Soil moisture detection with remote sensing for hydrological purposes. Hydrology.

1. luca.brocca@irpi.cnr.it http://hydrology.irpi.cnr.it
Luca Brocca
and many others 
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
Floods
Landslides
Rainfall
In situ validation
USE OF SATELLITE SOIL MOISTURE
DATA FOR HYDROLOGICAL
APPLICATIONS
Monday, September 23, 13

2. 25
September
2013
Trento
Importance of soil moisture
Campo et al. (2006, HYP)
Casentino basin
central Italy
30% increase of soil
moisture produces
a 8-fold increase of
peak discharge!
Monday, September 23, 13

3. 25
September
2013
Trento
Importance of soil moisture
Campo et al. (2006, HYP)
Casentino basin
central Italy
30% increase of soil
moisture produces
a 8-fold increase of
peak discharge!
Monday, September 23, 13

4. 25
September
2013
Trento
Importance of soil moisture
Campo et al. (2006, HYP)
Casentino basin
central Italy
30% increase of soil
moisture produces
a 8-fold increase of
peak discharge!
Runoff generation
Brocca et al. (2010, HESS)
Landslide
triggering
Brocca et al. (2012, RS)
Numerical
Weather
Prediction
Dharssi et al. (2011, HESS)
Erosion modelling
Nearing et al. (2005, CAT)
Plant production
Bolten et al. (2010,
JSTARS)
Water quality
modelling
Han et al. (2012, HYP)
Monday, September 23, 13

5. 25
September
2013
Trento
Soil moisture is needed by all
GEO Social Benefit Areas and
was ranked the second top
priority parameter (behind
precipitation) in a year 2010
GEO report on "Critical Earth
Observation Priorities".
http://sbageotask.larc.nasa.gov/
US-09-01a_SummaryBrochure.pdf
Need for soil moisture
Monday, September 23, 13

6. 25
September
2013
Trento
Soil moisture monitoring
Monday, September 23, 13

7. 25
September
2013
Trento
IN SITU
(TDR, FDR, Gravimetric,
Geophysical methods)
REMOTE SENSING
(AMSR-E, SAR, Scatterometer,
ASCAT, SMOS, SMAP...)
HYDROLOGICAL
MODELLING
Soil moisture monitoring
Monday, September 23, 13

8. 25
September
2013
Trento
Experimental Catchment
Soil moisture monitoring
Monday, September 23, 13

9. 25
September
2013
Trento
LaboratoryExperimental Catchment
TDR and FDR continuous
monitoring probes
TDR spot measurements
Soil moisture monitoring
Monday, September 23, 13

10. 25
September
2013
Trento
Soil moisture monitoring
Monday, September 23, 13

11. 25
September
2013
Trento
Soil moisture monitoring
International
Soil Moisture
Network
http://www.ipf.tuwien.ac.at/insitu/
Monday, September 23, 13

12. 25
September
2013
Trento
Coarse-resolution soil moisture product
Monday, September 23, 13

13. 25
September
2013
Trento
Typical catchment
size for
hydrological
studies.
Coarse-resolution soil moisture product
Monday, September 23, 13

14. 25
September
2013
Trento
~25 kmsatellite
pixels
Typical catchment
size for
hydrological
studies.
HYDROLOGIST
too coarse for
hydrological
applications !
Coarse-resolution soil moisture product
Monday, September 23, 13

15. 25
September
2013
Trento
PLOT SCALE
400-9000 m2
CENTRALITALY
Brocca et al., 2009 (GEOD)
Soil moisture temporal stability
Monday, September 23, 13

16. 25
September
2013
Trento
PLOT SCALE
400-9000 m2
CENTRALITALY
Brocca et al., 2009 (GEOD)
SMALL CATCHMENT
SCALE ~50 km2
Brocca et al., 2010 (WRR)
CATCHMENT SCALE
~250 km2
Brocca et al., 2012 (JoH)
Soil moisture temporal stability
Monday, September 23, 13

17. 25
September
2013
Trento
PLOT SCALE
400-9000 m2
CENTRALITALY
Brocca et al., 2009 (GEOD)
SMALL CATCHMENT
SCALE ~50 km2
Brocca et al., 2010 (WRR)
CATCHMENT SCALE
~250 km2
Brocca et al., 2012 (JoH)
USA
Cosh et al., 2006 (JoH)
AFRICA
de Rosnay et al., 2009 (JoH)
ASIA
Zhao et al., 2010 (HYP)
Soil moisture temporal stability
Monday, September 23, 13

18. 25
September
2013
Trento
1990 2000 20101980
Remote sensing of soil moisture
Monday, September 23, 13

19. 25
September
2013
Trento
1990 2000 20101980
SSM/I
Nimbus-7
Aqua
AMSR-E
TMI
TRMM
Coriolis
Windsat
METOP-A
ASCAT
SCAT
ERS-1&2
SMOS
SMAP
SMMR DMSP; F8-F16
AMSU
Remote sensing of soil moisture
Monday, September 23, 13

20. 25
September
2013
Trento
PURPOSE
VALIDATION OF SATELLITE SOIL MOISTURE
PRODUCTS WITH IN SITU OBSERVATIONS ACROSS
EUROPE
USE OF SATELLITE SOIL MOISTURE PRODUCT FOR:
1. RAINFALL ESTIMATION
2. FLOOD PREDICTION AND FORECASTING
3. LANDSLIDE MOVEMENT PREDICTION
Monday, September 23, 13

21. 25
September
2013
Trento
Validation of
remote sensing
soil moisture products
Monday, September 23, 13

22. 25
September
2013
Trento
Wagner et al., 1999 (RSE)
Satellite soil moisture product
• scatterometer (active microwave)
• C-band (5.7 GHz)
• VV polarization
• resolution 50/25 km
• daily coverage
• 2007 - ongoing
ASCAT
2007- …
Change detection algorithm takes account indirectly for surface roughness and
land cover variability.
Monday, September 23, 13

23. 25
September
2013
Trento
Owe et al., 2008 (JGR)
AMSR-E
2002-2011
LPRM algorithm three-parameter retrieval model (soil moisture, vegetation water
content, and soil/canopy temperature) for passive microwave data based on a
• radiometer (passive microwave)
• 6.9 - 10.7 - 18.7 - 36.5 GHz
• HH and VV polarization
• 74x43 km (6.9 GHz), 14x8 (36.5 GHz),
resampled at ~25 km
• daily coverage
• 2002 - 2011
Satellite soil moisture product
Monday, September 23, 13

24. 25
September
2013
Trento
“Consistent validation of H-SAF
soil moisture satellite and model
products against ground
measurements for selected sites
in Europe”
http://hsaf.meteoam.it/
In situ soil moisture network
Monday, September 23, 13

25. 25
September
2013
Trento
In-situ soil moisture
data at different
depths (5, 10, 15,
30, ...) for a total of 17
sites across four
different countries
(Italy, France, Spain
and Luxembourg).
Considering both
observed and
modelled data:
29 DATA SETS
In situ soil moisture network
Monday, September 23, 13

26. 25
September
2013
Trento
Italy
Vallaccia
5 cm
ASCAT
In situ validation
Monday, September 23, 13

27. 25
September
2013
Trento
Italy
Vallaccia
5 cm
AMSRE-LPRMAMSRE-NASA
AMSRE-PRIASCAT
In situ validation
Monday, September 23, 13

28. 25
September
2013
Trento
Italy
Vallaccia
5 cm
AMSRE-LPRMAMSRE-NASA
AMSRE-PRIASCAT
Regression matching CDF matching
In situ validation
Monday, September 23, 13

29. 25
September
2013
Trento
Correlation
coefficient between
all satellite products
and ground data sets
Brocca et al.,
2011 (RSE)
In situ validation
Monday, September 23, 13

30. 25
September
2013
Trento
Correlation
coefficient between
all satellite products
and ground data sets
Brocca et al.,
2011 (RSE)
Average
R-values ~0.80
In situ validation
Monday, September 23, 13

31. 25
September
2013
Trento
In situ validation (mountain regions)
Brocca et al., 2013 (VZJ)
ITALIAN
ALPS
Monday, September 23, 13

32. 25
September
2013
Trento
In situ validation (Africa)
MOROCCO
Tramblay et al., 2012 (HESS)
Monday, September 23, 13

33. 25
September
2013
Trento
In situ validation (USA)
… and in very interesting places !!!
HAWAII
Monday, September 23, 13

34. 25
September
2013
Trento
SM2RAIN
Monday, September 23, 13

35. 25
September
2013
Trento
R-metric
Monday, September 23, 13

36. 25
September
2013
Trento
RAINFALL
Doing Hydrology Backward
Brocca et al., 2013 (GRL)
Monday, September 23, 13

37. 25
September
2013
Trento
RAINFALL SOIL MOISTURE
Infiltration
evapotranspiration
Doing Hydrology Backward
Brocca et al., 2013 (GRL)
Monday, September 23, 13

38. 25
September
2013
Trento
RAINFALL SOIL MOISTURE
Infiltration
evapotranspiration
Doing Hydrology Backward
Brocca et al., 2013 (GRL)
Monday, September 23, 13

39. 25
September
2013
Trento
RAINFALL SOIL MOISTURE
Infiltration
evapotranspiration
Doing Hydrology Backward
Brocca et al., 2013 (GRL)
Monday, September 23, 13

40. 25
September
2013
Trento
Soil water
balance
equation
precipitation runoff
Evapo-
transpiration drainage
soil
depth
relative saturation
SM2RAIN
Monday, September 23, 13

41. 25
September
2013
Trento
Soil water
balance
equation
precipitation runoff
Evapo-
transpiration drainage
soil
depth
relative saturation
Inverting for p(t):
SM2RAIN
Monday, September 23, 13

42. 25
September
2013
Trento
Soil water
balance
equation
precipitation runoff
Evapo-
transpiration drainage
soil
depth
relative saturation
Assuming: + +
Inverting for p(t):
SM2RAIN
Monday, September 23, 13

43. 25
September
2013
Trento
Soil water
balance
equation
precipitation runoff
Evapo-
transpiration drainage
soil
depth
relative saturation
Assuming: + +
Inverting for p(t):
SM2RAIN
Monday, September 23, 13

44. 25
September
2013
Trento
Three sites in Italy, Spain and
France with hourly rainfall and
soil moisture observations are
selected
SM2RAIN testing: in-situ data
Monday, September 23, 13

45. 25
September
2013
Trento
Three sites in Italy, Spain and
France with hourly rainfall and
soil moisture observations are
selected
Estimation of daily rainfall for
1-year data
SM2RAIN testing: in-situ data
Monday, September 23, 13

46. 25
September
2013
Trento
Three sites in Italy, Spain and
France with hourly rainfall and
soil moisture observations are
selected
Estimation of daily rainfall for
1-year data
Italy
Spain
France
NS=0.82
NS=0.89
NS=0.81
SM2RAIN testing: in-situ data
Monday, September 23, 13

47. 25
September
2013
Trento
Results – ASCAT SWI
Estimation of
4-day rainfall
for 4-year data
Italy
Spain
NS=0.57
NS=0.62
Monday, September 23, 13

48. 25
September
2013
Trento
1) ASCAT TU-Wien (FTP)
2) AMSR-E LPRM - asc,
desc, asc+desc (VUA)
3) ESA – CCI SM product
4) ERA-Land (ECMWF)
and
1) TRMM 3B42v7
(standard satellite
rainfall product)
ASCAT GRID ~ 12.5 km
SM2RAIN testing: Italy
Brocca et al., 2013 (EGU poster)
Monday, September 23, 13

49. 25
September
2013
Trento
Correlation MAPS
AMSR-EASCAT
ESA-CCI
ERA-Land
TRMM
Monday, September 23, 13

50. 25
September
2013
Trento
Europe … Africa
Monday, September 23, 13

51. 25
September
2013
Trento
Europe … Africa
Monday, September 23, 13

52. 25
September
2013
Trento
Global scale
Brocca et al. (in preparation, NGS)
Monday, September 23, 13

53. 25
September
2013
Trento
Global scale
Brocca et al. (in preparation, NGS)
SM2RAIN(ASCAT) vs TRMM
Monday, September 23, 13

54. 25
September
2013
Trento
Antecedent Wetness
Conditions
Monday, September 23, 13

55. 25
September
2013
Trento
Antecedent Wetness Conditions
Brocca et al. 2009 (JoH) 2009 (JHE)
Monday, September 23, 13

56. 25
September
2013
Trento
P
Antecedent Wetness Conditions
Brocca et al. 2009 (JoH) 2009 (JHE)
Monday, September 23, 13

57. 25
September
2013
Trento
P
Rd
Antecedent Wetness Conditions
Brocca et al. 2009 (JoH) 2009 (JHE)
Monday, September 23, 13

58. 25
September
2013
Trento
P
Rd
Antecedent Wetness Conditions
SOIL
CONSERVATION
SERVICE METHOD
(SCS-CN)
Brocca et al. 2009 (JoH) 2009 (JHE)
Monday, September 23, 13

59. 25
September
2013
Trento
P
Rd
θ
Antecedent Wetness Conditions
SOIL
CONSERVATION
SERVICE METHOD
(SCS-CN)
Brocca et al. 2009 (JoH) 2009 (JHE)
Monday, September 23, 13

60. 25
September
2013
Trento
Tevere - PN
Cerfone
Timia
Assino
Genna
Topino
Niccone
Caina
Nestore
11 catchments
100-5000 km2
Italy
Tiber
River
ERS SCATTEROMETER SOIL
MOISTURE DATA
S vs θ relation: ERS SCAT
Brocca et al.,
2009 (JoH); 2009 (JHE)
Monday, September 23, 13

61. 25
September
2013
Trento
Tevere - PN
Cerfone
Timia
Assino
Genna
Topino
Niccone
Caina
Nestore
11 catchments
100-5000 km2
Italy
Tiber
River
ERS SCATTEROMETER SOIL
MOISTURE DATA
S vs θ relation: ERS SCAT
Brocca et al.,
2009 (JoH); 2009 (JHE)
Monday, September 23, 13

62. 25
September
2013
Trento
Tevere - PN
Cerfone
Timia
Assino
Genna
Topino
Niccone
Caina
Nestore
11 catchments
100-5000 km2
Italy
Tiber
River
ERS SCATTEROMETER SOIL
MOISTURE DATA
S vs θ relation: ERS SCAT
Brocca et al.,
2009 (JoH); 2009 (JHE)
Beck et al., 2010 (JSTARS)
Tramblay et al., 2010 (JoH), 2011 (NHESS)
Australia
France
Monday, September 23, 13

63. 25
September
2013
Trento
ALZETTE
RIVER
Average
T~17 days
S vs θ relation: ASCAT vs AMSR-E
Monday, September 23, 13

64. 25
September
2013
Trento
TIBER RIVER ALZETTE RIVER
S vs θ relation: ASCAT vs AMSR-E
Monday, September 23, 13

65. 25
September
2013
Trento
+0.04+0.14
TIBER RIVER ALZETTE RIVER
S vs θ relation: ASCAT vs AMSR-E
Monday, September 23, 13

66. 25
September
2013
Trento
S vs θ relation: whole ITALY
Analysis for 50
river basins
across the
whole Italian
territory
Monday, September 23, 13

67. 25
September
2013
Trento
S vs θ relation: whole ITALY
Tanaro River – Masio (4500 km²)
API5 ASCAT
SWI
Analysis for 50
river basins
across the
whole Italian
territory
Monday, September 23, 13

68. 25
September
2013
Trento
S vs θ relation: whole ITALY
Tanaro River – Masio (4500 km²)
API5 ASCAT
SWI
Analysis for 50
river basins
across the
whole Italian
territory
Monday, September 23, 13

69. 25
September
2013
Trento
Tramblay et al., 2012 (HESS)
S vs θ relation: Morocco
Monday, September 23, 13

70. 25
September
2013
Trento
Tramblay et al., 2012 (HESS)
S vs θ relation: Morocco
Monday, September 23, 13

71. 25
September
2013
Trento
Simplified
SOIL
MOISTURE
θ
Massari et al., 2013 (HESSD)
ou
ng
Monday, September 23, 13

72. 25
September
2013
Trento
Simplified
SOIL
MOISTURE
θ
S = a(1 - θ)
S
SOIL CONSERVATION
SERVICE METHOD (SCS-
CN)
θ
S
Massari et al., 2013 (HESSD)
ou
ng
Monday, September 23, 13

73. 25
September
2013
Trento
Simplified
SOIL
MOISTURE
θ
S = a(1 - θ)
S
SOIL CONSERVATION
SERVICE METHOD (SCS-
CN)
θ
S
EVENT-BASED
RAINFALL-RUNOFF
MODEL
Massari et al., 2013 (HESSD)
ou
ng
Monday, September 23, 13

74. 25
September
2013
Trento
DISCHARGE
Simplified
SOIL
MOISTURE
θ
S = a(1 - θ)
S
SOIL CONSERVATION
SERVICE METHOD (SCS-
CN)
θ
S
EVENT-BASED
RAINFALL-RUNOFF
MODEL
Massari et al., 2013 (HESSD)
ou
ng
Monday, September 23, 13

75. 25
September
2013
Trento
SCRRM: Greece
Early Warning
System for
Flood and Fire
forecasting
Massari et al., 2013 (HESSD)
Monday, September 23, 13

76. 25
September
2013
Trento
SCRRM: Greece
Early Warning
System for
Flood and Fire
forecasting
Massari et al., 2013 (HESSD)
Monday, September 23, 13

77. 25
September
2013
Trento
SCRRM: Greece
Early Warning
System for
Flood and Fire
forecasting
Massari et al., 2013 (HESSD)
ASCAT
AMSR-E
Monday, September 23, 13

78. 25
September
2013
Trento
Soil moisture
assimilation into
rainfall-runoff
modelling
Monday, September 23, 13

79. 25
September
2013
Trento
MISDc: "Modello Idrologico Semi-Distribuito in continuo"
W(t) S(t)
outlet
discharge
upstream
discharge
directly draining areas
linear reservoir IUH
EVENT-BASED
RAINFALL-RUNOFF
MODEL (MISD)
subcatchments
geomorphological IUH
channel routing
diffusive linear approach
rainfall excess
SCS-CN
e(t):
evapotranspiration
f(t):
infiltration
g(t):
percolation
Wmax
W(t)
s(t):
saturation
excess
SOIL WATER BALANCE
MODEL
S: soil potential maximum retention
W(t)/Wmax: saturation degree
r(t):
rainfall
Brocca et al., 2011 (HYP)
Rainfall-runoff model: MISDc
Monday, September 23, 13

80. 25
September
2013
Trento
MISDc: "Modello Idrologico Semi-Distribuito in continuo"
W(t) S(t)
outlet
discharge
upstream
discharge
directly draining areas
linear reservoir IUH
EVENT-BASED
RAINFALL-RUNOFF
MODEL (MISD)
subcatchments
geomorphological IUH
channel routing
diffusive linear approach
rainfall excess
SCS-CN
e(t):
evapotranspiration
f(t):
infiltration
g(t):
percolation
Wmax
W(t)
s(t):
saturation
excess
SOIL WATER BALANCE
MODEL
S: soil potential maximum retention
W(t)/Wmax: saturation degree
FREELY AVAILABLE !!!
http://hydrology.irpi.cnr.it/tools-and-files/misdc
r(t):
rainfall
Brocca et al., 2011 (HYP)
Rainfall-runoff model: MISDc
Monday, September 23, 13

81. 25
September
2013
Trento
Model implemented for real
time application for the
Umbria Region Civil
Protection Warning
System:
UPPER TIBER RIVER
Flood event of
January 2010
Jan-2010
http://www.cfumbria.it/
Real time flood forecasting
Monday, September 23, 13

82. 25
September
2013
Trento
Model implemented for real
time application for the
Umbria Region Civil
Protection Warning
System:
UPPER TIBER RIVER
Flood event of
January 2010
Jan-2010
http://www.cfumbria.it/
Real time flood forecasting
Monday, September 23, 13

83. 25
September
2013
Trento
Model implemented for real
time application for the
Umbria Region Civil
Protection Warning
System:
UPPER TIBER RIVER
Flood event of
January 2010
Jan-2010
http://www.cfumbria.it/
Real time flood forecasting
Monday, September 23, 13

84. 25
September
2013
Trento
Wagner et al., 1999 (RSE)
SWI: Soil Water Index
t: time
ti: acquisition time of
SSMti
SSMti
: relative surface soil
moisture
[0,1]
T: characteristic time
length
Soil Water Index (SWI)
Monday, September 23, 13

85. 25
September
2013
Trento
Wagner et al., 1999 (RSE)
SWI: Soil Water Index
t: time
ti: acquisition time of
SSMti
SSMti
: relative surface soil
moisture
[0,1]
T: characteristic time
length
SSM
SWI
Soil Water Index (SWI)
Monday, September 23, 13

86. 25
September
2013
Trento
1981
Soil moisture data assimilation
Monday, September 23, 13

87. 25
September
2013
Trento
Many studies performed synthetic experiments and tested different techniques and
approaches for soil moisture assimilation into rainfall-runoff modelling.
Soil moisture data assimilation
Monday, September 23, 13

88. 25
September
2013
Trento
Many studies performed synthetic experiments and tested different techniques and
approaches for soil moisture assimilation into rainfall-runoff modelling.
Aubert et al., 2003 (JoH)
Francois et al., 2003 (JHM)
Chen et al., 2011 (AWR)
Matgen et al., 2012 (AWR)
Brocca et al., 2010 (HESS)
Brocca et al., 2012 (IEEE TGRS)
However, very few studies employed REAL-DATA ... and the improvement in runoff prediction
obtained by the assimilation of soil moisture data is usually very limited.
Soil moisture data assimilation
Monday, September 23, 13

89. 25
September
2013
Trento
Many studies performed synthetic experiments and tested different techniques and
approaches for soil moisture assimilation into rainfall-runoff modelling.
1. Spatial Mismatch: i.e. point ("in-situ") or coarse (satellite) measurements are compared
with model predicted average quantities in space
 REPRESENTATIVENESS
2. Time Resolution: only recently soil moisture estimates from satellite data are available
with a daily (or less) temporal resolution (even if with a coarse spatial resolution) which is
required for RR applications
 DATA AVAILABILITY
3. Layer Depth: only the first 2-5 cm are investigated by remote sensing whereas in RR
models a "bucket" layer of 1-2 m is usually simulated
 ONLY SURFACE LAYER
4. Accuracy: the reliability at the catchment scale of soil moisture estimates obtained
through both in-situ measurements and satellite data is frequently poor
 TOO LOW QUALITY
Aubert et al., 2003 (JoH)
Francois et al., 2003 (JHM)
Chen et al., 2011 (AWR)
Matgen et al., 2012 (AWR)
Brocca et al., 2010 (HESS)
Brocca et al., 2012 (IEEE TGRS)
However, very few studies employed REAL-DATA ... and the improvement in runoff prediction
obtained by the assimilation of soil moisture data is usually very limited.
Soil moisture data assimilation
Monday, September 23, 13

90. 25
September
2013
Trento
time
relativesoilmoisture
observations
modeled soil moisture
updated soil moisture
Brocca et al., 2010 (HESS), 2012 (IEEE TGRS)
observations
Soil moisture data assimilation
Monday, September 23, 13

91. 25
September
2013
Trento
time
relativesoilmoisture
observations
modeled soil moisture
updated soil moisture
Brocca et al., 2010 (HESS), 2012 (IEEE TGRS)
observations
Soil moisture data assimilation
Monday, September 23, 13

92. 25
September
2013
Trento
time
relativesoilmoisture
observations
modeled soil moisture
updated soil moisture
Brocca et al., 2010 (HESS), 2012 (IEEE TGRS)
observations
Soil moisture data assimilation
Monday, September 23, 13

93. 25
September
2013
Trento
G is a constant
G=0 "perfect" model
G=1 direct insertion
time
relativesoilmoisture
observations
modeled soil moisture
updated soil moisture
Brocca et al., 2010 (HESS), 2012 (IEEE TGRS)
Kalman GAIN
model error
obs error
observations
Soil moisture data assimilation
Monday, September 23, 13

94. 25
September
2013
Trento
RAINFALL-
RUNOFF MODEL
COMPONENTS
Soil moisture data assimilation
Monday, September 23, 13

95. 25
September
2013
Trento
RAINFALL-
RUNOFF MODEL
DATA
ASSIMILATION
COMPONENTS
Soil moisture data assimilation
Monday, September 23, 13

96. 25
September
2013
Trento
RAINFALL-
RUNOFF MODEL
DATA
ASSIMILATION
COMPONENTS
OBSERVATIONS
Soil moisture data assimilation
Monday, September 23, 13

97. 25
September
2013
Trento
RAINFALL-
RUNOFF MODEL
SUB-COMPONENTS
Input/output data
Model parameter values
Model structure
DATA
ASSIMILATION
COMPONENTS
Technique (EKF, EnKF, PF, ...)
BIAS handling (CDF match, ...)
Error modelling (OBS, MOD)
OBSERVATIONS
Accuracy
Spatial/temporal resolution
Layer depth
Soil moisture data assimilation
Monday, September 23, 13

98. 25
September
2013
Trento
Niccone
Migianella
137 km2
Central Italy
Migianella experimental basin
Monday, September 23, 13

99. 25
September
2013
Trento
Runoff prediction
Brocca et al., 2012 (IEEE TGRS)
Monday, September 23, 13

100. 25
September
2013
Trento
Runoff prediction
Brocca et al., 2012 (IEEE TGRS)
Monday, September 23, 13

101. 25
September
2013
Trento
Runoff prediction
Brocca et al., 2012 (IEEE TGRS)
Monday, September 23, 13

102. 25
September
2013
Trento
Runoff prediction
Brocca et al., 2012 (IEEE TGRS)
Monday, September 23, 13

103. 25
September
2013
Trento
Runoff prediction
Brocca et al., 2012 (IEEE TGRS)
Monday, September 23, 13

104. 25
September
2013
Trento
improving
Runoff prediction
Brocca et al., 2012 (IEEE TGRS)
Monday, September 23, 13

105. 25
September
2013
Trento
Runoff prediction
Monday, September 23, 13

106. 25
September
2013
Trento
Runoff prediction
STRONG IMPROVEMENT
Monday, September 23, 13

107. 25
September
2013
Trento
without assimilation
with assimilation
without assimilation
with assimilation
model starts one months before the first events
Unknown initial conditions
Brocca et al., 2010 (HESS) – Open access
Monday, September 23, 13

108. 25
September
2013
Trento
without assimilation
with assimilation
without assimilation
with assimilation
model starts one months before the first events
SIM. ASS.
NS 36 83
|εQp| 43 18
|εRd| 59 24
Eff 62
Unknown initial conditions
Brocca et al., 2010 (HESS) – Open access
Monday, September 23, 13

109. 25
September
2013
Trento
without assimilation
with assimilation
without assimilation
with assimilation
model starts one months before the first events
SIM. ASS.
NS 36 83
|εQp| 43 18
|εRd| 59 24
Eff 62
Unknown initial conditions
Brocca et al., 2010 (HESS) – Open access
Monday, September 23, 13

110. 25
September
2013
Trento
Further applications …
Monday, September 23, 13

111. 25
September
2013
Trento
South Italy - Fiumarella
(33 km²)
USA - Lucky Hills
(0.04 km²)
Luxembourg - Bibesbach
(10.7 km²)
France - Valescure
(3.9 km²)
Central Italy - Assino
(165 km²)
Central Italy - Niccone
(137 km²)
Further applications …
Monday, September 23, 13

112. 25
September
2013
Trento
Summarizing …
Monday, September 23, 13

113. 25
September
2013
Trento
 the assimilation of the ECMWF product
has a slight impact due to the limited
time period (2009-2010)
Summarizing …
Monday, September 23, 13

114. 25
September
2013
Trento
 the assimilation of the ECMWF product
has a slight impact due to the limited
time period (2009-2010)
 for central Italy basins the assimilation
of ASCAT and AMSR-E provide a
significant improvement in model
performance
Summarizing …
Monday, September 23, 13

115. 25
September
2013
Trento
 the assimilation of the ECMWF product
has a slight impact due to the limited
time period (2009-2010)
 for central Italy basins the assimilation
of ASCAT and AMSR-E provide a
significant improvement in model
performance
 in south Italy a slight improvement can
be yet seen
Summarizing …
Monday, September 23, 13

116. 25
September
2013
Trento
 the assimilation of the ECMWF product
has a slight impact due to the limited
time period (2009-2010)
 for central Italy basins the assimilation
of ASCAT and AMSR-E provide a
significant improvement in model
performance
 in south Italy a slight improvement can
be yet seen
 in France no improvement can be
obtained due to the difficulties of
satellite data to retrieve soil moisture
over mountain areas
Summarizing …
Monday, September 23, 13

117. 25
September
2013
Trento
 the assimilation of the ECMWF product
has a slight impact due to the limited
time period (2009-2010)
 for central Italy basins the assimilation
of ASCAT and AMSR-E provide a
significant improvement in model
performance
 in south Italy a slight improvement can
be yet seen
 in France no improvement can be
obtained due to the difficulties of
satellite data to retrieve soil moisture
over mountain areas
 in Luxembourg the impact is limited due
to the presence of snow
Summarizing …
Monday, September 23, 13

118. 25
September
2013
Trento
 the assimilation of the ECMWF product
has a slight impact due to the limited
time period (2009-2010)
 for central Italy basins the assimilation
of ASCAT and AMSR-E provide a
significant improvement in model
performance
 in south Italy a slight improvement can
be yet seen
 in France no improvement can be
obtained due to the difficulties of
satellite data to retrieve soil moisture
over mountain areas
 in Luxembourg the impact is limited due
to the presence of snow
 in USA (arid catchment) soil moisture
temporal variability is limited thus the
assimilation do not have a significant
impact
Summarizing …
Monday, September 23, 13

119. 25
September
2013
Trento
Landslide prediction
Monday, September 23, 13

120. 25
September
2013
Trento
Torgiovannetto landslide
 Near Assisi
 Rock slope
(abandoned stone
quarry)
 First slide in 2003
 Landslide
monitoring
(extensometer,
inclinometer)
 Meteorological
monitoring (rainfall
and temperature)
Monday, September 23, 13

121. 25
September
2013
Trento
Rainfall versus displacements rate
Graziani et al.,
2009
Monday, September 23, 13

122. 25
September
2013
Trento
Data set
Soil moisture is estimated
through ASCAT and
considering an Antecedent
Precipitation Index
October 2007 – July 2009
Brocca et al., 2012 (RS) – Open access
Monday, September 23, 13

123. 25
September
2013
Trento
Rainfall events extraction
Monday, September 23, 13

124. 25
September
2013
Trento
................
Rainfall events extraction
Monday, September 23, 13

125. 25
September
2013
Trento
Multiple regression
1h max rainfall
Total rainfall
Displacements
Antecedent Precipitation Index (N=20 g)
Soil Water Index (T=75 g)
Monday, September 23, 13

126. 25
September
2013
Trento
Multiple regression
1h max rainfall
Total rainfall
Displacements
Antecedent Precipitation Index (N=20 g)
Soil Water Index (T=75 g)
1) only rainfall (Pmax-1h e Ptot)
2) rainfall + API20
3) rainfall + SWI75
4) rainfall + API20 + SWI75
Monday, September 23, 13

127. 25
September
2013
Trento
OBSERVED
ESTIMATED
1) only rainfall (Pmax-1h e Ptot)
Prediction of landslide movements
Monday, September 23, 13

128. 25
September
2013
Trento
2) rainfall + API20
OBSERVED
ESTIMATED
Prediction of landslide movements
Monday, September 23, 13

129. 25
September
2013
Trento
3) rainfall + SWI75
OBSERVED
ESTIMATED
Prediction of landslide movements
Monday, September 23, 13

130. 25
September
2013
Trento
Prediction of landslide movements
4) rainfall + API20 + SWI75
OBSERVED
ESTIMATED
Monday, September 23, 13

131. 25
September
2013
Trento
Prediction of landslide movements
Monday, September 23, 13

132. 25
September
2013
Trento
Landslide forecasting
Operational system
TORGIOVANNETTO
soil moisture
rainfall
LANDWARN
rainfall + soil moisture thresholds
Monday, September 23, 13

133. 25
September
2013
Trento
MALARIA OUTBREAKSNUMERICAL
WEATHER
PREDICTION
Capecchi, Albergel, De Rosnay, …
FLOOD DETECTION
Lacava, Temimi, ...
Montanari, Montosi, ...
Further soil moisture applications
EROSION
Todisco, Mannocchi, Bagarello, Ferro, ...
Soil moisture*Rainfall intensity
Soillosses
Monday, September 23, 13

134. 25
September
2013
Trento
Conclusions
(finally )
Monday, September 23, 13

135. 25
September
2013
Trento
Remote sensing soil moisture products are found accurate
for soil moisture estimation across Europe (and worldwide)
Conclusions
Monday, September 23, 13

136. 25
September
2013
Trento
Remote sensing soil moisture products are found accurate
for soil moisture estimation across Europe (and worldwide)
The use of soil moisture products might improve flood and
landslide prediction
Conclusions
Monday, September 23, 13

137. 25
September
2013
Trento
Remote sensing soil moisture products are found accurate
for soil moisture estimation across Europe (and worldwide)
The use of soil moisture products might improve flood and
landslide prediction
Satellite soil moisture product can be also employed as
additional tool for rainfall estimation
Soil moisture data obtained from coarse-resolution
sensors can provide useful information for many
applications, new important challenges and opportunities
for the use of these new sources of data are opened
Conclusions
Monday, September 23, 13

138. 25
September
2013
Trento
Remote sensing soil moisture products are found accurate
for soil moisture estimation across Europe (and worldwide)
The use of soil moisture products might improve flood and
landslide prediction
Satellite soil moisture product can be also employed as
additional tool for rainfall estimation
Soil moisture data obtained from coarse-resolution
sensors can provide useful information for many
applications, new important challenges and opportunities
for the use of these new sources of data are opened
Conclusions
Who is interested to obtain satellite soil moisture data can contact
me for getting information. Please do not hesitate.
Monday, September 23, 13

139. References cited
 Aubert, D. et al. (2003). Sequential assimilation of soil moisture and
streamflow data ... JoH., 280,145-161.
 Bolten, J.D. et al. (2010). Evaluating the utility of remotely-sensed
soil moisture for agricultural monitoring. JSTARS, 3, 57-66.
 Brocca, L., et al. (2009). Soil moisture temporal stability over
experimental areas of central Italy. GEOD, 148 (3-4), 364-374.
 Brocca, L., et al. (2009). Assimilation of observed soil moisture data
in storm rainfall-runoff modelling. JHE 14, 153-165.
 Brocca, L., et al. (2010). Improving runoff prediction through the
assimilation of the ASCAT soil moisture... HESS, 14, 1881-1893.
 Brocca, L., et al. (2010). Spatial-temporal variability of soil moisture
and its estimation across scales. WRR, 46,W02516.
 Brocca, L., et al. (2011). Distributed rainfall-runoff modelling for …
flood forecasting. HYP, 25, 2801-2813.
FOR FURTHER INFORMATION
URL: http://hydrology.irpi.cnr.it/people/l.brocca
URL IRPI: http://hydrology.irpi.cnr.it
This presentation is available for download at:
http://hydrology.irpi.cnr.it/repository/public/presentations/2013/seminatio-trento-l.-brocca
 Brocca, L. et al. (2011). Soil moisture estimation through ASCAT and AMSR-E sensors ... across Europe. RSE, 115, 3390-3408.
 Brocca, L., et al. (2012). Soil moisture spatial-temporal variability at catchment scale. JoH, 422-423, 63-75.
 Brocca, L., et al. (2012). Assimilation of surface and root-zone ASCAT soil moisture products into rainfall-runoff ... IEEE TGRS, 50(7), 1-14.
 Brocca, L., et al. (2012). Improving Landslide Forecasting Using ASCAT-Derived Soil Moisture Data: A Case Study ... RS, 4, 1232-1244.
 Brocca, L., et al. (…). Soil moisture estimation in alpine catchments through modelling and satellite observations. submitted to VZJ.
 Brocca, L., et al. (...). A new method for rainfall estimation through soil moisture observations. submitted to GRL
 Chen, F. et al. (2011). Improving hydrologic predictions of catchment model via assimilation of surface soil moisture. AWR, 34 526-535.
 Cosh, M.H. et al. (2006). Temporal stability of surface soil moisture in the Little Washita River and its applications... validation. JoH, 323, 168-177.
 de Rosnay, P. et al. (2009). Multi-scale soil moisture measurements at the Gourma meso-scale site in Mali. JoH, 375, 241-252.
 Dharssi, I. et al. (2011). Operational assimilation of ASCAT surface soil wetness at the Met Office, HESS, 15, 2729-2746.
 Francois, C. et al. (2003). Sequential assimilation of ERS-1 SAR data into a coupled land surface-hydrological model using EKF.JHM 4(2), 473–487.
 Han, E., et al. (2012). Application of data assimilation with the RZQM for soil moisture profile estimation. HYP, 26, 1707–1719.
 Jackson, T. et al. (1981). Soil moisture updating and microwave remote sensing for hydrological simulation. HSJ, 26, 3, 305-319.
 Koster, R.D. et al. (2011). Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow. Nature Geo, 3 613-616.
 Matgen, P. et al. (2012). Can ASCAT-derived soil wetness indices reduce predictive uncertainty in well-gauged areas? A comparison with in situ
observed soil moisture in an assimilation application. AWR, 44, 49-65.
 Nearing, M. et al. (2005). Modeling response of soil erosion and runoff to changes in precipitation and cover. CAT, 61, 131-154.
 Owe M., et al. (2008). Multi-sensor historical climatology of satellite-derived global land surface moisture. JGR, 113, F01002.
 Tramblay, Y., et al. (2012). Estimation of antecedent wetness conditions for flood modelling in Northern Morocco. submitted to HESS.
 Wagner, W., et al. (1999). A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data, RSE 70, 191-207.
 Zhao, Y. et al. (2010). Controls of surface soil moisture spatial patterns and their temporal stability in a semi-arid steppe. HYP, 24, 2507-2519.
Monday, September 23, 13

140. References cited
 Aubert, D. et al. (2003). Sequential assimilation of soil moisture and
streamflow data ... JoH., 280,145-161.
 Bolten, J.D. et al. (2010). Evaluating the utility of remotely-sensed
soil moisture for agricultural monitoring. JSTARS, 3, 57-66.
 Brocca, L., et al. (2009). Soil moisture temporal stability over
experimental areas of central Italy. GEOD, 148 (3-4), 364-374.
 Brocca, L., et al. (2009). Assimilation of observed soil moisture data
in storm rainfall-runoff modelling. JHE 14, 153-165.
 Brocca, L., et al. (2010). Improving runoff prediction through the
assimilation of the ASCAT soil moisture... HESS, 14, 1881-1893.
 Brocca, L., et al. (2010). Spatial-temporal variability of soil moisture
and its estimation across scales. WRR, 46,W02516.
 Brocca, L., et al. (2011). Distributed rainfall-runoff modelling for …
flood forecasting. HYP, 25, 2801-2813.
Thanks for your attention
FOR FURTHER INFORMATION
URL: http://hydrology.irpi.cnr.it/people/l.brocca
URL IRPI: http://hydrology.irpi.cnr.it
This presentation is available for download at:
http://hydrology.irpi.cnr.it/repository/public/presentations/2013/seminatio-trento-l.-brocca
 Brocca, L. et al. (2011). Soil moisture estimation through ASCAT and AMSR-E sensors ... across Europe. RSE, 115, 3390-3408.
 Brocca, L., et al. (2012). Soil moisture spatial-temporal variability at catchment scale. JoH, 422-423, 63-75.
 Brocca, L., et al. (2012). Assimilation of surface and root-zone ASCAT soil moisture products into rainfall-runoff ... IEEE TGRS, 50(7), 1-14.
 Brocca, L., et al. (2012). Improving Landslide Forecasting Using ASCAT-Derived Soil Moisture Data: A Case Study ... RS, 4, 1232-1244.
 Brocca, L., et al. (…). Soil moisture estimation in alpine catchments through modelling and satellite observations. submitted to VZJ.
 Brocca, L., et al. (...). A new method for rainfall estimation through soil moisture observations. submitted to GRL
 Chen, F. et al. (2011). Improving hydrologic predictions of catchment model via assimilation of surface soil moisture. AWR, 34 526-535.
 Cosh, M.H. et al. (2006). Temporal stability of surface soil moisture in the Little Washita River and its applications... validation. JoH, 323, 168-177.
 de Rosnay, P. et al. (2009). Multi-scale soil moisture measurements at the Gourma meso-scale site in Mali. JoH, 375, 241-252.
 Dharssi, I. et al. (2011). Operational assimilation of ASCAT surface soil wetness at the Met Office, HESS, 15, 2729-2746.
 Francois, C. et al. (2003). Sequential assimilation of ERS-1 SAR data into a coupled land surface-hydrological model using EKF.JHM 4(2), 473–487.
 Han, E., et al. (2012). Application of data assimilation with the RZQM for soil moisture profile estimation. HYP, 26, 1707–1719.
 Jackson, T. et al. (1981). Soil moisture updating and microwave remote sensing for hydrological simulation. HSJ, 26, 3, 305-319.
 Koster, R.D. et al. (2011). Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow. Nature Geo, 3 613-616.
 Matgen, P. et al. (2012). Can ASCAT-derived soil wetness indices reduce predictive uncertainty in well-gauged areas? A comparison with in situ
observed soil moisture in an assimilation application. AWR, 44, 49-65.
 Nearing, M. et al. (2005). Modeling response of soil erosion and runoff to changes in precipitation and cover. CAT, 61, 131-154.
 Owe M., et al. (2008). Multi-sensor historical climatology of satellite-derived global land surface moisture. JGR, 113, F01002.
 Tramblay, Y., et al. (2012). Estimation of antecedent wetness conditions for flood modelling in Northern Morocco. submitted to HESS.
 Wagner, W., et al. (1999). A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data, RSE 70, 191-207.
 Zhao, Y. et al. (2010). Controls of surface soil moisture spatial patterns and their temporal stability in a semi-arid steppe. HYP, 24, 2507-2519.
Questions?
Monday, September 23, 13