Estimativa da retenção de água em solos para fins de irrigação

• Ano de defesa: 2007
• Autor(a) principal: Urach, Felipe Lavarda
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; BR; Engenharia Agrícola; UFSM; Programa de Pós-Graduação em Engenharia Agrícola
• Palavras-chave em Português: Pedotransferência; Pedofunções; Retenção de água; Capacidade de campo; Ponto de murcha permanente; Pedotransfer; Pedofunctions; Water retention; Field capacity; Permanent wilting point; CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
• Link de acesso: http://repositorio.ufsm.br/handle/1/7593

The purpose of the present work was to establish and to test pedotransfer functions for water retention the Rio Grande do Sul s soils. Water retention data were obtained from Solano Peraza s dissertation, Irriga System database and in the literature. The first part of this work was the collect soil water retention data and pedotransfer functions for Rio Grande do Sul soils, forming the literature data base, in a total of 24 papers and 624 database of the water retention. The samples obtained from of Solano Peraza were collected soil profiles, in a total of 86 data of water retention, and the Irriga Project provided a database with a total of 253 data of water retention. With these database, multiple regression were done to obtain the pedotransfer functions for each database, using the option stepwise , to determine water retention in a determined potential ( -1, -6, -10, -33, -100, -500 e 1500 kPa) for different soils. To test the efficiency of the equations produced, observed vs. estimated water retention, for each water potencial, were graphed on 1:1 type retention. In almost all cases, total sand presented a high association with the water retention, followed by clay and silt content. With the reduction on in water tension (increase of the original potential), the correlation increased notably. The pedotransfer equations are efficient only when they are used to estimate moisture for soil similar to those used to obtain the equations. Besides, the database feature affects the prediction capacity of the equations produced. When some soils are predominant in the database, the equations produced show the features of those soils and, when they are used to soil moisture, the error will be larger. The contents of sand and clay together with the soil bulk density best described water retention in the linear multiple regressions. Sand content had a negative relation with water retention, while clay presented a positive relation. The soil bulk density showed a negative relation with water retention the potential of 6 to 500 kPa and a positive relation with water retained at 1500 kPa. The best estimation of water retention occurred at a potential of 1500 kPa.