Author(s): Yunlong Zhang; Xuan Wang
Linked Author(s):
Keywords: Basal crop coefficient; Meteorological parameters; Net radiation; Vapor pressure; Semiarid are
Abstract: The basal crop coefficient (K) is an important parameter for calculating the actual transpiration of vegetation. In the context of global climate change, it is necessary to analyze the relationship between the basal crop coefficient and meteorological factors (especially water and energy parameters). In this research, the basal crop coefficient was calculated by the normalized difference vegetation index (NDVI). Five meteorological parameters, including two parameters representing water conditions (i. e., vapor pressure and precipitation), two parameters representing energy conditions (i. e., net radiation and temperature) and wind speed parameter, were used to analyze the response of basal crop coefficient dynamics to meteorological conditions variations at Lake Baiyangdian, a semiarid area of north China. The analysis provided the following results: (a) During 2000-2014, the annual averaged basal crop coefficient of Lake Baiyangdian showed a slightly increasing trend (R =0.314). Annual averaged basal crop coefficient reached the maximum (0.693) in 2012, and the average K was 0.641; (b) Within a year, the basal crop coefficient of the entire area underwent constant fluctuations and the maximum K was 0.96 in the 240 day of year (August); (c) Each season had different driving factor of water/energy. In spring, summer and autumn, the regional basal crop coefficients were mainly affected by energy condition (net radiation), water condition (vapor pressure) and energy condition (net radiation), respectively. The correlation of vapor pressure to K was stronger than that for precipitation in summer. The research broadened our cognition about response degree of basal crop coefficient dynamics to water and energy variations through adding two important parameters of water and energy (i. e., net radiation and vapor pressure) that had seldom been discussed. It could be helpful for accurately understanding impacts of climate change on vegetation evapotranspiration and be beneficial for effective ecosystem management.
Year: 2018