Low-Cost Water Level Measurement Technologies for Assessing the Impact of Climate Change and Storm Surges in Coastal Areas, Suitable for Citizen Science Initiatives

Juan Francisco Martinez Osuna^1,2*Viviana Piermattei¹Giovanni Coppini¹Marco Marcelli^1,2

• ¹Foundation Euro-Mediterranean Center on Climate Change (CMCC), Lecce, Italy
• ²Department of Ecological and Biological Sciences, University of Tuscia, Viterbo, Lazio, Italy

The study of climate change and its impact on coastal areas has become increasingly important in recent years and understanding how storm surges and extreme events affect water levels in transitional and coastal zones has become a crucial aspect. The main objective of this work is to develop a low-cost, easy-to-install device capable of accurately measuring sea and river water levels, along with basic meteorological variables at the ocean-atmosphere interface. The proposed device, known as InterBox: Air-Sea Interface Observing System in a Box, represents a valuable component of the monitoring capacity required to assess the impact of climate change on coastal water levels, supporting the spatial and temporal mapping of its consequences in estuarine and coastal environments. In this context, ultrasonic sensors offer several advantages: high accuracy, non-invasiveness, fast installation, low-cost, real-time data acquisition, and flexibility to interface with diverse data loggers. Moreover, monitoring atmospheric pressure, air temperature, and humidity is essential to better understand the processes driving water level variability, storm surge dynamics, and compound flooding events. These variables provide critical context for interpreting hydrological and oceanographic measurements, enhancing the accuracy of predictive models, and contributing to the development of more robust Early Warning Systems. Strategically deploying these sensors along coasts and rivers could enable improved monitoring granularity, (that is, a higher level of spatial and temporal detail in the collected data, which in turn allows for a more accurate assessment of spatiotemporal variability). This is achieved by collecting integrated water level and meteorological data at multiple locations before, during, and after extreme events. These datasets can be incorporated into open data platforms such as EMODnet Physics and integrated into digital twins of the coastal ocean, supporting both planning and emergency response strategies.