Abstract. Here we present FOCA (Italian FlOod and Catchment Atlas), the first systematic collection of data on Italian river catchments for which historical discharge time series are available. Hydrometric information, including the annual maximum peak discharge and average daily annual maximum discharge, is complemented by several geomorphological, climatological, extreme rainfall, land-cover and soil-related catchment attributes. All hydrological information derives from the most recently released datasets of discharge and rainfall measurements. To enhance the reproducibility and transferability of the analysis, this paper provides a description of all the raw data and the algorithms used to build the basin attribute dataset. We also describe the approaches adopted to solve problems encountered during the digital elevation model elaboration in areas characterized by a complex morphology. Details about the data quality-control procedure developed to detect and correct errors are also reported. One of the main novelties of FOCA with respect to other national-scale datasets is the inclusion of a rich set of geomorphological attributes and extreme rainfall features for a large set of basins covering a wide range of elevations and areas. Using this first nationwide data collection (available at https://doi.org/10.5281/zenodo.10446258, Claps et al., 2023), a wide range of environmental applications, with a particular focus on flood studies, can be undertaken within the Italian territory.

中文翻译：

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FOCA：意大利洪水和流域描述符的新质量控制数据库

摘要。在这里，我们介绍 FOCA（意大利洪水和流域地图集），这是第一个关于意大利河流流域数据的系统收集，其中有历史流量时间序列。水文测量信息，包括年度最大峰值流量和年平均每日最大流量，由多种地貌、气候、极端降雨、土地覆盖和土壤相关流域属性进行补充。所有水文信息均来自最新发布的流量和降雨测量数据集。为了增强分析的再现性和可转移性，本文提供了所有原始数据和用于构建流域属性数据集的算法的描述。我们还描述了解决在复杂形态特征区域的数字高程模型精细化过程中遇到的问题所采用的方法。还报告了有关为检测和纠正错误而开发的数据质量控制程序的详细信息。与其他国家尺度数据集相比，FOCA 的主要新颖之处之一是包含了覆盖广泛海拔和区域的大量盆地的丰富地貌属性和极端降雨特征。使用第一个全国性数据收集（可在 https://doi.org/10.5281/zenodo.10446258，Claps 等人，2023 年获取），可以在以下范围内开展广泛的环境应用，特别是洪水研究。意大利领土。