Analysis On The Spatio-temporal Variability And Trends Of Agricultural Water And Thermal Resources From Climate Change Perspectives

The agricultural water and thermal resources is an important basis of agricultural zoning, croppingsystems, crop distribution and crop varieties configuration, and its number and allocation determines thebasic agricultural production conditions in a region. China’s agricultural water geothermal resources hasbeen a significant change with global warming in last50years, resulting in the significant change ofChina’s agricultural planting structure and crop distribution. Systematic analysis of the spatial andtemporal variability and trends of the China Agricultural water and thermal resources in the past50years has an important practical significance to the efficient use of agricultural resource, and adaptationand mitigation of climate change on agricultural production.The paper illustrates the effects of the data gaps of china’s surface climatological observationaldata on climate change trends, and then a set of interpolation programs for meteorological missing datais designed and compiled with spatial interpolation methods. Through interpolation trial, we put forwardthe optimal interpolation scheme. On this basis, we analyze the spatial and temporal variability andtrends of agriculture water and thermal resources, agricultural critical temperature and frost period.Dynamic change of agricultural land area in different accumulated temperature sections is analyzedfrom the time scale. Further, we analyze the wetness and dryness change in China, and estimate thedrought area and intensity. The major conclusions are as follows:(1) The different spatial interpolation algorithms are compiled and evaluated to bridge the missinggaps of meteorological observational dataset. The algorithms used are deterministic methods such asNN, IDW, IDWE, GIDW, MRLAD, GWR. The cross validation of the results indicates that the optimalexponent of the IDW, IDWE, GIDW is2-3, and the optimal search radius is250km to500km, and theoptimal interpolation number of station is6-20. When temperature is interpolated, the elevation-aidedinterpolations (EAI) are significantly better than bivariate interpolations. However, the EAIimprovement isn’t significant when other climate resources are interpolated. Furthermore, theinterpolation errors of various meteorological elements are obvious differences in the calendar months.Precipitation, sunshine hours, average wind speed, relative humidity is suitable to the IDW algorithm,and temperature is preferable to the GIDW or GWR algorithm.(2) The national average accumulated temperature and daily average temperature are significantlyincreasing in the past50years in crop growing season, and however diurnal, sunshine hours and solarradiation are significantly decreasing. At the same time, the national average precipitation and potentialevapotranspiration don’t change on the whole, and however the changes differ from region to region.The precipitation and the amount and number of effective precipitation has fell in the southwest andnortheast China, and also has rose in the southeast and northeast China. The primary factor determiningthe amount of agricultural resources is the amount of climatic resources in calendar year, and thesecondary is the duration of growing season. However, the primary factor also can vary from regions. (3) The trends of agricultural critical temperature (0℃,10℃) present the characteristics of first daybecoming earlier, terminal day postponing, duration prolonging, and the accumulated temperatureincreasing by50-90℃/10a, and mutations occurring mainly in the late1980s to the mid-1990s.Similarly, the first frost date significantly delayed, the last frost date became earlier, and the frost-freeperiod increased by2.5-5d/10a.(4) The areas of arable land, woodland and grassland in the section of low accumulatedtemperature were decreasing, and those in the section of high accumulated temperature were increasing.Compared with the1960s, the arable land areas in the section Ⅰ, section Ⅱ, and section Ⅳ ofaccumulated temperature over0℃(AT0℃) respectively decreased by7.74%,32.42%,8.39%, and theareas in the section Ⅴ increased by43.66%. Likewise, the arable land areas in the section Ⅱ, andsection Ⅳ of AT10℃also fell by35.14%and20.80%, and the areas in the section Ⅴ rose by21.05%.(5) The climate in the southwest and northeast China became drought, and however the climate inthe southeast and northwest China became wet over past50years. Compared to1960s, the extremelyarid area and the semi-arid area respectively expanded by56.92%and28.13%. The arid area andsemi-humid area fell by12.30%and11.43%at the same time. The weak downward trend of droughtareas is detected, but trends differ from region to region. The drought areas in the northeast, southeast,and southern China have significantly rose, and the areas in the southeast coast, the northwest inlandhave declined.The innovations of the research are as follows:(1) A set of interpolation programs for meteorological missing data is designed and compiled withspatial interpolation methods and theories. The effect of the exponent size, search radius, the number ofinterpolation points, and the elevation on the interpolation accuracy is evaluated through interpolationtrials. The optimal interpolation scheme for the different meteorological elements is given.(2) The first date and terminal date stably above5℃are regarded as the indicators of the first dateand terminal date of crop growing season. The spatial and temporal variability of agricultural water andthermal resources in the growing season is analyzed.(3) The spatial dynamic change of the arable land areas in the different sections of accumulatedtemperature and the dryness&wetness climate are estimated on the decadal time scale.