Study Of Response Mechanism And Simulation Of Winter Wheat Phenology To Soil Water Stress

Crop growth simulation models have played an important role in agricultural planning and management. The simulation of crop phenology is the basis of correct simulation of growth and development processes in crop models. Calculation of accumulative thermal time is a common way of simulating crop phonological development in crop models, while the effects of photoperiod and vernalization were also considered. However, the response of crop phenology to soil water stress is rarely quantified and often neglected. The main objective of this study was to explore and quantify the mechanism of phenology response of winter wheat(Triticum aestivum L.) to soil water stress. Experiments were conducted in plastic columns under a rainout shelter for winter wheats growing under water stresses at different growth stages in two seasons(October 2013 to June 2014, October 2014 to June 2015). Four different water deficit periods and two irrigation levels were involved.The water deficit periodswere wintering(D1), greening(D2), jointing(D3), and grain filling(D4) stage; irrigation levels included 45 mm(I1) and 90 mm(I2) at each event. In addition, there wasa control treatment(CK) with 90-mm irrigation at all four growth stages and a no-irrigation treatment(D). Thus, there were a total of 10 treatments with three replicates for each. In this study, relative water availability(Aw) was chosen as water stress indexto establish response function of winter wheat to water stress. Then the algorithm for prediction of winter wheat phenology was modified with the response function above, with an expectation that this new algorithm can reflect the differences in the dates of jointing, anthesis, and maturity of winter wheat, which were caused by soil water stresses. Some main conclusions were drawn as follows.(1) Water stressesat greening and jointing stages could dramatically inhibit plant height, leaf area index, and aboveground biomass of winter wheat.When water stress was more severe, the inhibition effects were more serious for plant height, leaf area index, and aboveground biomass. Water Stress at grain filling stage had little effect on above-ground biomass, but leaf area index decayed fastest. Water stress at wintering stage had little influence on yield,but water stress at jointing stage could reduce grain yield seriously. The number of kernels per spike reduced under water stress at greening stage.Water stressesat different stages all could influence the 1000-kernel weight, but water stress at grain filling reduced the most.(2) This study first proposed a more complete assumption for the response mechanism of winter wheat phenology to soil water stress.When the value of relative water availability(Aw) was below a certain value ofA(defined as the critical point of accelerating development), crop plants began to hasten development, while there was no effect on crop phonological developmentwhen above A. When Awwas below a certain value ofS(defined as the critical point of ceasing development), crop development stopped. Thus, it was reasonable to hypothesize that there existed a certain value ofD(defined as the critical point of decelerating development) between pointsA and S. Thus, Awwould hasten crop development between AD and delay development between DS. Whensoil water stress did not affect crop phonological development, the value of water modification factor(WMF) wasset as 1; when accelerating crop development, WMF was greater than 1; and when decelerating development, WMF was smaller than 1. Then, modified physiological day(MPD)was computed trough multiplying WMF withcalculated physiological day(PD) with temperature and photoperiod response functions. The values of MPD were used to quantify the phenology response of winter wheat to soil water stress.(3) Water modification factor(WMF) included three parameters, namely the value of relative water availabilityat the critical point of accelerating development, critical point of decelerating development, and point of ceasing development corresponding.The estimated values of Awat points A, D, and S were 0.30, 0.10, and 0.00, respectively.However,these three parameters may have different valuesfor other crops, which need to be estimated in further research.(4)The experimental data of 2014-2015 growing season were used to calibrate thephenology water stress response function. The estimated values of relative water availability of points A, D, and S were 0.30, 0.10, and 0.00, respectively. The root mean square error(RMSE) between simulated and observed jointing and flowering dates were 0.8 d and 1.7 d; the values of absolute relative error(ARE) were below 0.7% and 2.1%, respectively. When verifying thenew algorithm for prediction of winter wheat phenology, the RMSE between simulated and observed jointing and flowering dateswere 0.9 d and 1.1 d and ARE were less than 1.4% and 1.7%, respectively.In general, the phenology water stress response function developed in this studycouldaccurately simulate the differences in phenological datesof different winter wheat varieties, which werecaused by different scenarios of soil water stress.This response function needs to be evaluated further in more field experiments and then be embedded in current popular crop models, such as DSSAT-CERES-Wheat, to improve their simulation accuracy of phenology under water stress conditions. Consequently, modified crop models are supposed to have a better accuracy and applicabilityin arid and semi-arid areas in China.