Effect of DEMs generated from different sources on flood inundation mapping

Presented by:

Banamali Panigrahi (11AG62R16) Under the Guidance of

Dr. C. Chatterjee

Agricultural and Food Engineering Department Indian Institute of Technology

Kharagpur ,721 302

OutlinesOutlines

Odisha is one of the major flood affected states of India.

Flood inundation mapping plays a major role in conveying flood risk information.

One of the major issues in producing accurate flood inundation maps is uncertainty.

Flow estimation from hydrologic model Input data Modeling type Model set up and assumption Model parameters Lack of data

From the input data, topography is a key factor which affects flood inundation mapping

Introduction

Objectives

To compare the errors in elevation arising from different sources of DEMs, and

To study the effect of DEMs generated from different sources on flood inundation mapping

Study Area

Study Area

KushabhadraBhargavi

DayaK

uakh

ai

Ratnachira

Prachi

Devi

Figure: Drainage network of Study Area

Salient FeaturesLat:19˚ 50'38.53˝-20˚ 26'21˝Long:85˚ 51< 5.62=-86˚ 1< 12.61˝Boundaries extent: N-Jagatsinghpur S-Bay of Bengal & Ganjam District E-Khurda W-Bay of BengalAreal Extent: 520 Km2

Mean Elevation: 10 m

Balianta Gauge Station

Nimapada Gauge Station

Satellite Stereo pairCartoSat-1(Image paired Captured in 2008 and 2009)

Field Survey DataDifferential Global Positioning System (DGPS) dataCross-section Survey data (Superintendence Co. (P) Ltd.)

DEM Data90m- Shuttle Radar Topography Mission (SRTM) [http://srtm.csi.cgiar.org]

30m-Advanced Space borne Thermal Emission and Reflection (ASTER) [https://earthexplorer.usgs.gov]

30m-CartoSat-1 [http://bhuvan.nrsc.gov.in]

Discharge and Water level Data Balianta & Nimapada Gauge Station

Data Used

Nabatia

Haripur

Balanga

Suanda

Chandanpur

Banamalipur

Nimapada

Gop

Figure : Ground control points on the CARTOSAT-1 satellite data for respective base stations

DGPS Survey Elevation Data

Cross-section Survey data ( By Superintendence Co. (P) Ltd.)

90 cross-section survey was carried out in the entire study area.

•Kuakhai-13 Cs•Bhargavi-26 Cs• Daya-6 Cs• Kushabhadra-45 Cs

Cumulative chainage length and length from left bank to right bank was surveyed. All the data sets are available in hard copy as well as soft copy. Cs profile of rivers are available in auto-CAD format.

Figure : Cross-section points on the CartoSat-1 satellite data

Satellite Data (Stereo pair)

Ortho-rectification

Import Image

Block Adjustment

Block Development

Addition of GCP

Validation of DEM

Block Processing (DTM Generation)

DEM Generation

Triangulation

DGPS Survey Data

Datum Transfer

Post Processing of Field Data

Trim

ble B

usin

ess C

enter R

3 Softw

are

Figure: Flowchart for Methodology

Methodology

River Network

Hydrodynamic Parameters

Cross Sections

Boundary Conditions Comparison of

Water level Extent for different DEMs

Modeling of flow in river

Statistical Parameters

GPSelevation

Google earth elevation

ASTER DEM elevation

SRTM DEM elevation

BHUBAN CartoSat-1elevation

No. of locations 122 122 122 122 122

MIN (m) 03.63 09.00 05.00 07.00 -61.00

MAX (m) 16.60 19.00 37.00 20.00 -37.00

MEAN (m) 09.17 13.63 13.60 13.68 -46.32

SD (m) 03.13 02.70 05.70 02.94 04.65

SEM (m) 00.28 00.24 00.50 00.26 00.42

RMSE (m) 04.98 05.50 04.53 55.53

Table: Statistical Analysis for Elevations of DEMs and DGPS data for Study Area

Results and Discussion(i) DEM Generation

(i) Hydrodynamic Modeling

Figure. Comparison of elevation of DGPS points with elevation of Google earth, SRTM and ASTER DEM

Figure: 30m Generated CartoSat-1 DEMs for (a) DGPS, (b) Reduced Google Earth, (c) Google Earth, and available DEMs of (d) 90m SRTM & (e) 30m ASTER

Comparison of derived CartoSat-1 DEMs with available SRTM & ASTER DEM

(c)(b)

(d)

(a)

(e)

Statistical Parameters

DGPS survey elevation

DGPS Cartosat-1 DEM elevation

Reduced Google earth CartoSat-1 DEM elevation

Google earth CartoSat-1 DEM elevation

MIN (m) 03.62 02.89 01.86 04.69

MAX (m) 16.60 16.89 16.82 20.82

MEAN(m) 10.08 09.97 10.25 12.76

SD (m) 03.09 02.89 02.76 02.82

RANGE (m) 12.98 13.99 14.95 16.13

Table: Error Analysis of Generated CartoSat-1 DEMs Elevation and DGPS Survey data for Study Area

Statistical Parameters DGPS Cartosat-1 DEM elevation

Reduced Google earth

CartoSat-1DEM elevation

Google earth CartoSat-1 DEM elevation

MIN (m) 00.00 00.00 00.00

MAX (m) 08.97 08.22 12.57

MEAN (m) 01.58 02.25 04.75

SD (m) 02.02 02.12 02.71

RANGE (m) 08.97 08.21 12.57

Table: Analysis of Discrepancies (absolute values) between DGPS Survey and Generated CartoSat-1 DEMs Elevation Data for Study Area

Quantitative Analysis of CartoSat-1 DEMs for Floodplain

Statistical Parameters

Survey Cross section elevation

DGPS Cartosat-1 DEM elevation

Reduced Google earth CartoSat-1 DEM elevation

Google earth CartoSat-1 DEM elevation

Number of locations

1189 1189 1189 1189

MIN (m) -06.03 -01.91 -03.21 -03.26MAX (m) 20.40 21.23 22.27 26.27SD (m) 05.20 04.80 04.70 05.19MEAN (m) 08.03 08.25 08.80 12.57RANGE (m) 26.44 23.15 25.48 29.54

SEM (m) 00.15 00.13 00.13 00.15Table: Analysis of Discrepancies (absolute values) between Cross-section Survey Elevation and Elevation of Generated CartoSat-1 DEMs for Study Area

Table: Analysis of Cross-section Survey Elevation and Elevation of Generated CartoSat-1 DEMs for Study Area

Statistical Parameters e DGPSCartosat-1 DEM elevation

Reduced Google earth CartoSat-1 DEM elevation

Google earth DEM elevation

Number of locations 1189 1189 1189

MIN (m) 00.00 00.02 00.01MAX (m) 13.47 15.07 18.85SD (m) 02.46 02.68 03.64

MEAN (m) 02.99 03.50 05.28RANGE (m) 13.47 15.04 18.83SEM (m) 00.07 00.07 00.10

Quantitative Analysis of CartoSat-1 DEMs for River Bed

Sources of DEMs Floodplain River bed

RMSE MAE RMSE MAE

DGPSCartoSat-1 DEM 1.65 1.04 3.56 2.76

Reduced Google earth CartoSat-1 DEM 2.94 2.04 4.41 3.50

Google earth CartoSat-1 DEM 5.46 4.75 6.41 5.28

SRTM DEM 4.89 3.93 4.41 3.50

ASTER DEM 6.31 4.21 8.18 5.81

Comparative Analysis of DEMs generated from different sources

Table: Error Analysis Generated CartoSat-1 DEMs with SRTM and ASTER DEMs for Study Area.

1:1 Line

1:1 Line

1:1 Line 1:1 Line

1:1 Line

Figure: Scatter plots of floodplain elevation for different DEMs

Qualitative Analysis of DEMs generated from different DEM sources

1:1 Line1:1 Line

1:1 Line1:1 Line

1:1 Line

Qualitative Analysis of DEMs generated from different DEM sources

Figure: Scatter plots of river bed elevation for different DEMs

Figure :Cross-section Profile for Bhargavi River

Comparison of derived CS from different DEMs with Survey CS

Figure :Cross-section Profile for Kushabhadra River.

Comparison of derived CS from different DEMs with Survey CS

Simulation setup of MIKE-11

Figure :Generated data bases for Kushabhadra river system

H-point (blue) Cross section (C/S)

Q-point (Red ) System generated point at the mid of two Cross section (C/S)

Figure : Locations of H-point (Cross section) and Q-point (H-Q relation can be obtained)

Simulation setup of MIKE-11

Station Name Nash Sutcliffe Coefficient (NSC)

RMSE MAE R2

Nimapada 0.91 0.62 0.43 0.91

Table : Error function values for Nimapada gauging station during calibration for the year 2003 for MIKE 11.

Figure: Comparison of predicted and observed discharge at Nimapada during calibration for the year 2003 for MIKE 11.

Calibration of Kushabhadra River System

Year of Validation

Nash Sutcliffe Coefficient (NSE)

RMSE MAE R2

2004 0.89 0.58 0.44 0.89

2005 0.88 0.70 0.55 0.88

Table: Error function values for Nimapada gauging station during validation for the year 2004 and 2005 for MIKE 11

Figure: Comparison of predicted and observed discharge at Nimapada during validation for the year 2004 and 2005

Validation of Kushabhadra River System

Conclusions

Generated cartoSat-1 DEMs give better representation of elevation of terrain than available ASTER and SRTM DEMs.

Cartosat-1 DEM is derived using DGPS points show better result followed by reduced Google earth, Google earth, SRTM and ASTER DEMs.

Kushabhadra river system for MIKE 11 is well validated for Manning's roughness 0.0265.

Work to be Done

Calibration and validation of Kuakhai-Bhargavi river system for MIKE-11.

Comparison of water level extent of river for different sources of DEMs.

Quantification of effects of DEM on flood inundation modeling.

Thank you for your attention.

Citation Major findingsWerner (2001)

Estimating flood extent maps using a simple Inverse Distance Weighted (IDW) interpolation easily avoids the local depressions which are not directly connected to the main channel.

Merwade et al. (2005)

Locating the channel centerline along the thalweg , is a reference for assigning s ,n-coordinates to the bathymetric data. The resulting bathymetric data in the s ,n, z-coordinate system are used to create a square mesh or FishNet.

Merwade et al. (2006)

The variable-direction of the river channel bathymetry is accounted for by using a flow-oriented curvilinear coordinate system to establish a unidirectional flow channel.

Gorokhovich &Voustianiouk

(2006)

Absolute average vertical errors from CGIAR dataset is significantly better than a standard SRTM by considering the slope and aspect where the slope values greater than 10°.

Review of LiteratureReview of Literature

Citation Major findingsWilson et al.

(2007)Model accuracy is good at high water, while accuracy drops at low water due to incomplete drainage of the floodplain resulting from errors in topographic data and omission of floodplain hydrologic processes from this initial model.

Merwade et al. (2008a)

Creating surface representations of river systems is a challenging task because of issues associated with interpolating river bathy-metry and then integrating this bathymetry with surrounding topography.

Merwade et al. (2008b)

It is unknown how the uncertainties associated with topographic representation, flow prediction, hydraulic model, and inundation mapping techniques are transferred to the flood inundation map.

Cook and Merwade

(2009)

Providing an improved understanding of interplay among topography, geometric description and modelling approach in the final inundation mapping, showed that the flood inundation area reduces with improved horizontal resolution.

Cont……

Citation Major findingsGetirana et al.

(2009a)Proposed a new approach based on ‘burning’ concepts to obtain better defined watershed delineation in floodplains of large basins by using the spatial distribution of flooded areas from satellite images.

Getirana et al. (2009b)

To overcome D8 algorithm failure, a double burning method, known as floodplain burning (FB) method has been proposed. The proposed method introduces five coefficients requiring adjustment in order to obtain a relevant watershed delineation but minimizing DEM changes

Vaze et al. (2010)

Demonstrates that the loss of details by re sampling the higher resolution DEM to coarser resolution are much less compared to the details captured in the commonly available coarse resolution DEM derived from contour maps

Paz et al. (2010)

Hydro-dynamic models require river cross-sectional profiles that must comprise both main channel and floodplain in order to better represent the river hydraulics, the floodplain commonly being several times larger than the main channel when dealing with large rivers.

Cont……

Citation Major findings

Alsdorf et al. (2010)

Basically in flat river basins like the Amazon, surface waters are actively exchanged between river channels and floodplains

Yamazaki et al. (2011)

Floodplains have a key role as natural retarding pools which attenuate flood waves and suppress flood peaks in large basins

Yamazaki et al. (2012)

The flow connectivity is ensured by new Burning algorithm which is found to be essential for representing realistic water exchanges between river channels and floodplains in hydro-dynamics modeling.

Jung and Merwade

(2012)

Topography plays a significant role in hydraulic modeling used to derive water surface elevations corresponding to the design flow, and the geometry that defines the flow domain, including river cross sections and bathymetry mesh in a hydraulic model.

Cont……