Methods for evaluation of L and S factor for the universal soil loss equation (USCLE) in a watershed, involving geoprocessing and database. / Avaliação de métodos para obtenção dos fatores "L" e "S" da EUPS numa microbacia, via geoprocessamento e banco de dados.

AUTOR(ES)
DATA DE PUBLICAÇÃO

1997

RESUMO

This work deals with remote sensing, GIS, and database. The test site is the Ribeirão das Araras watershed, located in Araras, SP, Brazil. The Universal Soil Loss Equation (USLE) was modeled, with emphasis on the topographic factor, which is divided in slope lenght (L ) and slope (S ). Both were calculated by two different methos: L1 or method of the preferential direction by the superficial water flux (Kuntschik, 1996); L2 or ?isocômplere? method (Fernândez, 1996); S1 or abacus method (De Biase, 1992); S2 or grod method (Pereira Neto e Valério Filho, 1993). The USLE C factor was calculated by two different methods: a) ancillary data from field work; b) digital image processing. It was performed a sensitivity analysis of the USLE for L and S factors. Also, it was performed a comparison between the two methods fo C calculus. Another step was to make the land suitability map using GIS coupled to a tabular database. The estimate of erosion calculated by using USLE and the soil loss tolerance allowed the generation of the criticaly índex. Afterwards, this index was compared to the use adequacy map derived from the comparison between the land suitability map and the actual land use map. As a result it was found that the calculus of the C factor using digital image processing was not satisfactory. For the S factor, there was no statiscical difference between the methods used in its modeling. For the L factor, there was a statistical difference between the methods used; and the ?isocomplere? method seemed to give a good representation of the reality because it presented the lowest values for L. The GIS coupled to a database was a tool very useful to generate the land suitability maps. However it was found some difficulties with data sources, mainly with the low precision of the soil map. The comparison between the land suitability map and the criticality index was coherent.

ASSUNTO(S)

geoprocessing sensoriamento remoto. key words: universal soil lost equation (usle) equação universal de perdas de solo (eups) geoprocessamento data base remote sensing banco de dados

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