Data/hora: 02/06/2024 13:28:52

Provedor de dados: | 90
País: | Brazil
Título: | Spatial Interpolation of Rainfall Erosivity Using Artificial Neural Networks for Southern Brazil Conditions
Autores: | Moreira,Michel Castro; Oliveira,Thiago Emanuel Cunha de; Cecílio,Roberto Avelino; Pinto,Francisco de Assis de Carvalho; Pruski,Fernando Falco.
Data: | 2016-01-01
Ano: | 2016
Palavras-chave: | Erosive potential of rainfall; Soil conservation; Universal soil loss equation.
Resumo: | ABSTRACT Water erosion is the process of disaggregation and transport of sediments, and rainfall erosivity is a numerical value that expresses the erosive capacity of rain. The scarcity of information on rainfall erosivity makes it difficult or impossible to use to estimate losses occasioned by the erosive process. The objective of this study was to develop Artificial Neural Networks (ANNs) for spatial interpolation of the monthly and annual values of rainfall erosivity at any location in the state of Rio Grande do Sul, and a software that enables the use of these networks in a simple and fast manner. This experiment used 103 rainfall stations in Rio Grande do Sul and their surrounding area to generate synthetic rainfall series on the software ClimaBR 2.0. Rainfall erosivity was determined by summing the values of the EI30 and KE &gt;25 indexes, considering two methodologies for obtaining the kinetic energy of rainfall. With these values of rainfall erosivity and latitude, longitude, and altitude of the stations, the ANNs were trained and tested for spatializations of rainfall erosivity. To facilitate the use of the ANNs, a computer program was generated, called netErosividade RS, which makes feasible the use of ANNs to estimate the values of rainfall erosivity for any location in the state of Rio Grande do Sul.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832016000100537
Editor: | Sociedade Brasileira de Ciência do Solo
Relação: | 10.1590/18069657rbcs20150132
Formato: | text/html
Fonte: | Revista Brasileira de Ciência do Solo  v.40 2016
Fonte: | info:eu-repo/semantics/openAccess