A total of 40% of the world’s energy produced is utilized to maintain thermal comfort for the occupants of the building. Governments are taking measures collectively to regulate energy efficient buildings to reduce carbon emissions globally. Windows account for more than half of total energy losses in the buildings. The employment of energy efficient glazing in the construction industry is not common in Australia. This paper investigates several types of commercially available windows and their effectiveness in the hot and humid climate of Darwin. Although extensive literature is available for cold regions, these windows have not been studied in hot and humid climates such as the climate in Darwin. Building cooling loads of an academic building were calculated using Autodesk Revit Architecture and Carrier HAP. Double glazed variants offered approximately a 5% reduction in cooling loads and had a payback period of nearly 7 to 9 years, depending on the type of gas used to fill the pane cavity. The results indicate that triple glazed, or aerogel-based windows will provide about 11–12 % of energy saving in cooling loads. These can be a viable alternative and have a payback period of 11 years, while their average service life expectancy is 30 years. It was found that the feasibility of efficient glazing depends on market price, building usage, and energy efficiency of an overall building envelope.

Nowadays, wind energy is receiving considerable attention due to its availability, low cost, and environment-friendly operation. Wind turbines are rarely placed individually but rather in the form of a wind farm with a group of several wind turbines. The purpose of this research is to perform studies on wind turbine farms in order to find the best distribution for wind turbines that maximizes the produced power, hence minimizing the wind farm area. Wind Farm Area Optimization (WFAO) is performed for optimal placement of wind turbines using elitist teaching–learning-based optimization (ETLBO) techniques. Three different scenarios of wind (first is fixed wind direction and constant speed, second is variable wind direction and constant speed, and third is variable wind direction and variable speed) are considered to find the optimal number of turbines and turbine positioning in a minimized squared land area that maximizes the power production while minimizing the total cost. Other research carried out in the past was to find the optimal placement of the wind turbines in a fixed squared land area of $2 \mathrm{km}\times 2 \mathrm{km}$. In the present study, WFAO–ETLBO algorithm has been implemented to get the optimal land area for the placement of the same number of turbines used in the past research. For Case 1, there is a significant reduction in land area by approximately 30.75%, 45.25%, and 51.75% for each wind scenario, respectively. For Case 2, the reductions in land area for three different wind scenarios are respectively 30.75%, 7.2%, and 7.2%. For Case 3, there is a reduction of 7.2% in land area for each wind scenario. It has been observed that the results obtained by the WFAO–ETLBO algorithm with a significant reduction in the land area along with optimal placement of wind turbines are better than the results obtained from the wind turbines placement in the fixed land area of $2 \mathrm{km}\times 2 \mathrm{km}$.

Despite spending ample resources and procedural development in flood management, flood losses are still increasing worldwide. The losses caused by floods and costs incurred on management are two components of expected annual damages (EAD) due to floods. This study introduces a generalized approach for risk-based design where a range of probable floods are considered before and after a flood mitigation measure is implemented. The proposed approach is customized from the ISO Guide 31000 along with additional advantages of flood risk visualization. A Geographic Information System (GIS)-based design of a flood-protection dike is performed to exhibit the risk redistribution. The Chenab River is selected for the existing dike system. Detailed hazard behaviour and societal vulnerability are modelled and visualized for a range of all probable floods before and after the implementation of flood-protection dikes. EAD maps demonstrate the redistribution of induced and residual risks. It can be concluded that GIS-based EAD maps not only facilitate cost-effective solutions but also provide an accurate estimate of residual risks after the mitigation measures are applied. EAD maps also indicate the high-risk areas to facilitate designing secondary measures.

Due to population growth, climatic change, and growing water usage, water scarcity is expected to be a more prevalent issue at the global level. The situation in Australia is even more serious because it is the driest continent and is characterized by larger water footprints in the domestic, agriculture and industrial sectors. Because the largest consumption of freshwater resources is in the agricultural sector (59%), this research undertakes a detailed investigation of the water footprints of agricultural practices in Australia. The analysis of the four highest water footprint crops in Australia revealed that the suitability of various crops is connected to the region and the irrigation efficiencies. A desirable crop in one region may be unsuitable in another. The investigation is further extended to analyze the overall virtual water trade of Australia. Australia’s annual virtual water trade balance is adversely biased towards exporting a substantial quantity of water, amounting to 35 km³, per trade data of 2014. It is evident that there is significant potential to reduce water consumption and footprints, and increase the water usage efficiencies, in all sectors. Based on the investigations conducted, it is recommended that the water footprints at each state level be considered at the strategic level. Further detailed analyses are required to reduce the export of a substantial quantity of virtual water considering local demands, export requirements, and production capabilities of regions.

Agricultural damage due to floods in the Indus basin’s fertile land has been the most damaging natural disaster in Pakistan so far. Earthen dikes are protecting the vast areas of the floodplain from regular flooding. However, the floodplain is attractive to farmers due to its fertility and experiences regular crop production within and out of the dike area. This paper evaluates the flood risk in a floodplain of the Chenab river in Pakistan and recommends land-use changes to reduce the flood risk for crops and associated settlements within the study area. The objective of the land-use change is not just to reduce flood losses but also to increase the overall benefits of the floodplain in terms of its Economic Rent (ER). This preliminary study analyses the economic impacts of the risk-based land-use improvements on existing floodplain land uses. Expected Annual Damage (EAD) maps were developed using hydrodynamic models and GIS data. The developed model identified the areas where maize can be economically more productive compared to rice under flood conditions. Promising results were obtained for the settlement relocations. It was also observed that the infra-structure, running parallel to the river, plays a significant role in curtailing the extent of floods. The results show that a combination of structural and non-structural measures proves more effective. The study also recommends the inclusion of social and environmental damages as well as other types of non-structural measures to develop the most effective flood management strategy.

In this paper, the meta-heuristic multi-objective elitist teaching–learning based optimization technique is implemented for wind farm layout discrete optimization problem. The optimization of wind farm layout addresses the optimum siting among the wind turbines within the wind farm to accomplish economical, profitable, and technical features. The presented methodology is implemented with multi-objective optimization problem through different targets such as minimizing cost, power output maximization, and the saving of the number of turbines. These targets are investigated with some case studies of multi-objective optimization problems in three scenarios of wind (Scenario-I: fixed wind direction and constant speed, Scenario-II: variable wind direction and constant speed, and Scenario-III: variable wind direction and variable speed) for the optimal micro-siting of wind turbines in a given land area that maximizes the power production while minimizing the total cost. To check the effectiveness of the algorithm, firstly, the results obtained for the three different scenarios have been compared with past studies available in the literature. Secondly, the numbers of turbines have also been optimized by using teaching–learning based optimization. It has been observed that the proposed algorithm shows the optimal layouts along with the optimal number of turbines with minimum fitness evaluation. Finally, the concept of elitism has been introduced in the teaching–learning based optimization algorithm. It is proposed that if elitist-teaching–learning based optimization with elite size of 15% is used, computational expense can be significantly reduced. It can be concluded that that the results obtained by the proposed algorithm are more accurate and advantageous than others.