegetation coverage is independent from climate seasonality. • Climate seasonality and topography impact vegetation condition on the long-term scale. • Vegetation and fraction of precipitation falling as snow are selected to fit mean annual ω. Vegetation, climate and topography have been empirically formulated into the controlling parameter of the Budyko model (ω) to estimate evapotranspiration (ET). However, these variables, if simultaneously employed, may induce multicollinearity problems because of their potential interactions. Further, these interactions may vary with different time scales and subsequently result in the inaccurate estimation of ω. As such, we investigated the interactions of vegetation, climate and topography and their corresponding effects on ET modelling at different time scales by employing vegetation coverage (M), an improved climate seasonality and asynchrony index (SAI), the fraction of precipitation falling as snow (f s) and relative basin relief (BR/ B R ¯), in 30 catchments in China's Loess Plateau. We found that, on annual scale, M and SAI were significantly related to ω, while being independent from each other; in consequence, both of them should be parameterized into the Budyko model on the annual scale for better ET modelling. However, the links between M and SAI became stronger with increased time scales, the parameterization of ω should thus be reformatted for longer periods. When extended to a 30-year period, ω was closely related to the above variables, but M was highly intercorrelated with SAI and BR/ B R ¯ , and f s was significantly related to BR/ B R ¯. The independent M and f s were finally selected to fit ω, which allowed mean annual ET to be accurately modelled on long-term scale. Identification of the dominant factors applicable at different time scales can simplify the empirical parameterization of the Budyko formula and thereby facilitate more accurate estimation of ET. [ABSTRACT FROM AUTHOR]