Fuzzy Hydrologic Model in Tropical Watershed - Advances in Data, Methods, Models and Their Applications in Geoscience - page 288

2

( PS

PS




.2)
0.8

Q  (3)

where Q is the direct runoff or excess precipitation, P is the precipitation, S is potential
maximum storage in the watershed after beginning of the runoff .
The CN parameter relates to S (mm) as:

25,400

S 

 254

(4)

CN

5. Model implementation
5.1 Landuse map
The land use map was obtained by image processing of Advanced Spaceborne Thermal
Emission and Reflection Radiometer (ASTER) data (Abrams, 2000). Firstly, the ASTER
image was compensated for atmospheric effects and converted into surface reflectance,
through the Atmospheric Correction Now (ACORN) software, which involves a
MODTRAN4-based method for radiative transfer calculation (Imspec, 2001). The Leaf
Pigment Index (LPI) (Almeida & Souza Filho, 2004) was then calculated using ASTER
reflectance data to represent the continuous surface associated to the vegetation coverage of
the study area (Fig. 2). The LPI was calculated by:

LPI = (ASTER 1) / (ASTER 2) (5)

where ASTER 1 is the band 1 (0.52-0.60 m - visible green) and ASTER 2 is the band 2 (0.63-
0.69 m - visible red). The LPI indicates the amount of chlorophyll in plant foliage - higher
index values highlight areas in the image where photosyntetically active vegetation is
denser. Other vegetation indices such as the Normalized Difference Vegetation Index
(NDVI) (Rouse et al., 1974) and the Moisture Stress Index (MSI) (Rock et al., 1986) were also
tested, but the LPI showed to best represent the vegetation cover of the study area when the
results were confronted with field observations. The map generated with LPI was converted
to ASCII format, compatible with PCRaster EML.

5.2 Soil map
Soil data of the Quilombo River watershed were extracted from the soil map of Ribeira do
Iguape Region at 1/100,000 scale (Sakai et al., 1983). Basically, the watershed is composed of
four soil types: latosol, podzolic, inceptisol and organic soils. The soil map, originally in
paper format, was converted to digital vector data. These vector data were transformed to
raster data at 15 m resolution. The raster map was further converted to ASCII format.
The runoff estimate was obtained through the SCSCN model based on the hydrologic soil
groups defined by the USA Soil Conservation Service, where the soil is classified into one of
four different categories, ranging from A to D.
An important characteristic of the tropical soils in the São Paulo State is the fact that the
clay-rich soils provide high infiltration rates (Lombardi-Neto et al., 1991). Another particular
aspect of the studied watershed is that the organic soils are found in the bottom of the
valleys and have high moisture content (Barreto-Neto, 2004). Based on these soil
characteristics, the soil map was reclassified in agreement with the hydrologic soil groups
(Table 2 and Fig. 3).