Abstract ID: 3.12942 | Accepted as Talk | Talk | TBA | TBA

Understanding how surface water and groundwater are connected and contribute to stream flow and temperature patterns is a prerequisite for designing management strategies that minimise detrimental drought effects. However, complexity of river networks and limited accessibility of the sites create important obstacles to the monitoring capability required to inform this understanding. By integrating novel in-situ temperature sensors and stable water isotope techniques with remote sensing approaches and analyses, this study provides a new integrated method that spans beyond isolated traditional single point measurements. We hereby pioneered a multi-method approach for high resolution characterization of river water sources and temperature regimes and the investigation of the role of surface water-groundwater interactions thereon. Our research focuses on the SINCZONE research observatory, located in the central Italian Apennines, which benefits from long-term (>3 years) monitoring of climate, flow, temperature, and stable water isotopes. The Ussita stream (44 km2), which flows through the site, is known for its significant but temporally variable groundwater contributions. Isotope tracers were used to characterize spatio-temporal variations in groundwater contributions to flow, while cost-effective point-scale sensors monitored water temperature at hotspot locations. During contrasting hydro-climatological conditions, these observations were combined with high-resolution (cm-scale) drone-based thermal imagery of the water surface. Together this dataset provided detailed reach-scale characterizations of variations in temperature, water quality and thereby water sources. Specifically, this integrated approach enabled the detection and monitoring of surface water-groundwater interactions and their relationships with seasonal and climatological variations, such as droughts. Our relatively low-cost multi-method approach has a wide range of applications in other remote and mountainous areas, including the detection of environmental and anthropogenic influences on stream water temperature and flows.

Acknowledgements
This work was funded by the Next Generation EU – Italian NRRP, Mission 4, Component 2, Investment 1.5, call for the creation and strengthening of ‘Innovation Ecosystems’, building ‘Territorial R&D Leaders’ (Directorial Decree n. 2021/3277) – project Tech4You – Technologies for climate change adaptation and quality of life improvement, n. ECS0000009. This work reflects only the authors’ views and opinions, neither the Ministry for University and Research nor the European Commission can be considered responsible for them.