Search for: All records

In the natural environment, wildfires affect how water interacts with soil leading to potentially catastrophic phenomena such as flooding, debris flows, and decreased water quality. Wildfires can cause soil sealing from increased soil water repellency, which in turn reduces infiltration and increases flood risk during rainfall. A 2017 meta-analysis found two properties that were affected by soil burning processes: Sorptivity (the capacity of a soil to absorb or desorb liquid by capillarity, S) and hydraulic conductivity (the ability for soil to transmit water when saturated, Kfs). Changes in these properties act synergistically to reduce infiltration, which increases erosion by accelerating and amplifying surface runoff. Thus, this research seeks to understand how soils subjected to severe burning compare to unburned soils. Using a mini-disk infiltrometer, field tests measured hydraulic conductivity of soils burned under slash and burn piles during the winters of 2016-17, 2020-21, and 2023-23 to better understand changes that occur in soil-hydraulic properties over time. These slash and burn piles served as approximate impacts for wildfires. Slash and burn piles also allow for paired measurements of unburned soils immediately adjacent to the burned area. Hydraulic conductivity was not significantly different when comparing burned and unburned soils 1 year after being burned. However, there was a significant difference between the hydraulic conductivity of soils burned 3 years ago compared to both unburned soil and soils burned 1 year ago. This suggests an interim process between 1- and 3-years post-burn that reduces hydraulic conductivity of burned soils. 

ABSTRACT Changes in the volume, rate, and timing of the snowmelt water pulse have profound implications for seasonal soil moisture, evapotranspiration (ET), groundwater recharge, and downstream water availability, especially in the context of climate change. Here, we present an empirical analysis of water available for runoff using five eddy covariance towers located in continental montane forests across a regional gradient of snow depth, precipitation seasonality, and aridity. We specifically investigated how energy‐water asynchrony (i.e., snowmelt timing relative to atmospheric demand), surface water input intensity (rain and snowmelt), and observed winter ET (winter AET) impact multiple water balance metrics that determine water available for runoff (WAfR). Overall, we found that WAfR had the strongest relationship with energy‐water asynchrony (adjustedr² = 0.52) and that winter AET was correlated to total water year evapotranspiration but not to other water balance metrics. Stepwise regression analysis demonstrated that none of the tested mechanisms were strongly related to the Budyko‐type runoff anomaly (highest adjustedr² = 0.21). We, therefore, conclude that WAfR from continental montane forests is most sensitive to the degree of energy‐water asynchrony that occurs. The results of this empirical study identify the physical mechanisms driving variability of WAfR in continental montane forests and are thus broadly relevant to the hydrologic management and modelling communities. 

Abstract When people make choices, the items they consider are often embedded in a context (of other items). How this context affects the valuation of the specific item is an important question. High-value context might make items appear less attractive because of contrast—the tendency to normalize perception of an object relative to its background—or more attractive because of assimilation—the tendency to group objects together. Alternatively, a high-value context might increase prior expectations about the item's value. Here, we investigated these possibilities. We examined how unavailable context items affect choices between two target items, as well as the willingness-to-pay for single targets. Participants viewed sets of three items for several seconds before the target(s) were highlighted. In both tasks, we found a significant assimilation-like effect where participants were more likely to choose or place a higher value on a target when it was surrounded by higher-value context. However, these context effects were only significant for participants’ fastest choices. Using variants of a drift-diffusion model, we established that the unavailable context shifted participants’ prior expectations towards the average values of the sets but had an inconclusive effect on their evaluations of the targets during the decision (i.e. drift rates). In summary, we find that people use context to inform their initial valuations. This can improve efficiency by allowing people to get a head start on their decision. However, it also means that the valuation of an item can change depending on the context. 

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. 

An important consideration for water resources planning is runoff timing, which can be strongly influenced by the physical process of water storage within and release from seasonal snowpacks. The aim of this presentation is to introduce a novel method that combines light detection and ranging (LiDAR) with ground-penetrating radar (GPR) to nondestructively estimate the spatial distribution of bulk liquid water content in a seasonal snowpack during spring melt. This method was developed at multiple plots in Colorado in 2017 and applied at the small catchment scale in 2019. We developed this method in a manner to observe rapid changes that occur at subdaily timescales. Observed volumetric liquid water contents ranged from near zero to 19%vol within the scale of meters during method development. We also show rapid changes in bulk liquid water content of up to 5%vol that occur over subdaily timescales. The presented methods have an average uncertainty in bulk liquid water content of 1.5%vol, making them applicable for studies to estimate the complex spatio-temporal dynamics of liquid water in snow. During the spring snowmelt season of 2019, we applied this method to a small headwater catchment in the Colorado Front Range. A total of 9 GPR surveys of approximately 3 km in length were conducted over a six-week period. Additionally, five LiDAR scans occurred over the same area. Using this technique, we identify locations that melting snow accumulates and is stored as liquid water within the snowpack. This work shows that the vadose zone may be conceptualized, during snowmelt, as extending above the soil-snow interface to include variably saturated flow processes within the snowpack. 

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. 

{}