Hamish P. Cresswell

The Application of a Simple Spatial Multi-Criteria Analysis Shell to Natural Resource Management Decision Making

Natural resource management decision making generally requires the analysis of a variety of environmental, social and economic information, incorporating value judgement and policy and management goals. Justifiable decisions depend on the logical and transparent combination and analysis of information. This chapter describes the application of spatial multi-criteria analysis to natural resource assessment and priority setting at regional and national scales using a newly developed spatial multi-criteria analysis tool — the Multi-Criteria Analysis Shell for Spatial Decision Support (MCAS-S). MCAS-S is designed for use in participatory processes and workshop situations where a clear understanding of different approaches to spatial data management and information arrangement is necessary. The MCAS-S work environment provides for multiple map display, combination and manipulation, live update of changes, and development of spider/radar plots important in ecosystem service assessments. These and other capabilities promote clear visualisation of the relationships among the decision, the science, other constraints and the spatial data. The regional scale example illustrates the analysis of biodiversity and salinity mitigation trade-offs in revegetation in a participatory process. The national scale application illustrates reporting to policy clients on the tensions between resources use and conservation in Australian rangelands — essentially an expert analysis.

Deep drainage and land use systems. Model verification and systems comparison

Deep drainage or drainage below the bottom of the profile usually occurs when rain infiltrates moist soil with insufficient capacity to store the additional water. This drainage is believed to be contributing to watertable rise and salinity in some parts of the Liverpool Plains catchment in northern New South Wales. The effect of land use on deep drainage was investigated by comparing the traditional long fallow system with more intense ‘opportunity cropping’. Long fallowing (2 crops in 3 years) is used to store rainfall in the soil profile but risks substantial deep drainage. Opportunity cropping seeks to lessen this risk by sowing whenever there is sufficient soil moisture. Elements of the water balance and productivity were measured under various farming systems in a field experiment for 4 years in the southern part of the catchment. The experimental results were used to verify APSIM (Agricultural Production Systems Simulator) by comparing them with predictions of production, water storage, and runoff. The verification procedure also involved local farmers and agronomists who assessed the credibility of the predictions and suggested modifications. APSIM provided a realistic simulation of common farming systems in the region and could capture the main hydrological and biological processes. APSIM was then used for long-term (41 years) simulations to predict deep drainage under different systems and extrapolate experimental results. The results showed large differences between agricultural systems mostly because differences in evapotranspiration contributed to differences in profile moisture when it rained. The model predicted that traditional long fallow farming systems (2 crops in 3 years) are quite ‘leaky’, with average annual deep drainage of 34 mm. However, by planting crops in response to the depth of moist soil (opportunity or response cropping), APSIM predicted a much smaller annual drainage rate of 6 mm. Opportunity cropping resulted in overall greater water use and increased production compared with long fallowing. Furthermore, modelling indicated that average annual deep drainage under continuous sorghum (3 mm) is much less than under either long fallow cropping or continuous wheat (39 mm), demonstrating the importance of including summer cropping, as well as increasing cropping frequency, to reducing deep drainage.

Using a physically based model to conduct a sensitivity analysis of subsurface lateral flow in south-east Australia

Abstract Break of slope tree plantations are intended to intercept surface and subsurface lateral flow (SLF) on hillslopes and help alleviate the water imbalance in the agricultural landscapes of south-east Australia. More information on the occurrence of SLF in this region is required to assist the efficient identification of potential plantation sites. In this article, HILLS, a two-dimensional physically based model, is used to examine the sensitivity of SLF to rainfall, soil, and topographic attributes. The most influential soil property was the depth of the impeding layer. Gradient within 33 m above where SLF is determined was the topographic criteria that most effected SLF, regardless of the overall topographic shape. It was clear that as the amount of annual rainfall increased, higher hillslope gradients were required to move the excess water as SLF. Cumulative errors in the model water balance created uncertainty about the accuracy of the results, however, the general trends seem reliable. SLF did not account for a significant proportion of rainfall on the hypothetical hillslope considered. Field evidence suggests that more SLF occurs in the study region than is suggested from these results. Soil, topographic and rainfall properties alone may not be adequate to explain the occurrence of this type of flow, and the presence of a watertable may also be critical.

Application of Multifractal and Joint Multifractal Analysis in Examining Soil Spatial Variation: A Review

© 2012 Biswas et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Application of Multifractal and Joint Multifractal Analysis in Examining Soil Spatial Variation: A Review