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首页> 外文期刊>Crop and Pasture Science >Use of the APSIM wheat model to predict yield, drainage, and NO3- leaching for a deep sand
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Use of the APSIM wheat model to predict yield, drainage, and NO3- leaching for a deep sand

机译:使用APSIM小麦模型预测深沙的产量,排水和NO3-淋滤

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High rates of drainage and leaching of nitrates in deep sands in Western Australia are contributing to groundwater recharge and soil acidification in this region. Strategies are being soughtto increase water and nitrogen (N) use in the legume-based cropping systems. Choice of appropriate management strategies is complicated by the diversity of soil types, the range of crops, and the inherent season to season variability. Simulation models provide the means to extrapolate beyond the bounds of experimental data if accurate predictions of key processes can be demonstrated. This paper evaluates the accuracy of predictions of soil water content, evapotranspiration, drainage, inorganic N content insoil, nitrate (NO-3) leaching, wheat growth, N uptake, and grain yields obtained from the Agricultural Production Systems Simulator (APSIM) model when this was initialised with appropriate information on soil properties and wheat varieties commonly grown on deep sands in the 500 mm rainfall zone west of Moora in Western Australia. The model was found to give good predictions of soil water content,evapotranspiration, deep drainage, and overall NO-3 leaching. Temporal changes in inorganic N insoil were simulated, although the small concentrations in soil inorganic N precluded close matching of paired observed and predicted values. Crop growth and N uptake were closely predicted up to anthesis, but a poor fit between observed and predicted crop growth and N uptake was noted postanthesis. Reasons for the discrepancies between modelled and observed values are outlined.nnThe model was run with historical weather data (81 years) and different initial soil water and inorganic soil N profiles to assess the probability of drainage and NO-3 leaching, and the grain yield potentials for wheat grown on deep sands in the region west of Moora. Simulation showed that thesoil water and the soil inorganic N content at the beginning of each season had no effect on grain yield, implying that pre-seed soil NO-3 was largely lost from the soil by leaching. There was a 50% probability that 141 mm of winter rainfall could drain below 1·5 m and a 50% probability that 53 kgN/ha could be leached under wheat following a lupin crop, where initial soil water contents andsoil NO-3 contents used in the model were those measured in a deep sand after late March rainfall. Simulated application of N fertiliser at sowing increased both grain yield and NO-3 leaching. Splitting the N application between the time of sowing and 40 days after sowing decreased NO-3 leaching,increased N uptake by wheat, and increased grain yield, findings which are consistent with agronomic practice.nnThe high drainage and leaching potential of these soils were identified as the main reasons why predicted yields did not approach the French and Schultz potential yield estimates based on 20 kg grain yield per mm of rainfall. When the available water was reduced by simulated drainage, simulated grain yields for the fertilised treatments approached the potential yield line.
机译:西澳大利亚州深层沙子中硝酸盐的高排放和淋洗速率正在促进该地区的地下水补给和土壤酸化。正在寻求策略来增加豆类作物系统中水和氮的使用。适当的管理策略的选择因土壤类型的多样性,农作物的种类以及固有的季节变化而变得复杂。如果可以证明关键过程的准确预测,则仿真模型可以提供超出实验数据范围的推断方法。本文评估了通过农业生产系统模拟器(APSIM)模型获得的土壤水分,蒸散量,排水量,土壤无机氮含量,硝酸盐(NO-3)淋失,小麦生长,氮素吸收和谷物产量的预测准确性。首先用有关土壤性质和小麦品种的适当信息来初始化,这些信息通常生长在西澳大利亚州Moora以西500 mm降雨带的深沙上。发现该模型可以很好地预测土壤含水量,蒸散量,深层排水和整体NO-3淋洗。模拟了无机氮土壤的时间变化,尽管土壤无机氮的浓度较低,无法使成对的观测值和预测值紧密匹配。到花期之前,作物生长和氮素吸收都被紧密预测,但是在开花后,观察到的和预测的作物生长和氮素吸收之间的拟合度很差。概述了模型值与观测值之间差异的原因。nn该模型以历史天气数据(81年)和不同的初始土壤水和无机土壤氮素剖面运行,以评估排水和NO-3淋失的可能性以及谷物产量在莫奥拉以西地区深沙上种植小麦的潜力。模拟表明,每个季节开始时的土壤水分和土壤中的无机氮含量对谷物产量没有影响,这暗示着种子前的土壤NO-3通过淋洗从土壤中大量流失。羽扇豆种植后,小麦下有141%的冬季降雨可能会在1·5 m以下流失,而50%的概率有53 kgN / ha的浸出可能,其中使用了初始土壤水分和土壤NO-3含量模型中的数值是三月下旬降雨后在深沙中测得的数值。播种模拟施用氮肥可以提高谷物产量和NO-3浸出。在播种时间和播种后40天之间分配氮肥,减少了NO-3的淋失,增加了小麦对氮的吸收,增加了谷物的产量,这与农艺学实践是一致的。这是预测的产量未达到法国和Schultz的潜在产量估算的主要原因,该估算基于每毫米降雨量20公斤谷物的产量。当通过模拟排水减少可用水量时,施肥处理的模拟谷物产量接近潜在的产量线。

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