The permafrost module of iLand simulates permafrost and soil-surface organic layer (SOL) dynamics at a fine spatial (1 ha) and temporal (daily) resolution. It efficiently models daily changes in permafrost depth, annual SOL accumulation, and their complex effects on boreal forest structure and functions.

Permafrost Dynamics

The module simulates the annual freeze-thaw cycle of the active layer, driven by heat transfer from the atmosphere and the deeper permafrost layer. Key elements include:

• Active Layer: The top layer of soil that freezes and thaws annually.
• Zero Isoline: The depth where the soil temperature is 0°C, separating frozen and thawed soil.
• Energy Fluxes:
•  Primary Flux: Heat transfer from the atmosphere to the soil, driving active layer dynamics.
•  Secondary Flux: Heat transfer from the deeper permafrost layer, influencing the freezing process.
• Resistances: Thermal resistances of snow, SOL, and mineral soil are considered to affect heat transfer.
• Snow Depth: Modeled as a function of precipitation and temperature, affecting the insulating properties of the soil

Soil Organic Layer (SOL):

•  Composition: Includes litter and dead moss.
•  Dynamics: Depth is modeled based on litter and coarse wood production and decomposition.
•  Thermal Conductivity: Varies with soil moisture and texture.

SOL and Moss Dynamics

The module also simulates the growth dynamics of the moss layer, which plays a crucial role in insulating the permafrost. Key features include:

• Moss Growth: Influenced by light availability (affected by canopy cover), temperature, and litter accumulation.
• Moss Litter: Decomposes and contributes to the SOL, influencing its insulating properties.
• Effects on Ecosystem:
• Tree Establishment: Thick SOL layers can hinder tree seedling establishment.
• Water Cycle: Permafrost and SOL depth affect water availability for trees.
• Fire Dynamics: The moss layer acts as both fuel and insulation in fire events.

Settings in the project file

The “permafrost” section is a sub-section of “model.settings”. Example with full names: model.settings.permafrost.lambdaSnow, model.settings.permafrost.moss.light_sat. To enable / switch on the module, set model.settings.permafrost.enabled to true.

Key	Datatype	Description
enabled	Boolean	Permafrost sub module switched on when true
onlySimulate	Boolean	if true, permafrost is calculated but has no effect on the water cycle
initialGroundTemperature	numeric	Initial temperature in depth ‘groundBaseDepth’ below the active layer: at depth "groundBaseDepth" the temperature is assumed to remain +- constant within a year and to follow MAT with a 10yr delay. The initial value is given with 'initialGroundTemperature'. and the depth from which thermal energy flows
initialDepthFrozen	Numeric	depth (m) up to which the soil is frozen at the start of the simulation (1st of January). For permanent permafrost the value is capped at 2m.
groundBaseDepth	Numeric	depth (m) of the zone below the active layer from where the secondary heat flux (from below) originates
initialGroundTemperature	numeric	Initial temperature in depth ‘groundBaseDepth’ below the active layer: at depth "groundBaseDepth" the temperature is assumed to remain +- constant within a year and to follow MAT with a 10yr delay. The initial value is given with 'initialGroundTemperature'. and the depth from which thermal energy flows
lambdaOrganicLayer	Numeric	thermal conductivity W/m*K of soil organic layer and moss
organicLayerDensity	Numeric	density (kg/m3) of the soil organic layer (default: 50)
organicLayerDefaultDepth	Numeric	depth of the soil organic layer (m) (only relevant when dynamic carbon cycle is disabled) (default: 0.1)
maxFreezeThawPerDay	Numeric	cap for daily freezing and thawing (mm water column)
Section moss
biomass	Numeric	initial life moss kg/ha
bulk_density	Numeric	Density of the moss layer (kg/m3)
light_k	Numeric	Light extinction coefficient used for tree canopy and moss
light_comp	Numeric	light compensation point: light level (proportion of light above canopy) above which photosynthesis is possible
light_sat	Numeric	light saturation point: level of light (relative to light level above canopy) above which an increase in light does not increase GPP
respiration_b	Numeric	Annual loss of moss biomass due to respiration (flux to atmosphere)
respiration_q	numeric	Annual loss of moss biomass due to turnover (flux to litter)
CNRatio	Numeric	CN-ratio of moss litter entering the litter pool of iLand
r_decomp	Numeric	Decomposition rate of moss litter that enters the litter pool of iLand
r_deciduous_inhibition	Numeric	Parameter to calculate inhibition effect of fresh broadleaved litter (default: 0.45)

Related (new) parameters

Key	Datatype	Description
model.settings.snowDensity	Numeric	Density of snow in kg/m³ (default: 300)
model.settings.snowInitialDepth	Numeric	Depth of the snow pack (in m) at the start of the simulation (default: 0)

 

Permafrost visualization

When the permafrost module is enabled, you can visualize certain aspects in iLand. The following layers are available in the 'permafrost' section:

Option	description
maxDepthFrozen	maximum depth of freezing (m). Is 2m for full freeze.
maxDepthThawed	maximum depth of thawing (m). Is 2m for fully thawed soil
deepSoilTemperature	temperature of ground deep below the soil (C)
maxSnowCover	maximum snow height (cm)
SOLDepth	depth of the soil organic layer (litter+dead moss) (cm)
moss	depth of the life moss layer (cm)

Note that you can access / retrieve those grids in Javascript, e.g., to save them as files for external analysis.

 

Species parameter related to permafrost

The (new) species parameter “estSOLthickness” is used to specify the species-specific establishment response to thick soil organic layer (0: no effect).

Permafrost related outputs

Water-Output

Columns related to permafrost in the water output (annual timesteps)

Column	description
maxDepthFrozen	Permafrost: maximum depth of freezing (m). The value is 2m when soil is fully frozen in a year."
maxDepthThawed	Permafrost: maximum depth of thawing (m). The value is 2m if soil is fully thawed in a year.
maxSnowCover	Permafrost: maximum snow height (m) in a year.
SOLLayer	Permafrost: total depth of soil organic layer (excl. life moss) (m).
mossLayer	depth of the life moss layer (m).

 

Debug-Output (water)

Daily values for the state of permafrost (per resource unit) are in the water-debug output:

Column	description
pftop	top of frozen layer (m) when thawing (above that soil is thawed)
pfbottom	bottom of the frozen layer (m) (important for seasonal permafrost; soil is frozen *up to* this depth), for permanent permafrost, the bottom is 2m
pffreezeback	depth (m) up to which the soil is frozen again (in autumn)
delta_mm	change of water (mm within iLand water bucket), freezing is negative
delta_soil	change of ice layer (m) (within iLand water bucket), freezing is negative
thermalConductivity	Current conductivity of mineral soil W / m2 / K
soilfrozen	depth of soil (m) that is currently frozen (this is a part of the soil plant accessible soil)
waterfrozen	amount of water (mm) trapped currently in ice
current_capacity	Current field capacity of the (non-frozen) soil bucket (mm)
moss_fLight	Value of the light response for moss growth
moss_fDecid	Value of the limiting factor of deciduous litter
moss_fCanopy	Response value for the drying out  effect due to canopy openness

 

 Creating custom permafrost graphs

 

# R example code
# rids: data.frame with a selection of resource ids
# dbg_wc: file created by debug output
ggplot( rids %>% left_join(dbg_wc) %>% group_by(rid, year) %>% mutate(n=row_number()) %>% ungroup() %>% 
          mutate(   groundice.high = pmax(pftop, pffreezeback), 
                    topice.min = pmin(pftop, pffreezeback)), aes(x=n)) + 
  geom_ribbon( aes( ymax=2, ymin=pfbottom), fill="lightblue" ) + 
  geom_ribbon( aes( ymax=pfbottom, ymin=groundice.high), fill="darkgray" ) + 
  geom_ribbon( aes( ymax=groundice.high, ymin=topice.min), fill="lightblue" ) + 
  geom_ribbon( aes( ymax=topice.min, ymin=0), fill="darkgray" ) + 
  geom_ribbon (aes( ymax= -snow_height/300, ymin=0), fill="lightgray") +
  geom_line (aes(y=-temp/100)) +
  scale_y_reverse() + facet_wrap(~round(tmean,2)) + theme_bw()

The code creates figures such as: