Bibliographic Details
| Title: |
An Interactive Platform for Design Hydrograph Estimation in Small and Ungauged Basins: Pilot Implementation in the Lazio Region, Italy. |
| Authors: |
Grimaldi, Salvatore, Petroselli, Andrea, Cappelli, Francesco, Piscopia, Rodolfo, Bianchini, Stefano, Centola, Alessio, Scarola, Maria, de Gennaro, Valeria, Giove, Roberta Maria |
| Source: |
Water (20734441); Nov2025, Vol. 17 Issue 21, p3122, 15p |
| Subject Terms: |
DIGITAL twin, HYDROLOGIC models, PYTHON programming language, PROGRAMMING languages, WATERSHEDS, RUNOFF |
| Geographic Terms: |
LAZIO (Italy), ITALY |
| Abstract: |
Estimating design hydrographs in small and ungauged basins remains a significant challenge, primarily due to limited hydrometeorological data and the operational complexity of advanced modelling tools. This study presents an interactive digital twin platform to support hydrological modelling in such contexts. The aim of the proposed platform is to integrate three hydrological models—EBA4SUB (event-based rainfall–runoff model), COSMO4SUB (continuous rainfall–runoff model), and Virtual Rain (stochastic rainfall generator)—and automates key pre-processing tasks, including watershed delineation, Curve Number estimation, and rainfall input generation. Built on a three-tier architecture, the system comprises an interactive front end, a back-end database with spatial and meteorological data, and a suite of computational routines developed in Python and C#. The platform was deployed across the Lazio Region (Italy) for basins with contributing areas smaller than 400 km2. Users can interactively select watersheds via a map-based interface, obtain preliminary hydrological characterizations, and export model-ready inputs and outputs. The proposed platform offers several advantages: it reduces model preparation time, facilitates access to advanced modelling tools, standardizes input data at the regional level, and ensures reproducible pre-processing workflows. By lowering the technical and time barriers of hydrological modelling, the digital twin provides an effective framework for bringing science-based tools closer to real-world practice. [ABSTRACT FROM AUTHOR] |
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| Database: |
Biomedical Index |