Reference evapotranspiration (ET0) is an important part of the water cycle and energy cycle during crop growth. Understanding the influencing factors and spatiotemporal variations of ET0 can guide regional water-saving irrigation and regulate agricultural production. Data for daily meteorological observations of temperature, relative humidity, wind speed, and sunshine hours from 38 surface meteorological stations were used to analyze the spatiotemporal variations and trends in Shandong Province from 1980 to 2019. (1) The ET0 from 1980 to 2019 was 1070.5 mm, and there was a significant downward trend in the climate tendency rate of −7.92/10 a. The climate of Shandong Province became warmer and drier. The average annual temperature showed a significant upward trend, while the average annual relative humidity and average annual sunshine hours showed significant downward trends. (2) The annual ET0 ratio in spring, summer, autumn, and winter was 29%, 40%, 21%, and 10%, respectively. (3) A change in Shandong Province’s interannual ET0 occurred in 2002, with a decrease of 130.74 mm since then. (4) The ET0 was positively correlated with temperature, wind speed, and sunshine hours and negatively correlated with relative humidity. This study provides a scientific basis for the regulation and control of agricultural production in Shandong Province.
Reference evapotranspiration (ET0) is an important part of the water and energy cycles during crop growth. Understanding the influencing factors and spatiotemporal variations of ET0 is of positive significance for guiding regional water-saving irrigation and regulating agricultural production. Data for daily meteorological observations of temperature, relative humidity, wind speed, and sunshine hours from 40 surface meteorological stations and the methods of climate tendency rate, Morlet wavelet, M-K mutation, path analysis, sensitivity analysis, and contribution rate analysis were utilized, to analyze the spatiotemporal distribution characteristics and influencing factors in the Beijing–Tianjin–Hebei region from 1990 to 2019. The ET0 from 1990 to 2019 was 958.9 mm, and there was a significant downward trend in the climate tendency rate of −3.07 mm/10 a. The ET0 presents a spatial distribution pattern decreasing from southwest to northeast. A change in the Beijing–Tianjin–Hebei region’s interannual ET0 occurred in 2016, with a decrease of 41.12 mm since then. The ET0 was positively correlated with temperature, wind speed, and sunshine hours, and negatively correlated with relative humidity; among those, wind speed and temperature are the dominant factors affecting the change of ET0. This study provides a scientific basis for the regulation and control of agricultural production in the Beijing–Tianjin–Hebei region.
Reference evapotranspiration (ET0) is one of the significant parameters in agricultural irrigation, especially in Heilongjiang, a big agricultural province in China. In this research, the spatiotemporal variation characteristics of evapotranspiration (ET), relative moisture index (MI) and influencing factors of ET0 in Heilongjiang, which was divided into six ecology districts according to landforms, were analyzed with meteorological data observed over 40 years from 1980 and MOD16 products from 2000 to 2017 using Morlet wavelet analysis and partial correlation analysis. The results indicated that (1) the spatial distribution of ET and PET in Heilongjiang in humid, normal and arid years showed a distribution of being higher in the southwest and lower in the northwest, and higher in the south and lower in the north. The PET was higher than ET from 2002 to 2017, and the difference was small, indicating that the overall moisture in Heilongjiang was sufficient in these years. (2) In the last 40 years, the ET0 increased while the annual MI decreased. The annual minimum of MI in the six regions of Heilongjiang was −0.25, showing that all six regions were drought free. (3) The importance of the meteorological factors affecting ET0 was ranked as average relative humidity > average wind speed > sunshine duration. This research provides scientific guidance for the study of using remote sensing to reverse ET.
Reference evapotranspiration (ET0) is an important part of the water and energy cycles during crop growth. The study of its changing trend is of significance for guiding efficient water utilization and reasonable regulation of agricultural production. Based on daily meteorological data, including temperature, relative humidity, wind speed and sunshine hours, from 38 surface meteorological stations in Shandong Province from 1980 to 2019, the FAO56 Penman–Monteith formula was used to calculate the ET0 and analyse trend and influencing factors, combined with the methods of climate tendency rate, Morlet wavelet, sensitivity analysis and contribution rate analysis. ET0 had 26–30 main oscillation cycles during the 1980–2019 period, and 28‐, 18‐ and 8‐year time scales corresponded to the first, second and third main cycles of ET0, respectively, which determined the characteristics of ET0 change in the past 40 years. The annual average ET0 was significantly positively correlated with average temperature (T), wind speed (WS) and sunshine daily hours (SSD) and significantly negatively correlated with average relative humidity (RH), among which WS, SSD and RH were the main factors affecting ET0. On this basis, because T was not the dominant factor affecting ET0 change, a simplified ET0 calculation algorithm based on seasonal temperature was established that had high goodness of fit R2 accuracy. This study quantitatively analysed the periodic changes and causes of ET0 from a spatio‐temporal view and provided a scientific basis for the rational regulation of agricultural production in Shandong Province.
The aim of the present study was to accurately assess the changes in the degree of instantaneous pollution of natural river. In this paper, a pollutant diffusion model (LBM-CA) for vegetation open channel is constructed. This model consists partly of Cellular Automaton (CA), and the main task of this part is to simulate the pollutant diffusion. Flow influence coefficient is introduced into Cellular Automata to express the influence of vegetation on pollutant diffusion. In order to obtain the flow influence coefficients for each cellular, Lattice Boltzmann Method (LBM) is introduced in the LBM-CA model to simulate the flow in vegetation open channels. The results show that the LBM-CA model has high accuracy. The simulation results show that the existence of vegetation will lead to the accumulation of pollutants and prolong the residence time of pollutants in the vegetation area. The pollutant limits are embedded in the LBM-CA model to predict the pollution level of the basin at a specific time. LBM-CA model provides a method for simulating pollutants diffusion in natural rivers.
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