Advancing hydrological monitoring using image-based techniques: challenges and opportunities

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Salvatore Manfreda , Domenico Miglino, Khim Cathleen Saddi, Seifeddine Jomaa, Anette Etner, Matthew Perks, Salvador Peña-Haro, Thom Bogaard, Tim van Emmerik , Stefano Mariani, Ian Maddock, Flavia Tauro, Salvatore Grimaldi, Yijian Zeng, Gil Gonçalves, Dariia Strelnikova, Martina Bussettini, Giulia Marchetti, Barbara Lastoria, Bob Su, Michael Rode


Enhanced and effective hydrological monitoring plays a crucial role in understanding water-related processes in a rapidly changing world. This paper explores the challenges and opportunities associated with image-based hydrological monitoring techniques, and highlights the need for innovative approaches and technologies to overcome existing limitations. Image-based hydrological monitoring has shown to significantly enhance data collection, improve analysis and accuracy, and support effective and timely decision-making. The integration of remote and proximal sensing technologies, with the powers of big data analytics, and artificial intelligence are revolutionizing hydrological monitoring practices. By addressing these challenges and harnessing their potential, hydrological monitoring can evolve to meet the growing demands of water resources in order to face climate change and human needs. The present study reviews showcases and good practices of enhanced hydrological monitoring in different applications, reflecting the strengths and limitations of new approaches.



Engineering, Life Sciences


Environmental monitoring, Image processing, UAS, remote sensing, water quality


Published: 2023-11-18 00:04


CC BY Attribution 4.0 International