应用DSSAT模型对吉林省黑土玉米最佳栽培技术的模拟和校验研究I.模型品种参数校验和产量的敏感性分析

摘要

目前,应用农业模型去寻找改进农业生态系统的最佳农艺措施被认为是比单一的田间试验更为有效的途径之一.在应用和引进模型当中,一个很关键的环节是确定模型的输入参数对产量和土壤养分的敏感性,因为在一个地区的敏感性并不能保证在其他地区具有同样的影响.正因为如此,本文对农业技术转化决策系统(DSSAT)模型的农业管理参数进行敏感性分析.在吉林省黑土(ollisols)地区,于2008年田间试验条件下进行玉米(Zea mays L.)生长模拟(叶面积指数,地上于物质,籽粒重量),应用当地平均产量和生长期对玉米品种参数进行校验.模拟结果的综合分析表明:玉米提前播种8～10d比正常播种减产大约10%;玉米产量随播种密度呈现抛物线趋势,既当低密度下,产量曲线递增,但是当密度大于5株m-2时,产量增加平缓;产量和氮肥施用量呈典型的效应递减曲线,最佳施氮量为200～240 kg hm-2;最佳追肥时间为6月15日至6月28日.本研究证明DSSAT模型能够用于中国其他地区的玉米生长模拟,并且,本研究建立的敏感性分析方法能够用于其他作物,如水稻和小麦.进一步的研究需要包括测试土壤有机碳氮对作物生长管理参数的敏感性.%It is more efficient to use crop simulation models to evaluate alternative ways to improve agroecosytem performance than experiments only of the biophysical system. A key evaluation process prior to a model' s application is its sensitivity of yield and soil nutrients to input parameters because effects of parameters under one condition may not have the same sensitivity in other location. The purpose of this study was to evaluate and test the sensitivity of the DSSAT v4. 5 to changes in agricultural management parameters. Maize (Zea mays L. ) growth,development and yield was simulated using the DSSAT model in conjunction with a field experiment that was conducted in Northeastern China on a black soil (Mollisols). The cultivar coefficients were obtained using field data and then the sensitivity of the simulated LAI, aboveground biomass and yield to various input parameters was examined. Sowing 8 to 10 days earlier resulted in maize yield reductions of 10％. Yields increased curve-linearly with the increases in plant density in the low to mid range ( ＜ 5 plants m -2 ), and levelled off when the density reached 5 plants m-2. Fertilizer N rate followed a diminishing yield pattern with the maximum yield being obtained at a fertilizer N rate of N 200 ～ 240 kg hm-2. The best fertilizer N application date was 15 - 23 June. This work confirmed that DSSAT model could be a useful simulation tool to be used for simulating maize growth under other regions of China and sensitivity method established in this research could be used for other crops, such as rice and wheat. Sensitivity analysis of soil C and N in response to crop managements is required in future study.