Papers su riviste indicizzate su banca dati Scopus e/o WoS

  1. Domma, F.; Condino, F.; Franceschi, S; De Luca, D.L.; Biondi, D. (2022). On the extreme hydrologic events determinants by means of Beta-Singh-Maddala reparameterization. Scientific Reports 12, 15537. https://doi.org/10.1038/s41598-022-19802-4

  2. Grimaldi, S.; Volpi, E.; Langousis, A.; Papalexiou, S.M.; De Luca, D.L.; Piscopia, R.; Nerantzaki, S.D.; Papacharalampous, G.; Petroselli, A. (2022). Continuous hydrologic modelling for small and ungauged basins: a comparison of eight rainfall models for sub-daily runoff simulations. Journal of Hydrology, 610, Article 127866, https://doi.org/10.1016/j.jhydrol.2022.127866

  3. Ayalew, D.W.; Petroselli, A.; De Luca, D.L.; Grimaldi, S. (2022). An evidence for enhancing the design hydrograph estimation for small and ungauged basins in Ethiopia. Journal of Hydrology: Regional Studies, 42, 101123. https://doi.org/10.1016/j.ejrh.2022.101123

  4. De Luca, D.L.; Capparelli, G. (2022). Rainfall nowcasting model for early warning systems applied to a case over Central Italy. Natural Hazards, 112(1), 501–520, https://link.springer.com/article/10.1007/s11069-021-05191-w

  5. Petroselli, A.; De Luca, D.L.; Młyński, D.; Wałęga, A. (2022). Modelling annual maximum daily rainfall with the STORAGE (STOchastic RAinfall GEnerator) model. Hydrology Research 53(4), 47–561, https://doi.org/10.2166/nh.2022.100

  6. De Luca, D.L.; Apollonio, C.; Petroselli, A. (2022). The Benefit of Continuous Hydrological Modelling for Drought Hazard Assessment in Small and Coastal Ungauged Basins: A Case Study in Southern Italy. Climate, 10, 34. https://doi.org/10.3390/cli10030034

  7. Petroselli, A.; Apollonio, C.; De Luca, D.L.; Salvaneschi, P.; Pecci, M.; Marras, T.; Schirone, B. (2021) Comparative Evaluation of the Rainfall Erosivity in the Rieti Province, Central Italy, Using Empirical Formulas and a Stochastic Rainfall Generator. Hydrology, 8, 171. https://doi.org/10.3390/hydrology8040171

  8. De Luca, D.L.; Petroselli, A. (2021). STORAGE (STOchastic RAinfall GEnerator): A User-Friendly Software for Generating Long and High-Resolution Rainfall Time Series. Hydrology, 8(2), 76. https://doi.org/10.3390/hydrology8020076 (https://www.mdpi.com/2306-5338/8/2/76)

  9. Biondi D.; Greco A; De Luca D.L. (2021). Fixed-area vs storm-centered Areal Reduction factors: a Mediterranean case study. Journal of Hydrology, 595, 125654. https://doi.org/10.1016/j.jhydrol.2020.125654. (http://www.sciencedirect.com/science/article/pii/S002216942031115X)

  10. De Luca, D.L.; Petroselli, A.; Galasso, L. (2020). A Transient Stochastic Rainfall Generator for Climate Changes Analysis at Hydrological Scales in Central Italy. Atmosphere, 11(12), 1292. https://doi.org/10.3390/atmos11121292 (https://www.mdpi.com/2073-4433/11/12/1292)

  11. Greco, A.; De Luca, D.L.; Avolio, E. (2020) Heavy Precipitation Systems in Calabria Region (Southern Italy): High-Resolution Observed Rainfall and Large-Scale Atmospheric Pattern Analysis. Water, 12(5), 1468; https://doi.org/10.3390/w12051468 (https://www.mdpi.com/2073-4441/12/5/1468)

  12. De Luca, D.L.; Petroselli, A.; Galasso, L. (2020). Modelling climate changes with stationary models: is it possible or is it a paradox? In: Sergeyev Y., Kvasov D. (eds) Numerical Computations: Theory and Algorithms. NUMTA 2019. Lecture Notes in Computer Science, vol 11974. Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-030-40616-5_7

  13. De Luca, D.L.; Galasso, L. (2019). Calibration of NSRP models from extreme value distributions. Hydrology (Switzerland), 6, 89; https://doi.org/10.3390/hydrology6040089 (https://www.mdpi.com/2306-5338/6/4/89/htm)

  14. De Luca, D.L.; Galasso, L. (2018). Stationary and Non-Stationary Frameworks for Extreme Rainfall Time Series in Southern Italy. Water (Switzerland), 10, 1477; https://doi.org/10.3390/w10101477. (https://www.mdpi.com/2073-4441/10/10/1477)

  15. Versace, P., Capparelli, G., De Luca, D.L. (2018). TXT-tool 2.039-4.1: Flair model (forecasting of landslides induced by rainfalls). Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools: Volume 1: Fundamentals, Mapping and Monitoring, pp. 381-389. DOI: 10.1007/978-3-319-57774-6_28

  16. Versace P.; De Luca D.L. (2017). Deterministic and Probabilistic Rainfall Thresholds for Landslide Forecasting. In: Advancing Culture of Living with Landslides. Vol. 4, p. 169-176, Mikoš M., Casagli N., Yin Y., Sassa K., ISBN: 978-3-319-53484-8, DOI: 10.1007/978-3-319-53485-5_18 (https://link.springer.com/chapter/10.1007/978-3-319-53485-5_18)

  17. Versace, P., Capparelli, G., De Luca, D.L. (2017). TXT-tool 2.039-4.2 LEWIS Project: An Integrated System for Landslides Early Warning. Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools: Volume 1: Fundamentals, Mapping and Monitoring, pp. 509-535. DOI: 10.1007/978-3-319-57774-6_38

  18. De Luca, D.L.; Biondi, D. (2017). Bivariate return period for design hyetograph and relationship with T-year design flood peak. Water (Switzerland), 9 (9), art. no. 673. DOI: 10.3390/w9090673 (http://www.mdpi.com/2073-4441/9/9/673)

  19. Biondi D.; De Luca D.L. (2017). Rainfall-runoff model parameter conditioning on regional hydrological signatures: application to ungauged basins in southern Italy. Hydrology Research, 48(3): 714-725, ISSN: 1998-9563, DOI: 10.2166/nh.2016.097 (http://hr.iwaponline.com/content/early/2016/08/08/nh.2016.097)

  20. De Luca D.L.; Versace P. (2017). Diversity of Rainfall Thresholds for early warning of hydro-geological disasters. Advances in Geosciences, 44: 53-60, ISSN: 1680-7359, DOI: https://doi.org/10.5194/adgeo-44-53-2017 (http://www.adv-geosci.net/44/53/2017/)

  21. De Luca D.L.; Versace P. (2017). A comprehensive framework for empirical modeling of landslides induced by rainfall: the Generalized FLaIR Model (GFM). Landslides, 14(3): 1009-1030, ISSN: 1612-5118, DOI: 10.1007/s10346-016-0768-5 (https://link.springer.com/article/10.1007/s10346-016-0768-5)

  22. De Luca D.L.; Versace P. (2016). A general formulation to describe empirical rainfall thresholds for landslides. Procedia Earth And Planetary Science, 16: 98-107, ISSN: 1878-5220, DOI: 10.1016/j.proeps.2016.10.011 (http://www.sciencedirect.com/science/article/pii/S187852201630011X)

  23. De Luca D.L.; Cepeda J.M. (2016). A procedure to obtain analytical solutions of 1D Richards' equation for infiltration in two-layered soils. Journal of Hydrologic Engineering, 21(7), Article number 04016018, DOI: 10.1061/(ASCE)HE.1943-5584.0001356 (http://ascelibrary.org/doi/abs/10.1061/(ASCE)HE.1943-5584.0001356)

  24. Biondi D.; De Luca D.L. (2015). Process-based design flood estimation in ungauged basins by conditioning model parameters on regional hydrologic signatures. Natural Hazards, 79(2): 1015-1038, DOI: 10.1007/s11069-015-1889-1. (https://link.springer.com/article/10.1007/s11069-015-1889-1)

  25. De Luca D.L. (2014). Analysis and modeling of rainfall fields at different resolutions in Southern Italy. Hydrological Sciences Journal, 59(8): 1536-1558, ISSN: 0262-6667, DOI: 10.1080/02626667.2014.926013 (http://www.tandfonline.com/doi/abs/10.1080/02626667.2014.926013)

  26. De Luca D.L.; Versace P.; Capparelli G. (2014). Performance of I–D thresholds and flair model for recent landslide events in Calabria region (southern Italy). In: Sassa, Canuti, Yin. Landslide Science for a Safer Geoenvironment: Vol. 3: Targeted Landslides. p. 281-286, Springer International Publishing Switzerland 2014, ISBN: 978-3-319-04996-0, DOI: 10.1007/978-3-319-04996-0 (https://link.springer.com/chapter/10.1007/978-3-319-04996-0_43)

  27. Biondi D.; De Luca D.L. (2013). Performance assessment of a Bayesian Forecasting System (BFS) for real time flood forecasting. Journal of Hydrology, 479: 51-63 DOI: 10.1016/j.jhydrol.2012.11.019. (http://www.sciencedirect.com/science/article/pii/S0022169412009833)

  28. Biondi D.; De Luca D.L. (2012). A Bayesian approach for real-time flood forecasting, Physics and Chemistry of the Earth, 42-44: 91-97, ISSN: 1474-7065, DOI:10.1016/j.pce.2011.04.004. (http://www.sciencedirect.com/science/article/pii/S1474706511000593)

  29. De Luca D.L., Cepeda J.M. (2012). Models for landslides induced by precipitation in Norway. Proceedings of 86° Conference of Italian Geological Society, Rende (CS) - Italy, 18-20 September 2012.

  30. Capparelli G., De Luca D.L., Versace P. (2012). Development of a hydrological landslide model at regional scale. Applications in the central part of Calabria region (southern Italy). Proceedings of 86° Conference of Italian Geological Society, Rende (CS) - Italy, 18-20 September 2012.

  31. Sirangelo B.; Ferrari E.; De Luca D.L. (2011). Occurrence analysis of daily rainfalls through non-homogeneous Poissonian processes. Natural Hazard and Earth System Sciences, 11: 1657-1668, ISSN: 1561-8633, eISSN: 1684-9981, DOI:10.5194/nhess-11-1657-2011. (http://www.nat-hazards-earth-syst-sci.net/11/1657/2011/)

  32. De Luca D.L.; Biondi D.; Capparelli G.; Galasso L.; Versace P. (2010). Mathematical models for early warning systems. In Global Change Facing Risks and Threats to Water Resources, Proceedings of the sixth World FRIEND Conference, Fez, Morocco, 25-29 October 2010, pp. 485-495, IAHS Publications 340, Wallingford, UK, ISSN: 0144-7815, ISBN: 978-1-907161-13-1.

  33. Versace P.; Sirangelo B.; De Luca D.L. (2009). A space-time generator for rainfall nowcasting: the PRAISEST model. Hydrology and Earth System Sciences, 13(4): 441-452, Copernicus Publications, Göttingen, Germany, ISSN: 1027-5606, eISSN: 1607-7938, DOI:10.5194/hess-13-441-2009. (http://www.hydrol-earth-syst-sci.net/13/441/2009/

  34. Sirangelo B.; Versace P.; De Luca D.L. (2007). Rainfall Nowcasting by at site stochastic model PRAISE. Hydrology and Earth System Sciences, 11: 1341 - 1351, Copernicus Publications, Göttingen, Germany, ISSN: 1027-5606, eISSN: 1607-7938, doi:10.5194/hess-11-1341-2007. (http://www.hydrol-earth-syst-sci.net/11/1341/2007/)

  35. Sirangelo B.; De Luca D.L. (2006). A stochastic approach to rainfall forecasting in space-time domain: the PRAISEST model. In Risk Analysis V: Simulation and Hazard Mitigation (Risk Analysis 2006), pp. 43-55, Wessex Institute of Technology Press, (United Kingdom). ISBN: 1743-3541, ISSN: 1746-448X (print), 1743-3541 (online), DOI: 10.2495/RISK060051. (https://www.witpress.com/Secure/elibrary/papers/RISK06/RISK06005FU1.pdf)