Simulation of Preferential Flow in Snow With a 2‐D Non‐Equilibrium Richards Model and Evaluation Against Laboratory Data

Leroux, Nicolas; Marsh, Christopher B.; Pomeroy, John W.

doi:10.1029/2020wr027466

Cited by 11 publications

(13 citation statements)

References 36 publications

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“…8B-C, right). To this end, our work joins previous efforts (Hirashima et al, 2019;Leroux et al, 2020) to show that preferential flow has a strong impact in the fate of meltwater transport in snow and, in particular, prolongs the travel paths of melt.…”

Section: The Influence Of Preferential Infiltration On Melt Transportmentioning

confidence: 59%

“…We present a Darcy-scale model that accounts for preferential meltwater infiltration and refreezing through snow. Previous models of unstable melt infiltration (Hirashima et al, 2014;Leroux & Pomeroy, 2017;Leroux et al, 2020) build upon the Richards equation and require heterogeneous snow properties combined with imbibition/draining hysteresis and/or dynamic capillary pressure to capture flow instability. In comparison, our model incorporates a Richards-like equation extended with a higher-order term in saturation (Eq.…”

Section: A Need For Well-controlled Experiments Of Melt Infiltrationmentioning

confidence: 99%

“…Such extension has been shown to give rise to a gravity fingering instability and requires only a small number of model parameters. In comparison to other recent models of unstable meltwater infiltration (Hirashima et al, 2014;Leroux & Pomeroy, 2017;Leroux et al, 2020), the infiltration model we adopt has a simpler formulation while remaining still robust in producing infiltration patterns consistent with experimental observations (Cueto-Felgueroso & Juanes, 2009b;Cueto-Felgueroso et al, 2020a,b). The model accounts for the phase change process of melt refreezing to ice by (1) modeling a decrease in local snow porosity due to refreezing and (2) updating the thermal budget based on the release of latent heat.…”

Section: Introductionmentioning

confidence: 97%

“…Within the snow hydrology literature, more recent models have explored alternatives or extensions to the Richards equation in order to capture unstable infiltration of meltwater (Hirashima et al, 2014(Hirashima et al, , 2019Leroux & Pomeroy, 2019;Leroux et al, 2020). These studies assume the snowpack is at the melting point (isothermal condition) such that no phase change occurs between melt and ice.…”

Section: Introductionmentioning

confidence: 99%

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A thermodynamic nonequilibrium model for preferential infiltration and refreezing of melt in snow

Moure

Jones

Pawlak

et al. 2022

Preprint

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The transport of meltwater through porous snow is a fundamental process in hydrology that remains poorly understood but essential for more robust prediction of how the cryosphere will respond under climate change. Here we propose a continuum model that resolves the nonlinear coupling of preferential melt flow and the nonequilibrium thermodynamics of ice-melt phase change at the Darcy scale. We assume that the commonly observed unstable melt infiltration is due to the gravity fingering instabililty, and capture it using the modified Richards equation that is extended with a higher-order term in saturation. Our model accounts for changes in porosity and the thermal budget of the snowpack caused by melt refreezing at the continuum scale, based on a mechanistic estimate of the ice-water phase change kinetics formulated at the pore scale. We validate the model in 1D against field data and laboratory experiments of infiltration in snow and find generally good agreement. Compared to existing theory of stable melt infiltration, our 2D simulation results show that preferential infiltration delivers melt faster to deeper depths, and as a result, changes in porosity and temperature can occur at deeper parts of the snow. The simulations also capture the formation of vertical low porosity annulus known as ice pipes, which have been observed in the field but lack mechanistic understanding to date. Our results demonstrate how melt refreezing and unstable infiltration reshape the porosity structure of snow and impacts thermal and mass transport in highly nonlinear ways, which are not captured by simpler models.

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Section: The Influence Of Preferential Infiltration On Melt Transportmentioning

confidence: 59%

Section: A Need For Well-controlled Experiments Of Melt Infiltrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A thermodynamic nonequilibrium model for preferential infiltration and refreezing of melt in snow

Moure

Jones

Pawlak

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…cm to m) (e.g. Leroux et al, 2020; Williams et al, 2010) with only recent advances using remote sensing techniques applied at plot‐scales (up to tens of meters) (e.g. Webb et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Extending the vadose zone: Characterizing the role of snow for liquid water storage and transmission in streamflow generation

Webb

Musselman

Ciafone

et al. 2022

Hydrological Processes

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Streamflow response in headwater catchments is highly sensitive to the hydrologic connectivity of hillslopes to streams during spring snowmelt. Despite strong evidence at point‐ to plot‐scales of flow paths creating lateral connectivity within an alpine snowpack, meltwater is commonly assumed to infiltrate vertically through the snowpack. Hydrologic models only treat the horizontal (downstream) routing of water once released from the snowpack and/or soil column. This assumption limits our ability to represent the full dynamic nature of hydrologic connections in snow‐dominated mountainous headwaters. Thus, the goal of this study is to assess the mechanisms that control the spatiotemporal distribution of liquid water in an alpine snowpack during the spring snowmelt season. We utilize terrestrial laser scanning (TLS), ground penetrating radar (GPR), and manual observations to map the seasonal dynamics of snow depth, snow water equivalent (SWE), and within‐snow liquid water content (LWC). We compare these observations to point‐scale parameter sensitivity analyses with a modular snow model (SUMMA). The results show high spatial variability of LWC in an alpine snowpack during snowmelt. Statistical analyses show LWC is most highly correlated to snow depth (r2 = 0.62). However, including the distance to bare soil and topographical slope slightly improved the coefficient of determination (r2 = 0.67). While hydrologic models have the flexibility to simulate many of the observed dynamics in snowpack liquid water storage, model simulations using previously published parameter ranges always underestimated the high liquid water storage at one of the three sites. This is likely a result of current model structures that lack capabilities for surface ponding of water within a snowpack or surface runoff laterally through a snowpack. Our slope‐scale characterization of the spatiotemporal distribution of in‐snow LWC, together with a model‐based sensitivity assessment, will inform future efforts in hydrologic model development and catchment observations.

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Anticipating how rain-on-snow events will change through the 21st century: lessons from the 1997 new year’s flood event

Rhoades,

Zarzycki,

Hatchett

et al. 2024

Clim Dyn

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The California-Nevada 1997 New Year’s flood was an atmospheric river (AR)-driven rain-on-snow (RoS) event and remains the costliest in their history. The joint occurrence of saturated soils, rainfall, and snowmelt generated inundation throughout northern California-Nevada. Although AR RoS events are projected to occur more frequently with climate change, the warming sensitivity of their flood drivers across scales remains understudied. We leverage the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) to recreate the 1997 New Year’s flood with horizontal grid spacings of 3.5 km across California, with forecast lead times of up to 4 days, and across six warming levels ranging from pre-industrial conditions to $$+3.5\,^\circ$$ + 3.5 ∘ C. We describe the sensitivity of the flood drivers to warming including AR duration and intensity, precipitation phase, intensity and efficiency, snowpack mass and energy changes, and runoff efficiency. Our findings indicate current levels of climate change negligibly influence the flood drivers. At warming levels $$\ge 1.7\,^\circ$$ ≥ 1.7 ∘ C, AR hazard potential increases, snowpack nonlinearly decreases, antecedent soil moisture decreases (except where the snowline retreats), and runoff decreases (except in the southern Sierra Nevada where antecedent snowpack persists). Storm total precipitation increases, but at rates below warming-induced increases in saturation-specific humidity. Warming intensifies short-duration, high-intensity rainfall, particularly where snowfall-to-rainfall transitions occur. This study highlights the nonlinear tradeoffs in 21st-century RoS flood hazards with warming and provides water management and infrastructure investment adaptation considerations.

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Simulation of Preferential Flow in Snow With a 2‐D Non‐Equilibrium Richards Model and Evaluation Against Laboratory Data

Cited by 11 publications

References 36 publications

A thermodynamic nonequilibrium model for preferential infiltration and refreezing of melt in snow

A thermodynamic nonequilibrium model for preferential infiltration and refreezing of melt in snow

Extending the vadose zone: Characterizing the role of snow for liquid water storage and transmission in streamflow generation

Anticipating how rain-on-snow events will change through the 21st century: lessons from the 1997 new year’s flood event

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