Quantitative Analysis Of The Causes Of Winter Wheat Yield Changes In Henan Province In The Past 40 Years

In the past nearly 100 years,China’s climate warming rate was significantly higher than the global average,and it has become a significant area affected by climate warming.The most significant warming of the four seasons is winter and spring.As the most significant agriculture affected by climate,climate warming causes changes in agricultural climate resources,which significantly affects the growth and development of crops.Winter wheat is one of the main crops in China,and its growth period spans winter and spring.As a crop affected by climate warming,studying the relationship between winter wheat yield and climate change will help to deepen the understanding of the response model of crop yield and climate change.At the same time,it can be used as a regional demonstration to assess the impact of global climate change on agriculture,and it also provides a theoretical basis for the agricultural sector to formulate scientific and reasonable adaptive measures.Based on the daily meteorological data,ENSO,PDO,sunspots,winter wheat yield and agricultural production conditions data in Henan Province from 1979 to 2018,this paper uses the MK trend test method and wavelet analysis to describe the growth period and main seasons of winter wheat in Henan Province in the past 40 years;use HP filtering method to separate climate yield and combine with cross wavelet transform to analyze the correlation between climate change and climate yield at multiple time scales,and use residual trend method to quantitatively analyze the effects of climate change and human activities on winter wheat yield;Based on the machine learning algorithm,four different simulation output models are constructed,and the optimal model is selected using the average absolute error,the error rate and the root mean square error.The main conclusions are as follows:(1)The increasing trend of precipitation is not significant.The first major periods of the growth period,winter and spring precipitation are 25 a,18a and 28 a respectively.Under the dominance of the first major period,the growth period and winter precipitation will trend to be more after 2018,the precipitation in spring tends to be less.The minimum temperature and spring temperature during the growth period show a significant upward trend.The wavelet analysis results show that the average temperature and maximum temperature during the growth period after 2018 will continue to rise under the dominance of the first main cycle,while the minimum temperature will continue to drop;the winter temperature will still heat up under the dominance of the main cycle.There are obvious upward and downward trends in the sunlight hours in winter and spring,among which the sunlight hours in spring under the dominance of a period of 22 a show a trend of less sunlight hours in spring after2018.The relative humidity during the growth period dropped significantly,and under the dominance of the cycle of 28 a,the relative humidity showed a decrease trend after2018.(2)Climatic yield has 7 cycles in the study interval,and the amplitude of the volatility becomes weaker as the cycle increases,indicating that the impact of climate fluctuations on winter wheat yield is weakening.The cross-wavelet transform results of climate yield,meteorological factors and tele-correlation factors show that the effects of precipitation and temperature during the growth period on climate yield are significantly positively correlated in their respective time domains and frequency domains;winter precipitation and climate yield in the time domain,the significant positive correlation of 2 years turns into a significant negative correlation of 3-4 years,and the significant negative correlation of 10-12 years.The winter temperature and climate yield both show a significant negative correlation of about 3a.Positive correlation.There is a significant negative correlation between relative humidity in winter and climate yield of 2-3 years and 10-12 years;there is a significant positive correlation between sunlight hours in spring and climate yield of 2-4 years and 1-3years,relative humidity in spring and climate yield shows a significant negative correlation of 2 years and 1-3 years;there is a significant negative correlation between ENSO and climate production in the time domain of 1-5 years and a significant positive correlation of 9-11 years;PDO and climate production have a period of 8-11 years from a significant positive correlation to a significant negative correlation;there is a significant negative correlation between sunspots and climate production around 8-12 years.(3)Correlation analysis shows the minimum temperature in spring,relative humidity in spring,sunlight hours in spring,minimum temperature in winter,sunlight hours in winter and sunspots reflecting climate change,and winter wheat sown area,irrigation area,and chemical fertilizer application that reflect human activities as 9main impact factors.The Residual trend analysis calculates the relative contribution rate based on the main influencing factors obtained from the correlation analysis.The result is that climate change increases the yield of winter wheat,with a relative contribution rate of 43.52%.(4)The error rates of the simulation results of the four machine learning models based on the main influencing factors are all less than 5%,indicating that these factors have a significant effect on winter wheat yield.Among them,the random forest model has the best fitting effect than the other three machine learning models,and is completely consistent with the actual output change trend,the RMSE is 41.84,the simulated error rate is only 1.82%,signifies that the prediction is also better,higher accuracy of the model.In addition,according to random forest,the importance of nine main factors affecting winter wheat yield is sorted,and it is found that the importance of chemical fertilizer application is the highest,while the importance of relative humidity in spring is the lowest.The importance of the two is 17.76% and 4.89%respectively.This study quantitatively analyzes the impact of climate change and human activities on winter wheat yield,which will help enrich the research field of agricultural climate change in Henan Province;secondly,this article decomposes climate yield from winter wheat yield to study the volatility and local correlation of winter wheat yield,extending Finally,the establishment of a production model allows relevant departments to predict production based on relevant data,thereby responding to the crisis of possible reduction in grain production in advance and stabilizing grain growth.