Spatial And Temporal Distribution Characteristics And Influencing Mechanism Of Evapotranspiration In North China Plain

As an important agricultural growing area in China,the total water resources in the North China Plain region are small and unevenly distributed within the year.The growth and development of crops are strongly dependent on precipitation and irrigation,and long-term well irrigation leads to a gradual decline in groundwater.With the development of the national economy,agricultural water consumption has been continuously compressed,and irrigation water is the main component of agricultural water consumption in China.Evapotranspiration（ET）,also known as crop water requirement,including plant transpiration and inter-plant evaporation,is the basis for formulating irrigation schedules.It is of great significance to improve the efficiency and management level of agricultural water use in the North China Plain by proposing a practical calculation model of ET and finding out the spatial and temporal distribution of ET.Based on the daily meteorological data of the North China Plain from January1970 to June 2021,the Blaney-Criddle（BC）model for calculating the reference crop（ET₀）after least squares rate determination at different spatial and temporal scales was proposed for areas with inadequate meteorological data,the optimal rate determination time scale was judged by evaluation indexes and the spatial model was established,the applicability of the optimal rate determination model in different sub-regions of the North China Plain was analyzed.The spatial and temporal distribution characteristics and influence factors of ET₀in the North China Plain under the optimal rate model were investigated;the spatial and temporal distribution characteristics of ET₀ under the meteorological factor and Penman Monteith（PM）model were analyzed for the study area,and the distance that can promote the most obvious spatial process clustering（optimal distance）was determined by spatial autocorrelation analysis.The optimal hotspot analysis tool explored the statistically significant spatial cold hotspot distribution characteristics of ET₀,and a sensitivity analysis was conducted using a Geo-temporal weighted regression model（GTWR）to determine the main meteorological factors affecting the distribution of cold hotspots in different spaces;based on remote sensing data in 2015 and 2020,the Surface Energy Balance Algorithm for Land（SEBAL）model to estimate the vegetation index of the North China Plain,and compare and analyze with MODIS data to evaluate the credibility of the SEBAL model in the North China Plain,estimate the amount of TEM in Langfang based on the SEBAL model,and evaluate and analyze the change pattern and spatial and temporal distribution characteristics of ET.The main conclusions are as follows:（1）The quarterly calibrated BC model has the best performance in the North China Plain.The coefficients b and a range from 0.537 to 1.813 and-5.598 to 0.311,respectively.The quarterly calibrated BC model of typical stations can give satisfactory results（R²>0.85）,the meteorological factor that has the greatest influence on ET₀ is the maximum temperature;The range of annual total ET₀ calculated by the BC model is larger than that of the standard PM model,and the spatial distribution of annual total ET₀ in the first and fourth quarters is basically the same,while that in the second and third quarters is basically the same.（2）The inverse distance weight interpolation method was used to extend the data from point to surface.The relative humidity and temperature are the main factors affecting ET₀ in the North China Plain.The time series test analysis shows that ET₀decreases year by year during the study period.The best distance from the first to the fourth quarter of the North China Plain is 87,84,98 and 87 km;the ET₀ hot spot area（cold spot area）in the second and third quarters of the study area is in good agreement with the ET₀ high value area（low value area）,and the ET₀ cold spot area in the first quarter is more consistent with the ET₀ low value area;In the Beijing-Tianjin-Hebei region,ET₀ is mainly affected by average temperature and wind speed.In Shandong Province,ET₀ is mainly affected by average temperature and relative humidity,and in Henan Province,ET₀ is mainly affected by relative humidity and wind speed.（3）According to the image data of April 2015 and May 2020,the vegetation index calculated based on the SEBAL model is in line with the ground object conditions in the spatial distribution of the North China Plain;based on the SEBAL model,the ET of Langfang is overestimated compared with the MODIS original data.The spatial distribution is basically the same,showing the distribution characteristics of high in the north and low in the south.The annual variation of ET in Langfang is basically consistent with the temperature.The spatial distribution characteristics of the second and third quarters are similar.