Watershed analysis in Guatemala
Including collected and generated data for
Guatemala as well as some basic regional
statistics calculated for the 40 major watersheds.
Maps prepared by the
Spatial Information and Analysis Group, DECRG, World Bank
September 2001Data sources, too numerous to mention…..sorry!
Municipios
Colours represent departments, municipal boundaries shaded in gray.
40 Major Watersheds
Rio PazWatershed
LandSat ETM images
Rio PazWatershed
Elevation
Terrain Typology
Plains - Greens
Lowlands - Yellows
Hills - Red
Mountains - Grey
High Mountains - White
Land Cover
Forests - Green
Agriculture - Light Yellow
Water - Blue
Other - Pink
Urban - Red
Population Density
Poverty Rate (General)
Low - Green
Medium - Yellow
High - Orange
Critical - Red
Poverty (General)
Population per municipio classified as being poor
Poverty Rate (Extreme)
Low - Green
Medium - Yellow
High - Orange
Critical - Red
Poverty (Extreme)
Population per municipio classified as being extremely poor
Forest / Agri. on Slopes
Forests - Green
Agriculture - Orange
Defining upper watershed areas
5 example methods
1) Use an elevation cut off across the region
2) Split each watershed into 3 based on elevation
3) Derive 3 terrain types (Meybeck) across the region
4) Use a flow length cut off across the region
5) Split each watershed into 3 based on flow length
1) Elevation - Region
Low - Green
Mid - Yellow
High - Grey
2) Elevation - By shed
Low - Green
Mid - Yellow
High - Grey
3) Terrain - Region
Low - Green
Mid - Yellow
High - Grey
4) Flowlength - Region
Low - Green
Mid - Yellow
High - Grey
5) Flowlength - By shed
Low - Green
Mid - Yellow
High - Grey
Comparing the 5 examplesHow much land is in each region?
% area in each region
0%
10%
20%
30%
40%
50%
60%
70%
Low Mid High
Elev-Region
Elev-Shed
Terrain-Region
Flow-Region
Flow-Shed
Comparing the 5 examplesHow many people are in each region?
Population in each region
-
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
9,000,000
Low Mid High
Elev-Region
Elev-Shed
Terrain-Region
Flow-Region
Flow-Shed
Comparing the 5 examplesHow many poor are in each region?
Poor (General) in each region
-
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
4,500,000
Low Mid High
Elev-Region
Elev-Shed
Terrain-Region
Flow-Region
Flow-Shed
Comparing the 5 examplesHow much forest is in each region?
km2 of forest per region
-
5,000
10,000
15,000
20,000
25,000
30,000
Low Mid High
Elev-Region
Elev-Shed
Terrain-Region
Flow-Region
Flow-Shed
Defining upper watershed areas
There is a lot of variation across the 5 methods
methods 2 and 5 (that split each watershed into 3) consistently give high values in the high region,
methods 1 and 4 consistently give low values in the high regions
method 3 consistently gives values that lie in between
Taking method 3 as an example….
Class Area (km2) Agriculture (km2) Forest (km2) Low 62,175 (57%) 30,668 (58%) 27,438 (57%)Mid 16,958 (16%) 9,416 (18%) 5,830 (12%)High 29,297 (27%) 12,698 (24%) 15,128 (31%)Total 108,429 52,781 48,395
Defining High / Mid / Low landsUsing Method 3: Terrain Typologies (Meybeck et al. 2001)
Class Population (2000) Poverty (General) Poverty (Extreme)Low 2,498,093 (22%) 1,552,135 (25%) 542,990 (21%) Mid 3,197,987 (28%) 1,187,251 (19%) 430,058 (17%) High 5,694,926 (50%) 3,494,186 (56%) 1,621,909 (63%)Tot 11,391,006 6,233,572 2,594,956
Population estimated for year 2000 per municipality, (MAGA / BID)
Poverty rates per municipality from official Guatemala poverty map (SEGEPLAN / World Bank)
Selecting watersheds to analyse
We could remove a certain number of watersheds by imposing criteria such as
We are only interested in watersheds that have > 20% of there area classified as ‘high’. Taking method 3 as an example, this would remove all low lying watersheds
Selected Watersheds
Selected watersheds shaded in yellow
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