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Soil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner [email protected] Department of Geodesy and Geoinformation (GEO) Vienna University of Technology (TU Wien) www.ipf.tuwien.ac.at

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Page 1: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Soil Moisture Measurements from Space and Application to Operational Hydrology

Wolfgang [email protected]

Department of Geodesy and Geoinformation (GEO)Vienna University of Technology (TU Wien)

www.ipf.tuwien.ac.at

Page 2: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Soil Moisture

Definition, e.g.

Average

Thin, remotely sensed soil layer

Root zone: layer of interest for most applications

Soil profile

)(m Volume Total)(m VolumeWater

3

3=θ Air

Water

Solid Particles

Cross-section of a soil

∫ ∫⋅

=Area Depth

dzdxdyzyxDepthArea

),,(1 θθ

Page 3: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Microwaves

Microwaves (1 mm – 1 m wavelength)• All-weather, day-round measurement capability• Very sensitive to soil water content below relaxation frequency of water (< 10

GHz)• Penetrate vegetation and soil to some extent

– Penetration depth increases with wavelength

Dielectric constant of water

The dipole moment of water moleculescauses “orientational polarisation”, i.e.a high dielectric constant

Page 4: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Measurement Principles

Radars measure the energy scattered back from the surfaceRadiometers measure the self-emission of the Earth’s surface

SAR

SCAT

ERS-1/2

SAR und scatterometer on European RemoteSensing Satellites ERS-1 and ERS-2

Active Sensors Passive Sensor

Page 5: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

5

Microwave missions for soil moisture

33 years of passive and active satellite microwave observations for soil moisture

Page 6: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

News Sensors & Products

Page 7: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Recent Successes & Prospects

Recent successes• 2002: First global soil moisture data set from ERS SCAT published• 2003: NASA soil moisture product based on AMSR-E put into operations• 2007: First merged multi-radiometer soil moisture product • 2009: ASCAT soil moisture product available in NRT• 2010: First SMOS soil moisture data released• 2011: International Soil Moisture Network (ISMN) takes off• 2012: First ECV soil moisture data set covering 1978-2010 released

Prospects• 2013: Launch of Sentinel-1

– First operational soil moisture product at ≤ 1 km spatial resolution• 2014: Lauch of SMAP

– First active/passive sensor at L-band

Page 8: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Operational EUMETSAT/H-SAF ASCAT Services

Page 9: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

European C-Band Scatterometers

ERS Scatterometer• λ = 5.7 cm• VV Polarization• Resolution: 50 / 25 km

Data availability• ERS-1: 1991-2000• ERS-2: since 1995

–gaps due to loss of gyros (2001) and on-board tape recorder (2003)

• Operations conflict with ERS SAR

METOP Advanced Scatterometer• λ = 5.7 cm• VV Polarization• Resolution: 50 / 25 km

Data availability• >15 years• METOP-A: since 2006• METOP-B: launch in 2012

Daily global scatterometer coverage: ERS (left) and METOP (right)

Page 10: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Backscatter from Vegetated Surfaces

Except for dense forest canopies, backscatter from vegetation is due to surface-, volume- and multiple scattering

Surface scattering(attenuated by

vegetation canopy)

Volume scattering Surface-volume interaction

0000ninteractiosurfacevolumetotal σσσσ ++=

Page 11: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Backscatter versus Soil Moisture & Vegetation

Dense Forest

Grassland& agriculture Grassland &

agriculturewith 30 %

forest cover

Grassland &agriculturewith 60 %

forest cover

Simulations performed with a radiative transfer mixing model

Page 12: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

SCAT Seasonal Soil Moisture Dynamics

Mean ERS scatterometer surface soil moisture (1991-2007)

Page 13: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

SCAT Noise from Error Propagation

Page 14: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Validation

Available independent data• In-situ measurements• Modelled soil moisture data• Other satellite products

Best Practices• Assessment of absolute product accuracy (RMSE)• Assessment of relative accuracy and anomalies (R, unbiased RMSE)

Methods• Direct comparisons• Triple collocation• R-metric

Page 15: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

International Soil Moisture Network (ISMN)

http://www.ipf.tuwien.ac.at/insitu

Page 16: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Soil Moisture Scaling Properties

High variability in time• Remotely sensed layer exposed to atmosphere

Distinct but temporally stable spatial patterns

Temporal stability means that spatial patterns persist in time• Vachaud et al. (1985)

– Practical means of reducing an in-situ soil moisture network to few representative sites

• Vinnikov and Robock (1996)– Large-scale atmosphere-driven soil moisture field– Small-scale land-surface soil moisture field

Page 17: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

In-Situ Soil Moisture Time Series

Mean (red) and station (black) in-situ soil moisture time series. REMEDHUS network in Spain. © University of Salamanca

Page 18: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Temporal Stability

( ) ( ) ( ) ( ) ( )tyxyxdyxcydxdtyxA

t prprppr

r ,,,,,,1 θθθ +=′′′′= ∫∫Ρ

Regional scalesoil moisture

Local scalesoil moisture

Linear scaling coefficients

Model Error ≅ 5 %

Page 19: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Scaling by CDF Matching

Mainly due to uncertain soil hydrologic properties and soil moisture scaling properties (temporal stability), absolute soil moisture values from any source (in-situ, model, remote sensing) are highly uncertainBiases are removed by Cumulative Distribution Function (CDF) matching

Source 1 CDF

Source 2 CDF

Scipal, K., Drusch, M., W. Wagner (2008) Assimilation of a ERS scatterometer derived soil moisture index in the ECMWF numerical weather prediction system, Advances in Water Resources, 31, 1101-1112.

Page 20: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

ASCAT versus Model

ASCAT versus 3 cm simulated degree of saturation for products, ms, SWI, and SWI* and investigated sites: a) Vallaccia, b) Cerbara, and c) Spoleto.

Brocca, L., Melone, F., Moramarco, T., Wagner, W., & Hasenauer, S. (2010). ASCAT Soil Wetness Index validation through in-situ and modeled soil moisture data in Central Italy. Remote Sensing of Environment, 114, 2745-2755.

Page 21: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

ASCAT vs. AMSR-E

Validation over networks in Italy, France, Luxemburg and Spain3 AMSR-E productsASCAT and AMSR-E LPMR performed bestASCAT particularly good in case of anomaly correlations

Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., Dorigo, W., Matgen, P., Martínez-Fernández, J., Llorens, P., Latron, J., Martin, C., & Bittelli, M. (2011). Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study accross Europe. Remote Sensing of Environment, 115, 3390-3408

ASCAT

Page 22: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Triple Collocation ASCAT vs. AMSR-E vs. ERA-Interim

New statistical method for the estimation of errors of three data sets• Errors must not be correlated

ASCAT

AMSR-E

GLDAS

Dorigo, W.A., Scipal, K., Parinussa, R.M., Liu, Y.Y., Wagner, W., de Jeu, R.A.M., & Naeimi, V. (2010). Error characterisation of global active and passive microwave soil moisture datasets. Hydrology and Earth System Sciences, 14, 2605-2616

AMSR-E better::ASCAT better

Page 23: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Validation of SMOS and ASCAT over France

Validation over SMOSMANIA networkAn

omal

y

Parrens, M., E. Zakharova, S. Lafont, J.-C. Calvet, Y. Kerr, W. Wagner, J.-P. Wigneron (2012) Comparing soil moisture retrievals from SMOS and ASCAT over France, Hydrology and Earth System Sciences, 16, 423-440.

Page 24: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Validation of SMOS and ASCAT (Operational & Assimilated)

Validation over networks in the US, Europe and Australia• (Initial) operational ASCAT product performs similar to SMOS• Assimilation improves correlation to in-situ data

Correlations between ASCAT and in situ data against correlations between ECMWF SM-DAS-2 and in situ data, then same for SMOS and SM-DAS-2, SMOS and ASCAT.

Same as above but for anomaly correlation values instead of normalised time series.

Albergel, C., de Rosnay, P., Gruhier, C., Muñoz-Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y., & W., W. (2012). Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment, 118, 215-226

Page 25: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Time Series Correlation ASCAT versus SMOS

Page 26: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Applications

Monitoring of extreme hydrologic eventsRunoff forecastingData assimilationNumerical Weather PredictionLandslide monitoringVegetation monitoringAgricultural monitoringEpidemiological predictionGHG budgetClimate studiesGround water modelling

Page 27: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Monitoring of Extreme Events: Heavy Rain & Hail

Heavy Rain & Hail on 1/7/2012

Page 28: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Monitoring of Extreme Events: Droughts

Page 29: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

SCAT Soil Moisture versus River Runoff

Sambesi – Nana‘s Farm 60 days shift

RunoffShifted Runoff

Time

Run

off

So il Mois ture (Blu e L ine)

Scipal, K., C. Scheffler, W. Wagner (2005) Soil moisture-runoff relation at the catchment scale as observed with coarse resolution microwave remote sensing, Hydrology and Earth System Sciences, 9(3), 173-183.

Page 30: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Time Shift andCatchment Size

Page 31: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Event-based Rainfall-Runoff Modelling

"Curve Number Method"

( ) SWIdcSSPSPQ ⋅+=

+−

= with8.0

2.0 2Q … runoffP … precipitationS … retentionSWI … Soil Water Index

Brocca L, Melone F, Moramarco T, et al. (2009) Antecedent wetness conditions based on ERS scatterometer data, Journal of Hydrology, 364(1-2), 73-87.

Page 32: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Improving Runoff Prediction through Assimilation

If improvement can be achieved depends on the quality of the in situ measurements and the applied calibration and data assimilation strategies

Cumulated runoff for the observed and simulated data with and without ASCAT SWI assimilation for four catchments in Italy.

Brocca, L., Melone, F., Moramarco, T., Wagner, W., Naeimi, V., Bartalis, Z., & Hasenauer, S. (2010). Improving runoff prediction through the assimilation of the ASCAT soil moisture product. Hydrology and Earth System Sciences, 14, 1881-1893

Page 33: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Improved Soil Moisture Estimates through Assimilation

Draper, C.S., Reichle, R.H., De Lannoy, G.J.M., & Liu, Q. (2012). Assimilation of passive and active microwave soil moisture retrievals. Geophysical Research Letters, 39, L04401

Page 34: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

ASCAT Assimilation at NWP Centres

Impact on temperature and humidityCentres

• ECMWF• Mete Office• Meteo France• ZAMG

AustraliaTropics

North America NorthernHemisphere

Skill of relative humidity forecasts

Dharssi, I., Bovis, K.J., Macpherson, B., & Jones, C.P. (2011). Operational assimilation of ASCAT surface soil wetness at the Met Office. Hydrology and Earth System Sciences, 15, 2729-2746

Page 35: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Afternoon rain more likely over drier soils

Taylor, C.M., de Jeu, R.A.M., Guichard, F., Harris, P.P., & Dorigo, W.A. (2012). Afternoon rain more likely over drier soils. Nature, 489, 423-426.

Dark red = rain falls most likely over drier soils

Pink = rain falls likely over drier soils

Blue = rain falls likely over wetter soils

Dark blue = rain most falls likely over wetter soils

Page 36: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Prediction of Water-Borne Diseases

Unpublished results of Brocca, Montosi & Montanari

Page 37: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Landslide Monitoring

Brocca, L., F. Ponziani, T. Moramarco, F. Melone, N. Berni, W. Wagner (2012) Improving Landslide Forecasting Using ASCAT-Derived Soil Moisture Data: A Case Study of the Torgiovannetto Landslide in Central Italy, Remote Sensing, 4(5), 1232-1244.

Comparison between observed (circles) and estimated (triangles) crack aperture of the Torgiovannetto Landslidein Central Italy from the beginning to the end of the selected rainfall events.

Page 38: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Climate Change: Merging of Multi-Satellite Data Sets

E R S -1/2 S C A T

1991-2011

M E TO P A S C A T

2006-now

EO S /A cquaA M S R -E

2002-now

C oriolisW indsat

2003-now

T R M MTM I

1998-now

D M SPS S M /I

1987-now

N im b us 7S M M R

1978-1987

A ctiveLevel 2

R etrieva l

A ctiveLevel 2

R etrieva l

P ass ive Level 2

R etrieva l

P ass ive Level 2

R etrieva l

P ass ive Level 2

R etrieva l

P ass ive Level 2

R etrieva l

P ass ive Level 2

R etrieva l

A ctive E C V D ata1991-now

Passive E C V D ata1978-now

R eferenceG LD A S,

E R A -In terim

M erg ingA ctive

Level 2 D ata

M erg ingP ass ive Level 2

D ata

M erg ingA ctive-P ass ive

D ata Sets

A ctive-Passive

E C V D ata1978 -now

L evel 1D ata Sets

E CVProduction

System

Ancilla ry D ata

F or Ac tive R etrieva l

Anc illa ry D ata

For P assive Retrieva l

Page 39: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Trend 1988-2010

Dorigo et al. (1988-2010) in harmonized multi-satellite surface soil moisture, Geophysical Research Letters, 39, L18405, 1-7.

Page 40: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Conistent Trends in Modelled Soil Moisture (top), Precipitation (middle) and NDVI (bottom) Time Series

Dorigo et al. (1988-2010) in harmonized multi-satellite surface soil moisture, Geophysical Research Letters, 39, L18405, 1-7.

Page 41: Soil Moisture Measurements from Space -   · PDF fileSoil Moisture Measurements from Space and Application to Operational Hydrology Wolfgang Wagner ww@ipf.  Department of

Outlook

Availability and quality of satellite soil moisture data sets is improving• METOP-A + METOP-B• AMSR-2

Future Opportunities• Sentinel-1

– 1 km soil moisture and freeze/thaw– 30 m water bodies

• Soil Moisture Active Passive (SMAP)

Early Announcement• Satellite Soil Moisture Validation and Application Workshop

– 1-3 July 2013 at ESA ESRIN, Frascati, Italy– Co-organisation ESA, EUMETSAT, WMO, GEWEX, CEOS and GCOS