A review of the contamination of soil with lead II. Spatial distribution and risk assessment of soil lead.

Contamination of soil with lead has occurred on a global scale. Exposure to lead may cause adverse effects to human health and the environment. It is therefore desirable to obtain a quantitative estimate of the potential risk of lead contamination. Numerous studies have been conducted collecting lead concentration data from both natural and contaminated soil on a range of scales. Very few of these studies have made serious attempts to spatially describe the data. In order to identify contaminated land and to enable development of appropriate environmental guidelines, it is essential to have an understanding of the universal range of lead concentrations. Such data also assists in assessing any potential risk to the environment or human health. This paper reviews the multitude of data collected on soil Pb concentrations. Lead surveys are discussed on the basis of land use, with Australian data presented separately. Data from lead surveys of agricultural, urban and industrial areas, as well as nationwide surveys are summarised. A small but increasing number of studies have employed spatial prediction techniques such as kriging to map the distribution of lead concentrations in soil. These studies are also summarised and a brief description of the basis for their use presented. Finally, environmental and health risk assessment is discussed and some methodologies in use around the world reviewed.

Variability and uncertainty in spatial, temporal and spatiotemporal crop-yield and related data.

Application of the theories of precision agriculture to the practicalities of broad-acre farming relies on successful handling of the ramifications of uncertainty in information, i.e. information pertaining to the spatial and temporal variation of those factors which determine yield components and/or environmental losses. This paper discusses the uncertainty of yield and related variables as measured by their spatial and temporal variance. The magnitude of these two components gives a suggestion as to the appropriate scale of management. Simultaneous reporting on spatial and temporal variation is rare and the theory of these types of process is still in its infancy. Some brief theory is presented, followed by several examples from the Rothamsted classic experiments, yield-monitoring experiments in Australia, a long-term barley trial in Denmark, and a soil moisture monitoring network. It is clear that annual temporal variation is much larger than the spatial variation within single fields. This leads to the conclusion that if precision agriculture is to have a sound scientific basis and ultimately a practical outcome then the null hypothesis that still remains to be seriously researched is: 'given the large temporal variation in yields relative to the scale of a single field, then the optimal risk aversion strategy is uniform management.'