The Italian multiparametric network for detection and monitoring of earthquake-related crustal fluids alterations

Seismic signals coupling to physical (e.g., temperature, pH, Eh, electrical conductivity, flow rate) and geochemical changes in ground and spring waters as well as variations in soil flux regimes (e.g., CO₂, CH₄, radon) represent a valuable tool to better understand the interaction between tectonics and crustal fluids dynamics (e.g., Italiano et al., 2001, 2004; Wang and Manga, 2021; Chiodini et al., 2020; Gori and Barberio, 2022 and references therein). Pre-, co- and post-seismic modifications are markers of the local tectonic stress acting in the crust and are extremely site-specific due to the local geological and lithological features besides being simultaneously influenced by other environmental conditions (e.g., meteorological and climatic). Therefore, local continuous monitoring of all the involved parameters is needed to delineate crustal fluids response to seismicity site by site.
Multiparametric stations have been set up in Italy starting from the end of 2021, placed on the major seismogenic structures, and widely distributed among the Alps, Apennines and Pianura Padana. They are equipped with: (i) sensors installed in water wells measuring water level, temperature, and electrical conductivity; (ii) meteorological sensors measuring atmospheric pressure, temperature, rain, humidity, wind speed and direction; (iii) seismic sensors providing accelerometric and velocimetric datasets; (iv) radon sensors; (v) CO₂ soil flux chamber. 
Data are transmitted in near real-time to an ad hoc developed dynamic relational database (MUDA-geophysical and geochemical MUltiparametric DAtabase) and displayed in a dedicated website (http://muda.mi.ingv.it). The built-in philosophy is to easily compare distinct parameters from the various sensors and possibly recognize cause-effect relationships among them. 
To our knowledge, our new multiparametric network is the first developed in Italy showing all these features.
A statistic approach is also applied to the time-series to investigate intra-annual and inter-annual trends and correlations among different parameters. Alternative methods (e.g., signal decomposition, spike detection) will be presented and discussed. 

References
-Chiodini G., Cardellini C., Di Luccio F., Selva J., Frondini F., Caliro S., Rosiello A., Beddini G., Ventura G., 2020: Correlation between tectonic CO2 Earth degassing and seismicity is revealed by a 10-year record in the Apennines, Italy. Science Advances, https://www.science.org/doi/10.1126/sciadv.abc2938
-Gori F., Barberio M.D., 2022: Hydrogeochemical changes before and during the 2019 Benevento seismic swarm in central-southern Italy. Journal of Hydrology, 604:127250
-Italiano F., Martinelli G., Nuccio P.M., 2001: Anomalies of mantle-derived helium during the 1997 – 1998 seismic swarm of Umbria-Marche, Italy. Geophysical Research Letters, 28(5):839-842
-Italiano F., Martinelli G., Rizzo A., 2004: Geochemical evidence of seismogenic-induced anomalies in the dissolved gases of thermal waters: A case study of Umbria (Central Apennines, Italy) both during and after the 1997–1998 seismic swarm. Geochemistry, Geophysics, Geosystems, 5:11, doi:10.1029/2004GC000720
-Wang C.-Y., Manga M., 2021: Water and Earthquakes. Lecture Notes in Earth System Sciences, Springer Cham, 387 pp., https://doi.org/10.1007/978-3-030-64308-9