Anne Verhoef is Senior Lecturer (Associate Professor) in Soil Physics and Micrometeorology at the University of Reading, Reading, UK. Dr Verhoef has expertise in: (i) Land surface simulation modelling and experimental campaigns relating to heat, water and gas transfer in soils, as well as to the land surface energy-, water and carbon balance; ii) within soil and -canopy transfer of heat, water and gas. Special interest is in the area of soil thermal properties and soil heat flux. She has led major programmes of work in these research areas in the UK and abroad (EFEDA, HAPEX-Sahel). She currently has 4 large UK NERC grants (a further 3 previously), on 2 of those she is the PI. She collaborates widely with researchers in the UK and overseas.
This paper describes a method that employs Earth Observation (EO) data to calculate spatiotempora... more This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.► We employ Earth Observation data to calculate area-average values of soil heat flux. ► The method involves harmonic analysis of land surface temperature (LST) data. ► Thermal inertia is derived from soil texture and soil moisture data. ► Improved large-scale estimates of soil heat flux will aid model verification. ► More reliable soil heat flux estimates will improve energy balance closure.
Soil moisture content, θ, of a bare and vegetated UK gravelly sandy loam soil (in situ and repack... more Soil moisture content, θ, of a bare and vegetated UK gravelly sandy loam soil (in situ and repacked in small lysimeters) was measured using various dielectric instruments (single-sensor ThetaProbes, multi-sensor Profile Probes, and Aquaflex Sensors), at depths ranging between 0.03 and 1 m, during the summers of 2001 (in situ soil) and 2002 (mini-lysimeters). Half-hourly values of evaporation, E, were calculated from diurnal changes in total soil profile water content, using the soil water balance equation.For the bare soil field, Profile Probes and ML2x ThetaProbes indicated a diurnal course of θ that did not concur with typical soil physical observations: surface layer soil moisture content increased from early morning until about midday, after which θ declined, generally until the early evening. The unexpected course of θ was positively correlated to soil temperature, Ts, also at deeper depths. Aquaflex and ML1 ThetaProbe (older models) outputs, however, reflected common observations: θ increased slightly during the night (capillary rise) and decreased from the morning until late afternoon (as a result of evaporation). For the vegetated plot, the spurious diurnal θ fluctuations were less obvious, because canopy shading resulted in lower amplitudes of Ts. The unrealistic θ profiles measured for the bare and vegetated field sites caused diurnal estimates of E to attain downward daytime and upward night-time values.In the mini-lysimeters, at medium to high moisture contents, θ values measured by (ML2x) ThetaProbes followed a relatively realistic course, and predictions of E from diurnal changes in vertically integrated θ generally compared well with lysimeter estimates of E. However, time courses of θ and E became comparable to those observed for the field plots when the soil in the lysimeters reached relatively low values of θ. Attempts to correct measured θ for fluctuations in Ts revealed that no generally applicable formula could be derived.
A soil vegetation atmosphere transfer scheme (SVAT), describing the fluxes of heat, water vapour ... more A soil vegetation atmosphere transfer scheme (SVAT), describing the fluxes of heat, water vapour and CO2 between a multi-component vegetated land surface and the atmosphere, has been developed. The SVAT has been calibrated and tested using 30 days of micrometeorological and physiological measurements collected over a sparse savannah in the Sahel. The model explicitly represents the four major functional components of the savannah: shrubs (C3 photosynthesis), grasses (C4), herbs (C3) and bare soil. The leaf conductance model for the shrub, grass and herb components was calibrated against porometry measurements made in the field. The performance of the SVAT was tested against independent surface flux and temperature measurements. Agreement between the model predictions and measurements of the total net radiation, sensible and latent heat fluxes, net CO2 exchange and surface temperatures was good: in all cases at least 80% of the variance in the measurements was explained by the model. Separate flux and surface temperature predictions for the four surface components were satisfactory, although complete verification was difficult as data were lacking for some variables. Predicted water use efficiency (WUE) of the vegetation showed a strong, non-linear dependence on vapour pressure deficit, especially for the bushes and the grasses. WUE for the grasses was about three times as large as the values found for the bushes and herbs. A SVAT model like this can be employed to address the possible effects of CO2 enrichment and climate change on the competitive balance between different species in a plant community or in research concerning productivity and water use efficiency in mixed crops, such as agroforestry systems.
This paper describes a method that employs Earth Observation (EO) data to calculate spatiotempora... more This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.► We employ Earth Observation data to calculate area-average values of soil heat flux. ► The method involves harmonic analysis of land surface temperature (LST) data. ► Thermal inertia is derived from soil texture and soil moisture data. ► Improved large-scale estimates of soil heat flux will aid model verification. ► More reliable soil heat flux estimates will improve energy balance closure.
Soil moisture content, θ, of a bare and vegetated UK gravelly sandy loam soil (in situ and repack... more Soil moisture content, θ, of a bare and vegetated UK gravelly sandy loam soil (in situ and repacked in small lysimeters) was measured using various dielectric instruments (single-sensor ThetaProbes, multi-sensor Profile Probes, and Aquaflex Sensors), at depths ranging between 0.03 and 1 m, during the summers of 2001 (in situ soil) and 2002 (mini-lysimeters). Half-hourly values of evaporation, E, were calculated from diurnal changes in total soil profile water content, using the soil water balance equation.For the bare soil field, Profile Probes and ML2x ThetaProbes indicated a diurnal course of θ that did not concur with typical soil physical observations: surface layer soil moisture content increased from early morning until about midday, after which θ declined, generally until the early evening. The unexpected course of θ was positively correlated to soil temperature, Ts, also at deeper depths. Aquaflex and ML1 ThetaProbe (older models) outputs, however, reflected common observations: θ increased slightly during the night (capillary rise) and decreased from the morning until late afternoon (as a result of evaporation). For the vegetated plot, the spurious diurnal θ fluctuations were less obvious, because canopy shading resulted in lower amplitudes of Ts. The unrealistic θ profiles measured for the bare and vegetated field sites caused diurnal estimates of E to attain downward daytime and upward night-time values.In the mini-lysimeters, at medium to high moisture contents, θ values measured by (ML2x) ThetaProbes followed a relatively realistic course, and predictions of E from diurnal changes in vertically integrated θ generally compared well with lysimeter estimates of E. However, time courses of θ and E became comparable to those observed for the field plots when the soil in the lysimeters reached relatively low values of θ. Attempts to correct measured θ for fluctuations in Ts revealed that no generally applicable formula could be derived.
A soil vegetation atmosphere transfer scheme (SVAT), describing the fluxes of heat, water vapour ... more A soil vegetation atmosphere transfer scheme (SVAT), describing the fluxes of heat, water vapour and CO2 between a multi-component vegetated land surface and the atmosphere, has been developed. The SVAT has been calibrated and tested using 30 days of micrometeorological and physiological measurements collected over a sparse savannah in the Sahel. The model explicitly represents the four major functional components of the savannah: shrubs (C3 photosynthesis), grasses (C4), herbs (C3) and bare soil. The leaf conductance model for the shrub, grass and herb components was calibrated against porometry measurements made in the field. The performance of the SVAT was tested against independent surface flux and temperature measurements. Agreement between the model predictions and measurements of the total net radiation, sensible and latent heat fluxes, net CO2 exchange and surface temperatures was good: in all cases at least 80% of the variance in the measurements was explained by the model. Separate flux and surface temperature predictions for the four surface components were satisfactory, although complete verification was difficult as data were lacking for some variables. Predicted water use efficiency (WUE) of the vegetation showed a strong, non-linear dependence on vapour pressure deficit, especially for the bushes and the grasses. WUE for the grasses was about three times as large as the values found for the bushes and herbs. A SVAT model like this can be employed to address the possible effects of CO2 enrichment and climate change on the competitive balance between different species in a plant community or in research concerning productivity and water use efficiency in mixed crops, such as agroforestry systems.
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Papers by Anne Verhoef