the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Jun 2026
Italian Fluvial Sediment Transport Database: A Comprehensive Hub for Archiving and Analyzing Hydrological Data
Abstract. Fluvial sediment transport plays a key role in geomorphological and hydrological processes, influencing river morphology, watershed and coastal sediment balances, and the environmental response to climatic and anthropogenic changes. In Italy, the availability of homogeneous and long-term data is strongly limited due to the discontinuity of monitoring activities and the fragmentation of existing sources. This study presents the development of a relational database and web application specifically designed for the collection, storage, and consultation of sediment transport data, aimed at integrating and enhancing heterogeneous datasets from both historical and contemporary monitoring networks: the Italian Sediment Transport Database (ISTD). The database architecture, developed in PostgreSQL with the PostGIS extension, enables a direct link between observational data and their associated geographical, instrumental, and methodological metadata, ensuring traceability, interoperability, and the possibility to perform multi-temporal analyses. The web interface, built using open-source technologies, allows controlled data entry and interactive data exploration through maps, tables, and export functions. Analysis of the archived datasets highlights strong instrumental, temporal, and spatial heterogeneity: some physical-chemical parameters (e.g., pH and electrical conductivity) show standardized measurement protocols, whereas sediment transport variables exhibit high methodological variability. Time series range from sub-daily to annual observations, with denser coverage in northern Italian basins (e.g., Po, Adige, Piave, Tagliamento) since 1924. Despite these inconsistencies, integration within a unified relational framework enhances the value of a largely underused data heritage. The experience gained through this project enabled the identification of both the limitations and the potential of Italy’s sediment monitoring system, providing operational guidance for methodological standardization, metadata improvement, and data harmonization at the national scale. The ISTD represents a concrete step toward establishing a shared sedimentological archive that supports scientific research, environmental management, and sustainable river basin planning.
- Preprint
(1793 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 31 Jul 2026)
- RC1: 'Comment on essd-2026-157', Michael Nones, 25 Jun 2026 reply
Data sets
Italian Fluvial Sediment Transport Database (version 1.0) M. Luppichini et al. https://doi.org/10.5281/zenodo.18799025
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 29 | 3 | 1 | 33 | 3 | 3 |
- HTML: 29
- PDF: 3
- XML: 1
- Total: 33
- BibTeX: 3
- EndNote: 3
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
The manuscript presents the ISTD, a database of sediment transport measured along Italian rivers. The text reads clearly, and the presented material is very interesting and useful in many applications.
A few comments that I hope will be useful in further developing an already good manuscript:
- lines 94-101: here you address limitations in terms of data connected to total sediment transport. It would be good to see a more extended discussion on the influence of natural and human-driven pressures on suspended and bedload, and on the need for proper, but separated, datasets to actually understand different processes. This might help in further connecting this paragraph to the following one on collecting suspended sediments data in Italy
- l.107-108: can you name these virtuous cases?
- l.143-147: standards on sediment transport data are very much limited, but the sentence “This participatory process enabled the identification of the most effective approaches to standardize data formats and ensure consistency and interoperability across heterogeneous datasets.” sounds a bit too risky, as questions might arise on how “most effective” was evaluated. Did you consider other approaches? What was the rationale behind the process of standardisation? Do you think that different stakeholders might have led to different standards? More details on this would help, especially if other scholars would like to replicate the approach in other regions
- sec. 2.1: in describing the database, it would help knowing a bit more about sustainability (where is the server hosted and how its long-term functioning will be guaranteed, to avoid problems that happened in the past?) and quality control (how are the different roles established? do you have guidelines?). The quality check procedure might be even more important in the case of newly measured data
- before describing the results, it might be good to provide a map of Italy with both rivers and river basins reported in the database. Even if accessible online, such a map could help readers see how monitored rivers are distributed across the country. This might supplement the detail given at lines 386-389
- l.298-303: I fully agree on the need for metadata to obtain reliable and interpretable results, and this loss of details questions the reliability of the data associated with “unknown”. It would help to have some comments on the quality of those data, and their limits of applicability. Authors are encouraged to provide more critical feedback on the database
- is Figure 7 (and the related analysis) influenced by the temporal coverage of the data, for example with old data monitored less frequently?
- l. 372: I would not call it “temporal complementarity” as I see this term too positive, while, in my opinion, the lack of contemporary measurements hinders many analyses. But I leave this point to the authors
- please consider moving Fig. 8 and its description as the first point of sec. 3.1, to first describe where the data were measured, and then what they look like
- please adjust the alignment of the first panel (Watershed with Sediment data) in Fig. 9
- l. 451-452: please explicitly state which EU directives
- l. 487-490: I agree on the need for data quality assurance and documented procedures. But, from your sentence, it is not fully clear how the “rapid visualization and analysis of temporal distribution and data gaps” in your database contributes towards these aspects. I suggest rephrasing this paragraph
- l. 493-495: please check the language
- l.504: this is the first time you spoke about the “data call”. I suggest adding more comments in the Introduction, as readers might get confused
- l.513-519: you presented here a few significant limitations. What are the plans to address them? I suggest integrating this paragraph with the following one, presenting actionable steps and not remaining too vague. Accountability and bureaucracy might also be major obstacles, and authors are encouraged to provide critical comments on this