Soil and Soil Moisture:From Measurement to

Mesoscale

Benjamin HatchettDivision of Atmospheric Sciences

Desert Research InstituteReno, Nevada

Overview• Soils 101• A ‘Deeper View’ of Soil Moisture• Surface Energy Budget and Implications from

Micro to Mesoscale• Measurement Methods

An Introduction to Soils“In the structure and functioning of landscapes, soils are

the matrix through which energy, water, biomass, and nutrients flow…the interface in the cycling of water between the atmosphere and land…the location of large transformations of energy.”

Bonan, 2002

Soil Formation• Two processes form soil– Chemical Weathering Reactions!– Physical Weathering Disintegration!

• Soil type influenced by various factors:– Climate– Geology – Topography– Time

Physical Weathering……Is the actual disintegration of rocks due to SCOURING by wind, water, and/or ice

In simple terms…

time

Water and Wind in Death Valley

Melt/Freeze, Wet/Dry = Expansion/Contraction(cracks in sidewalk)

Plants help too!!!!

Chemical Weathering• Climate important: Kinetic rates increase with

temp.• Rocks dissolve due to reactions between rock

minerals and water, acid, or other chemicals– Hydrolysis Mg2SiO4 + 4H+ + 4OH- 2Mg⇌ 2+ + 4OH- + H4SiO4

– Dissolution CO2 + H2O -> H2CO3 then H2CO3 + CaCO3 -> Ca(HCO3)2

– Oxidation 4Fe + 3O2 → 2 Fe2O3

Soil Structure• Soils Composed of:– Organic Matter (>80% organic soil, <10% mineral soil)– Minerals (From parent geology, ~55% in mineral soil)– Air – Water

• Type, abundance, arrangement of particles govern heat flow, water flow, nutrient availability

5 General Soil Structure Profiles

Place matters!!!

Soil Texture• Relative abundance of sand, silt, and clay determines soil texture• Irregular shapes createvoids, called pore spaces• Porosity = Volume of soiloccupied by air and water

Implications of Porosity• Close packing: How much space?• Sand: Low porosity, large pore space, fast water

movement• Clay: High Porosity, small pore space, very slow

water movement

So, porosity has strong influence on spatial and temporal presence and patterns of soil moisture presence.Has implications for remote sensing and modeling applications

General Patterns?• Soil Type– Don’t worry about

something-sols, think agriculture and place…

• Soil Moisture– Green = Wet– Red/Yellow = Dry

Soil Thermodynamics• Soils are repository of heat– Moderates diurnal and seasonal range in Tsurf– Gain heat during day/warm months– Lose heat during night/cold months

Soil Temperature Equation

C1 = Thermal ConductivityCV = Volumetric Heat CapacityK = Thermal Diffusivity Constant

•Thermal conductivity and heat capacity depend on:•Mineral Composition (e.g. quartz)•Porosity (less pores = higher conductivity)•Organic Matter Content (very porous, low C1, insulate)•Water Content (C1 =20x air, CV = 3500x air)

Thermodynamic Responses to Soil Moisture

• Note nonlinearities…– Implications for modeling

Warner, 2004

Soil Water

• Richards Equation

(from Darcy’s Law):K = Hydraulic

conductivityψ = Pressure headθ = Water Content

• Influence of time and place…

The Surface Energy Budget

Simple Model of the Surface Energy Budget

Rn H LE GRn = Total RadiationH = Surface Sensible Heat FluxLE = Latent Energy Heat FluxG = Ground (Soil) Heat Flux

• Role of Soil in Each Term:•H: Heat from soil warms (-)/cools air (+)•LE: Heat used to evaporate water/freeze water•G: Heat stored in soil (remember C1 and CV terms from thermodynamic equation)

Evaporation Rates and Model Initialization

• Nonlinear evaporation rate– Limit = hydraulic diffusivity/moisture threshold (remember soil structure!)

• How will model initialization runs vary as a result?

Warner, 2004

Linked In: EvapotranspirationEtot=Edir+Et+Ec

Etot = Total Evaportranspiration from Soil and VegetationEdir = Direct Evaporation from SoilEt = Transpiration from Plant CanopyEc = Evaporation from Canopy Intercepted RainfallRepresents a moisture flux that can be approximated by comparing resistances to potential flux (Ohm’s Law: Flux=P/R)

• Resistances include:•Available Soil Moisture•Canopy (Stomatal) Resistance (Vegetation type, ‘Greeness’)•Atmospheric Winds, Stability

Bottom Line: Many Interacting Factors in Soil Moisture/Energy Budget !!!

Microscale• Effect Varies with Topography– Slope– Aspect– Topographic Convergence

• Vegetation Growth– Crops have ideal growth temperature

• Heat stress (out of LE to evaporate, increases H)– Plant diseases due to condensation

• Local Surface Temperatures – Moderated by Soil Moisture

• Wet soils = cold, Dry soils = warm (heat capacity)• Diurnal and seasonal flux of sensible heat• Latent heat use (evaporation cools,

condensation warms)

Influence on Mesoscale Convection• Soil Moisture linked to Mesoscale

Convection (e.g. Betts and Ball 1998, Sullivan et al. 2000)– Remains open research question due

to many feedbacks/complicating factors

– Sometimes wet soils suppress convection, dry soils aid propagation (Taylor and Ellis, 2006)• Role of Evaporation• Patchiness of wet/dry, creating gradients

(Sahel, Central Plains US) that force surface PBL

BUT! Not always true… Findell and Eltahir 2003 found that antecedent wet soils aided convection in SE US

• Dry soil heats quickly with afternoon insolation, results in very high sensible heat flux to boundary layer

Soil Moisture

Soil Moisture, Soil Temperature, ABL Heat Flux

Soil Temperature

2m Air Temperature

Large-eddy simulation of a coupled land-atmosphere system

Response of the atmospheric boundary layer to heterogeneous soil moisture. The dramatic changes in boundary layer structure result from the non-linear dependence of soil properties on soil moisture.

Sullivan et al. 2000

Modeling the ABL

Siquiera et.al 2008

Bowen Ratio and ABL Heights as Functions of Soil Moisture

Siquiera et.al 2008

Measurement Methods• Passive Remote Sensing• Aircraft• Towers• Field Collection

Scales of Measurement• Satellite Data– 50km resolution

• Aircraft Data– 1km resolution

• Tower Data– 10m resolution

• Field Data– To <10cm resolution

• Problem with scale…– Spatial variation in SM at larger scales and application

of same retrieval algorithms to all scales – Nonlinearities, once again!

Field Measurement Techniques• Used to calibrate/verify Remote

Sensing Data• Neutron Depth Moisture Gauge– Single Radium-Berillium source probe– Number of neutrons deflected back to

probe is proportional to H20 in soil– Gives total water content in profile

• Gamma Meter– Two probes, Cs 137 in one, detector in

other– Intensity of radiation received

proportional to density of material, density in soil constant except for changes in water content

Factors in Soil Reflectance• “A goal of remote sensing is to disentangle spectral

response recorded and indentify proportions and influences of the characteristics within the instantaneous field of view of the sensor system” (Jensen, 2007)– Soil Texture– Soil Moisture Content– Organic Matter– Fe-Ox Content– Salinity– Surface Roughness– Vegetation

Soil Response

• Note absorption bands• Why wet soils appear

darker!• Implications of SM:• Precipitation• Measurement timing• Soil type!

Porosity RevistedDry Soil Wet Soil

Microwave Remote Sensing• Use of RADAR

-Pulse of microwave energy that interacts with Earth’s terrain-Measure of material’s electrical characteristics:

-Complex Dielectic Constant “ability to conduct electrical energy” (why microwave!)-Dry surfaces = 3-8um-Water = 80um-Therefore, amount of moisture on surface influence amount of backscattered energy

Jackson (1993) Inverse Soil Moisture Retrieval Model

• Model is a summation of research since 1970s that has established and verified use of passive microwave emission from land surfaces

Advanced Microwave Scanning Radiometer: Earth Observing System (AMSR-E)

West Africa, June 2006Note Moisture Gradient, Pattern

Gantner et. al

Food for Thought…• Soil moisture is difficult phenomena to measure

and model because…– Place matters! (Soil type, vegetation, topography)– Time matters! (For measurement, e.g. pre/post

precip, initial conditions)

But Improving Our Understanding and Measurement Capabilities Will…

• Improve Land Surface Component of Coupled Models

• Increase abilities to forecast:– Convective Processes– Seasonal Climate– QPF

References• Bonan, G. 2002 Ecological Climatology. Cambridge Univ. Press• Betts, A. K., and J. H. Ball, 1998 J. Atmos. Sci., 55, 1091–1108.• Findell, K. L., and E. A. B. Eltahir, 2003 J. Hydrometeorology, 4, 552-569• Findell, K. L., and E. A. B. Eltahir 2003 J. Hydrometeorology, 4, 570-583• Findell, K.L. 2003 Journal of Geophysical Research 108(d8): 8385• Harpstead, M.I., T.J. Sauer, W.F. Bennett. 2001 Soil Science Simplified. Blackwell Publishing• Jensen, J.R. 2007 Remote Sensing of the Environment. Prentice Hall.• Marshall, C. 1999 COMAP Symposium 99-1• Taylor C.M., and Ellis R.J. 2006 Geophysical Research Letters 33(3) • Siqueira, M., K. Gabriel, Submitted 2008. J. Hydrometeorology• Warner, T.T. 2004. Desert Meteorology. Cambridge Univ. Press• https://courseware.e-education.psu.edu/simsphere/workbook/figures/7.3.gif• http://www.nrmsc.usgs.gov/files/norock/research/soil_moisture.gif• http://www.mmm.ucar.edu/modeling/les/images/les_lg.jpg• http://nature.berkeley.edu/biometlab/images/olive_apilles.GIF• http://grapevine.com.au/~pbeirwirth/images/bagoview.jpg• http://oceanworld.tamu.edu/resources/environment-book/groundwater.html• http://www.orcbs.msu.edu/environ/programs_guidelines/wellhead/glossary_faq/

capillary_fringe.jpg• http://techalive.mtu.edu/meec/module06/Packing.htm• http://research.eeescience.utoledo.edu/lees/papers_PDF/Saxton_1986_SSSAJ_files/Fig_6.gif• http://www.eol.ucar.edu/projects/cases/maps.html• http://gis.esri.com/library/userconf/proc99/proceed/papers/pap365/p3654.gif• http://weather.msfc.nasa.gov/surface_hydrology/surface_hydrology_inverse_model.html

Questions????