Abstract
This paper investigates the impact that various representations of thermal fluxes at the soil surface have on the estimation of seasonal variations in temperature and stored thermal energy in the soil close to the surface. Three theoretical formulations representing turbulent, non-turbulent and vegetation-covered soil surface conditions are considered. The influence of shading from nearby objects (e.g. vegetation) has also been investigated. Numerical predictions of soil temperature and stored thermal energy are compared with experimental results from a large-scale field test (performed by others). The results of both one-dimensional and two-dimensional simulations are shown to be capable of representing specific aspects of field behaviour. Various sources of meteorological data have been used to define surface boundary conditions. In particular, simulations were performed using (a) data measured on-site, (b) data obtained from the British Atmospheric Data Centre and (c) data generated using analytical expressions from the literature. It was found that correct representation of the heat transfer processes occurring at the soil surface is of critical importance. In particular, it was found that the use of publicly available sources of data, or mathematical/analytical expressions for meteorological data, may be adequate when on-site measurements are not available.
Highlights
The estimation of both thermal fluxes at the soil surface and shallow temperature profiles is important for the design of several engineering applications that either are in direct contact with or otherwise use the soil as a reservoir/source of thermal energy
The study and assessment of infrastructure and systems that store or extract thermal energy from the ground requires an ability to correctly represent the temperature profile of the soil and the amount of energy stored in it as well as to accurately describe the heat fluxes occurring on its surface
Two further formulations discussed by Herb et al (2008) are considered. The first of these was developed by Edinger and Brady (1974) and accounts for natural convection, implying that it can be applied for nonturbulent heat transfer processes
Summary
F hC hE k Lv summer daily average solar radiation: W/m2 winter daily average solar radiation: W/m2 midsummer daily average air temperature: °C fully dense canopy cover evaporation coefficient forced convection weighing coefficient natural convection weighing coefficient: m/(s °C1/3) sheltering coefficient specific heat capacity of air: J/(kg K) midwinter daily average air temperature: °C diurnal shading factor midsummer average amplitude air temperature: °C midwinter average amplitude air temperature: °C convective heat transfer coefficient: W/(m2 K) evaporative heat transfer coefficient: W/(m2 K) soil thermal conductivity: W/(m K) latent heat of vaporisation of water: J/kg qa qG qsat R R1 = 0·5(A − B) R2 = 0·5(A + B) Rd ra,c rs T T1 = 0·5(C − D) T2 = 0·5(C + D) T3 = 0·5(E − F) T4 = 0·5(E + F) Ta,k Tc,k Tk t U a ac as air vapour pressure: kPa surface vapour pressure: kPa saturated vapour pressure: kPa solar radiation: W/m2 solar radiation coefficient: W/m2 solar radiation coefficient: W/m2 effective solar radiation: W/m2 canopy cover aerodynamic resistance: s/m stomata resistance: s/m soil temperature: °C air temperature coefficient: °C air temperature coefficient: °C air temperature coefficient: °C air temperature coefficient: °C air absolute temperature: K canopy cover absolute temperature: K surface absolute temperature: K time: s wind velocity: m/s soil thermal diffusivity: m2/s canopy cover albedo surface albedo. Modelling thermal fluxes at the soil surface Muñoz-Criollo, Cleall and Rees g daily period: s−1 ec canopy cover infrared emissivity eG surface infrared emissivity es sky infrared emissivity qv,a air virtual temperature: °C1/3 qv,s surface virtual temperature: °C1/3 n canopy cover density ra air density: kg/m3 s
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