Comprehensive Dataset Report on Large Dams in Italy and the Characteristics of Their Upstream Catchment Areas

List of Key Chapter Titles

1. Introduction
2. Classification, Types, and Uses of Large Dams in Italy
3. Structural Characteristics of Dams
4. Geomorphological and Climatic Characteristics of the Upstream Catchment Areas
5. 1 Catchment Attributes
6. 2.1 Geomorphological Attributes
7. 2.2 Soil, Land Cover, and NDVI Attributes
8. 2.3 Climatic Attributes
9. 2.4 Extreme Rainfall Attributes
10. Interaction Between Infrastructure and Upstream Catchment Areas
11. Data Availability
12. Conclusion

Document Introduction

This report addresses a long-standing critical data gap in Italy by systematically constructing and releasing for the first time a comprehensive national dataset covering all 528 large dams under the jurisdiction of the Italian General Directorate for Dams and their upstream catchment areas. Currently, global and European-scale dam databases (such as GOODD, GRanD, GDW, the AMBER project dataset, etc.) have insufficient coverage for Italy and generally lack key characteristics describing the hydrological response of upstream basins. Existing domestic resources in Italy (e.g., the digital map from the General Directorate for Dams, ISPRA reports) also tend to focus on the structural information of the dams themselves, overlooking crucial attributes of the catchment areas—such as geomorphology, climate, land cover, and soil—that are vital for flood formation. This study aims to provide an integrated resource combining dam structural information with the natural characteristics of the watersheds, to support refined hydrological research, flood risk assessment, and water resource management decision-making.

The core content of this dataset consists of two main modules: dam structural attributes and upstream catchment characteristics. The dam attributes section integrates data from official sources, including for each dam: name, geographic coordinates, construction start and end years, primary functions (e.g., power generation, irrigation, flood control, water supply), operational status, construction type (e.g., gravity dam, arch dam, embankment dam, weir, etc.), dam height, reservoir storage capacity, reservoir surface area, allowable maximum water level elevation, and spillway crest elevation. Among these, reservoir surface area and allowable maximum water level elevation are significant incremental information in this dataset compared to other global or national datasets, crucial for accurately estimating a reservoir's flood attenuation capacity.

The upstream catchment characteristics section is another major contribution of this study. Based on the 30-meter resolution SRTM digital elevation model, the research team used GIS tools (e.g., r.basin) to automatically delineate the upstream watershed for each dam, with manual corrections applied only to a few topographically complex basins (e.g., the Panaro Dam and Lago Pusiano upstream areas). For these 523 valid watersheds, four major categories of attributes were calculated and integrated: Geomorphological attributes (e.g., area, mean elevation, mean slope, Horton's stream order ratio, main channel length, shape factor, etc.); Soil and Land Cover attributes (including saturated hydraulic conductivity based on soil texture, proportions of five land cover classes based on CORINE land cover data, and long-term statistical Normalized Difference Vegetation Index (NDVI) with its spatiotemporal variation characteristics); Climatic attributes (based on monthly average precipitation and temperature data extracted from the BIGBANG 4.0 dataset, calculating annual average precipitation/temperature, Fourier coefficients for the annual cycle of precipitation/temperature, precipitation variability, etc.); and Extreme Rainfall attributes (based on an improved Italian extreme rainfall dataset, obtaining watershed-average Intensity-Duration-Frequency curve parameters 'a' and 'n', and L-moment statistics through spatial interpolation). These attributes are consistent with the Italian catchment characteristics database (FOCA) previously built by the author's team, significantly expanding the number of watersheds in Italy with high-information-density characteristic descriptions.

This report not only provides the raw data but also conducts preliminary analysis based on the dataset, exploring the interaction between dams and their upstream watersheds, particularly their potential role in flood mitigation. The report analyzes the distribution of qualitative indicators such as the reservoir-to-watershed area ratio and storage-to-watershed area ratio among Italian dams. For the first time, it quantitatively calculates the potential storage volume available for flood control for each dam based on the elevation difference (ΔH) between the allowable maximum water level and the spillway crest. The analysis reveals that approximately 50% of Italian dams (with a reservoir/watershed area ratio less than 1/150) likely have minimal spontaneous flood attenuation effect. Furthermore, the empirical distribution of ΔH values shows that 75% of dams have a ΔH of less than 2 meters, which limits the operational space for effective flood control while maintaining their primary functions of power generation or irrigation.

This dataset is publicly available through the Zenodo platform and aims to serve as an authoritative foundational resource for researchers, policymakers, dam operators, and stakeholders engaged in water resource planning, flood risk management, climate change impact assessment, and hydrological model calibration. It represents the most comprehensive integrated information repository on dams and watersheds in Italy to date, establishing a solid data foundation for systematic hydrological and engineering research from the national to the watershed scale.