Reference evapotranspiration change and the causes across the Yellow River Basin during 1957–2008 and their spatial and seasonal differences

Abstract

[1] As an indicator of atmospheric evaporating capability over a hypothetical reference surface, reference evapotranspiration (ET 0 ) is the most important hydrological and meteorological variable to reflect climate change. This is particularly true for the Yellow River Basin, which faces serious water shortages and is vulnerable to climate change. In this study, the ET 0 at 80 sites during 1957-2008 in the Yellow River Basin was calculated using the Penman-Monteith method with the calibrated Angstrom coefficients. Spatial and seasonal patterns of changes in ET 0 as well as the concerned climatic variables are specially focused on using advanced statistical tests and GIS method. The entire Yellow River Basin is characterized by complicated spatial variability in the change of ET 0 . Significant negative trends are mainly distributed in the southeast corner, northern side, and midwest of the Yellow River Basin, while significant increases of ET 0 mainly occur in the middle part and southwest corner of the basin. Still, no coherent spatial patterns in ET 0 trends are seen in any season. The dominance of warming trends in temperature and decreasing trends in wind speed and sunshine duration can be found in the basin. Relative humidity presents insignificant or weak trends at many sites but with a mixed spatial structure of positive and negative trends at both annual and seasonal scales. The combined effects of climatic variables to ET 0 changes and their spatial and seasonal variability are revealed by further analysis of sensitivity of ET 0 to climatic variables and the contribution of climatic variables to ET 0 changes over six homogenous regions identified by a rotated empirical orthogonal function (REOF) clustering method on annual and seasonal scales. The decline of surface wind speed offsets the increasing effect of the temperature increase and is mainly responsible for the ET 0 reduction in the west and north of the Loess Plateau. The reduced sunshine duration is the leading factor for ET 0 decrease in the middle-lower Yellow River Plain, especially during the summer time. The increasing mean temperature plays the most important role in the ET 0 increase in the source area of the Yellow River Basin. Furthermore, regional actual evapotranspiration and ET 0 present complementary behavior, but does not accurately fall in the 1:1 complementary relationship of the Bouchet's hypothesis, especially for the high elevation subregions. In addition, although precipitation changes are the main driving factors for drought variation, increasing ET 0 intensified the drought in middle regions.

Quantifying Climatic Impact on Reference Evapotranspiration Trends in the Huai River Basin of Eastern China

“…This result was echoed with results of Wang et al [37], Zhang et al [89], and McVicar et al [63]. As shown above, RH was the most sensitive factor for ET ref in the whole HRB, while WS was the least sensitive factor to the ET ref in the same regions.…”

Reference evapotranspiration change and its sensitivity to climate variables in southwest China

“…Mann-Kendall method is a rank-based nonparametric method for assessing the significance of trends. As MannKendall method does not need any distribution assumption for the data, it is recommended by World Meteorological Organization and has been widely used to assess the significance of trends in hydro-meteorological time series (Wang et al 2012;Tabari et al 2012). A statistic S is calculated as follows:…”

“…The quality of meteorological data was examined, and no apparent error was found. Missing monthly data are about 0.47 % as an average for the 57 stations, and were supplemented by the median meteorological data from three neighboring stations (Wang et al 2012). …”

Parametric Modelling of Potential Evapotranspiration: A Global Survey

“…Apparently, the particular hydroclimatic regime at these areas does not allow representing PET through simplified radiation-based approaches, thus requiring either more complex parameterizations or additional variables to explain the seasonal patterns of PET due to energy or water limitations, i.e., relative humidity and/or wind speed [41,42]. PET has been proven sensitive to potential changes in climate in regions with a lower temperature, less solar radiation, and greater relative humidity, while the influence of the wind velocity and relative humidity in its estimation is supported by several studies [41][42][43][44][45][46][47].…”