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Construction of a Bayesian Network for the Assessment of Agri-Environmental Measures – The Case Study of the Venice Lagoon Watershed

机译:评估农业环境措施的贝叶斯网络的建设-以威尼斯泻湖流域为例

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A methodological framework was designed to assess the effectiveness of agri-environmental policy measures adopted by the Veneto Region to reduce diffuse water pollution of agricultural origin. Two already existing methodologies were combined in a new flexible approach for policy assessment: Conceptual Modelling and Bayesian Networks (BNs). The former supported the development of a shared conceptual model (a cognitive map) of the agro-ecosystem of the study area; while the latter allowed the development of a probabilistic model coherent with the cognitive map. BNs were selected because they allow analyses with scarce data; they can be updated when further information becomes available, and are easily understandable by layperson. The paper reports the results obtained in the Venice Lagoon Watershed (VLW) case study, where the current agri-environmental measures were assessed in order to identify their effectiveness in terms of reduction of nitrogen releases in water bodies connected to the lagoon ecosystem. Preliminary results obtained by implementing expert opinions in the BN pointed out the likely limited effects of the measures on the declared objective of
机译:设计了一种方法框架,以评估威尼托大区为减少农业起源的弥漫性水污染而采取的农业环境政策措施的有效性。在一种灵活的新政策评估方法中,将两种已经存在的方法结合在一起:概念建模和贝叶斯网络(BNs)。前者支持研究区域农业生态系统共享概念模型(认知图)的开发。后者允许开发与认知图一致的概率模型。选择BN是因为它们允许使用稀有数据进行分析;当有更多信息可用时,可以对其进行更新,并且通俗易懂。该论文报告了在威尼斯泻湖流域(VLW)案例研究中获得的结果,该案例研究对当前的农业环境措施进行了评估,以便确定它们在减少与泻湖生态系统相关的水体中氮释放方面的有效性。在国阵中执行专家意见所获得的初步结果指出,这些措施可能对有限的既定目标产生有限的影响

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