• Energy Research

Soils in arid and semi-arid environments are threatened by salinization. A cost-effective and efficient way to reclaim saline land is through leaching. This will be most effective in situations where direct human impact is the cause for salinity, e.g., in environments affected by industrial use or land rehabilitation following mining. Irrigation, which is the most common means of achieving salt leaching, is not feasible for the reclamation of mine sites’ salt-affected soils located in remote areas, and thus, land reclamation largely relies on natural climatic conditions. This study was conducted to assess the effect of different climatic conditions of semi-arid environments on spatio-temporal salt leaching from brine-affected soil, and investigate the efficacy of the reduction of soil bulk density as a reclamation technique for saline land experiencing water scarcity. Three regions (represented by the Australian cities of Roma, Mount Isa, and Quilpie) representing semi-arid environments of Australia were selected, and their climatic scenarios (23 years) were applied to a validated HYDRUS-1D model. A brine-affected soil typical to Queensland, Australia, was chosen for this study. The investigations established that a greater number of individual high rainfall events resulted in a greater reduction of salinity in Roma (96%) and Mount Isa (93.31%) compared with Quilpie (58.75%), in which the soil salinity approached a level (<2 dS m−1) that was suitable for sustaining plant growth. Soil salinity reduced to 8 dS m−1 under the climatic conditions of the Quilpie region. This study also demonstrated that the success of salt leaching from a brine-affected soil is a consequence of a sensitive response to the depth of individual rainfall events rather than rainfall distribution and the total amount of rainfall, and is controlled by the physical properties of the soil. Where climatic conditions cannot solely assist with salt leaching, reclamation may be successful by reducing soil bulk density.

Alum sludge is a byproduct of water treatment plants and its use as a soil stabilizer has gained increasing attention due to its economic and environmental benefits. Its application has been shown to improve the strength and stability of soil, making it suitable for various engineering applications. However, to go beyond just measuring the effects of alum sludge as a soil stabilizer, this paper explores the use of artificial intelligence (AI) methods to predict the California bearing ratio (CBR) of soils stabilized with alum sludge. Three AI methods, including two black box methods (artificial neural network and support vector machines) and one grey box method (genetic programming), were used to predict CBR based on a database with nine input parameters. The results showed that all three AI models were able to predict CBR with good accuracy, with coefficient of determination (R2) values ranging from 0.94 to 0.99 and mean absolute error (MAE) values ranging from 0.30 to 0.51. In a novel approach, the genetic programming method was used to produce an equation to estimate CBR, which included seven inputs and accurately predicted CBR. The analysis of sensitivity and importance of parameters showed that the number of hammer blows for compaction was the most important parameter, while the parameters for maximum dry density of soil and mixture were the least important. This study suggests that AI methods can effectively predict the performance of alum sludge as a soil stabilizer, and the proposed equation using genetic programming can be a useful tool for predicting CBR.

This article reports on a study of an agricultural region in southeast Queensland, Australia that is undergoing rapid change with development of an extensive coal seam gas industry and some large open cut coal mines. The region has become a locus of land use conflict between various industries: farming, grazing, mining and gas extraction. The effects of these multiple industries on each other, on environmental assets, infrastructure and economic and social systems entail many risks. Infrastructure shortfalls, a two-speed economy, widening social divisions, threatened livelihoods and stress in the face of rapid and far-reaching change associated with a new industry are evident in the words of those experiencing the impacts that provide the data reported in the paper. These problems are shown to be characterised by connectedness, complexity, uncertainty, disputed science, conflict, multiple stakeholders and an associated multiplicity of perspectives and values. The problem-solving and management strategies being adopted are unlikely to satisfactorily resolve the 'wicked' problems associated with this resources boom because they tackle aspects of the problem in a fragmented way, rely on inconclusive 'science', cannot readily incorporate hard to quantify aspects, values and subjective considerations, involve a restricted group of key decision-makers, and are dependent on formal rules and planning. The article proposes characteristics of alternative mechanisms involving adaptive risk management and multi-stakeholder participation. However the authors also caution that most of the barriers identified are not easily overcome.