INSAR TO UNDERSTAND GROUNDWATER FLOW

SYSTEMS AND SUPPORT GROUNDWATER

MANAGEMENT

Castellazzi, Pascal (1) ; Martel, Richard (1) ; Rivera, Alfonso (2) ; Calderhead, Angus (1) ; Garfias, Jaime (3)

1 : Institut national de la recherche scientifique, Québec (Québec)

2 : Commission Géologique du Canada, Québec (Québec)

3 : Universidad Autónoma del Estado de México (UAEMéx), Toluca, Mexique

Introduction

1. Context

2. InSAR principles and limitations

3. Case study 1: subsidence and fracturing in Toluca, Mexico

4. Case study 2: InSAR vs GRACE in Central Mexico

5. Case study 3: InSAR to monitor building stability in karstic settings

6. Conclusions

Global depletion of groundwater resources

Wada, Y., L.P.H. van Beek, C.M. van Kempen, J. Reckman, S. Vasak, and M.F.P. Bierkens. 2010. Global depletion of groundwater resources. Geophysical Research Letters 37: 5.

Recharge Extraction

Depletion (mm/yr for 2000)

Global monitoring of

depleting groundwater

ressources?

-Drinking water scarcity

-Sustainable food production

-Instability and geopolitical crisis

-Sustainable development

Introduction

Land Subsidence

San Juan de Aragón well

Mexico city

1936 - 2005

elastic

inelastic

Land

subsidence

Clay Interbeds compaction

Context

ΔGWS: GW storage change

Δh: Head change

S: Storativity

Ss: Specific storage coefficient

Ssk: Specific skeletal storage coefficient

Sy: Specific Yield

Δu: Compaction

ΔGWS = Δh A S

S = ΔGWS/(Δh A)

Δu = S Δh

Unconfined aquifer storaitivity: S = Sy + b Ss ~ Sy

…2 to 3 order of magnitude greater than:

Confined storativity: S = b Ss = b (Ssk + Ssw,)

= b (ρ g (α + n βw ))

Δu = Ss b Δh ~ Ssk b Δh

InSAR

SAR data aquisition Temporal density of the

time-series is limited by

the SAR satellite repeat

path:

Radarsat 1/2 : 24 days

Envisat : 35 days

ALOS-1: 46 days

TerraSAR: 11 days

ALOS-2: 14 days

Sentinel-1/2: 12 or 6

days

InSAR principles

Source: Eurepean Space Agency

InSAR principles

InSAR

Can be isolated

during process

(SARScape – IDL)

Isolated or reduced

Phase difference between two images Application over time-series

Producing multiple interferograms

Issues

2. Granular noise 3. Atmospheric delay

1. Phase ambiguity (wrapped over 2π)

InSAR principles

Processing strategies

InSAR principles

Persistent Scatterer Interferometry

(Ferretti et al., 2001)

Small Baseline Subset

Intereferometry

(Berardino et al., 2002)

Number of SAR images needed 20+ 12+

Strategy Analyse the phase variations over

coherent targets only

Analyse the phase over the whole scene

Phase ambiguity • Inversion phase variations over time

to displacement

• Independent for each ground target

• Phase de-correlation happens over

λ/4 of disp. between 2 acquisitions

• Spatial phase unwrapping

• Spatial smoothening decrease

resolution

• Able to resolve high displacement

rates over λ/4 between 2 acquisitions

Noise – S/N ratio Discriminate coherent ground targets Increase S/N by reducing resolution

Atm. delay Atm. filtering valuable only where

ground targets are dense (>100/km2)

Atm. filtering over the whole scene

Precision +/- 2 to 4mm/yr +/- 4 to 10mm/yr

Computing

(approx. with decent desktop)

+/- 50 hours with 25 images +/- 10 hours (depend on resolution)

SBAS vs PSI

Amplitude

SBAS

Smothened

PSI

Better resolution

Independant unwr. for

each ground target

Sensitive to

de-correlation

Trouble in solving the phase ambiguity

depending on SAR stack temporal density

InSAR principles

Case study 1:

fracturing in Toluca, MexicoSettings

… Consequence of compaction of non-

continuous highly compressible clay

interbeds.

Wastewater infiltration

Structural damages

Case study 1:

fracturing in Toluca, MexicoSettings

Case study 1:

fracturing in Toluca, MexicoInSAR results

Castellazzi P., Arroyo-Domínguez N., Martel R.,

Calderhead A., Normand J., Gárfias J., Rivera A.

(2016). Recent changes in land subsidence caused

by groundwater extraction in five major cities of

Central Mexico monitored with high spatial

resolution InSAR time-series. International Journal

of Applied Earth Observation and Geoinformation.

Envisat

2003-2010

SBAS-InSAR

Radarsat-2

2012-2014

SBAS-InSAR

Sentinel-1A

2014-2016

SBAS-InSAR

Sentinel-1A

2014-2016

PSI

Case study 1:

fracturing in Toluca, MexicoInSAR results

Vertical displacement (VD) Horizontal gradient of VD

Case study 1:

fracturing in Toluca, MexicoInSAR results

Lerma-Santiago-Pacifico (LSP) basin :

133 848 km2

8 of Mexico’s 35 most populated

cities

• Mexico

• Guadalajara – Zapopan

• Léon

• Aguascalientes

• Querétaro

• Morelia

• Toluca

Provides water to 30+ Millions people

38% of the water supply of Mexico city

Major importance in the economy

Case study 2:

InSAR vs GRACE in Central Mexico Settings

ΔGWS = ΔTWS – (ΔSWS + ΔSMS + ΔSPS)

ΔSWS

ΔSMS

Truncation/Filteration

To simulate GRACE

resolution

Case study 2:

InSAR vs GRACE in Central Mexico GRACE signal

decomposition

GW Storage change

GRACE TWS trend map GRACE GWS trend map GW budgets - Gouvernance InSAR

Case study 2:

InSAR vs GRACE in Central Mexico

GWS (annually averaged)

Spatial leakages estimationCastellazzi P., Martel R., Rivera A., Huang J., Pavlic G., Calderhead A.,

Chaussard E., Gárfias J. (2016). Groundwater depletion in Central Mexico: use

of GRACE and InSAR to support water resources management.

Water Resources Research.

Case study 2:

InSAR vs GRACE in Central Mexico Spatial analysis of

land subsidence patterns

Field observations are important

to better interpret geodetic methods

Potential of InSAR for downscaling GRACE-derived GWS data

Full resolution GRACE resolution

easy

difficult

?

Example for Glacier

mass loss monitoring:

See Farinotti et al., 2015

Case study 2:

InSAR vs GRACE in Central Mexico

…see:

Castellazzi P., Martel R., Longuevergne L., Rivera A. (2016). Assessing groundwater depletion and aquifer-

system dynamics using GRACE and InSAR: limitations and potential. Groundwater

Case study 3:

InSAR to monitor building stabilitySettings

Case study 3:

InSAR to monitor building stabilityInSAR results

Targets over InSAR coherence Targets projected on a city map

Case study 3:

InSAR to monitor building stabilityPSI results

Stable pixels (noise)

Building A1

Building B1

InSAR is developing fast:

• Data availability

• Data coverage

• spatial resolution

• Image stack temporal density

• Processing algorithms with user interface

InSAR is helpful for:

• localizing groundwater deficit area within a watershed

• understanding the dynamics of GW extraction

• Delimiting lithological discontinuities in over-pumped aquifers.

• Monitoring sinkhole occurrence in Karstic environments – Implications for civil security

Perspectives of combination geodetic observations:

GRACE-FO mission (NASA/GFZ), GRACE-2

NiSAR (NASA), Radarsat-3, Sentinel-1A/1B, ALOS-2

-> InSAR and GRACE could be combined in the perspectives of a independent volumetric

groundwater depletion mapping

Conclusions

Published:

Castellazzi P., Martel R., Rivera A., Huang J., Pavlic G., Calderhead A., Chaussard E., Gárfias J. (2016). Groundwater

depletion in Central Mexico: use of GRACE and InSAR to support water resources management. Water Resources

Research.

Castellazzi P., Arroyo-Domínguez N., Martel R., Calderhead A., Normand J., Gárfias J., Rivera A. (2016). Recent changes

in land subsidence caused by groundwater extraction in five major cities of Central Mexico monitored with high spatial

resolution InSAR time-series. International Journal of Applied Earth Observation and Geoinformation.

Castellazzi P., Martel R., Longuevergne L., Rivera A. (2016). Assessing groundwater depletion and aquifer-system

dynamics using GRACE and InSAR: limitations and potential. Groundwater

Castellazzi P., Martel R., Garfias J., Calderhead A., Salas-Garcia J., Huang J., Rivera A. (2014). Groundwater deficit and

land subsidence in Central Mexico monitored by GRACE and RADARSAT-2. 2014 Ieee International Geoscience and

Remote Sensing Symposium (Igarss): 2597-2600.

….Upcoming:

Castellazzi P., Martel R., Garfias J., Rivera A. Ground fracturing risks related to compaction of the depleting aquifer of

Toluca Valley, Mexico. To be submitted in fall 2016.

Castellazzi P., Longuevergne, L., Martel R., Garfias J., Rivera A. Downscaling GRACE-derived groundwater storage

change maps to the water management scale using InSAR. To be submitted in winter 2017.

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