Analysis Of Drought Characteristics Of Winter Wheat In Hebei Province Based On Crop Water Deficit Abnormal Index

In the context of the global warming and drying trend,the frequent occurrence of drought events has caused serious impacts on agriculture,water resources,water ecosystems and socio-economic development.As an important agricultural province in China,Hebei Province's agricultural development is crucial to food security in the north and national food security.It is of great significance for the development of agriculture and the development of the entire society and economy to explore the evolutionary laws and causes of changes in agricultural drought.Considering that few previous people have conducted a comprehensive and in-depth analysis of the dynamic evolution process of winter wheat drought in Hebei Province and its climate driving effect,this study selected winter wheat as the main food crop,referring to the national standard agricultural drought assessment index-crop water deficit anomaly index?CWDI?Relevant calculation method,statistical analysis of water demand,precipitation and CWDI spatial and temporal changes in different growth periods of winter wheat in Hebei Province in the past 52 years,and the sensitivity analysis and contribution rate were introduced into the field of agricultural drought to analyze The sensitivity of the factor change,further explore the cause and mechanism of winter wheat drought,through preliminary research,the following conclusions were obtained:?1?In terms of time,the average annual potential evapotranspiration,precipitation,and water demand of winter wheat in Hebei Province from 1967 to 2018 showed a significant decreasing trend,with a change rate of-0.6789mm/a,-0.0128mm/a,-0.916mm/a.Winter wheat needs a large amount of water in the late growth period,but less in the middle period.CWDI is generally greater than zero,with significant time changes?2?The change trend of CWDI in different growth periods is different: the jointing-heading and heading-mature periods show a decreasing trend.The deceleration rate is 0.0447/a,-0.661/a.The sowing-turning-green and turning-joint periods increased significantly.The rate of change is 0.1129/a,0.0049/a;in time,the frequency of "heavy drought" and "extra drought" in winter wheat growth period is higher,and it is more affected by the "extra drought" in the jointing-heading and heading-mature periods.In terms of spatial variation,the occurrence frequency of "heavy drought" and "extra drought" during the sowing-turning-green period is higher in the central and northern regions and lower in the south and southwest regions.In the southeast,the frequency was higher in the northeast of the jointing-heading period,and the high-frequency areas in the heading-maturation period were concentrated in the south and the central and eastern parts.?3?In terms of changes in meteorological factors,the annual average temperature,daily maximum temperature,and daily minimum temperature in Hebei Province from 1967 to 2018 showed a significant upward trend,with change rates of 0.0135?/a,0.0177?/a,and 0.0464?/a,respectively.The average wind speed,sunshine hours,and relative humidity showed a downward trend,and the rates of change were-0.0134m/s,-9.71h/a,and-0.042%/a,respectively.During the growth period of winter wheat,the three temperature indicators showed an increasing trend,and WS,SH,and RH decreased significantly,with a change rate of 0.163ms/a,-0.470h/a,and-0.180%/a.In terms of spatial variation,T_ave,Tmax,and T_min decreased from south to north and from east to west,WS decreased gradually from southeast to northwest,SH decreased gradually from northeast to southwest,and east to central;RH decreased gradually from southeast to northwest.?4?Correlation coefficient analysis shows that the correlation coefficients of T_ave,Tmax,T_min,SH and CWDI are positive,WS and RH coefficients are negative,and the absolute value of the correlation coefficient is SH > RH > Tmax > T_ave> T_min > WS The correlation coefficient between RH and CWDI is negative during the greening-joint period,and the correlation coefficient between T_ave,Tmax,T_min,WS,SH and CWDI is basically positive.The absolute value of the correlation coefficient is WS> T_min> SH> T_ave > RH> T_min;the correlation coefficient between RH and CWDI during the jointing-heading period is negative,the correlation coefficient between other meteorological factors and CWDI is basically positive,and the absolute value of the correlation coefficient is RH> SH> WS> T_ave> Tmax> T_min;the correlation coefficient during heading-mature period is WS > RH> Tmax> SH> T_ave> T_min,where RH is negative and other meteorological factors are basically positive.?5?Sensitivity analysis shows that the sensitivity coefficient of CWDI to T_ave,Tmax and T_min is positive,and the sensitivity coefficient of WS and RH is negative.The sensitivity coefficients of different growth stages are very different: the absolute value of the sensitivity coefficient of CWDI to T_ave is heading-mature> joint-heading> sowing-turning green> turning green-joint;the absolute value of the Tmax sensitivity coefficient is heading-mature> joint-Heading> sowing-turning green> turning green-jointing;the absolute value of the sensitivity coefficient for T_min is jointing-heading> heading-mature> turning green-jointing> sowing-turning green;the absolute value of the sensitivity coefficient for WS is turning green-jointing> jointing-heading> sowing-turning green> heading-maturity;the absolute value of the sensitivity coefficient to SH is jointing-heading> heading-maturity> sowing-turning green> turning green-jointing;the absolute value of RH sensitivity coefficient is jointing-heading> heading-mature> turning green-joint > Sowing-turn green.Contribution rate analysis shows that the dominant factors for CWDI during different growth periods are sowing and returning to green?SH?,returning to green and jointing?WS?,jointing and heading?WS?,and heading and maturity?WS?.