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Identification and testing of early indicators for N leaching from urine patches

机译:尿液中氮浸出的早期指标的鉴定和测试

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Nitrogen leaching from urine patches has been identified as a major source of nitrogen loss under intensive grazing dairy farming. Leaching is notoriously variable, influenced by management, soil type, year-to-year variation in climate and timing and rate of urine depositions. To identify early indicators for the risk of N leaching from urine patches for potential usage in a precision management system, we used the simulation model APSIM (Agricultural Production Systems SIMulator) to produce an extensive N leaching dataset for the Waikato region of New Zealand. In total, nearly forty thousand simulation runs with different combinations of soil type and urine deposition times, in 33 different years, were done. The risk forecasting indicators were chosen based on their practicality: being readily measured on farm (soil water content, temperature and pasture growth) or that could be centrally supplied to farms (such as actual and forecast weather data). The thresholds of the early indicators that are used to forecast a period for high risk of N leaching were determined via classification and regression tree analysis. The most informative factors were soil temperature, pasture dry matter production, and average soil water content in the top soil over the two weeks prior to the urine N application event. Rainfall and air temperature for the two weeks following urine deposition were also important to fine-tune the predictions. The identified early indicators were then tested for their potential to predict the risk of N leaching in two typical soils from the Waikato region in New Zealand. The accuracy of the predictions varied with the number of indicators, the soil type and the risk level, and the number of correct predictions ranged from about 45 to over 90%. Further expansion and fine-tuning of the indicators and the development of a practical N risk tool based on these indicators is needed.
机译:在集约化放牧的奶牛场中,尿液中的氮浸出已被确定为氮损失的主要来源。众所周知,浸出是可变的,受管理,土壤类型,气候,尿液沉积时间和时间以及速率逐年变化的影响。为了确定从尿片中浸出N的风险的早期指标,以在精密管理系统中潜在使用,我们使用模拟模型APSIM(农业生产系统模拟器)为新西兰怀卡托地区产生了广泛的N浸出数据集。在总共33个不同的年份中,总共进行了近4万次模拟实验,模拟了土壤类型和尿液沉积时间的不同组合。风险预测指标是根据其实用性选择的:可以在农场上轻松测量(土壤含水量,温度和牧草生长),也可以集中提供给农场(例如实际和天气预报数据)。通过分类和回归树分析确定了用于预测氮淋溶高风险期的早期指标的阈值。信息量最大的因素是土壤温度,牧草干物质生产以及尿素氮施用事件前两周内表层土壤的平均土壤含水量。尿液沉积后两周的降雨和气温对于调整预测值也很重要。然后测试确定的早期指标,以预测其在新西兰怀卡托地区的两种典型土壤中浸出氮的风险。预测的准确性随指标的数量,土壤类型和风险水平的不同而变化,正确的预测的数量范围从大约45%到90%以上。需要进一步扩展和微调指标,并根据这些指标开发实用的N风险工具。

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