This document summarizes topics related to flood monitoring and mapping using remote sensing techniques including unmanned aerial vehicles (UAVs). It discusses how digital elevation models from satellites and UAVs can be used to identify flood-prone areas and monitor river morphology. Case studies on the Bradano River basin in Italy demonstrate flood mapping using 1D and 2D hydrologic models. The document also presents an approach called soil moisture analytical relationship (SMAR) to measure soil moisture from surface measurements and discusses its application in Niger.

1. UNIVERSITÀ DEGLI STUDI DELLA BASILICATA
DICEM – salvatore.manfreda@unibas.it
Surface Hydrology and Flood Plains
Prof. Salvatore MANFREDA
APPLIED COURSE ON UAVs FOR ENVIRONMENTAL MONITORING
University of Basilicata, Matera – 27-31 Luglio 2015

2. Flood
Exposure
at
the
Global
Scale

3. Flood
Monitoring

4. Are
Natural
Hazard
increasing?

5. Number
of
Reported
Events

6. Flood
Mapping

7. Flood
Mapping:
LimitaCons

8. Geomorphic
Approaches

9. Geomorphic
Approaches

10. Digital
ElevaCon
Models
• The
increasing
availability
of
digital
terrain
models
has
given
a
strong
impulse
to
the
development
of
so
called
distributed
and
DEM-­‐based
models.
• Digital
terrain
model
obtained
through
interferometric
data
gathered
by
the
space
shuIle
campaign
by
NASA
with
a
cellsize
of
90m.
(CGIAR-­‐CSI:
hIp://srtm.csi.cgiar.org/)
• ASTER
GDEM
30m
available
from
June
2009
(hIp://
asterweb.jpl.nasa.gov/gdem.asp
)
• AddiConal
informaCon
at
high
resoluCon
may
be
obtained
by
the
use
of
UAVs.

11. Advantages
In
the
Use
of
UAVs
• Ability
to
monitor
the
river
morphology
over
a
relaCvely
large
area
up
to
0.5km2;
• Possibility
to
monitor
flood
extent
and
flow
velocity
at
the
surface;
•
Possibility
to
update
flood
risk
a]er
rapid
changes
of
the
river
morphology
(e.g.
in
riverbanks);
• Possibility
to
monitor
the
temporary
deposits
of
floaCng
materials
and
flood
damages
over
an
area.

12. Basin
morphology
contains
an
extraordinary
amount
of
informaCon.
Digital
Eleva+on
Models
(DEMs)
based
approaches
for
the
idenCficaCon
of
flood-­‐prone
areas
over
large
regions
or
for
a
preliminary
iden+fica+on
in
non-­‐studied
areas.
Basin
Morphology
(Large
Scale)
12

13. Basin
Morphology
(Small
Scale)
Lidar
DEM
with
2m
resoluCon
Generally
in
hydrology
most
of
the
problems
related
to
flood
risk
are
related
to
small
basins
or
flat
region.
In
these
case,
we
need
• Detailed
descripCon
of
the
DEM;
• Need
to
monitor
changes
in
river
morphology;
• Small
scale
surveys
may
help
in
understanding
erosional/
deposiConal
processes.

14. Downslope
Index
Mod.
Topographic
Index
ln[hl/H]
[hr-­‐H]/tan(αd)
ln[hr/H]
[hr-­‐H]/D
Linear
binary
classifiers
Contribu+ng
area
[km2]
Slope
[-­‐]
Eleva+on
difference
to
the
nearest
channel
[m]
Curvature
[-­‐]
Distance
to
the
nearest
channel
[m]
DEM-­‐derived
morphologic
descriptors
of
the
Bradano
River
basin
(Basilicata,
Italy).
Single
features
Composite
indices

15. 15
APPLICATION:
BRADANO
RIVER
(ITALY)
(A) Flood
map
derived
by
using
a
1-­‐D
approach
over
the
enCre
basin
of
Bradano.
(B)
Flood
map
derived
by
using
a
2-­‐D
approach
at
the
outlet
of
Bradano
River
basin.
(A)
(B)
En+re
basin
Outlet

16. Measuring
soil
moisture
based
on
surface
measurements
InfiltraCon
Soil
Water
Losses

17. Soil
Moisture
AnalyCcal
RelaConship
(SMAR)
(Manfreda
et
al.,
HESS
2014)

18. SMAR
applicaCon
in
NIGER

19. SMAR
applicaCon
in
NIGER
Comparison
between
the
relaCve
saturaCon
at
5
cm
(s1)
and
the
averaged
value
over
100,
130,
and
135
cm
depth,
and
the
filtered
value
(s2SMAR
–
black
line)
obtained
with
SMAR
for
two
sites
located
atWankama
(A)
and
Tondikiboro
(B),
respecCvely

20.
….Thanks