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PREDICTING LAKE ALKALINITY AND DEPTH FOR CLASSIFYING IRISH LAKES UNDER THE EU WATER FRAMEWORK DIRECTIVE TYPOLOGY

机译:根据欧盟水框架指令类型,预测湖泊碱度和深度以对爱尔兰湖泊进行分类

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The EU Water Framework Directive (WFD) typology for Ireland groups lakes based on their altitude, alkalinity, water depth and area. Alkalinity and depth data are, however, lacking for many unmonitored lakes on the Irish WFD programme. In light of legislative requirements to categorise these lakes, we examined relationships between the alkalinity and depth of lakes and the hydrological, morphological and geological characteristics of their catchments. We used a decision-tree learning approach to categorise lakes into their predicted Irish WFD typology categories. We then tested our model predictions using data from an independent set of 62 lakes. Alkalinity type was predicted correctly 87% of the time, with greatest success of classification in the low alkalinity category. The most important variable for predicting water depth was the range of slope within 50m of the lake shore. However, lake depth category was predicted correctly only 54% of the time, and predictions were particularly poor for shallow lakes. This latter model is therefore not proposed for use in typology assignment for WFD purposes. Our predictions allowed WFD alkalinity category to be assigned for 790 lakes on the Irish WFD programme and provide insights into relationships between catchment hydrological, morphological and geological characteristics and in-lake conditions in Ireland.
机译:针对爱尔兰的欧盟水框架指令(WFD)类型根据湖泊的高度,碱度,水深和面积对湖泊进行分组。但是,爱尔兰WFD计划缺少许多未监测湖泊的碱度和深度数据。根据对这些湖泊进行分类的法律要求,我们研究了湖泊的碱度和深度与其流域的水文,形态和地质特征之间的关系。我们使用决策树学习方法将湖泊归类为预测的爱尔兰WFD类型学类别。然后,我们使用来自62个独立湖泊的数据测试了模型预测。正确预测了碱度类型的使用率达87%,在低碱度类别中的分类成功最大。预测水深的最重要变量是距湖岸50m以内的坡度范围。但是,只有54%的时间正确预测了湖泊深度类别,而对于浅水湖泊的预测特别差。因此,不建议将后一种模型用于WFD目的的类型分配中。我们的预测允许在爱尔兰WFD计划中为790个湖泊指定WFD碱度类别,并提供有关爱尔兰集水区水文,形态和地质特征与湖内条件之间关系的见解。

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