A new geomorphic index for the detection of flood-prone areas at large scale

XXXVCONVEGNONAZIONALEDIIDRAULICAECOSTRUZIONIIDRAULICHEBologna,14-16Settembre2016

Anewgeomorphicindexforthedetectionofflood-proneareasatlargescale

C. Samela1, T. J. Troy2, A. Sole1 e S. Manfreda1

1Università degli Studi della Basilicata, Potenza, 85100, Italy, [email protected];2 Lehigh University, Bethlehem, PA 18015, USA.

Valutazione e mitigazione di pericolosità e rischio idraulico


CATERINASAMELA“Anewgeomorphicindexforthedetectionofflood-proneareasatlargescale”

FLOOD HAZARD

Thesecountriesareallconsideredleastdevelopedordeveloping.

More people are affected by floods than by any other type of natural disaster.New analysis (World Resources Institute, 2016) shows that approximately 21 million peopleworldwide are affected by river floods each year on average.



MOTIVATION: WHY SIMPLIFIED PROCEDURES?Hydrologicalandhydraulicmodelsarethebestapproachforderivingdetailedinundationmaps,buttheyrequire:ü largeamountsofmoneyandtimeü significantamountofdataandparameters notavailableforallareas.

Poordensityofgaugingstationsinsomeregions(Asia,Africa,Australia).(Herold andMouton,2011)

Floodriskassessmentindatapoorenvironmentsposesagreatdealofchallenge.



GEOMORPHIC PROCEDURESBasinmorphologycontainsanextraordinaryamountofinformation.

Research questions:1) Does exist a physical attribute of the surface able to reveal if a portionof a river basin is exposed to flooding?

2) Is it possible to use such descriptor to map the flood exposure overlarge scale/unstudied areas?

Aim:Develop a practical and cost-effective way to efficiently characterizefloodplains in non studied areas using readily available data.



LINEAR BINARY CLASSIFICATION

ü SRTM:NASAShuttleRadarTopographyMission(hydrosheds.cr.usgs.gov/index.php).

ü ASTER:METI(Japan)andNASAAdvancedSpaceborne ThermalEmissionandReflectionRadiometerGlobalDigitalElevationModel(http://asterweb.jpl.nasa.gov/gdem.asp).

DEM(SRTM)oftheUpperTevere RiverBasinat90mofresolution.

INPUTDATA1. Digitalrepresentationsoftheterrainmorphology(DEMs)

Datasource:remotesensedelevationdatasetsavailableatmoderateresolutionovertheentireglobe:

2. Standard Flood hazard mapsData source: Flood inundation maps obtained byhydraulic simulations.

Alinearbinaryclassificationisperformedtodividethebasincellsinflood-proneandnotpronetofloodareas.Linearclassifiersseparatethedatasetsusinga“linearboundary”.

(Degiorgis etal.,2012;Manfredaetal.,2014)


ln(hl/H)

(hr-H)/tan(αd)

GeomorphicFloodIndex,ln(hr/H)

(hr-H)/D

DownslopeIndex,DWi(Hjerdtetal.,2004)

Mod.Topographic Index,Tim(Manfredaetal.,2011)

TESTED MORPHOLOGIC DESCRIPTORS

Contributingarea,A[km2]

Slope,S[-]

Elevation differencetothenearest channel,H[m] Curvature,∇

2H [-]

Distance tothenearestchannel [m]

DEM-derivedmorphologicdescriptorsfortheBradanoRiverbasin(Basilicata,Italy).

Singlefeatures Compositeindices

Newly formulated



WATER LEVEL ESTIMATEh is calculated for each basin location assuming a scaling relationship with thecontributing area in that location (A) by using an hydraulic scaling relation:

h ≈𝑏𝐴$

hl function of the contributing areain the location (Al) under exam

(A)

hr ≈ bArn

H

D(B)

Location under exam

Nearest element of the river network

along the flow pathFlow path

hr computed as a function of thecontributing area Ar in the section ofthe drainage network (‘R’ stands forriver) hydrologically connected to thepoint under exam.

hr≈𝒃𝑨𝒓𝒏hl ≈𝒃𝑨𝒍𝒏



Ethiopia,AFRICA(Samela et al., 2015)

8river basin in(ITALY):• Tiber• Chiascio• Basento• Cavone• Agri• Sinni• Noce• Bradano

TESTING THE RELIABILITY IN DIFFERENT CONTEXTS

United States ofAmerica

(Samela et al., 2016)

(Manfreda et al., 2015)



TESTS

Sensitivity of the classifiers to changes in the input data interms of:i. DEM resolution;ii. standard flood maps adopted (1-D or 2-D hydraulic

model);iii. dominant topography of the training area;

• Are the thresholds identified for the various indices related to basincharacteristics, such as topography?

• How robust are the thresholds and how transferrable?

iv. size of the training area;• What percentage of a basin's area requires calibration?


APPLICATION: BRADANO RIVER (ITALY)

Entire basin Outlet1. Marked topography;2. Standardflood hazard map derived

witha1-Dhydraulic model;3. moderateresolution DEM(90m).

1. Extremely flat topography;2. Standardflood hazard map derived

witha2-Dhydraulic model;3. Highresolution DEM (LiDAR10m).

OutletArea(A) (B)

(A)SRTMDEMoftheentireBradanoRiverbasin.(B)LiDARDEMoftheoutletofBradanoRiver.


BRADANORIVER- Entire Basin -

BRADANORIVER- Outlet-

OPTIMALClassifierAUC≈1

RANDOMClassifierAUC≈0.5

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1ROC Curves - Features

False Positive Rate, RFP

True

Pos

itive

Rat

e, R

TP

Contributing area (A)Curvature (Ñ2H)Slope (S)Flow distance (D)Elevation difference (H)

(A)

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1ROC Curves - Indices

False Positive Rate, RFPTr

ue P

ositiv

e R

ate,

RTP

TImDWiGFIln(hl/H)(hr-H)/DWi(hr-H)/D

(B)

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8



True

Pos

itive

Rat

e, R

TP


(C)

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8



True

Pos

itive

Rat

e, R TP

TImDWiGFIln(hl/H)(hr-H)/DWi(hr-H)/D

(D)

APPLICATION: BRADANO RIVER (ITALY)


TEST: SENSITIVITY OF THRESHOLDS TO TOPOGRAPHY - Calibrationintensub-catchmentindividually(500-yearflood);- ValidationacrossthetributaryusingtheFEMA(FederalEmergencyManagement

Agency)floodhazardmaps.

Drainage area529000 km2


0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8



True

Pos

itive

Rat

e, R

TP

(C)


Steepest basin,mean slope 34%

Flattest basin,mean slope 2%

OPTIMALClassifierAUC≈1

RANDOMClassifierAUC≈0.5

APPLICATION: OHIO RIVER BASIN (USA)

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8



True

Pos

itive

Rat

e, R

TP

(A)


0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8


False Positive Rate, RFPTr

ue P

ositiv

e R

ate,

RTP

(B)

ln(hl/H)GFI(hr-H)/DWi(hr-H)/DTImDWi

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8



True

Pos

itive

Rat

e, R

TP

(D)

ln(hl/H)GFI(hr-H)/DWi(hr-H)/DTImDWi


VALIDATION ON AREAS WITH SIMILAR TOPOGRAPHY

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1True Positive rate: RTP(Calibration) VS RTP(Validation)

RTP(Calibration)

RTP

(Val

idat

ion)

(A)

Flow distance (D)Elevation difference (H)ln(hl/H)GFI

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1False Positive rate: RFP(Calibration) VS RFP(Validation)

RFP(Calibration)

RFP

(Val

idat

ion)

(B)

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1True Positive rate: RTP(Calibration) VS RTP(Validation)

RTP(Calibration)

RTP

(Val

idat

ion)

(C)

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1False Positive rate: RFP(Calibration) VS RFP(Validation)

RFP(Calibration)

RFP

(Val

idat

ion)

(D)

HILLY SUB-BASINS

FLAT SUB-BASINS


ln(hl/H)

(hr-H)/tan(αd)

GeomorphicFloodIndex,ln(hr/H)

(hr-H)/D

DownslopeIndex,DWi(Hjerdtetal.,2004)

Mod.Topographic Index,Tim(Manfredaetal.,2011)

TESTED MORPHOLOGIC DESCRIPTORS

Contributingarea,A[km2]

Slope,S[-]

Elevation differencetothenearest channel,H[m] Curvature,∇

2H [-]

Distance tothenearestchannel [m]

DEM-derivedmorphologicdescriptorsfortheBradanoRiverbasin(Basilicata,Italy).

Compositeindices

Newly formulated

Singlefeatures



TEST: TRANSFERABILITY OF THE PARAMETERS

- Swapthethresholdstodelineatethefloodplainsinsub-basinswithadifferenttopography;

- ValidationacrossthetributaryusingtheFEMAfloodhazardmaps.

bestperformingGeomorphicFloodIndex

ln(hr/H)followedbytheflow

distance,D


TRANSFERABILITY OF PARAMETERS: VALIDATION

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1True positive rates: RTP(CalibrationFLAT) VS RTP(ValidationHILLY)

RTP(CalibrationFLAT)

RTP

(Val

idat

ion H

ILLY

)

(A)

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1False positive rates: RFP(CalibrationFLAT) VS RFP(ValidationHILLY)

RFP(CalibrationFLAT)

RFP

(Val

idat

ion H

ILLY

)

(B)

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1True positive rates: RTP(CalibrationHILLY) VS RTP(ValidationFLAT)

RTP(CalibrationHILLY)

RTP

(Val

idat

ion FL

AT)

(C)

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1False positive rates: RFP(CalibrationHILLY) VS RFP(ValidationFLAT)

RFP(CalibrationHILLY)

RFP

(Val

idat

ion FL

AT)

(D)

Flow distance (D)Elevation difference (H)ln(hl/H)GFI

FLAT TO HILLY SUB-BASINS

HILLY TO FLAT SUB-BASINS



TEST: PERCENTAGE OF BASIN'S AREA REQUIRED FOR CALIBRATION

12square grids:from4%to0.01%oftheOhiodrainage area.

Each element ofthegridswas used as calibration area.


D H GFI ln(hl/H)

0.01% 8.9% 130.0% 17.9% 12.0%0.02% 6.5% 123.7% 15.3% 13.0%0.04% 5.2% 116.7% 15.7% 11.9%0.06% 4.9% 114.0% 14.1% 11.5%0.08% 4.0% 111.2% 13.9% 14.6%0.10% 3.8% 110.1% 13.3% 12.1%0.30% 3.3% 102.9% 12.8% 9.0%0.50% 3.2% 102.8% 12.6% 11.0%1% 3.1% 90.9% 11.4% 7.3%2% 2.3% 82.4% 9.8% 6.0%3% 2.1% 87.3% 10.9% 6.1%4% 2.4% 81.6% 8.8% 5.7%

0.0%

20.0%

40.0%

60.0%

80.0%

100.0%

120.0%

140.0%

THRESHOLDS COEFFICIENT OF VARIATION

TEST: PERCENTAGE OF BASIN'S AREA REQUIRED FOR CALIBRATION


TEST: PERCENTAGE OF BASIN'S AREA REQUIRED FOR CALIBRATIONCOEFFICIENT OF VARIATION OF THE THRESHOLDS

0 2000 4000 6000 8000 10000 12000 14000 160002

3

4

5

6

7

8

9Flow path distance D

Calibration area (km2)

Coe

ffici

ent o

f Var

iatio

n (%

)

0 2000 4000 6000 8000 10000 12000 14000 1600080

85

90

95

100

105

110

115

120

125

130Elevation difference H


Coe

ffici

ent o

f Var

iatio

n (%

)

0 2000 4000 6000 8000 10000 12000 14000 160008

9

10

11

12

13

14

15

16

17

18

Geomorphic Flood Index ln(hr/H)


Coe

ffici

ent o

f Var

iatio

n (%

)

0 2000 4000 6000 8000 10000 12000 14000 160005

6

7

8

9

10

11

12

13

14

15

ln(hl/H)


Coe

ffici

ent o

f Var

iatio

n (%

)



TEST: VALIDATION OVER THE CONTINENTAL U.S. USING FEMA’S FLOODPLAIN MAPS

Pictorial representation of the 100 yr flood-prone areas for the continental U.S.according to the linear binary classifierbased on the GFI.The large-scale map allows to see that theindex produces a realistic description of theflood prone areas, with the possibility toextend the flood hazard information inthose portions of the Country where theFEMA’s maps are lacking (grey areas).

EXAMPLEOF APPLICATION



GeomorphicFlood Index ln(hr/H)

CONCLUSIONS

Performancelesssensitiveto:ü thedifferenttopographyofthetrainingarea.ü thesizeofthecalibrationarea;ü theresolutionoftheadoptedDigitalElevationModel(DEM);ü thereferencehydraulicmapusedforcalibration.

The geomorphic procedure proposed can be a useful tool to have a preliminary but efficientdelineation in unstudied areas with simple data requirements, low costs and reducedcomputational times.

This kind of simplified approach is generally of high interest to both researchers and decision-makers since increasing portions of the population affected by flooding live in developing countrieswhere data availability is often poor.



RELATED PUBLICATION

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Thanks for your attentionQuestions?

Considerations?

1. Samela, C., Troy, T. J., & Manfreda, S. (2016), Flood Hazard Mapping over Large Regions, Advances in water Resources. (Under Review).2. Samela, C., Manfreda, S., De Paola, F., Giugni, M., Sole, A., & Fiorentino, M. (2015). Dem-based approaches for the delineation of flood prone areas in

an ungauged basin in Africa, Journal of Hydrologic Engineering.3. Manfreda, S., Samela, C., Gioia, A., Consoli, G., Iacobellis, V., Giuzio, L., Cantisani, A., & Sole, A. (2015). Flood-Prone Areas Assessment Using Linear

Binary Classifiers based on flood maps obtained from 1D and 2D hydraulic models, Natural Hazards.4. Manfreda, S., F. Nardi, C. Samela, S. Grimaldi, A.C. Taramasso, G. Roth, A. Sole (2014). Investigation on the Use of Geomorphic Approaches for the

Delineation of Flood Prone Areas, Journal of Hydrology.5. Manfreda, S., C. Samela, A. Sole and M. Fiorentino (2014). Flood-Prone Areas Assessment Using Linear Binary Classifiers based on Morphological

Indices, ASCE-ICVRAM-ISUMA 2014.6. Di Leo, M., Manfreda, S., Fiorentino, M. (2011). An automated procedure for the detection of flood prone areas: r.hazard.flood, Geomatics Workbooks

n. 10 - "FOSS4G-it: Trento 2011", 83-89.7. Manfreda, S., Di Leo, M., & Sole, A. (2011). Detection of Flood Prone Areas using Digital Elevation Models. Journal of Hydrologic Engineering, 16(10),

781-790.

A new geomorphic index for the detection of flood-prone areas at large scale

Engineering

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