7 research outputs found

    Towards a European civil code. - 2nd rev. and expanded ed

    No full text

    Grain size, composition, porosity and permeability contrasts within cross-bedded sandstones in Tertiary fluvial deposits, central Spain

    Get PDF
    Permeability measured with a portable probe pcrmcflmeter on outcrops of cross·bcdded sandstones ranges betwecn 0·9 and 19 O. The highest pcrmeability (2-19 0 with an avcrage of8·5 D) occurs in thc coarsest grained foresct laminae (CFL). intermediate values (2-120 with an average of 5·3 D) occur in fincr grained foreset laminac (FFL) and thc lowest values (0·9-1 0 0 with un avcrage of 4·8 D) occur in boltomsct laycrs (BL). In the cross·bcds the uverage grain sizc rangcs from medium graincd sand in the CFL to finc grained s,lnd in thc FFL and BL. In all three subf'lcies. the average size of the primary pores is approximately It/> unit smaller than the averagc grain size. The abundance of unstablc carbonatc clasts correlatcs with incrcasing avcrage grain size, micritic clasts being most abundant in the CFL. Converscly. quartz content incrcascs with decreasing grain size and is highest in the FFL and BL. Oiagenetic destruction of primary porosity by compact ion and cementation. as well �IS generation of sccondary porosity through dissolution, were controlled by the original mineralogical composition of the sand. Contrasts in grain size detcrmine the primary pore size contrasts and differences in composition bctwecn CFL. FFL and BL. Permeability contrasts reflect variations in averagc primary pore size rather than differenccs in total porosity. Probe permeability contrasts between eFL. FFL and BL depend on contrasts in llverage pore size and contrasts in mineralogical composition between the subfacies

    Soybean yield estimation by an agrometeorological model in a GIS Produtividade de soja estimada por modelo agrometeorológico num SIG

    Get PDF
    Agrometeorological models interfaced with the Geographic Information System - GIS are an alternative to simulate and quantify the effect of weather spatial and temporal variability on crop yield. The objective of this work was to adapt and interface an agrometeorological model with a GIS to estimate soybean [Glycine max (L.) Merr.] yield. Yield estimates were generated for 144 municipalities in the State of Paraná, Brazil, responsible for 90% of the soybean production in the State, from 1996/1997 to 2000/2001. The model uses agronomical parameters and meteorological data to calculate maximum yield which will be penalized under drought stress. Comparative analyses between the yield estimated by the model and that reported by the Paraná State Department of Agriculture (SEAB) were performed using the "t" test for paired observations. For the 1996/1997 year the model overestimated yield by 10.8%, which may be attributed to the occurrence of fungal diseases not considered by the model. For 1997/1998, 1998/1999 and 1999/2000 no differences (P > 0.05) were found between the yield estimated by the model and SEAB's data. For 2000/2001 the model underestimated yield by 10.5% and the cause for this difference needs further investigation. The model interfaced with a GIS is an useful tool to monitor soybean crop during growing season to estimate crop yield.<br>Os modelos agrometeorológicos integrados em Sistemas de Informação Geográfica - SIG são uma alternativa para simular e quantificar o efeito da variabilidade espacial e temporal do clima sobre a produtividade agrícola. O objetivo deste trabalho foi adaptar e integrar um modelo agrometeorológico num SIG para estimar a produtividade da soja [Glycine max (L.) Merr.]. Foram geradas estimativas de produtividade para 144 municípios do Estado do Paraná, responsáveis por 90% da produção de soja no Estado, em cinco anos-safra no período de 1996/1997 a 2000/2001. O modelo utiliza parâmetros agronômicos e dados meteorológicos para o cálculo da produtividade máxima, a qual é penalizada quando ocorre estresse hídrico. A análise da comparação entre as estimativas municipais obtidas pelo modelo e aquelas divulgadas pela Secretaria de Estado da Agricultura e do Abastecimento (SEAB) do Paraná foi feita através do teste "t" para pares de observação. No ano safra 1996/1997 o modelo superestimou a produtividade em 10,8% em relação à SEAB, o que pode ser atribuído à ocorrência de oídio, cujo efeito não é considerado no modelo. Nos anos safras de 1997/1998, 1998/1999 e 1999/2000 não foram identificadas diferenças (P > 0,05) entre as estimativas do modelo e da SEAB. Em 2000/2001 a produtividade foi subestimada pelo modelo em 10,5%, sendo que as causas desta diferença precisam ser melhor investigadas. O modelo integrado no SIG mostrou ser uma ferramenta viável para acompanhar a cultura da soja ao longo da estação de crescimento, e estimar a produtividade em municípios do Estado do Paraná
    corecore