Transcript Soils and Soil Moisture: Importance from Measurement to

Soil and Soil Moisture:
From Measurement to Mesoscale
Benjamin Hatchett
Division of Atmospheric Sciences
Desert Research Institute
Reno, 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
– Physical Weathering
Reactions!
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…
Melt/Freeze, Wet/Dry =
Expansion/Contraction
(cracks in sidewalk)
time
Water and Wind in Death Valley
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
– Dissolution
– Oxidation
Mg2SiO4 + 4H+ + 4OH- ⇌ 2Mg2+ + 4OH- + H4SiO4
CO2 + H2O -> H2CO3 then H2CO3 + CaCO3 -> Ca(HCO3)2
4Fe + 3O2 → 2 Fe2O3
Soil Structure
• Soils Composed of:
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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 create
voids, called pore spaces
• Porosity = Volume of soil
occupied 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 Conductivity
CV = Volumetric Heat Capacity
K = 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
Warner, 2004
• Note nonlinearities…
– Implications for modeling
Soil Water
• Richards
Equation
(from Darcy’s Law):
K = Hydraulic
conductivity
ψ = Pressure head
θ = Water Content
• Influence of time
and place…
The Surface Energy Budget
Simple Model of the Surface Energy
Budget
Rn H  LE G
Rn = Total Radiation
H = Surface Sensible Heat Flux
LE = Latent Energy Heat Flux
G = 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
Warner, 2004
• Nonlinear evaporation rate
– Limit = hydraulic diffusivity/moisture threshold (remember soil structure!)
• How will model initialization runs vary as a result?
Linked In: Evapotranspiration
Etot=Edir+Et+Ec
Etot = Total Evaportranspiration from Soil and Vegetation
Edir = Direct Evaporation from Soil
Et = Transpiration from Plant Canopy
Ec = Evaporation from Canopy Intercepted Rainfall
Represents 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
Soil Moisture, Soil Temperature, ABL
Heat Flux
• Dry soil heats quickly
with afternoon
insolation, results in
very high sensible
heat flux to boundary
layer
Soil Moisture
Soil Temperature
2m Air Temperature
Large-eddy simulation of a coupled
land-atmosphere system
Sullivan et al. 2000
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.
Modeling the ABL
Siquiera et.al
2008
Bowen Ratio and ABL Heights as Functions
of Soil Moisture
Siquiera et.al
2008
Measurement Methods
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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)
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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 Revisted
Dry 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 2006
Note 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
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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
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Questions????