Stefano Ferraris

2.9k total citations
61 papers, 1.2k citations indexed

About

Stefano Ferraris is a scholar working on Environmental Engineering, Civil and Structural Engineering and Atmospheric Science. According to data from OpenAlex, Stefano Ferraris has authored 61 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Environmental Engineering, 18 papers in Civil and Structural Engineering and 16 papers in Atmospheric Science. Recurrent topics in Stefano Ferraris's work include Soil and Unsaturated Flow (17 papers), Soil Moisture and Remote Sensing (14 papers) and Hydrology and Watershed Management Studies (13 papers). Stefano Ferraris is often cited by papers focused on Soil and Unsaturated Flow (17 papers), Soil Moisture and Remote Sensing (14 papers) and Hydrology and Watershed Management Studies (13 papers). Stefano Ferraris collaborates with scholars based in Italy, United Kingdom and Ethiopia. Stefano Ferraris's co-authors include Marcella Biddoccu, Eugenio Cavallo, Gianmarco Manzini, Davide Canone, Francesca Opsi, Andrea Pitacco, Mario Putti, Riccardo Scalenghe, Pietro Teatini and Matteo Camporese and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Water Resources Research.

In The Last Decade

Stefano Ferraris

60 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Stefano Ferraris Italy 20 391 344 283 218 206 61 1.2k
Teferi Tsegaye United States 15 235 0.6× 529 1.5× 235 0.8× 145 0.7× 159 0.8× 43 1.0k
Yunwu Xiong China 20 669 1.7× 298 0.9× 309 1.1× 158 0.7× 266 1.3× 52 1.4k
Patrick Andrieux France 17 433 1.1× 278 0.8× 143 0.5× 256 1.2× 229 1.1× 37 1.1k
Antonino Maltese Italy 17 173 0.4× 369 1.1× 118 0.4× 257 1.2× 328 1.6× 84 1.0k
Bruno Cheviron France 17 352 0.9× 633 1.8× 116 0.4× 234 1.1× 138 0.7× 47 1.1k
J. M. Blonquist United States 13 160 0.4× 597 1.7× 335 1.2× 147 0.7× 311 1.5× 20 1.2k
Paolo Nasta Italy 21 321 0.8× 569 1.7× 419 1.5× 111 0.5× 240 1.2× 66 1.1k
Ebrahim Babaeian United States 16 192 0.5× 1.0k 3.0× 302 1.1× 266 1.2× 300 1.5× 25 1.4k
Didier Michot France 17 378 1.0× 551 1.6× 220 0.8× 145 0.7× 96 0.5× 41 1.1k
D. King France 17 635 1.6× 634 1.8× 247 0.9× 325 1.5× 159 0.8× 28 1.5k

Countries citing papers authored by Stefano Ferraris

Since Specialization
Citations

This map shows the geographic impact of Stefano Ferraris's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stefano Ferraris with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefano Ferraris more than expected).

Fields of papers citing papers by Stefano Ferraris

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stefano Ferraris. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stefano Ferraris. The network helps show where Stefano Ferraris may publish in the future.

Co-authorship network of co-authors of Stefano Ferraris

This figure shows the co-authorship network connecting the top 25 collaborators of Stefano Ferraris. A scholar is included among the top collaborators of Stefano Ferraris based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stefano Ferraris. Stefano Ferraris is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Nardo, Elvira Di, et al.. (2025). Hyperparameter optimization of machine learning models for predicting actual evapotranspiration. Machine Learning with Applications. 20. 100661–100661. 1 indexed citations
2.
Fedotov, Sergei, et al.. (2024). Stochastic model for subsurface water flow in Swiss catchments. Advances in Water Resources. 196. 104883–104883.
3.
Nardo, Elvira Di, et al.. (2024). Identifying time patterns of highland and lowland air temperature trends in Italy and the UK across monthly and annual scales. SHILAP Revista de lepidopterología. 10(2). 173–194. 1 indexed citations
4.
5.
Meo, Rosa, et al.. (2024). Analysis of Diurnal Air Temperature Trends and Pattern Similarities in Highland and Lowland Stations of Italy and UK. International Journal of Climatology. 44(15). 5398–5417. 3 indexed citations
6.
Ferraris, Stefano, et al.. (2023). Machine Learning as a Strategic Tool for Helping Cocoa Farmers in Côte D’Ivoire. Sensors. 23(17). 7632–7632. 3 indexed citations
7.
Palazzi, Elisa, Jost von Hardenberg, Gianna Vivaldo, et al.. (2022). Aquifer recharge in the Piedmont Alpine zone: historical trends and future scenarios. Hydrology and earth system sciences. 26(2). 407–427. 7 indexed citations
8.
9.
Canone, Davide, et al.. (2019). Thorough wetting and drainage of a peat lysimeter in a climate change scenario. Hydrological Processes. 34(5). 1269–1284. 2 indexed citations
10.
Capello, Giorgio, Marcella Biddoccu, Stefano Ferraris, Andrea Pitacco, & Eugenio Cavallo. (2017). Year-round variability of field-saturated hydraulic conductivity and runoff in tilled and grassed vineyards. SHILAP Revista de lepidopterología. 58. 739–744. 6 indexed citations
11.
Mitterer, Christoph, et al.. (2017). The role of soil volumetric liquid water content during snow gliding processes. Cold Regions Science and Technology. 136. 17–29. 21 indexed citations
12.
Brocca, Luca, Angelica Tarpanelli, Tommaso Moramarco, et al.. (2013). Soil Moisture Estimation in Alpine Catchments through Modeling and Satellite Observations. Vadose Zone Journal. 12(3). 1–10. 27 indexed citations
13.
Freppaz, Michele, et al.. (2012). A Characterization of Snow Gliding and Potential Predisposing Factors in a Full-Depth Slab Avalanche Release Area (Valle d’Aosta, NW Italian Alps). 561–568. 6 indexed citations
14.
Cremonese, Edoardo, F. Diotri, Stefano Ferraris, et al.. (2009). Innovative devices for the SWE estimation at the basin scale: a field study in the Western Alps.. PORTO Publications Open Repository TOrino (Politecnico di Torino). 175–179. 1 indexed citations
15.
Cassiani, Giorgio, et al.. (2009). Time-lapse surface-to-surface GPR measurements to monitor a controlled infiltration experiment. Research Padua Archive (University of Padua). 11 indexed citations
16.
Scalenghe, Riccardo & Stefano Ferraris. (2009). The First Forty Years of a Technosol. Pedosphere. 19(1). 40–52. 45 indexed citations
17.
Ferraris, Stefano, et al.. (2008). Methodology for calculating equivalent field scale soil hydraulic system parameters taking into account hysteresis. The EGU General Assembly. 10. 1 indexed citations
18.
Godio, Alberto & Stefano Ferraris. (2005). Time lapse geophysics for monitoring an infiltration test in the vadose zone. PORTO Publications Open Repository TOrino (Politecnico di Torino). 46. 201–216. 5 indexed citations
19.
Putti, Mario, et al.. (2003). Monitoring of hydrological parameters related to peat oxidation in a subsiding coastal basin south of Venice, Italy. IAHS-AISH publication. 458–462. 6 indexed citations
20.
Paniconi, Claudio, Stefano Ferraris, Mario Putti, Giorgio Pini, & Giuseppe Gambolati. (1970). Invited Paper Three-dimensional Numerical Codes For Simulating Groundwater Contamination: FLOW3D, Flow In Saturated And Unsaturated Porous Media. WIT Transactions on Ecology and the Environment. 5. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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