18 resultados para Concentration of Land
Resumo:
Electrical resistivity of soils and sediments is strongly influenced by the presence of interstitial water. Taking advantage of this dependency, electrical-resistivity imaging (ERI) can be effectively utilized to estimate subsurface soil-moisture distributions. The ability to obtain spatially extensive data combined with time-lapse measurements provides further opportunities to understand links between land use and climate processes. In natural settings, spatial and temporal changes in temperature and porewater salinity influence the relationship between soil moisture and electrical resistivity. Apart from environmental factors, technical, theoretical, and methodological ambiguities may also interfere with accurate estimation of soil moisture from ERI data. We have examined several of these complicating factors using data from a two-year study at a forest-grassland ecotone, a boundary between neighboring but different plant communities.At this site, temperature variability accounts for approximately 20-45 of resistivity changes from cold winter to warm summer months. Temporal changes in groundwater conductivity (mean=650 S/cm =57.7) and a roughly 100-S/cm spatial difference between the forest and grassland had only a minor influence on the moisture estimates. Significant seasonal fluctuations in temperature and precipitation had negligible influence on the basic measurement errors in data sets. Extracting accurate temporal changes from ERI can be hindered by nonuniqueness of the inversion process and uncertainties related to time-lapse inversion schemes. The accuracy of soil moisture obtained from ERI depends on all of these factors, in addition to empirical parameters that define the petrophysical soil-moisture/resistivity relationship. Many of the complicating factors and modifying variables to accurately quantify soil moisture changes with ERI can be accounted for using field and theoretical principles.
Resumo:
This project examined the potential for historical mapping of land resources to be upgraded to meet current requirements for natural resource management. The methods of spatial disaggregation used to improve the scale of mapping were novel and provide a method to rapidly improve existing information. The thesis investigated the potential to use digital soil mapping techniques and the multi-scale identification of areas within historical land systems mapping to provide enhanced information to support modern natural resource management needs. This was undertaken in the Burnett Catchment of South-East Queensland.
Resumo:
This comprehensive study aimed to determine the sources and driving factors of organic carbon (OC) and elemental carbon (EC) concentrations in ambient PM2.5 in urban schools. Sampling was conducted outdoors at 25 schools in the Brisbane Metropolitan Area, Australia. Concentrations of primary and secondary OC were quantified using the EC tracer method, with secondary OC accounting for an average of 60%. Principal component analysis distinguished the contributing sources above the background and identified groups of schools with differing levels of primary and secondary carbonaceous aerosols. Overall, the results showed that vehicle emissions, local weather conditions and secondary organic aerosols (SOA) were the key factors influencing concentrations of carbonaceous component of PM2.5 at these schools. These results provide insights into children’s exposure to vehicle emissions and SOA at such urban schools.