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| Alvarenga,Lívia Alves; Mello,Carlos Rogério de; Colombo,Alberto; Cuartas,Luz Adriana. |
| ABSTRACT The scarcity of field data to develop soil maps through a pedological survey is one of the main limitations to using distributed hydrological models, especially in small and medium-sized watersheds. The aim of this study was to compare a distributed hydrological model prediction to a soil map based on a pedological survey and a moisture zone map obtained using the Height Above the Nearest Drainage - HAND model. The Distributed Hydrology Soil Vegetation Model - DHSVM, which is a physically-based and distributed hydrological model, was applied to a mountainous watershed, located in the region of the Mantiqueira Range in the south of Minas Gerais in southeastern Brazil, and was compared to both maps mentioned above, taking the soil map developed by... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Pedological survey; HAND; Calibration and validation; DHSVM. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832017000100311 |
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| Arruda,Gustavo Pais de; Demattê,José A. M.; Chagas,César da Silva; Fiorio,Peterson Ricardo; Souza,Arnaldo Barros e; Fongaro,Caio Troula. |
| ABSTRACT Digital soil mapping is an alternative for the recognition of soil classes in areas where pedological surveys are not available. The main aim of this study was to obtain a digital soil map using artificial neural networks (ANN) and environmental variables that express soil-landscape relationships. This study was carried out in an area of 11,072 ha located in the Barra Bonita municipality, state of São Paulo, Brazil. A soil survey was obtained from a reference area of approximately 500 ha located in the center of the area studied. With the mapping units identified together with the environmental variables elevation, slope, slope plan, slope profile, convergence index, geology and geomorphic surfaces, a supervised classification by ANN was... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Map extrapolation; Pedological survey; Landscape attributes; Pedological classes; Data mining. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000300266 |
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