SlideShare ist ein Scribd-Unternehmen logo
1 von 20
Comparison of One and Three
Dimensional MODFLOW
Subsidence Results
Dave Colvin - Leonard Rice Engineers
NGWA Groundwater Summit
Garden Grove, CA
May 7, 2012
1
Purpose
and
Need
2
Subsidence Overview
• Lowering of ground
surface
• Based on Terzaghi
equation
• Before pumping,
geostatic load (pressure
or stress) is balanced
• Pumping reduces pore
pressure; increases
stress on ‘skeleton’
• “Stress” = Change in
water level
Reference:
Poland (1984). Guidebook to Studies of Land
Subsidence due to Ground Water Withdrawal.
UNESCO. International Hydrological Programme
Working Group
Data Characteristics
• Long periods of record
• Accurate monitoring
results
• Varied collection
methods
• Varied data types
• Expensive
4
• Drilling and Well
Testing
• Remote Sensing
• Survey Based
• Geotechnical
Laboratory Analyses
• Geophysics
– Downhole
– Airborne/Surface
Data Collection Methods
Subsidence Modeling
Data Collection
Conceptual Model Development
3D Lithology Database
Conceptual Model Development
3D Lithology Database
Conceptual Model Development
3D Lithology Database
Conceptual Model Development
3D Lithology Database
Conceptual Model Development
3D Lithology Database
Groundwater
Clay Layer 1
Clay Layer 2
Upper Aquifer
Middle Aquifer
Lower Aquifer
Ground Surface
Constant Head Cells
-defined by water level
elevations
or
-groundwater flow
model heads
1D Subsidence Concept
USGS MODFLOW SUB-WT
• Simulates vertical
compaction in
groundwater flow
models
• Simulates groundwater
storage changes in
aquitards (or interbeds)
• Calculates changes in
geostatic stress due to
lowering of the water
table
• Allows for time variable
hydraulic and
subsidence properties
Reference:
Galloway and Leake(2007) MODFLOW Ground Water Model - User Guide to the
Subsidence and Aquifer-System Compaction Package (SUB-WT) for Water Table
Aquifers. U.S. Geological Survey Techniques and Methods 6-A23.
Modeled Head Impacts
using SUB-WT
0.0
50.0
100.0
150.0
200.0
250.0
300.0
350.0
400.0
450.0
500.0
550.0
600.0
Drawdown(ft)
Year
3D SUB-WT Model
Drawdown Result Comparison
Base Model Well #1
SWT Model - Well #1
Base Model Well #2
SUB-WT Model Well #2 Maximum
difference of 27.8
feet
MODFLOW Subsidence Water Budget Impacts
Reference:
Faunt, C.C., ed., 2009, Groundwater Availability of the Central Valley Aquifer,
California: U.S. Geological Survey Professional Paper 1766
Clay Layer 1
Compaction
3D Subsidence Models
1D vs. 3D SUB-WT
Subsidence Results
840
860
880
900
920
940
960
980
1000
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1940 1960 1980 2000 2020 2040 2060 2080 2100 2120
GroundWaterLevel(ftNAVD88)
Subsidence(ft)
Year
1D vs. 3D Subsidence Model Comparison
3D Modeled Subsidence
1D Modeled Subsidence
Head
1D vs. 3D SUB-WT
Subsidence Results
Modeled Subsidence Results (Feet)
Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Scenario 6 Scenario 7 Scenario 8
Year 3D 1D 3D 1D 3D 1D 3D 1D 3D 1D 3D 1D 3D 1D 3D 1D
2020 0.4 0.5 0.4 0.5 0.4 0.5 0.3 0.5 0.3 0.4 0.3 0.4 0.3 0.4 0.3 0.4
2080 0.7 0.9 1.2 1.5 1.5 1.9 1.1 1.4 0.8 1.1 1.1 1.4 1.7 2.0 1.3 1.5
2117 0.8 1.0 1.2 1.5 1.5 1.9 1.1 1.4 1.0 1.2 1.2 1.6 1.8 2.2 1.3 1.6
3D - Percent of 1D
Result
78% 77% 78% 78% 78% 78% 84% 82%
Water
movement
horizontally
and vertically
within
aquifers and
aquitards
Groundwater
Clay Layer 1
Clay Layer 2
Upper Aquifer
Middle Aquifer
Lower Aquifer
Ground Surface
Movement
of water
restricted
to the
vertical
plane
1 D 3 D
3D Subsidence Models
Conclusions
• Use of the MODFLOW
subsidence packages can
have significant impacts on
model predicted:
– Head
– Storage
• 1D subsidence modeling
may be more appropriate in
locations where:
– Available data are obtained
from one borehole or
location
– Geologic heterogeneity of
clay thickness or bedrock
structure is poorly
understood
– Regional groundwater flow
models are not available
• 1D models assume that
horizontal flow is
insignificant compared to
other storage and water
budget components
• 1D subsidence models over
predict subsidence by
approximately 20%
• 3D groundwater flow
modeling may be used to
obtain subsidence results in
one cell
• Availability and quality of
input data must be balanced
with the confidence needs in
the subsidence predictions
18
QUESTIONS?
19
THANK YOU!
20

Weitere ähnliche Inhalte

Was ist angesagt?

Validation_SWOT_ground_airborne_Fjortoft.ppt
Validation_SWOT_ground_airborne_Fjortoft.pptValidation_SWOT_ground_airborne_Fjortoft.ppt
Validation_SWOT_ground_airborne_Fjortoft.ppt
grssieee
 
Dimitrov_IGARSS.ppt
Dimitrov_IGARSS.pptDimitrov_IGARSS.ppt
Dimitrov_IGARSS.ppt
grssieee
 
APPLICATION OF KRIGING IN GROUND WATER STUDIES
APPLICATION OF KRIGING IN GROUND WATER STUDIESAPPLICATION OF KRIGING IN GROUND WATER STUDIES
APPLICATION OF KRIGING IN GROUND WATER STUDIES
Abhiram Kanigolla
 
MO4_T04_3_R_Sato.pptx
MO4_T04_3_R_Sato.pptxMO4_T04_3_R_Sato.pptx
MO4_T04_3_R_Sato.pptx
grssieee
 
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Achmad Darul
 
Thresholds of Detection for Falling Snow from Satellite-Borne Active and Pas...
Thresholds of Detection for Falling Snow  from Satellite-Borne Active and Pas...Thresholds of Detection for Falling Snow  from Satellite-Borne Active and Pas...
Thresholds of Detection for Falling Snow from Satellite-Borne Active and Pas...
grssieee
 
ASCE Cold Region Conference-July 2015 (1)
ASCE Cold Region Conference-July 2015 (1)ASCE Cold Region Conference-July 2015 (1)
ASCE Cold Region Conference-July 2015 (1)
Pegah Rajaei
 
20110728_IGARSS_GDPS(ryu)fin1.pptx
20110728_IGARSS_GDPS(ryu)fin1.pptx20110728_IGARSS_GDPS(ryu)fin1.pptx
20110728_IGARSS_GDPS(ryu)fin1.pptx
grssieee
 
MONITORING LONG TERM VARIABILITY IN THE ATMOSPHERIC WATER VAPOUR CONTENT USIN...
MONITORING LONG TERM VARIABILITY IN THE ATMOSPHERIC WATER VAPOUR CONTENT USIN...MONITORING LONG TERM VARIABILITY IN THE ATMOSPHERIC WATER VAPOUR CONTENT USIN...
MONITORING LONG TERM VARIABILITY IN THE ATMOSPHERIC WATER VAPOUR CONTENT USIN...
grssieee
 
WETLAND MAPPING USING RS AND GIS
WETLAND MAPPING USING RS AND GISWETLAND MAPPING USING RS AND GIS
WETLAND MAPPING USING RS AND GIS
Abhiram Kanigolla
 
A_Framework_of_Ontology-Based_Knowledge_Information_Processing_for_Change_Det...
A_Framework_of_Ontology-Based_Knowledge_Information_Processing_for_Change_Det...A_Framework_of_Ontology-Based_Knowledge_Information_Processing_for_Change_Det...
A_Framework_of_Ontology-Based_Knowledge_Information_Processing_for_Change_Det...
grssieee
 

Was ist angesagt? (19)

Validation_SWOT_ground_airborne_Fjortoft.ppt
Validation_SWOT_ground_airborne_Fjortoft.pptValidation_SWOT_ground_airborne_Fjortoft.ppt
Validation_SWOT_ground_airborne_Fjortoft.ppt
 
Dimitrov_IGARSS.ppt
Dimitrov_IGARSS.pptDimitrov_IGARSS.ppt
Dimitrov_IGARSS.ppt
 
APPLICATION OF KRIGING IN GROUND WATER STUDIES
APPLICATION OF KRIGING IN GROUND WATER STUDIESAPPLICATION OF KRIGING IN GROUND WATER STUDIES
APPLICATION OF KRIGING IN GROUND WATER STUDIES
 
MO4_T04_3_R_Sato.pptx
MO4_T04_3_R_Sato.pptxMO4_T04_3_R_Sato.pptx
MO4_T04_3_R_Sato.pptx
 
Gis
GisGis
Gis
 
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
 
Poster AGU 2013
Poster AGU 2013Poster AGU 2013
Poster AGU 2013
 
Thresholds of Detection for Falling Snow from Satellite-Borne Active and Pas...
Thresholds of Detection for Falling Snow  from Satellite-Borne Active and Pas...Thresholds of Detection for Falling Snow  from Satellite-Borne Active and Pas...
Thresholds of Detection for Falling Snow from Satellite-Borne Active and Pas...
 
ASCE Cold Region Conference-July 2015 (1)
ASCE Cold Region Conference-July 2015 (1)ASCE Cold Region Conference-July 2015 (1)
ASCE Cold Region Conference-July 2015 (1)
 
Assessing GHG exchange at landscape scale
Assessing GHG exchange at landscape scaleAssessing GHG exchange at landscape scale
Assessing GHG exchange at landscape scale
 
20110728_IGARSS_GDPS(ryu)fin1.pptx
20110728_IGARSS_GDPS(ryu)fin1.pptx20110728_IGARSS_GDPS(ryu)fin1.pptx
20110728_IGARSS_GDPS(ryu)fin1.pptx
 
Historical Review of Astro-Geodetic Observations in Serbia
Historical Review of Astro-Geodetic Observations in SerbiaHistorical Review of Astro-Geodetic Observations in Serbia
Historical Review of Astro-Geodetic Observations in Serbia
 
Hidden Depths and Hidden Data
Hidden Depths and Hidden DataHidden Depths and Hidden Data
Hidden Depths and Hidden Data
 
MONITORING LONG TERM VARIABILITY IN THE ATMOSPHERIC WATER VAPOUR CONTENT USIN...
MONITORING LONG TERM VARIABILITY IN THE ATMOSPHERIC WATER VAPOUR CONTENT USIN...MONITORING LONG TERM VARIABILITY IN THE ATMOSPHERIC WATER VAPOUR CONTENT USIN...
MONITORING LONG TERM VARIABILITY IN THE ATMOSPHERIC WATER VAPOUR CONTENT USIN...
 
Some Developments in Climate Science Since IPCC AR4 Prepared for the Climate ...
Some Developments in Climate Science Since IPCC AR4 Prepared for the Climate ...Some Developments in Climate Science Since IPCC AR4 Prepared for the Climate ...
Some Developments in Climate Science Since IPCC AR4 Prepared for the Climate ...
 
WETLAND MAPPING USING RS AND GIS
WETLAND MAPPING USING RS AND GISWETLAND MAPPING USING RS AND GIS
WETLAND MAPPING USING RS AND GIS
 
The use of a hand-held mid-infrared spectrometer for the rapid prediction of ...
The use of a hand-held mid-infrared spectrometer for the rapid prediction of ...The use of a hand-held mid-infrared spectrometer for the rapid prediction of ...
The use of a hand-held mid-infrared spectrometer for the rapid prediction of ...
 
Applications of remote sensing in glaciology
Applications of remote sensing in glaciologyApplications of remote sensing in glaciology
Applications of remote sensing in glaciology
 
A_Framework_of_Ontology-Based_Knowledge_Information_Processing_for_Change_Det...
A_Framework_of_Ontology-Based_Knowledge_Information_Processing_for_Change_Det...A_Framework_of_Ontology-Based_Knowledge_Information_Processing_for_Change_Det...
A_Framework_of_Ontology-Based_Knowledge_Information_Processing_for_Change_Det...
 

Ähnlich wie Comparison of One and Three Dimensional MODFLOW Subsidence Results

igarss11swot-vadon-callahan-psc-s3.110725.pptx
igarss11swot-vadon-callahan-psc-s3.110725.pptxigarss11swot-vadon-callahan-psc-s3.110725.pptx
igarss11swot-vadon-callahan-psc-s3.110725.pptx
grssieee
 
4 ROMAN_IGARSS'11.ppt
4 ROMAN_IGARSS'11.ppt4 ROMAN_IGARSS'11.ppt
4 ROMAN_IGARSS'11.ppt
grssieee
 
DSD-NL 2014 - iMOD Symposium - 10. iMOD Gebruikersdag - Bodemdaling, Gilles E...
DSD-NL 2014 - iMOD Symposium - 10. iMOD Gebruikersdag - Bodemdaling, Gilles E...DSD-NL 2014 - iMOD Symposium - 10. iMOD Gebruikersdag - Bodemdaling, Gilles E...
DSD-NL 2014 - iMOD Symposium - 10. iMOD Gebruikersdag - Bodemdaling, Gilles E...
Deltares
 
geog537_2002_metrics
geog537_2002_metricsgeog537_2002_metrics
geog537_2002_metrics
Tammy Kobliuk
 
3178_IGARSS11.ppt
3178_IGARSS11.ppt3178_IGARSS11.ppt
3178_IGARSS11.ppt
grssieee
 
DSD-INT 2014 - Symposium Next Generation Hydro Software (NGHS) - How to set u...
DSD-INT 2014 - Symposium Next Generation Hydro Software (NGHS) - How to set u...DSD-INT 2014 - Symposium Next Generation Hydro Software (NGHS) - How to set u...
DSD-INT 2014 - Symposium Next Generation Hydro Software (NGHS) - How to set u...
Deltares
 
2017 ASPRS-RMR Big Data Track: Using NASA's AppEEARS to Slice and Dice Big Ea...
2017 ASPRS-RMR Big Data Track: Using NASA's AppEEARS to Slice and Dice Big Ea...2017 ASPRS-RMR Big Data Track: Using NASA's AppEEARS to Slice and Dice Big Ea...
2017 ASPRS-RMR Big Data Track: Using NASA's AppEEARS to Slice and Dice Big Ea...
GIS in the Rockies
 

Ähnlich wie Comparison of One and Three Dimensional MODFLOW Subsidence Results (20)

Physical based models of Landslides' triggering
Physical based models of Landslides' triggeringPhysical based models of Landslides' triggering
Physical based models of Landslides' triggering
 
Cosan Ayan
Cosan AyanCosan Ayan
Cosan Ayan
 
igarss11swot-vadon-callahan-psc-s3.110725.pptx
igarss11swot-vadon-callahan-psc-s3.110725.pptxigarss11swot-vadon-callahan-psc-s3.110725.pptx
igarss11swot-vadon-callahan-psc-s3.110725.pptx
 
DSD-INT 2019 - Global Data Services and Analysis Frameworks - Twigt
DSD-INT 2019 - Global Data Services and Analysis Frameworks - TwigtDSD-INT 2019 - Global Data Services and Analysis Frameworks - Twigt
DSD-INT 2019 - Global Data Services and Analysis Frameworks - Twigt
 
Geotechnical Examples using OpenSees
Geotechnical Examples using OpenSeesGeotechnical Examples using OpenSees
Geotechnical Examples using OpenSees
 
DSD-INT 2023 Next-Generation Flood Inundation Mapping for Taiwan - Delft3D FM...
DSD-INT 2023 Next-Generation Flood Inundation Mapping for Taiwan - Delft3D FM...DSD-INT 2023 Next-Generation Flood Inundation Mapping for Taiwan - Delft3D FM...
DSD-INT 2023 Next-Generation Flood Inundation Mapping for Taiwan - Delft3D FM...
 
4 ROMAN_IGARSS'11.ppt
4 ROMAN_IGARSS'11.ppt4 ROMAN_IGARSS'11.ppt
4 ROMAN_IGARSS'11.ppt
 
LINUX Tag 2008: 4D Data Visualisation and Quality Control
LINUX Tag 2008: 4D Data Visualisation and Quality ControlLINUX Tag 2008: 4D Data Visualisation and Quality Control
LINUX Tag 2008: 4D Data Visualisation and Quality Control
 
Ground inventory and geospatial techniques for estimation of groundwater quality
Ground inventory and geospatial techniques for estimation of groundwater qualityGround inventory and geospatial techniques for estimation of groundwater quality
Ground inventory and geospatial techniques for estimation of groundwater quality
 
DSD-NL 2014 - iMOD Symposium - 10. iMOD Gebruikersdag - Bodemdaling, Gilles E...
DSD-NL 2014 - iMOD Symposium - 10. iMOD Gebruikersdag - Bodemdaling, Gilles E...DSD-NL 2014 - iMOD Symposium - 10. iMOD Gebruikersdag - Bodemdaling, Gilles E...
DSD-NL 2014 - iMOD Symposium - 10. iMOD Gebruikersdag - Bodemdaling, Gilles E...
 
02_waman_mcvay SOIL.pdf
02_waman_mcvay SOIL.pdf02_waman_mcvay SOIL.pdf
02_waman_mcvay SOIL.pdf
 
Drought Vulnerability Modeling for Georgia - Rebecca Peoples
Drought Vulnerability Modeling for Georgia - Rebecca PeoplesDrought Vulnerability Modeling for Georgia - Rebecca Peoples
Drought Vulnerability Modeling for Georgia - Rebecca Peoples
 
Grace satellite technology
Grace satellite technologyGrace satellite technology
Grace satellite technology
 
geog537_2002_metrics
geog537_2002_metricsgeog537_2002_metrics
geog537_2002_metrics
 
3178_IGARSS11.ppt
3178_IGARSS11.ppt3178_IGARSS11.ppt
3178_IGARSS11.ppt
 
DSD-INT 2014 - Symposium Next Generation Hydro Software (NGHS) - How to set u...
DSD-INT 2014 - Symposium Next Generation Hydro Software (NGHS) - How to set u...DSD-INT 2014 - Symposium Next Generation Hydro Software (NGHS) - How to set u...
DSD-INT 2014 - Symposium Next Generation Hydro Software (NGHS) - How to set u...
 
Swat & modflow
Swat & modflowSwat & modflow
Swat & modflow
 
TAICCAT 2015期末簡報
TAICCAT 2015期末簡報TAICCAT 2015期末簡報
TAICCAT 2015期末簡報
 
2017 ASPRS-RMR Big Data Track: Using NASA's AppEEARS to Slice and Dice Big Ea...
2017 ASPRS-RMR Big Data Track: Using NASA's AppEEARS to Slice and Dice Big Ea...2017 ASPRS-RMR Big Data Track: Using NASA's AppEEARS to Slice and Dice Big Ea...
2017 ASPRS-RMR Big Data Track: Using NASA's AppEEARS to Slice and Dice Big Ea...
 
Pre-Injection Assessment of Time-Lapse Seismic Repeatability at the Aquistore...
Pre-Injection Assessment of Time-Lapse Seismic Repeatability at the Aquistore...Pre-Injection Assessment of Time-Lapse Seismic Repeatability at the Aquistore...
Pre-Injection Assessment of Time-Lapse Seismic Repeatability at the Aquistore...
 

Kürzlich hochgeladen

Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 bAsymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Sérgio Sacani
 
dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...
dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...
dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...
dkNET
 
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptxSCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
RizalinePalanog2
 

Kürzlich hochgeladen (20)

Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified
Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verifiedConnaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified
Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified
 
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 bAsymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
 
PSYCHOSOCIAL NEEDS. in nursing II sem pptx
PSYCHOSOCIAL NEEDS. in nursing II sem pptxPSYCHOSOCIAL NEEDS. in nursing II sem pptx
PSYCHOSOCIAL NEEDS. in nursing II sem pptx
 
GBSN - Microbiology (Unit 3)
GBSN - Microbiology (Unit 3)GBSN - Microbiology (Unit 3)
GBSN - Microbiology (Unit 3)
 
Feature-aligned N-BEATS with Sinkhorn divergence (ICLR '24)
Feature-aligned N-BEATS with Sinkhorn divergence (ICLR '24)Feature-aligned N-BEATS with Sinkhorn divergence (ICLR '24)
Feature-aligned N-BEATS with Sinkhorn divergence (ICLR '24)
 
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
 
IDENTIFICATION OF THE LIVING- forensic medicine
IDENTIFICATION OF THE LIVING- forensic medicineIDENTIFICATION OF THE LIVING- forensic medicine
IDENTIFICATION OF THE LIVING- forensic medicine
 
Pulmonary drug delivery system M.pharm -2nd sem P'ceutics
Pulmonary drug delivery system M.pharm -2nd sem P'ceuticsPulmonary drug delivery system M.pharm -2nd sem P'ceutics
Pulmonary drug delivery system M.pharm -2nd sem P'ceutics
 
dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...
dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...
dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...
 
GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)
 
Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...
Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...
Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...
 
Dopamine neurotransmitter determination using graphite sheet- graphene nano-s...
Dopamine neurotransmitter determination using graphite sheet- graphene nano-s...Dopamine neurotransmitter determination using graphite sheet- graphene nano-s...
Dopamine neurotransmitter determination using graphite sheet- graphene nano-s...
 
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRLKochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
 
Proteomics: types, protein profiling steps etc.
Proteomics: types, protein profiling steps etc.Proteomics: types, protein profiling steps etc.
Proteomics: types, protein profiling steps etc.
 
pumpkin fruit fly, water melon fruit fly, cucumber fruit fly
pumpkin fruit fly, water melon fruit fly, cucumber fruit flypumpkin fruit fly, water melon fruit fly, cucumber fruit fly
pumpkin fruit fly, water melon fruit fly, cucumber fruit fly
 
Clean In Place(CIP).pptx .
Clean In Place(CIP).pptx                 .Clean In Place(CIP).pptx                 .
Clean In Place(CIP).pptx .
 
Call Girls Alandi Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Alandi Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Alandi Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Alandi Call Me 7737669865 Budget Friendly No Advance Booking
 
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptxSCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
 
Justdial Call Girls In Indirapuram, Ghaziabad, 8800357707 Escorts Service
Justdial Call Girls In Indirapuram, Ghaziabad, 8800357707 Escorts ServiceJustdial Call Girls In Indirapuram, Ghaziabad, 8800357707 Escorts Service
Justdial Call Girls In Indirapuram, Ghaziabad, 8800357707 Escorts Service
 
FAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
FAIRSpectra - Enabling the FAIRification of Spectroscopy and SpectrometryFAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
FAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
 

Comparison of One and Three Dimensional MODFLOW Subsidence Results

  • 1. Comparison of One and Three Dimensional MODFLOW Subsidence Results Dave Colvin - Leonard Rice Engineers NGWA Groundwater Summit Garden Grove, CA May 7, 2012 1
  • 3. Subsidence Overview • Lowering of ground surface • Based on Terzaghi equation • Before pumping, geostatic load (pressure or stress) is balanced • Pumping reduces pore pressure; increases stress on ‘skeleton’ • “Stress” = Change in water level Reference: Poland (1984). Guidebook to Studies of Land Subsidence due to Ground Water Withdrawal. UNESCO. International Hydrological Programme Working Group
  • 4. Data Characteristics • Long periods of record • Accurate monitoring results • Varied collection methods • Varied data types • Expensive 4 • Drilling and Well Testing • Remote Sensing • Survey Based • Geotechnical Laboratory Analyses • Geophysics – Downhole – Airborne/Surface Data Collection Methods Subsidence Modeling Data Collection
  • 5. Conceptual Model Development 3D Lithology Database
  • 6. Conceptual Model Development 3D Lithology Database
  • 7. Conceptual Model Development 3D Lithology Database
  • 8. Conceptual Model Development 3D Lithology Database
  • 9. Conceptual Model Development 3D Lithology Database
  • 10. Groundwater Clay Layer 1 Clay Layer 2 Upper Aquifer Middle Aquifer Lower Aquifer Ground Surface Constant Head Cells -defined by water level elevations or -groundwater flow model heads 1D Subsidence Concept
  • 11. USGS MODFLOW SUB-WT • Simulates vertical compaction in groundwater flow models • Simulates groundwater storage changes in aquitards (or interbeds) • Calculates changes in geostatic stress due to lowering of the water table • Allows for time variable hydraulic and subsidence properties Reference: Galloway and Leake(2007) MODFLOW Ground Water Model - User Guide to the Subsidence and Aquifer-System Compaction Package (SUB-WT) for Water Table Aquifers. U.S. Geological Survey Techniques and Methods 6-A23.
  • 12. Modeled Head Impacts using SUB-WT 0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0 450.0 500.0 550.0 600.0 Drawdown(ft) Year 3D SUB-WT Model Drawdown Result Comparison Base Model Well #1 SWT Model - Well #1 Base Model Well #2 SUB-WT Model Well #2 Maximum difference of 27.8 feet
  • 13. MODFLOW Subsidence Water Budget Impacts Reference: Faunt, C.C., ed., 2009, Groundwater Availability of the Central Valley Aquifer, California: U.S. Geological Survey Professional Paper 1766
  • 14. Clay Layer 1 Compaction 3D Subsidence Models
  • 15. 1D vs. 3D SUB-WT Subsidence Results 840 860 880 900 920 940 960 980 1000 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1940 1960 1980 2000 2020 2040 2060 2080 2100 2120 GroundWaterLevel(ftNAVD88) Subsidence(ft) Year 1D vs. 3D Subsidence Model Comparison 3D Modeled Subsidence 1D Modeled Subsidence Head
  • 16. 1D vs. 3D SUB-WT Subsidence Results Modeled Subsidence Results (Feet) Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Scenario 6 Scenario 7 Scenario 8 Year 3D 1D 3D 1D 3D 1D 3D 1D 3D 1D 3D 1D 3D 1D 3D 1D 2020 0.4 0.5 0.4 0.5 0.4 0.5 0.3 0.5 0.3 0.4 0.3 0.4 0.3 0.4 0.3 0.4 2080 0.7 0.9 1.2 1.5 1.5 1.9 1.1 1.4 0.8 1.1 1.1 1.4 1.7 2.0 1.3 1.5 2117 0.8 1.0 1.2 1.5 1.5 1.9 1.1 1.4 1.0 1.2 1.2 1.6 1.8 2.2 1.3 1.6 3D - Percent of 1D Result 78% 77% 78% 78% 78% 78% 84% 82%
  • 17. Water movement horizontally and vertically within aquifers and aquitards Groundwater Clay Layer 1 Clay Layer 2 Upper Aquifer Middle Aquifer Lower Aquifer Ground Surface Movement of water restricted to the vertical plane 1 D 3 D 3D Subsidence Models
  • 18. Conclusions • Use of the MODFLOW subsidence packages can have significant impacts on model predicted: – Head – Storage • 1D subsidence modeling may be more appropriate in locations where: – Available data are obtained from one borehole or location – Geologic heterogeneity of clay thickness or bedrock structure is poorly understood – Regional groundwater flow models are not available • 1D models assume that horizontal flow is insignificant compared to other storage and water budget components • 1D subsidence models over predict subsidence by approximately 20% • 3D groundwater flow modeling may be used to obtain subsidence results in one cell • Availability and quality of input data must be balanced with the confidence needs in the subsidence predictions 18

Hinweis der Redaktion

  1. One dimensional subsidence models are often used due to lack of available input data.  While these are useful screening level models, integration of subsidence modeling into a three dimensional flow model should be considered, particularly if a flow model already exists.  MODFLOW SUB-WT and SUB packages rely on the Terzaghi theory of one-dimensional consolidation to calculate subsidence.  Although these calculations are based in the vertical dimension, use of these packages impacts the water balance and subsequent results of groundwater flow models. This presentation will provide details on the differences in model results between one and three dimensional subsidence modeling using the MODFLOW SUB-WT package.
  2. Investigation into evidence of laterally continuous clay layers possibly from lacustrine lake deposits.
  3. Investigation into evidence of laterally continuous clay layers possibly from lacustrine lake deposits.
  4. Investigation into evidence of laterally continuous clay layers possibly from lacustrine lake deposits.
  5. Investigation into evidence of laterally continuous clay layers possibly from lacustrine lake deposits.
  6. Investigation into evidence of laterally continuous clay layers possibly from lacustrine lake deposits.