Response And Simulation Study On Spring Maize Productivity Of Meteorological Factor In The Northwest Semiarid Region

In recent decades,climate change has important influence on agricultural production activities,especially the maize production in the northwest semiarid region the most sensitive to climate change,only make full use of resources,reasonable layout and precise management were to improve crop yield and the most important way to adapt to climate change.It is a scientific problem to assess the impact of climate change and adaptation strategy.Through studies the spring maize in the northwest semiarid region productivity and agricultural climate time variation characteristics,this article had clear the response mechanism of each other,at the same time using the crop model and agricultural information technology to predict crop productivity for different agricultural ecological sections,plan planting districts,adjust and control management measures and variety,such as the sustainable high yield and stable yield has important theory meaning and application value.This study was conducted in 2014-2016 in the middle area of Gansu province,which represents the northwest arid rain-fed agriculture area,and carried out the experimental study on the productivity of spring maize under different fertilizing gradient and planting modes.By observing and collecting corn crop data,soil data and meteorological data,using AquaCrop model for its parameter debug and validation,and local management measures to make use of localization AquaCrop model parameter optimization.By observing and collecting corn crop data,soil data and meteorological data,the research debugged and validated AquaCrop model parameters,and optimized local management measures for spring maize.Using local 35-year historical meteorological data and different simulation scenarios,the local climate productivity of spring maize were simulated,and the history of the region climate change characteristics and the impact on productivity of spring maize were analyzed,and the regression equation of the meteorological factor productivity of spring mazie were be established.By using CIMP5 climate model,the temperature and rainfall were forecast for the future changes in the region,finally combining with AquaCrop model,maize cultivation researches,climate model,and using object-oriented programming technology,digital management platform for maize growth was developed.The main conclusions are as follows:?1?Using Hsiao recommended maize parameters to calibrated and verificated AquaCrop model,they research got the spring maize yield in arid and biological observations and simulated values basic linear relationship,the root mean square error of the measured and simulated yield under different treatments was 245.34⁷45.10 kg/hm²,standard root mean square error was 6.94%⁹.49%,observation and simulation of biomass in the whole stages of root mean square error was737.13⁹14.21 kg/hm²,standard root mean square error was 4.17%⁴.73%,0¹0 cm soil moisture content of the simulation and the measured almost has the same change trend,root mean square error was 2.21%³.16%,the standard root mean square error was 8.65%¹0.74%,simulation precision have low overestimate the trend with the increase of nitrogen fertilizer and water stress,but overall was a good way to simulate arid spring maize growth process,the model can be used as a spring corn production prediction in the region,such as regulating effective tool.?2?Using the calibration model parameters to study changing trends of spring maize under different management levels,the research got the regression model between spring maize yield and planting density,nitrogen fertilizer rate and the growing stage,which R² were all greater than 0.98,the optimum management measures of Gansu center region under all-film double-furrow sowing were as follows:the optimal seeding time was from late April to early May,planting density was45000-65000 plants/hm²,the nitrogen application rate was 240-240 kg/hm².In conclusion,AquaCrop model was a useful tool for agricultural decision-making and optimize the cultivation mode to increase the yield of maize,which also contributes to the transformation of agricultural technology.?3?While the temperature and precipitation under setting range increasing?precipitation reduced by 15%—rising 15%,temperatures reduce by 1.5?—rising 1.5??,the yield range of all plating models were reduced,Under different climate scenarios,spring maize yields of all-film double-furrow sowing were greater than single ridge and open field cultivation,and the yield fluctuation was smallest which the average yield curve slope was 0.0834,which indivated that it has strong ability to adapt to climate change.The yield potential reached maximum in temperature raised 1.5?and precipitation increased 15%situation,compared with the original climate,the yield of open field planting,single-row ridge planting and all-film double-furrow sowing average increased 13.45%,11.57%and 17.67%,respectively.Temperature had extremely significant effect on the yield of three planting patterns,the precipitation was very significant for yield of open field planting,and significant for yield of single-row ridge planting and all-film double-furrow sowing,and the increasing of the temperature and rainfall had the positive effect on spring maize yield.?4?The trend of different monthly and inter-annual changes in the agricultural meteorological factors of 35-year in the region was analyzed,the monthly maximum temperature was gradually reduced by average trend rate of-0.85?·(10a^-1),while the lowest temperature was the opposite of that by average trend rate of 1.56?·(10a^-1).Annual rainfall and reference crop evapotranspiration showed a decreasing trend by average trend rate of-0.811mm·(10a^-1)and-1.538 mm·(10a^-1),respectively.While average temperature and sunshine duration had increased by the 0.425?·(10a^-1)and 0.1h·(10a^-1),respectively.By Affected climate change the discrete degree and variation coefficient of spring maize yield were much greater than the biomass,at the same time each decades spring maize yield relative variation distribution was also significantly greater than the of biomass,common illustrates the yield was greater sensitivity on climate than the biomass.Use Box-Behnken test method,regression models of between the meteorological factors and yield and biomass were established?P<0.0001?,the all the factors influence of spring maize yield and biomass orders were as follows:temperature>reference crop transpiration>rainfall,and all of them reached significant or even significant levels.?5?The climate model of CMIP5 has a good relationship with the temperature simulation and monitoring value?r=0.5486,n=375?.Average temperature and minimum temperature in the future had increased state,the average temperature increased slightly low,a whole range of 0.98².84?,the lowest temperature increasing the range was 1.35².87?,the highest temperature in the near future there was a downturn of 0.92¹.68?,but was increased in middle and late of this century.The linear relationship between rainfall simulation and monitoring value was poor,and the relative absolute error of simulation was 23.03%⁵2.08%.The rainfall prediction were decreased in recent and medium,and the drought was more severe with radiation force increases,the decline range was5.96%¹4.83%,but in the end of the rainfall was increased,in the range of 5.34%⁵.34%.In the future,the productivity of spring maize in the region has an increasing trend,and the yield and biomass increased by 18.49%and 12.41%,respectively.?6?Crop growth model as the core,combining with the knowledge model and database,the application of object-oriented structured and modular program design,Based on crop model and climate model of corn digital platform was developed,which had realized multi-function as one of the integrated digital platform,such as the agricultural information management,model parameter calibration,productivity prediction,cultivation strategy evaluation,analysis of time and space,climate model evaluation,climate predictions.This can provide precise and normative decision service for user.