Preprints
https://doi.org/10.5194/essd-2026-725
https://doi.org/10.5194/essd-2026-725
18 Sep 2026
 | 18 Sep 2026
Status: this preprint is currently under review for the journal ESSD.

A long-term multiscale Critical Zone dataset integrating environmental monitoring and an open-air laboratory: The Alento River Catchment Observatory

Nunzio Romano, Harry Vereecken, Heye R. Bogena, Giorgio Cassiani, Matteo Censini, Giovanna Armiento, Marco Proposito, Lorenzo De Silvestri, Eyal Ben Dor, Nicolas Francos, Christian Massari, János Mészáros, Tünde Takáts, Caterina Mazzitelli, Benedetto Sica, Ugo Lazzaro, and Paolo Nasta

Abstract. This paper presents an open-access dataset from the Alento River Catchment (ARC) in southern Italy, a strategic Mediterranean Critical Zone observatory integrating long-term environmental monitoring with an open-air laboratory. Long-term observations of weather variables, streamflow, reservoir water level, groundwater depth, soil water content, and soil matric potential are complemented by targeted field campaigns involving hydrogeophysical surveys, stable water isotope analyses, soil physical and hydraulic measurements, spectral measurements, and high-resolution UAV-based mapping. The principal value of the ARC dataset lies in the coordinated integration of continuous and campaign-based observations across multiple spatial and temporal scales and Critical Zone compartments, providing a basis for linking localized soil and subsurface processes with field- and catchment-scale hydrological responses. Since 2016, the ARC has been a component of the European TERrestrial Environmental Observatories (TERENO) network. The dataset includes both directly measured and derived products, with documented processing procedures, quality-control information, calibration results, and missing-data records. The principal value of the ARC dataset lies in the coordinated integration of continuous and campaign-based observations across multiple spatial and temporal scales and Critical Zone compartments. The combined observations can support the development, calibration, evaluation, and intercomparison of process-based hydrological and Critical Zone models, the evaluation of Earth Observation products, and the investigation of scale-dependent relationships among point-, field-, hillslope-, and catchment-scale observations. The complete dataset is openly accessible through Figshare under a CC BY 4.0 license. (Romano et al., 2026; https://doi.org/10.6084/m9.figshare.31229608).

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Nunzio Romano, Harry Vereecken, Heye R. Bogena, Giorgio Cassiani, Matteo Censini, Giovanna Armiento, Marco Proposito, Lorenzo De Silvestri, Eyal Ben Dor, Nicolas Francos, Christian Massari, János Mészáros, Tünde Takáts, Caterina Mazzitelli, Benedetto Sica, Ugo Lazzaro, and Paolo Nasta

Status: open (until 25 Oct 2026)

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Nunzio Romano, Harry Vereecken, Heye R. Bogena, Giorgio Cassiani, Matteo Censini, Giovanna Armiento, Marco Proposito, Lorenzo De Silvestri, Eyal Ben Dor, Nicolas Francos, Christian Massari, János Mészáros, Tünde Takáts, Caterina Mazzitelli, Benedetto Sica, Ugo Lazzaro, and Paolo Nasta

Data sets

Complete dataset reflecting the spatial and thematic components of the Alento critical zone (CZ) observatory. N. Romano et al. https://doi.org/10.6084/m9.figshare.31229608

Nunzio Romano, Harry Vereecken, Heye R. Bogena, Giorgio Cassiani, Matteo Censini, Giovanna Armiento, Marco Proposito, Lorenzo De Silvestri, Eyal Ben Dor, Nicolas Francos, Christian Massari, János Mészáros, Tünde Takáts, Caterina Mazzitelli, Benedetto Sica, Ugo Lazzaro, and Paolo Nasta
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Latest update: 18 Sep 2026
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Short summary
Understanding how climate and land-use change affect water resources requires observations that connect processes from soils and vegetation to groundwater and streams. The Alento dataset is presented that integrates environmental monitoring with targeted field observations across multiple Critical Zone components and scales. The dataset offers a distinctive resource for studying water storage and movement, evaluating environmental models, and improving understanding of water-limited regions.
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