Climate change refers to the statistically significant changes in the mean and dispersion values of meteorological factors. Characterizing potential evapotranspiration (ET0) and its climatic causes will contribute to the estimation of the atmospheric water cycle under climate change. In this study, based on daily meteorological data from 26 meteorological stations in Heilongjiang Province from 1960 to 2019, ET0 was calculated by the Penman–Monteith formula, linear regression method and the Mann–Kendall trend test were used to reveal the seasonal and inter-annual changing trend of ET0. The sensitivity-contribution rate method was used to clarify the climatic factors affecting ET0. The results showed that: (1) From 1960 to 2019, the maximum temperature (Tmax), minimum temperature (Tmin) and average temperature (Tmean) showed an increasing trend, with climate tendency rate of 0.22 °C per decade (10a), 0.49 °C/(10a), 0.36 °C/(10a), respectively. The relative humidity (RH), wind speed (U) and net radiation (Rn) showed a decreasing trend, with a climate tendency rate of −0.42%/(10a), −0.18 m/s/(10a), −0.08 MJ/m2/(10a), respectively. (2) ET0 showed a decreasing trend on seasonal and inter-annual scales. Inter-annually, the average climate tendency rate of ET0 was −8.69 mm/(10a). seasonally, the lowest climate tendency rate was −6.33 mm/(10a) in spring. (3) ET0 was negatively sensitive to Tmin, and RH, while positively sensitive to Tmax, Tmean U and Rn, its sensitivity coefficient of U was the highest, which was 1.22. (4) The contribution rate of U to ET0 was the highest on an inter-annual scale as well as in spring and autumn, which were −8.96%, −9.79% and −13.14%, respectively, and the highest contribution rate to ET0 were Rn and Tmin in summer and winter, whose contribution rates were −4.37% and −11.46%, respectively. This study provides an understanding on the response of evapotranspiration to climatic change and further provides support on the optimal allocation of regional water resource and agricultural water management under climate change.
The shortage of water resources is a long-standing constraint on the development of the Chinese economy and society. In this paper, the climate change occurring in Hulan River Basin is analyzed using the data collected at Wangkui Meteorological Station from 1960 to 2020. The overall temperature in the basin shows an upward trend, with a cumulative increase of 1.6 °C, as does the precipitation, which reaches 566.2 mm. In contrast, there is a downward trend shown by wind speed, with a cumulative decrease of 1.313 m/s. GIS remote sensing technology is applied to build a SWAT distributed hydrological model for the purpose of conducting runoff simulation in Hulan River Basin, and SWAT-CUP software is used to correct and analyze the simulation results. The parameters of snow melt are set to improve the accuracy of the model. The runoff data collected from Lanxi Hydrological Station from 2008 to 2020 are used to verify the model. The results show that the efficiency coefficient (NES) and correlation coefficient (R2) are 0.75 and 0.84, respectively, in the validation period from 2010 to 2013, while they are 0.77 and 0.93, respectively, in the correction period from 2014 to 2016, meeting the criteria of model evaluation. It can be seen from results noted above that SWAT is applicable in Hulan River Basin, providing a certain reference for the management of hydrological and water resources available in this region and for the construction of a distributed hydrological model of rivers in those high-latitude cold regions.
Crop water production function models (WPFMs) are a required method to study the relationships between yield and water consumption under regulated deficit irrigation (RDI). In this study, a pot experiment was established to study the effect of water deficit during both individual growth stages and across two consecutive growth stages of rice on yield, water consumption, and water use efficiency (WUE) in 2017 and 2018. Light, medium, and severe water deficits were set as 80~90%, 70~80%, and 60~70% of fully saturated soil moisture content, respectively. The accuracies of five WPFMs were tested based on the experimental results. The results showed that yields and WUE of a light water deficit were higher than those of medium and severe water deficits at each growth stage. The yields and WUE of light drought stress treatments in the flowering and milky stages were higher than the fully saturated soil moisture control by 4~7.4% and 5.3~20.6%, respectively. Water consumption decreased with increasing water deficit across two consecutive growth stages. The Minhas model had the highest simulation accuracy of the five WPFMs, with relatively lower AE, RMSE, Cv, CRM, and higher R2, which were 0.0002, 0.0634, 6.9965, 0.0002, and 0.9951 in 2017 and 0.0110, 0.0760, 8.9882, 0.0131, and 0.9923 in 2018, respectively. The sensitivity indices for the Minhas model more accurately reflected the sensitivity of rice yield to water deficit at different growth stages in 2017 and 2018, compared with the Jensen model, Stewart model, Blank model, and Singh model. Rice yield was most sensitive to water deficit at the jointing and booting stage. The results indicate that the Minhas model is the most suitable WPFM for guiding rice irrigation practices in cold black soil regions of China.
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