SEAWATCH Project: A year of advancements in Short-Range K-Band Radar for Coastal Monitoring

Coastal regions are crucial for human settlements and economic development. However, their distinctive environmental characteristics, particularly in deltas, bays, and gulfs, render them highly vulnerable to threats such as erosion phenomena and pollution. The effective management of these areas depends on the accurate predictions of wave dynamics and their interactions with the shoreline and seabed. Reliable forecasts require numerical wave propagation models to be initialized with precise data and detailed bathymetric representations, and their accuracy depends on calibration operations using high-quality sea state observations.

Sea state data are typically collected through in-situ sensors, such as buoys and drifters, or remote sensing devices, including radars and video-monitoring systems [1]. Remote sensing technologies are often preferred due to their ability to provide both spatial and temporal information. Among these, ground-based radar systems like High-Frequency and X-band radars have proven effective in retrieving wave spectra and coastal sea state information. However, these systems face notable limitations, including difficulties in acquiring data near the shoreline. Additionally, they are bulky, heavy, and cumbersome, which complicates the deployment stage.

To address these challenges, the Italian PRIN-PNRR 2022 Project SEAWATCH—Short-Range K-Band Wave Radar System Close to the Coast—was launched on November 30, 2023. SEAWATCH focuses on developing an innovative, portable, short-range K-band radar prototype specifically designed for sea state monitoring in nearshore zones. Thanks to its compact size, lightweight design, and low power requirements, the system enables flexible, on-demand surveys, meeting critical safety and environmental management needs in harbors and coastal zones.

This communication outlines the key activities and initial results achieved during the first year of the SEAWATCH project. This last is organized into six milestones, supported by a robust collaboration between research units to ensure efficient knowledge sharing and steady progress. Preliminary here results shown highlight the radar prototype potential to overcome traditional limitations, offering enhanced spatial resolution and real-time monitoring capabilities near the coastline [2]-[4].

Future efforts will focus on further refining the radar prototype and validating its performance across diverse coastal environments.

 

References:

• P. Neill, M. Reza Hashemi, Chapter 7 - In Situ and Remote Methods for Resource Characterization, Editor(s): Simon P. Neill, M. Reza Hashemi, In E-Business Solutions, Fundamentals of Ocean Renewable Energy, Academic Press, 2018, Pages 157-191.
• Afolabi, L. A., et al. (2025). Underestimation of Wave Energy from ERA5 Datasets: Back Analysis and Calibration in the Central Tyrrhenian Sea. Energies, 18(1), 3.
• Ludeno, G., Antuono, M., Soldovieri, F., & Gennarelli, G. (2024). A Feasibility Study of Nearshore Bathymetry Estimation via Short-Range K-Band MIMO Radar. Remote Sensing, 16 (2), 261.
• Ludeno, G.; Esposito, G.; Lugni, C.; Soldovieri, F.; Gennarelli, G. A Deep Learning Strategy for the Retrieval of Sea Wave Spectra from Marine Radar Data.  Mar. Sci. Eng.2024, 12, 1609.

 

Acknowledgment: This work was supported and funded by the European Union—NextGenerationEU PNRR Missione 4 “Istruzione e Ricerca”—Componente C2 Investimento 1.1, “Fondo per il Programma Nazionale di Ricerca e PRIN—SEAWATCH—Short-rangE K-bAnd Wave rAdar sysTem Close to tHe coast CUP B53D23023940001, and partially funded by the research project STRIVE—La scienza per le transizioni industriali, verde, energetica CUP B53C22010110001.