Leonardo Alfonso

1.7k total citations
59 papers, 1.1k citations indexed

About

Leonardo Alfonso is a scholar working on Water Science and Technology, Global and Planetary Change and Civil and Structural Engineering. According to data from OpenAlex, Leonardo Alfonso has authored 59 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Water Science and Technology, 26 papers in Global and Planetary Change and 18 papers in Civil and Structural Engineering. Recurrent topics in Leonardo Alfonso's work include Flood Risk Assessment and Management (24 papers), Hydrology and Watershed Management Studies (23 papers) and Water Systems and Optimization (17 papers). Leonardo Alfonso is often cited by papers focused on Flood Risk Assessment and Management (24 papers), Hydrology and Watershed Management Studies (23 papers) and Water Systems and Optimization (17 papers). Leonardo Alfonso collaborates with scholars based in Netherlands, Italy and Sweden. Leonardo Alfonso's co-authors include Roland K. Price, Dimitri Solomatine, Arnold H. Lobbrecht, Maurizio Mazzoleni, Giuliano Di Baldassarre, Elena Ridolfi, Andréja Jonoski, Cristiana Di Cristo, Angelo Leopardi and Micah Mukolwe and has published in prestigious journals such as The Science of The Total Environment, Water Research and Water Resources Research.

In The Last Decade

Leonardo Alfonso

56 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
Leonardo Alfonso Netherlands 21 539 506 375 301 251 59 1.1k
Christopher Hutton United Kingdom 14 640 1.2× 496 1.0× 225 0.6× 251 0.8× 180 0.7× 26 1.0k
Muhammad A. Al-Zahrani Saudi Arabia 19 470 0.9× 384 0.8× 297 0.8× 205 0.7× 208 0.8× 40 1.1k
Mohsen Nasseri Iran 21 560 1.0× 745 1.5× 533 1.4× 159 0.5× 351 1.4× 102 1.5k
Yousef Hassanzadeh Iran 19 445 0.8× 561 1.1× 393 1.0× 201 0.7× 93 0.4× 59 1.3k
Jafar Yazdi Iran 25 546 1.0× 578 1.1× 503 1.3× 423 1.4× 69 0.3× 69 1.3k
João P. Leitão Switzerland 25 660 1.2× 1.2k 2.3× 839 2.2× 351 1.2× 346 1.4× 84 1.8k
S. Adarsh India 22 345 0.6× 769 1.5× 481 1.3× 148 0.5× 208 0.8× 141 1.4k
Mohd. Ahmed Saudi Arabia 20 333 0.6× 553 1.1× 550 1.5× 351 1.2× 96 0.4× 82 1.4k
Philippe Gourbesville France 20 580 1.1× 800 1.6× 311 0.8× 158 0.5× 249 1.0× 80 1.2k
Davar Khalili Iran 24 554 1.0× 1.0k 2.0× 295 0.8× 129 0.4× 228 0.9× 57 1.5k

Countries citing papers authored by Leonardo Alfonso

Since Specialization
Citations

This map shows the geographic impact of Leonardo Alfonso'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 Leonardo Alfonso with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonardo Alfonso more than expected).

Fields of papers citing papers by Leonardo Alfonso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leonardo Alfonso. 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 Leonardo Alfonso. The network helps show where Leonardo Alfonso may publish in the future.

Co-authorship network of co-authors of Leonardo Alfonso

This figure shows the co-authorship network connecting the top 25 collaborators of Leonardo Alfonso. A scholar is included among the top collaborators of Leonardo Alfonso 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 Leonardo Alfonso. Leonardo Alfonso 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.
Shu, Kai, et al.. (2025). Prediction of natural runoff in China based on multi-scenario climate models with self-attention neural networks. Water Research. 282. 123768–123768. 1 indexed citations
2.
Alfonso, Leonardo, et al.. (2024). Towards integrating community and institutional flood early warning systems: A framework applied to an Andean tropical case. International Journal of Disaster Risk Reduction. 116. 105126–105126. 1 indexed citations
3.
4.
Chen, Kan, Xiaofei Shi, Zhihao Zhang, et al.. (2024). Using unsupervised learning to classify inlet water for more stable design of water reuse in industrial parks. Water Science & Technology. 89(7). 1757–1770. 2 indexed citations
5.
Jiang, Jiping, Leonardo Alfonso, Ruiyi Yang, et al.. (2023). Deriving analytical expressions of the spatial information entropy index on riverine water quality dynamics. Journal of Hydrology. 623. 129806–129806. 6 indexed citations
6.
Alfonso, Leonardo, et al.. (2023). Locating Multiple Leaks in Water Distribution Networks Combining Physically Based and Data-Driven Models and High-Performance Computing. Journal of Water Resources Planning and Management. 149(12). 3 indexed citations
7.
Mazzoleni, Maurizio, et al.. (2020). Unravelling the influence of human behaviour on reducing casualties during flood evacuation. Hydrological Sciences Journal. 65(14). 2359–2375. 33 indexed citations
8.
Comes, Tina, et al.. (2018). Information Sharing and Coordination in Collaborative Flood Warning and Response Systems. Journal of the Association for Information Systems. 1 indexed citations
9.
Mazzoleni, Maurizio, Uta Wehn, Leonardo Alfonso, et al.. (2018). Exploring the influence of citizen involvement on the assimilation of crowdsourced observations: a modelling study based on the 2013 flood event in the Bacchiglione catchment (Italy). Hydrology and earth system sciences. 22(1). 391–416. 27 indexed citations
10.
Solomatine, Dimitri, et al.. (2017). Towards socio-hydroinformatics: optimal design and integration of citizen-based information in water-system models. EGUGA. 12370. 1 indexed citations
11.
Alfonso, Leonardo, et al.. (2017). Dimensioning of precipitation citizen observatories in an uncertainty-aware context. EGU General Assembly Conference Abstracts. 18523. 2 indexed citations
12.
Mazzoleni, Maurizio, Uta Wehn, Leonardo Alfonso, et al.. (2017). Towards assimilation of crowdsourced observations for different levels of citizen engagement: the flood event of 2013 in the Bacchiglione catchment. University of Twente Research Information. 5 indexed citations
13.
Alfonso, Leonardo, et al.. (2017). Rainfall and streamflow sensor network design: a review of applications, classification, and a proposed framework. Hydrology and earth system sciences. 21(6). 3071–3091. 72 indexed citations
14.
Alfonso, Leonardo, et al.. (2016). Optimal design of hydrometric monitoring networks with dynamic components based on Information Theory. EGU General Assembly Conference Abstracts. 2 indexed citations
15.
Ridolfi, Elena, Leonardo Alfonso, Giuliano Di Baldassarre, & Francesco Napolitano. (2016). Optimal cross-sectional sampling for river modelling with bridges: An information theory-based method. AIP conference proceedings. 3 indexed citations
16.
17.
Mazzoleni, Maurizio, Leonardo Alfonso, & Dimitri Solomatine. (2015). Improving flood prediction by assimilation of the distributed streamflow observations with variable uncertainty and intermittent behavior. EGU General Assembly Conference Abstracts. 15856. 1 indexed citations
18.
19.
Ridolfi, Elena, Leonardo Alfonso, Giuliano Di Baldassarre, et al.. (2013). An entropy approach for the optimization of cross-section spacing for river modelling. Hydrological Sciences Journal. 59(1). 126–137. 32 indexed citations
20.
Ridolfi, Elena, Kun Yan, Leonardo Alfonso, et al.. (2012). Optimization of floodplain monitoring sensors through an entropy approach. IRIS Research product catalog (Sapienza University of Rome). 12407. 2 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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