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SENSITIVITY ANALYSIS OF THE VIRGINIA PHOSPHORUS INDEX MANAGEMENT TOOL

机译:弗吉尼亚磷指数管理工具的敏感性分析

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The phosphorus index (P-Index) is a risk assessment and management tool to aid in reducing the risk to water quality due to movement of excess phosphorus (P) from fields. An allowable P application rate is specified based on the computed risk. This study focused on the Virginia P-Index. The objectives were to determine the factors to which the P-Index is most sensitive and to determine the factors to which the resulting P application rate recommendations are most sensitive. A differential analysis was used to calculate relative sensitivity for nine baseline scenarios: a low, medium, and high baseline within three different regions of Virginia. Impact of user variability in estimating factor values was evaluated using a probability distribution analysis. The P-Index was most sensitive in the low and medium baseline scenarios to P management factors, including annual application rate, method of fertilizer application, and source availability factor. In high-risk baseline scenarios, the P-Index was most sensitive to transport factors (erosion, runoff, or leaching). User variability had a greater impact on the P-Index and on P application rate recommendations as P risk increased over each of the three regions. The closer a field's P-Index value is to a threshold between P recommendation rate categories, the higher the probability that alternate P application rates will be recommended due to user variability. The results highlight the need for consistent estimation of factor values, particularly the factors to which the P-Index is most sensitive and particularly in the higher-risk situations
机译:磷指数(P-Index)是一种风险评估和管理工具,可帮助减少由于田间过量磷(P)的迁移而对水质造成的风险。根据计算出的风险指定允许的P施用率。这项研究的重点是弗吉尼亚P指数。目的是确定P指数最敏感的因素,并确定所得出的P施用率建议最敏感的因素。差异分析用于计算九种基线情况的相对敏感性:弗吉尼亚州三个不同区域内的低,中和高基线。使用概率分布分析来评估用户可变性对估计因子值的影响。在中低基准情景下,P指数对P管理因素(包括年施用量,施肥方法和源可利用因素)最敏感。在高风险基准情景中,P指数对运输因子(侵蚀,径流或浸出)最敏感。用户可变性对P指数和P施用率建议有更大的影响,因为在这三个区域中每个区域的P风险都在增加。字段的P-Index值越接近P个推荐率类别之间的阈值,由于用户的可变性而推荐替代P个应用率的可能性就越高。结果强调需要对因子值进行一致的估计,尤其是P-Index最敏感的因子,尤其是在高风险情况下

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