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Throughout communities and ecosystems both within and downstream of mountain forests, there is an increasing risk of wildfire. After a wildfire, stakeholder management will vary depending on the rate and spatial heterogeneity of forest re-establishment. However, forest re-establishment and recovery after a wildfire is closely linked to interactions between the temporal evolution of plant-available water (PAW) and spatial patterns in available energy. Therefore, we propose a conceptual model that describes spatial heterogeneity in long-term watershed recovery rate as a function of topographically-mediated interactions between available energy and the movement of water in the subsurface (i.e. subsurface hydrologic redistribution). As vegetation becomes re-established across a burned landscape in response to topographic and subsurface controls on water and energy, canopies shade the ground surface and reduce wind speed creating positive feedbacks that increase PAW. Furthermore, slope aspect differentially impacts the spatial patterns in regrowth and re-establishment. South aspect slopes receive high solar radiation, and consequently are warmer and drier, with lower standing biomass and greater drought stress and mortality compared to north aspect slopes. To date, most assessments of these impacts have taken a bulk approach, or an implicitly one-dimensional conceptual approach that does not include spatial heterogeneity in hydroclimate influenced by topography and vegetation. The presented conceptual model sets a starting point to further our understanding of the spatio-temporal evolution of PAW storage, energy availability, and vegetation re-establishment and survival in forested catchments after a wildfire. The model also provides a template for collaboration with diverse stakeholders to aid the co-production of next generation management tools to mitigate the negative impacts of future wildfires. 

Extensive efforts have been made to observe the accumulation and melting of seasonal snow. However, making accurate observations of snow water equivalent (SWE) at global scales is challenging. Active radar systems show promise, provided the dielectric properties of the snowpack are accurately constrained. The dielectric constant (k) determines the velocity of a radar wave through snow, which is a critical component of time-of-flight radar techniques such as ground penetrating radar and interferometric synthetic aperture radar (InSAR). However, equations used to estimate k have been validated only for specific conditions with limited in situ validation for seasonal snow applications. The goal of this work was to further understand the dielectric permittivity of seasonal snow under both dry and wet conditions. We utilized extensive direct field observations of k, along with corresponding snow density and liquid water content (LWC) measurements. Data were collected in the Jemez Mountains, NM; Sandia Mountains, NM; Grand Mesa, CO; and Cameron Pass, CO from February 2020 to May 2021. We present empirical relationships based on 146 snow pits for dry snow conditions and 92 independent LWC observations in naturally melting snowpacks. Regression results had r2 values of 0.57 and 0.37 for dry and wet snow conditions, respectively. Our results in dry snow showed large differences between our in situ observations and commonly applied equations. We attribute these differences to assumptions in the shape of the snow grains that may not hold true for seasonal snow applications. Different assumptions, and thus different equations, may be necessary for varying snowpack conditions in different climates, suggesting that further testing is necessary. When considering wet snow, large differences were found between commonly applied equations and our in situ measurements. Many previous equations assume a background (dry snow) k that we found to be inaccurate, as previously stated, and is the primary driver of resulting uncertainty. Our results suggest large errors in SWE (10–15%) or LWC (0.05–0.07 volumetric LWC) estimates based on current equations. The work presented here could prove useful for making accurate observations of changes in SWE using future InSAR opportunities such as NISAR and ROSE-L. 

Abstract. Modeling the multidimensional flow of liquid waterthrough snow has been limited in spatial and temporal scales to date. Here,we present simulations using the inverse TOUGH2 (iTOUGH2) model informed by the modelSNOWPACK, referred to as SnowTOUGH. We use SnowTOUGH to simulate snowmetamorphism, melt/freeze processes, and liquid water movement intwo-dimensional snowpacks at the plot scale (20 m) on a sloping groundsurface during multi-day observation periods at three field sites innorthern Colorado, USA. Model results compare well with sites below the treelineand above the treeline but not at a site near the treeline. Results show theimportance of longitudinal intra-snowpack flow paths (i.e., parallel toground surface in the downslope direction and sometimes referred to aslateral flow), particularly during times when the snow surface (i.e.,snow–atmosphere interface) is not actively melting. At our above-treelinesite, simulations show that longitudinal flow can occur at rates orders ofmagnitude greater than vertically downward percolating water flow at a meanratio of 75:1 as a result of hydraulic barriers that divert flow. Our near-treeline site simulations resulted in slightly less longitudinal flow thanvertically percolating water, and the below-treeline site resulted innegligible longitudinal flow of liquid water. These results show theincreasing influence of longitudinal intra-snowpack flow paths withelevation, similar to field observations. Results of this study suggest thatintra-snowpack longitudinal flow may be an important process forconsideration in hydrologic modeling for higher-elevation headwatercatchments.