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Identification of potential areas susceptible to flood inundation in the Lower Guayas River Basin Santiago Lopez Graduate Student Department of Geography.

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Presentation on theme: "Identification of potential areas susceptible to flood inundation in the Lower Guayas River Basin Santiago Lopez Graduate Student Department of Geography."— Presentation transcript:

1 Identification of potential areas susceptible to flood inundation in the Lower Guayas River Basin Santiago Lopez Graduate Student Department of Geography

2 1.Introduction Evaluate the sensitivity of: DEM-based surface Landsat ETM image for characterizing flood inundation through statistical tests involving the comparison of flood areas extracted from geomorphology and soils maps.

3 Hypothesis There is no significant relationship between potential flood inundation areas obtained from geomorphology and soil maps and potential inundation zones determined with the aid of a DEM-based surface and a Landsat ETM satellite image.

4 2. Study Area Lower Guayas River Basin, Ecuador Ecuador Peru Colombia flythrough

5 3. Cartographic/conceptual model

6 4.Methods and Data a. Satellite image processing Tasseled cap transformation Wetness = TM TM TM TM4 – TM5 – TM7

7 The wetness index derived from the tasseled cap transformation

8 (1/d 1 n )V 1 +(1/d 2 n )V 2 +(1/d 4 n )V 4 +(1/d 5 n )V 5 +(1/d 6 n )V 6 +(1/d 7 n )V 7 +(1/d 8 n )V 8 (1/d 1 n )+(1/d 2 n )+(1/d 4 n )+(1/d 5 n )+(1/d 6 n )+(1/d 7 n )+(1/d 8 n ) A= b.Generation of the Digital Elevation Model Inverse Distance Weighting (IDW) i=1 Σ (1/di n ) i=1 n Σ (1/di n )V i n A= A = interpolated value di= distance to known value n= decay parameter

9 Elevation Distance DEM Mean DEM Convex areas c. Determination of convex areas based on the difference between the DEM and a mean DEM

10 4. Results a. Potential flood inundation areas based on wetness index

11 b. Potential flood inundation areas from DEM-based surface

12 c. Potential flood inundation areas derived from soil and geomorphologic units

13 Flood areas derived from the Landsat image vs. Map of Flooded Areas Chi-square 19.00, significant at a 0.05 level Reject null hypothesis Cramer’s Phi = 0.12 DEM areas vs. Map of Flooded Areas Chi-square 26.98, significant at a 0.05 level Reject null hypothesis Cramer’s Phi = 0.17 d. Statistical Analysis

14 5. Conclusions Integration of geomorphologic and soils data, simple DEM-based surfaces, and satellite images maybe a useful first approach to characterize flood inundation areas in regions where spatial data is scarce or non available. Important limitations for site-specific studies. For finer scale studies specific hydrologic data (e.g. profiles of flood elevation and in-situ flood measurements) could enable the analyses to be linked to real properties of the river flow regime.

15 6.Future research Compare results with a DEM generated with Arc Info's TOPOGRID model, which seems to generate surfaces more representative of the actual topography, specially for hydrologic modeling purposes. Derive a wetness index using the DEM and test its sensitivity in relation to the wetness index derived from the ETM scene. Wi = ln (A/tanB) Where Wi = wetness index; A = upslope contributing area; B = surface slope

16 Thank you! (?)


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