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Research at Virginia Tech
ByDr. John M. Galbraith
May 2006
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Jim Baker
• Updated the VALUES database in Virginia– Dataset of all soil series with soil properties and yields
of crops and forages– Data is used for land value assessment and for
nutrient management planning
• Research is conducted by VA Dept. Health employees supervised by Jim on septic system efficiency and suitability of C horizons for percolation
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Dr. Matt Eick and Lucien Zelazny
• P-index for Virginia (progress)
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Carl Zipper
• Powell River Research and Education Center Director– (With Galbraith and Prisley and Wynne) – Carbon sequestration potential for marginal
farmland in VA under various future land use scenarios
• Based on STATSGO and HEL definition• Identifies marginal cropland and current land use• Identifies buffers around streams in cropland that
may be reforested
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W. Lee Daniels• Mineral sand mining reclamation
– Sand mining removes entire regolith, separates heavy mineral sands, replaces dispersed sediment back into pits.
– Problems• sands and clays (slimes) separated vertically and horizontally
in the deposit• Topsoil replaced when slimes are still wet or not replaced at
all– Solutions
• Work the soil when dry, rip 2 directions, apply phosphorus and lime and seed to a mixture of legumes and nurse crops
• Second or third year, return to normal cropping and fertilization
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W. Lee Daniels
• Mountaintop Mining– (With Haering and Galbraith and Thomas)
Four articles published on mapping and reclamation of mine soils
– Recognition of densic horizons and restricted depth classes
– 2 new series proposed on mined areas– Recognition of impeded drainage classes– Subsidence interpretations– Land use interpretations
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W. Lee Daniels
• N-index – With Pat Donovan, developing a N-index for
soil management in VA
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W. Lee Daniels
• Wetlands– Working with VDOT to develop an
assessment of their wetland mitigation success – 10 pairs of mitigated wetlands-reference wetlands, study near completion
– Recommendations for reclamation, creation, and mitigation of wetlands for state agencies and consultants
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Differential Soil Properties at Fort Lee (Cummings, 1999)
0-15 cm pH % C % N
Reference 4.76 2.89 0.18
Mitigation 5.31 0.82 0.07
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Differential Soil Properties at Fort Lee (Cummings, 1999)
Bulk DensityMg/m3
Surface(0-15 cm)
Subsurface(70 cm)
Reference 0.71 1.42
Mitigation 1.75 1.71
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W. Lee Daniels
• Acid-Sulfate soils– Problem
• Very low pH• Poor water quality• Corrosion steel and concrete• Toxic to fish and microbes• Subsidence
– Solution• Identify location of deposits• Classify the potential hazards of each deposit
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Inside the culvert at Clifton Forge
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o PPA < 10 Mg CaCO3/1000 Mg material (total-S < 0.2%): can readily be managed.
o PPA 10 - 60 Mg CaCO3/1000 Mg material (total-S = 0.2 - 2%): can be remediated with intense management.
o PPA > 60 Mg CaCO3/1000 Mg material (total-S > 2%): extremely difficult to remediate.
If sulfidic materials can have high pH values, then how do we know how bad they are?
Potential peroxide acidity (PPA) and total-S
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Compiling a state-wide sulfide hazard map for Virginia: the final
map.
Sulfides undocumented1
2
3
4
Sulfides documentedN
Sulfides undocumented
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Compiling a state-wide sulfide hazard map for Virginia: the final map.
All formations, based on draft version of digital
geologic map of Virginia.
CharacterizedNot characterized
Sulfides documented. Acid potential unknown.
Sulfides not documented.
1: PPA < 10; S < 0.5%.
2: PPA < 10; S > 0.5%.
3: PPA 10 - 60.
4: PPA - more than 10% of samples > 60.
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John Galbraith
Focus Areas– Wetlands: Inventory, Soils, Hydrology, and
Mitigation– Mine Soil: Reforestation potential, Mapping,
Classification, Interpretation, and Hydrology– Urban Soil: Mapping, Classification,
Interpretation, and Hydrology– GIS Resource Inventory and Analysis (SOC)– Decision Support Systems and User Guides
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DSS Projects
http://clic.cses.vt.edu/SoilsInfo/– Va_Septic – based on Soil Data Viewer– Va_On-site – based on VHD regulations– SSURGO 2.x User’s Guide– Pasture Land Management System (PLMS)– Charts for Ver. 5.0 Field Indicators of Hydric
Soils (soon to be available at Mid-Atlantic Hydric Soils Committee web site)
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John Galbraith
• Andy Jones, Galbraith, Burger, Fox, Zipper– Problem – Abandoned mine soils are
intentionally compacted, smoothed, seeded to fescue and Sericea lespedeza, and grazed. Native seedlings cannot reestablish.
– Solution - Identify soils where establishment of trees is economically and environmentally feasible and cost-effective.
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Forest Capability Class
• We developed a suitability classification based on B.D., % rocks, pH, E.C., slope, aspect, and rooting depth (water holding capacity)
• Soils can be rated to see if it is economical to plant either hybrid poplar, white pine, native oaks, or if it should be left alone and grazed
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LandLand--use Effects on Growing Season use Effects on Growing Season Length Indicators in Southeast Virginia Length Indicators in Southeast Virginia
Wet FlatsWet Flats (Great Dismal Swamp) Amanda C. Burdt and John M. Galbraith
– Problem: Growing season misses the seasonal high water table, and the growing season used for regulations is incorrect
– Solution: Measure hydric soils indicators, soil temperatures, growing seasons, and hydrology under three land uses
(Published 2005)
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Treatments
3
21
Forest
Early-successionalfield
Tilled bare ground
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Hydroperiod for Hall Property in 2001
-50
-40
-30
-20
-10
0
10
20
12/30/00 2/18/01 4/9/01 5/29/01 7/18/01 9/6/01 10/26/01 12/15/01 2/3/02 3/25/02 5/14/02
Wat
er ta
ble
dept
h (c
m)
Forest (Well 10)Field (Well 5)Bare ground (Well 3)
0
1
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12/30/00 2/18/01 4/9/01 5/29/01 7/18/01 9/6/01 10/26/01 12/15/01 2/3/02 3/25/02 5/14/02
Date
Prec
ipita
tion
(cm
)
frost-free days frost-free
30 cm depth
rainfall
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Soil Temperature at 50 cm at Hall
Crossover of forest treatment occurs in March and SeptemberCrossover of forest treatment occurs in March and September
~ 3 to 5 °C
0
5
10
15
20
25
30
12/30/00 2/18/01 4/9/01 5/29/01 7/18/01 9/6/01 10/26/01 12/15/01 2/3/02 3/25/02 5/14/02 7/3/02Date
Soil
tem
pera
ture
(oC
)
ForestFieldBare
Crossover of forest treatment occurs in March and SeptemberCrossover of forest treatment occurs in March and September
~ 3 to 5 °C
Circles represent times where soil temp. was below 5C. Blue bars are “growing season”
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Results and Conclusions1. For the Great Dismal Swamp Ecosystem in Southeast Virginia,
the published frost-free days “growing season” is March 14 to Nov. 29 (259 days) on the east side and March 29 to Nov. 7 (222 days) on the west side.
2. We found the growing season measured at 50cm to be year round under forest, and all but one week under early successional(field) and under bare cropland.
3. The coldest days were in the first two weeks of January.
4. The forest soil was warmer and drier than the field which was warmer and drier than the cropland.
5. A year round growing season should be declared for all thermicwetlands, maybe all mesic wetlands as well. Frigid?
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Measuring CO2 efflux from wetland soils under three land uses
• Problem: Hard to measure soil temperature at 50 cm
• Solution: Measure CO2 efflux at surface as a measure of biological activity
• Results and Conclusions: CO2 efflux in Forest > Field > Cropland.
• Could use 5C to estimate base rate of efflux, use that to see when activity was at a minimum.
(published 2006)
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CO2 and Soil Temperature Relations –Treatment Differences
Note: The relationships between the natural log of the soil CO2 efflux rates and measured soil temperature and moisture at 15 cm were analyzed using multiple regression analysis (Neter et al., 1996) using SAS™ software (Statistical Analysis Systems, Cary, NC).
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CO2 and the Baseline in a Forest Plot
0
5
10
15
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40
2/11
2/16 3/7 3/20 4/7 5/7 6/6 7/3 8/5 9/2 10/7
11/3
11/14 12
/112
/14 1/1 1/20 2/2 2/17 3/4 3/16 4/6 5/5 6/13
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2001 and 2002 Sampling Dates
Soil
CO
2Ef
flux
Rat
es (µ
mol
m-2
s-1)
Soil
Tem
pera
ture
(°C
) and
Soi
l Moi
stur
e (%
)
Soil Temperature at 15 cm Soil CO2 Efflux Soil Moisture to 15 cm
(0.3 CO2 baseline)
CO2 efflux is dependent on soil temperature and moisture. Red – temperature dip
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HGM, Hydrology and Hydric Soil Indicators in Piedmont Slope Wetlands and Wet
Floodplains
• Problem: Soils at inflection point of hill and in floodplain are wet, don’t always meet an indicator
• Solution: Measure the hydrology and hydric soil technical standard
• Results and Conclusions: Soils are hydric. In backswamps, water may be oxygenated. At the inflection point, water flows through, may take Fe with it. High OC at inflection point masks indicators.
(in publication draft stage)
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Discharge in Humid Riverine Systems With Seeps
GroundwaterDischarges in rock fissures
River
Regional Water Table
Impermeable layer, possibly bedrock
Gravelly layer
Flooding Recharge
Runoff recharge
YazoostreamBackswamp
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Study Site:5 Landscape Positions
Terraces and Uplands
InflectionMidpointMidpoint
LeveeLevee
River
Monitoring Well
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Rt.6
29
Levee
Midpoint
InflectionInflection
Upland
HighlandTerrace
Monitoring Well
River
Non-hydric
Non-hydric
Used to develop New Indicator F19
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Using public domain data to predict the occurrence of hydric soil
Published 2004
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Integrating National Wetland Integrating National Wetland Inventory maps using Remote Inventory maps using Remote
Sensing and GIS toolsSensing and GIS tools
Eva Pantaleoni and John Galbraith, Virginia Tech
2006(in progress)
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Using Remote Sensing to Improve NWI
• Purpose: To explore the ability of raw ASTER bands and GIS data layers in predicting wetland location using a logistic regression model
• ASTER bands are able to detect wetland with an accuracy of 28% when open water features are not included in the model.
• The model improves significantly when soil, hydrographyand elevation data are introduced in the model (accuracy=52% at 0.95 probability level).
• Most of misclassified wetlands were forested wetlands• Other errors were due to the dry year and
georectification problems (pixels did not match)
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Compare this areato ASTER wetlands
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Compare this areato NWI wetlands
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Assessment of National Wetlands Inventory (NWI) Landscape Position
Classification SystemAlexis E. Sandy and John M. Galbraith
• The National Wetland Inventory (NWI) is a project of the FWS that has produced wetland maps for approximately 90 percent of the coterminous United States (US Fish and Wildlife Service, 2002).
• They are adding hydrogeomorphic and other characteristic descriptors that are needed for assessment of wetland functions
• Updating process is still conducted manually
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Functions Implied by Landscape Position Descriptors
• Functions Implied– Surface water detention– Stream flow maintenance– Shoreline stabilization– Nutrient transformation– Sediment retention
• Procedure: 180 wetlands representing 6 landscape positions were visited and soils, vegetation, and hydrology indicators recorded.
• The data were input to see if they clustered and differentiated enough to be diagnostic for making an automated method to identify the 6 positions.
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PRELIMINARY RESULTS: Wetland Plant Status
ES1
ES2ES3ES4
ES5ES6
ES7ES8ES9ES10
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ES12ES13ES14ES15
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ES18ES19
ES20
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ES25ES26
ES27ES28ES29
ES30
LE1
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LE12LE13LE14
LE15LE16
LE17LE18LE19LE20
LE21
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LE25LE26
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LE30
LR1LR2
LR3
LR4LR5
LR6LR7
LR8LR9
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LR19LR20
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LR22LR23LR24LR25
LR26LR27
LR28LR29
LR30
LS1 LS2
LS3LS4
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LS8LS9
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LS15LS16
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LS19LS20LS21
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LS26LS27 LS28
LS29LS30
TE1
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TE7TE8
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TE12TE13TE14
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PO1PO2
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PO18 PO19
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Axis 1
Axis 2
•Stress = 0.136
•Dimensions = 3
Legend:ES = EstuarineLE = LenticLS = Lotic StreamLR = Lotic RiverPO = PondTE = Terrene
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PRELIMINARY RESULTS: Hydrology Primary & Secondary
Indicators
ES1ES2ES3ES4ES5ES6ES7ES8ES9ES10ES11ES12ES13ES14ES15ES16ES17ES18ES19ES20ES21ES22ES23ES24ES25ES26ES27ES28ES29ES30
LE1
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LE3LE4LE5
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LE15LE16
LE17 LE18
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LE23 LE24
LE25
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LE30
LR1LR2LR3LR4LR5LR6LR7LR8LR9LR10LR11LR12LR13LR14LR15LR16LR17LR18LR19LR20LR21LR22LR23LR24LR25LR26LR27LR28LR29LR30
LS1LS2
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LS8LS9
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LS11LS12
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LS21 LS22
LS23
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LS25 LS26LS27
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TE1
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TE31TE32
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TE36
PO1
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PO4PO5PO6PO7
PO8PO9
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PO11PO12
PO13PO14
PO15PO16
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PO23PO24
PO25
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PO29
PO30
Axis 1
Axis 2
•Stress = 0.097
•Dimensions = 3
Legend:ES = EstuarineLE = LenticLS = Lotic StreamLR = Lotic RiverPO = PondTE = Terrene
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PRELIMINARY RESULTS: Field Hydric Soil Indicators
•Stress = 0.117
•Dimensions = 3
Legend:ES = EstuarineLE = LenticLS = Lotic StreamLR = Lotic RiverPO = PondTE = Terrene
ES1ES2ES3ES4ES5ES6ES7ES8ES9 ES10ES11ES12ES13ES14ES15 ES16ES17ES18ES19 ES20ES21ES22ES23ES24ES25ES26 ES27ES28ES29 ES30
LE1
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LE26
LE27LE28
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LR1LR2LR3LR4LR5LR6LR7LR8
LR9
LR10LR11
LR12LR13
LR14LR15
LR16
LR17LR18
LR19
LR20
LR21
LR22LR23LR24LR25LR26LR27
LR28LR29
LR30
LS1LS2LS3LS4
LS5
LS6LS7
LS8
LS9LS10LS11LS12LS13LS14LS15LS16LS17LS18LS19LS20LS21LS22LS23LS24LS25
LS26LS27
LS28
LS29
LS30
TE1
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TE8TE10TE11
TE12
TE13TE14
TE15
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TE19TE20
TE23
TE25
TE26TE27TE28
TE29TE30
TE31TE32
TE33TE34TE35TE36
PO1
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PO5PO6
PO7PO8
PO9
PO10PO11
PO12
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PO22 PO23
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PO26PO27PO28
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PO30
Axis 1
Axis 2
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PRELIMINARY RESULTS
Distance Measure Axis Stress† Increment Cumulative Axis Pair r Orthogonality
-------%-------1 0.255 0.660 0.660 1 vs 2 -0.438 80.92 0.190 0.116 0.776 1 vs 3 0.288 91.73 0.136 0.118 0.893 2 vs 3 -0.205 95.8
1 0.344 0.441 0.441 1 vs 2 -0.167 97.2Jaccard 2 0.179 0.247 0.687 1 vs 3 0.095 99.1
3 0.097 0.272 0.960 2 vs 3 -0.130 98.3
1 0.368 0.237 0.237 1 vs 2 -0.058 99.7
Jaccard 2 0.185 0.334 0.571 1 vs 3 -0.164 97.3
3 0.117 0.318 0.889 2 vs 3 0.346 88.0† Kruskal's Stress Measure; stress of 0.20 = poor; 0.10 = fair; 0.050 = good; 0.025 = excellent; 0.000 = perfect.
Hydrology Primary and Secondary Indicators
Hydric Soil Characteristics
and Field Indicators of Hydric Soil
Bray-Curtis (Sorenson)
R2
Wetland Plant Indicator Status
Table I-1. Measures of Kruskal's stress, proportion of variance explained (R2), and orthogonality for dimensions retained for NWI landscape position classes as a result of a Non-metric Multidimensional Scaling (NMS) analysis. Analysis is based on field validated wetland plant occurrence, hydrology primary and secondary indicators, and hydric soil characteristics and field indicators of hydric soil.
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Other Wetland-related Studies– Multi-state Problem Red Parent Materials Study
– Multi-state Piedmont Floodplains Indicator Study
– Proposed (Multi-state Young Sandy Dune Soils Indicator) may include use of Lidar and multispectral data to ID and locate sandy wetlands and use of photospectroscopy to ID SOC content in sandy soils
– Eh change/time in-situ study (leave for 4 hrs)
– Impact of roads on wetlands in rural and suburban Virginia Coastal Plain areas
– Using Wetness Index to enhance NHD stream network data in the Ridge and Valley
– Mine Soil Wetlands and Series Drainage Class Study at Powell River
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Hydrology and drainage class study for coal mine soils
Neo-wetlands formed in 20 years on mine soil in southwest Virginia. Soils with dense, compacted subsoils perch water on or near the surface, forming wetlands. The soils range from somewhat excessively drained to very poorly drained, yet are mapped as a consociation of excessively drained soils with a few wet spot symbols.
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Urban Soils Hydrology Study
• In Fairafx Co., VA we have selected two-three sites where we will install piezometernests to determine hydrologic drainage patterns in representative urban soils
• Study to begin in 2006
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Research Programs• Wetlands and Stream Ecology http://clic.cses.vt.edu/soils/wetlands/Wetlands_VT_2006.pdf
• GIS, GPS, and Remote Sensing http://clic.cses.vt.edu/soils/OGIS.pdf