**About the Editors**

#### **Davide Luciano De Luca**

Davide Luciano De Luca is an Assistant Professor in Hydrology and Hydraulics Structures c/o University of Calabria (Italy), Department of Informatics, Modeling, Electronics and System Engineering, from 28/12/2012 to date. His research activities can be divided into three main areas: 1) rainfall field modeling; 2) analysis of hydrological phenomena at slope scale; 3) uncertainty evaluation in rainfall–runoff modeling. His scientific production, updated in September 2022, includes: a) 1 book; b) 35 papers in journals which are indexed on Scopus and/or WoS databases; c) 46 other papers and abstracts.

#### **Andrea Petroselli**

Andrea Petroselli is Associate Professor at Tuscia University (Italy), Department of Economics, Engineering, Society, Business Organization. He is an expert in modeling and monitoring hydrological processes. Recent research topics span from infiltration modeling to rainfall–runoff modeling. He is a member of GISTAR - GIS Terrain Analysis Research Group (www.gistar.org), a web portal for researchers and professionals involved in the investigation, development, and application of GIS-based terrain analysis tools for hydrologic and geomorphic models, and a member of MechHydroLab - Mechanical Engineering for Hydrology and Water Science (www.mechydrolab. org/), a multidisciplinary laboratory composed of mechanical engineers, hydrologists, and water scientists with the goal of combining mechanical engineering technologies and hydrological sciences toward the development of novel experimental systems for advanced environmental monitoring.

### *Editorial* **Advances in Modelling of Rainfall Fields**

**Davide Luciano De Luca 1,\* and Andrea Petroselli 2,\***


Rainfall is the main input for all hydrological models, such as rainfall–runoff models and the forecasting of landslides triggered by precipitation, with its comprehension being clearly essential for effective water resource management as well. The need to improve the modelling of rainfall fields constitutes a key aspect both for efficiently realizing early warning systems and for carrying out analyses of future scenarios related to occurrences and magnitudes for all induced phenomena.

The aim of this Special Issue was to provide a collection of innovative contributions for rainfall modelling, focusing on hydrological scales and a context of climate changes. The first group of papers regarded the study of global precipitation products and their downscaled versions [1], the estimation of peak discharges in rainfall–runoff modeling under different rainfall depth–duration–frequency formulations [2], stormwater infiltration practices in rapidly urbanizing cities with the aim of designing resilient urban environments [3], and a novel temporal stochastic rainfall simulator [4] aiming to generate long and high-resolution rainfall time series, with the advantage of being strongly user friendly and parsimonious in terms of employed input parameters. Moreover, other works focused on determining the quantities of runoff by knowing the amount of rainfall in order to calculate the required quantities of water storage in reservoirs and to determine the likelihood of flooding [5], some analyzed intrastorm pattern recognition through fuzzy clustering [6], and others investigated the use and combination of pluviograph and daily records to assess rain behavior in urban areas, selecting a suitable method that would provide the best results of IDF relationships [7]. Finally, a sensitivity analysis of the rainfall–runoff modeling parameters in data-scarce urban catchment areas was performed aiming to improve the rainfall–runoff model calibration process [8], satellite-based rainfall estimations were compared with ground data [9], machine learning and process-based models for rainfall–runoff simulations were applied [10], and deep convective systems associated with extreme rainfall storms were examined in tropical regions [11].

We believe that the contribution from the latest research outcomes presented in this Special Issue can shed novel insights on the comprehension of the hydrological cycle and all the phenomena that are a direct consequence of rainfall.

Moreover, all these proposed papers can clearly constitute a valid base of knowledge for improving specific key aspects of rainfall modelling, mainly concerning climate change and how it induces modifications in properties such as magnitude, frequency, duration, and the spatial extension of different types of rainfall fields. The goal should also consider providing useful tools to practitioners for quantifying important design metrics in transient hydrological contexts (quantiles of assigned frequency, hazard functions, intensity–duration–frequency curves, etc.).

**Author Contributions:** Writing—original draft preparation, D.L.D.L. and A.P.; writing—review and editing, D.L.D.L. and A.P. All authors have read and agreed to the published version of the manuscript.

**Citation:** De Luca, D.L.; Petroselli, A. Advances in Modelling of Rainfall Fields. *Hydrology* **2022**, *9*, 142. https://doi.org/10.3390/ hydrology9080142

Received: 25 July 2022 Accepted: 8 August 2022 Published: 10 August 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

