Located in the critical zone at the intersection between surface water and groundwater, hyporheic zones (HZ) host a variety of hydrological, biological and biogeochemical processes regulating water availability and quality and sustaining riverine ecosystems. However, difficulty in quantifying water fluxes along this interface has limited our understanding of these processes, in particular under dynamic flow conditions where rapid variations can impact large-scale HZ biogeochemical function. In this study, we introduce an innovative measurement assimilation chain for determining uncertainty-quantified hydraulic and thermal HZ properties, as well as associated uncertainty-quantified high-frequency water fluxes. The chain consists in the assimilation of data collected with the LOMOS-mini geophysical device with a process-based, Bayesian approach. The application of this approach on a synthetic case study shows that hydraulic and thermal HZ properties can be estimated from LOMOS-mini measurements, their identifiability depending on the Peclet number – summarizing the hydrological and thermal regime. Hydraulic conductivity values can be estimated with precision when greater than ~10−5m · s−1 when other HZ properties are unknown, with decreasing uncertainty when other HZ properties are known prior to starting the LOMOS-mini measurement assimilation procedure. Water fluxes can be estimated in all regimes with varying accuracy, highest accuracy is reached for fluxes greater than ~10−6m · s−1, except under highly conductive exfiltration regimes. We apply the methodology on in situ datasets by deriving uncertainty-quantified HZ properties and water fluxes for 2 data points collected during field campaigns. This study demonstrates that the LOMOS-mini monitoring technology can be used as complete and stand-alone sampling solution for quantifying water and heat exchanges under dynamic exchange conditions (time resolution < 15 min).