ABSTRACT The optimization and extension of existing gauging networks are a challenging task, which can be done under consideration of many different aspects. One possibility is to maximize the obtained information on regional hydrological characteristics by new gauges compared to existing ones. For this, information theory approaches are most suitable. Here, the principle of maximum entropy is applied to calculate the probability of non-similarity of catchments to determine locations of new gauges according to the catchment characteristics that are most relevant for the hydrological conditions. The realization in an interactive application, provided online, makes use easy for practitioners and scientists. Goodness-of-fit measures are applied to investigate the explanatory power of the model and the contribution of each characteristic to the model, which gives information on the most influential properties of the catchment. The relevance of the proposed approach is proven by comparing hydrological signatures between similar and non-similar catchment.

中文翻译：

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使用最大熵通过附加仪表增加水文网络的信息内容

摘要 现有测量网络的优化和扩展是一项具有挑战性的任务，可以在考虑许多不同方面的情况下完成。一种可能性是与现有测量仪相比，通过新测量仪最大限度地提高获得的区域水文特征信息。为此，信息论方法是最合适的。在这里，最大熵原理被应用于计算流域非相似性的概率，以根据与水文条件最相关的流域特征来确定新仪表的位置。在线提供的交互式应用程序中的实现使从业者和科学家可以轻松使用。应用拟合优度度量来研究模型的解释力和每个特征对模型的贡献，它提供了有关流域最有影响力的特性的信息。通过比较相似和非相似流域之间的水文特征，证明了所提议方法的相关性。