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Value of historical climate knowledge, SOI-based seasonal climate forecasting and stored soil moisture at sowing in crop nitrogen management in south eastern Australia

机译:历史气候知识,基于SOI的季节性气候预测以及播种时土壤水分在澳大利亚东南部作物氮管理中的价值

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This paper explores the value of using historical climate knowledge, Southern Oscillation Index (SOI) and stored soil moisture at sowing time of wheat and canola crops to manage nitrogen application for increasing economic benefits from crop production and reducing drainage of farming systems at Walbundrie in Southeast Australia. The Agricultural Production System Simulator (APSIM) was used to simulate crop production and drainage passing the crop root zone in response to nitrogen application rates from 0 to 300kgNha super(-) super(1)year super(-) super(1) using historical climate records from 1889 to 2002. The skills of SOI phases to forecast growing season rainfall and crop yield were analysed. The impact of nitrogen management based on historical climate knowledge, SOI phases and stored soil moisture was assessed. The results showed that while the optimal N rate for maximum economic return was around 150kgNha super(-) super(1)year super(-) super(1) based on long-term average climatic conditions, it varied significantly from year to year depending on rainfall. Compared with current N application rate of 100kgNha super(-) super(1)year super(-) super(1) in the study region, the optimal N rate of 150kgNha super(-) super(1)year super(-) super(1) derived from historical climate knowledge could lead to an increase of wheat gross margin by AU$74ha super(-) super(1)year super(-) super(1). The April to May SOI phases were useful predictors of growing season rainfall and grain yield of wheat and canola crops. The optimal N rates were 100, 150, 200kgNha super(-) super(1)year super(-) super(1) in the years when April/May SOI phases were fallingegative, near zero, and rising/positive, respectively. Based on such management, wheat gross margin was only increased by 2%, 0%, and 1%, respectively, corresponding to a mean increase in gross margin of AU$6ha super(-) super(1), compared with N management at the optimal fixed N rate of 150kgNha super(-) super(1)year super(-) super(1). Stored soil water at sowing time (SSMS) showed positive correlation with crop yield. However, combining April/May SOI phases and SSMS to manage N application only increased wheat gross margin by AU$8.8ha super(-) super(1), and reduced deep drainage by 1.7mmyear super(-) super(1) for wheat, compared with N management based historical climate knowledge. Similar results were obtained for a continuous canola cropping system.
机译:本文探讨了利用历史气候知识,南方涛动指数(SOI)和小麦和油菜籽播种时储存的土壤水分来管理氮肥的应用的价值,以增加作物生产的经济效益并减少东南部Walbundrie的农业系统的排水澳大利亚。农业生产系统模拟器(APSIM)用于模拟从0到300kgNha的氮肥施用量,通过历史的作物生产和通过作物根区的排水使用历史数据记录了1889年至2002年的气候记录。分析了SOI阶段预测生长季节降雨量和农作物产量的技能。基于历史气候知识,SOI阶段和存储的土壤水分,评估了氮管理的影响。结果表明,基于长期平均气候条件,获得最大经济回报的最佳氮肥率约为150kgNha super(-)super(1)year super(-)super(1),但每年之间差异很大,具体取决于在降雨。与研究区域目前100kgNha super(-)年super(-)super(1)的氮肥施用量相比,最佳150kgNha super(-)年super(-)super(-)超级施氮量(1)根据历史气候知识得出的结果可能会使小麦的毛利率增加AU $ 74ha super(-)super(1)year super(-)super(1)。 SOI的4月至5月阶段是预测小麦和油菜籽生长季节降雨和谷物单产的有用指标。在4月/ 5月SOI阶段分别为下降/负,接近零和上升/正的年份中,最佳N速率分别为100、150、200kgNha super(-)super(1)year super(-)super(1)。 。根据这种管理,与N管理相比,小麦的毛利率仅分别增加了2%,0%和1%,相当于AU $ 6ha super(-)super(1)的平均毛利率增加。 150kgNha super(-)super(1)year super(-)super(1)的最佳固定氮比率。播种期土壤水分与农作物产量呈正相关。但是,将四月/五月SOI阶段和SSMS结合起来管理氮肥施用,只会使小麦的毛利润增加8.8澳元/公顷super(-)super(1),而小麦的深层排水却减少1.7mmyear super(-)super(1),与基于N管理的历史气候知识相比。连续油菜种植系统获得了相似的结果。

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