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The sensitivity of the water balance of a wet multilayer model pine canopy to variations in meteorological input

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Abstract

A multilayer canopy model of a pine forest is used to investigate the sensitivity of the water balance of the wet canopy to variations in meteorological input. The multilayer model does not take into account large-scale eddies, which are now considered to be of importance to canopy transport. It does, however, provide realistic simulations of wet canopy water balance and often predicts interception loss rates higher than those predicted by a unilayer model for the same meteorological input. Stable layers both within and above the canopy are often simulated during rainfall events, and these may help to spontaneously generate large-scale eddies or waves within forest canopies. The sensitivity study for a wet canopy suggests that low vapour pressure deficits and low wind speeds are associated with unstable surface conditions, and increasing values of both variables are associated with decreasing canopy drainage values and increasing evaporative losses. Low short- or long-wave radiation inputs are associated with stable surface conditions, and increasing values of both variables are associated with decreasing canopy drainage values and increasing evaporative losses. Increasing temperature is associated with increasing surface stability and increasing canopy drainage and decreasing evaporative losses. In real situations the tendency for increasing temperature to cause surface stability and decreased evaporative loss is probably compensated by the opposite effects of increasing short- or long-wave radiation. The model simulations suggest that wet forest canopies may be better ventilated at low temperatures, if other meteorological conditions are constant.

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Abbreviations

D :

Drainage of intercepted water I (mm)

E :

Evapotranspiration per rainfall cycle (mm)

E I :

Evaporation of intercepted water I (mm)

E S :

Soil evaporation (mm)

E T :

Bulk canopy transpiration (mm)

λE :

Latent heat flux (W/m2)

λE A :

Adiabatic component of latent heat flux (1 - Ω) λE x(W/m2)

λE D :

Diabatic component of latent heat flux ΩλE Q(W/m2)

λE q :

‘Equilibrium’ latent heat flux ΩλE Q (W/m2)

λE X :

‘Exchange’ latent heat flux ϱc PδeR/γrS(W/m2)

H :

Sensible heat flux (W/m2)

I :

Interception of water by canopy (mm)

K :

Extinction coefficient of radiation, eddy diffusivity

L :

Leaf area index

P :

Rainfall intensity (mm/h)

P + :

Mean rainfall rate during cycle (mm/h)

Q A :

Available energy at effective evaporating surface (W/m2)

Q L :

Incident long-wave radiation at canopy surface (W/m2)

Q L + :

Net long-wave radiation at effective surface (W/m2)

Q S :

Incident short-wave radiation at canopy surface (W/m2)

Ri :

Richardson number

S T :

Total storage of water on canopy (mm)

S U :

Excess storage of water on canopy contributing to drainage (Rutter et al., 1971) (mm)

C P :

Specific heat capacity of air at constant pressure (J/kg °C)

δe R :

Potential vapour pressure deficit at z R(mb)

k :

Von Karman's constant

r A :

Bulk aerodynamic resistance to transfer of water vapour between canopy and z R(s/m)

r S :

Bulk canopy stomatal resistance (s/m)

s :

Slope of curve of saturation vapour pressure versus temperature at mean air temperature (mb/°C)

u R :

Wind speed at z R(m/s)

z R :

Reference level in ‘mixed layer’ (100 m)

z 0 :

Canopy roughness length (m)

α :

Canopy albedo

γ :

Psychrometric constant (mb/°C)

ɛ :

Long wave emissivity of canopy

ε:

Potential temperature at z R(°C)

λ :

Latent heat of vapourisation of water (J/kg)

η :

Loss ratio E/P + (%)

μ :

Sine of angle of sun above horizon

ϱ :

Air density (kg/m3)

Ω:

Uncoupling coefficient 1/(1 + (γ/(s + γ))(r s /r A ))

W :

Referring to wetting phase of rainfall cycle

D :

Referring to drying phase of rainfall cycle

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  1. School of Geography, University of Leeds, LS2 9JT, Leeds, England

    J. G. Lockwood

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Lockwood, J.G. The sensitivity of the water balance of a wet multilayer model pine canopy to variations in meteorological input. Climatic Change 20, 23–56 (1992). https://doi.org/10.1007/BF00144107

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  • DOI: https://doi.org/10.1007/BF00144107

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