Abstract Deeds J, Amirhbahman A, Norton SA, Bacon LC. 2020. A hydrogeomorphic and condition classification for Maine, USA, lakes. Lake Reserv Manage. 36:122–138. The water quality of lakes is influenced by natural landscape features, anthropogenic watershed activities, and local-scale characteristics of lake basins. Lake assessment for water quality standards is enhanced by a lake classification framework that allows for comparison of lakes of similar types and the creation of benchmark water quality values from reference lakes. Conventional lake classifications, such as those based on trophic state alone, commonly do not incorporate the natural features of the landscape or lake-specific characteristics that influence lake condition. We present a hydrogeomorphic (HGM)-based lake classification, tested with linear mixed effects modeling, to determine which natural features of lakes and their watersheds show the greatest influence on lake condition. A priori classification schemes were created for model testing using combinations of various HGM features. Model strength was evaluated based on ability to predict mean lake total phosphorus and specific conductivity values. Aggregated Level IV Ecoregions stratified by 2 categories of maximum lake depth offered the most robust lake classification. We defined condition classes of reference, intermediate, and altered lakes based on the gradient of developed watershed area that is unique to each lake class. This approach to lake classification has implications for any region or study, as HGM variables relevant to the population of lakes of interest may be tested for efficacy in a variety of schemes to suit the goals of the classification.

中文翻译：

---

美国缅因州湖泊的水文地貌和条件分类

Abstract Deeds J、Amirhbahman A、Norton SA、Bacon LC。2020. 美国缅因州湖泊的水文地貌和条件分类。湖泊保护区管理。36:122-138。湖泊水质受自然景观特征、人为流域活动和湖盆局部尺度特征的影响。湖泊分类框架增强了对水质标准的湖泊评估，该框架允许比较相似类型的湖泊并从参考湖泊中创建基准水质值。传统的湖泊分类，例如仅基于营养状态的分类，通常不包含影响湖泊状况的自然景观特征或湖泊特定特征。我们提出了一种基于水文地貌 (HGM) 的湖泊分类，并通过线性混合效应模型进行了测试，确定湖泊及其流域的哪些自然特征对湖泊状况的影响最大。使用各种 HGM 特征的组合为模型测试创建了先验分类方案。根据预测平均湖泊总磷和特定电导率值的能力评估模型强度。按最大湖泊深度的 2 个类别分层的综合 IV 级生态区提供了最稳健的湖泊分类。我们根据每个湖泊类别所特有的已开发流域面积的梯度，定义了参考湖泊、中间湖泊和蚀变湖泊的条件类别。这种湖泊分类方法对任何地区或研究都有影响，因为与感兴趣的湖泊群体相关的 HGM 变量可能会在各种方案中进行有效性测试，以适应分类目标。