The ability to characterize hydrologically relevant differences between places is at the core of our science. A common way to quantitatively characterize hydrological catchments is through the use of descriptors that summarize relevant physical aspects of the system, typically by aggregating heterogeneous geospatial information into a single number. Such descriptors capture various facets of catchment functioning and structure, identify similarity or dissimilarity among catchments, and transfer hydrological information to unobserved locations. However, so far there is no agreement on how catchment descriptors should be selected, aggregated, and evaluated. Even worse, little is known about the existence of potential biases in the current practices to characterize catchments. In this systematic review, we analyze 742 research articles published between 1967 and 2021 to provide a categorized overview of current and historical practices of catchment characterization (i.e., data sources, aggregation and evaluation methods) in hydrological science and related disciplines. We uncover the existence of substantial biases in catchment characterization: (1) only 16% of the analyzed studies are in dry environments, even though such environments cover 42% of global land surface, suggesting that most catchment descriptors are tailored to represent energy-limited environments and are potentially less effective in water-limited environments; (2) only 30% of studies use subsurface features for catchment characterization despite the dominance of subsurface flow; (3) only 4% and 9% of descriptors are aggregated in spatially- and vertically-differentiated way, respectively, while the majority of descriptors are simple averages and do not account for hydrologically-relevant variabilities of features within catchments; (4) 25% of all studies analyzed do not evaluate the usefulness of catchment descriptors, and none quantifies their uncertainty. We demonstrate the potential effects of these biases on our ability to effectively characterize catchments and identify functional similarity of catchment behavior with illustrative examples. Finally, we suggest possible ways to derive more robust, comprehensive and hydrologically meaningful catchment descriptors.

中文翻译：

---

流域特征：当前描述、知识差距和未来机遇

描述不同地点之间水文相关差异的能力是我们科学的核心。定量表征水文流域的一种常见方法是使用描述符来总结系统的相关物理方面，通常是将异构地理空间信息聚合为一个数字。这些描述符捕获流域功能和结构的各个方面，识别流域之间的相似性或相异性，并将水文信息传输到未观测的位置。然而，到目前为止，对于如何选择、聚合和评估流域描述符尚未达成一致。更糟糕的是，人们对当前描述流域特征的做法是否存在潜在偏差知之甚少。在这篇系统综述中，我们分析了 1967 年至 2021 年间发表的 742 篇研究文章，对水文科学及相关学科中流域特征描述（即数据源、汇总和评估方法）的当前和历史实践进行了分类概述。我们发现流域特征中存在重大偏差：(1) 只有 16% 的分析研究是在干燥环境中进行的，尽管此类环境覆盖了全球陆地表面的 42%，这表明大多数流域描述符都是为代表能源有限而定制的。环境，并且在水资源有限的环境中可能效果较差； (2) 尽管地下流占主导地位，但只有 30% 的研究使用地下特征来描述流域特征； (3) 只有 4% 和 9% 的描述符分别以空间和垂直差异的方式聚合，而大多数描述符是简单平均值，并且没有考虑流域内特征的水文相关变化； (4) 在所有分析的研究中，25% 没有评估流域描述符的有用性，也没有量化其不确定性。我们通过说明性示例证明了这些偏差对我们有效描述流域特征和识别流域行为功能相似性的能力的潜在影响。最后，我们提出了获得更稳健、更全面和具有水文意义的流域描述符的可能方法。