Tracking water in snow: Bridging sensor and and model simulations

Forecasting wet slab avalanches remains one of the most demanding challenges in operational avalanche forecasting. A key obstacle is the difficulty of observing and quantifying liquid water content (LWC) and tracking its infiltration into the snowpack. Field measurements are labor-intensive, highly variable in space, and often influenced by user application or sensor design — making them impractical for forecasting operations. In this study, we evaluated LWC measurements obtained from two capacitive sensors, the SLF SnowPro-17 and -25, and compared them with simulations from the snow cover model SNOWPACK. We analyzed five selected days with pronounced melt events during spring 2025 at Bridger Bowl Ski Area, Montana. The SnowPro-17 measured LWC on the sidewall and the SnowPro-25 was inserted into the pit wall. We then analyzed measurements from the two sensors to assess consistency and potential bias. For each of the five days, we also analyzed liquid water infiltration by layer, comparing field measurements with model-simulated LWC. This allowed us to assess how well the model captured both the timing and magnitude of infiltration processes relative to in-situ observations. Our results show that, the absolute LWC values differ by approximately 1% by vol. on average between measurements from the capacitive sensors, but the timing of liquid water infiltration is largely consistent across both measurements and model simulations. Within our sample, the SnowPro-17 consistently reports higher mean LWC values than the SnowPro-25, and exhibits greater variability, indicated by a larger standard deviation. We found good agreement when we compared in-situ sensor measurements to LWC infiltration in snow cover model simulations. This suggests that, despite measurement challenges and sensor variability, SNOWPACK can provide valuable information on the timing of LWC infiltration. For practitioners, this work highlights that reliable forecasting of wet slab avalanches depends on understanding when and how liquid water reaches critical layers. Because direct LWC measurements are rarely feasible in operational settings, using physically based models may offer a practical pathway forward.