Three Dimensional Conceptualisation of Hydrogeological Environment to Underpin Groundwater Management in Irrigation Area

Australian irrigated agriculture utilises about 70?% of all water used in the country, 21?% of which is derived from groundwater. Sustainability for irrigated agriculture also depends on keeping the watertables at a safe level below the rootzone to avoid salinisation and reduction in crop yields. There is a vital need to understand groundwater and aquifer systems and their roles in the sustainability of irrigated agriculture in order to manage groundwater properly. This study builds on the previous hydrogeological and groundwater investigations of the Coleambally Irrigation Area (CIA) in New South Wales of Australia. It presents a new approach which systematically characterises regional hydrogeological environment using a three-dimensional (3-D) conceptual framework developed in ArcGIS. The 3-D hydrological conceptualisation of the CIA has integrated disparate sources of data into a coherent knowledge base for a better visualisation of hydrogeological characteristics and a comprehensive analysis of groundwater flow and aquifers. As an application example, the model was used to develop cross-sectional models of the area and to estimate regional-scale net recharge. The results have provided a basis for the numerical modelling and added values to procedures which underpin irrigation system management investment decisions through improving the understanding of hydrogeology underlying the area and creating an action-oriented dialogue among stakeholders.     

Awareness as a foundation for developing effective spatial data infrastructures

The development of an effective spatial data infrastructure (SDI) often occurs in a fragmented organizational environment requiring a high level of inter-organizational collaboration. Different organizations from various jurisdictions need to work together closely when agreeing on how they will jointly register, store, use and share data and how they will make their data available to the wider society. However, this collaboration is generally regarded as very difficult. For example people often resist data sharing across organizational boundaries due to loss of control, power and independency. Organizational issues are thus considered one of the fundamental constraints to inter-organizational sharing of spatial data.     

What determines the efficiency of Australian mining companies?

We examine the firm‐specific determinants of technical efficiency in Australian mining companies using data envelopment analysis (DEA). To do so, we employ panel data sourced from individual mining companies listed on the Australian Securities Exchange (ASX) over the period 2010–2014. To ensure valid statistical inference in the presence of serial correlation between DEA efficiency scores, we apply Simar and Wilson's two‐stage bootstrap method. We find that ownership concentration, firm size, firm age, product portfolio, product diversification and growth status significantly contribute to efficiency gains. However, other firm‐specific factors, such as capacity utilisation, financial risk and overseas operations appear to have limited impact on the technical efficiency of mining firms.     

Multi-reservoir Operation Rules: Multi-swarm PSO-based Optimization Approach

Reservoir operation rules are intended to help an operator so that water releases and storage capacities are in the best interests of the system objectives. In multi-reservoir systems, a large number of feasible operation policies may exist. System engineering and optimization techniques can assist in identifying the most desirable of those feasible operation policies. This paper presents and tests a set of operation rules for a multi-reservoir system, employing a multi-swarm version of particle swarm optimization (MSPSO) in connection with the well-known HEC-ResPRM simulation model in a parameterization–simulation–optimization (parameterization SO) approach. To improve the performance of the standard particle swarm optimization algorithm, this paper incorporates a new strategic mechanism called multi-swarm into the algorithm. Parameters of the rule are estimated by employing a parameterization–simulation–optimization approach, in which a full-scale simulation model evaluates the objective function value for each trial set of parameter values proposed with an efficient version of the particle swarm optimization algorithm. The usefulness of the MSPSO in developing reservoir operation policies is examined by using the existing three-reservoir system of Mica, Libby, and Grand Coulee as part of the Columbia River Basin development. Results of the rule-based reservoir operation are compared with those of HEC-ResPRM. It is shown that the real-time operation of the three reservoir system with the proposed approach may significantly outperform the common implicit stochastic optimization approach.     

Dynamic land use and land cover changes and their effect on forest resources in a coastal village of Matemwe,Zanzibar, Tanzania

Recent land cover change estimates show overall decline of tropical forests at the regional and global scales caused by multiple social, cultural and economic factors. There is an overall concern on the prevailing land use practices, such as shifting cultivation and extraction of forest materials as agents of forests losses, but also new, emerging land uses are threatening tropical forests. Understanding of the long-term development and driving forces of forest changes are needed, especially at local levels where many decisions on forest policies and land uses are made. This paper addresses the importance of such information for improved estimates of forest dynamics by studying local level land cover and land use changes during the last 50–70 years in the Eastern African tropical island of Zanzibar, Tanzania. The paper discusses the role of traditional and new land uses mainly subsistence farming, tourism and government interference through tree planting, in the long-term development of the forests at the village level. The material for the study is gathered from the interpretation of archival maps and aerial photographs combined with contemporary digital aerial photographs. The analyses are based on the mapping, spatial sampling and spatio-temporal change trajectory analysis (LCTA) of forest land cover, forest land uses and settlement patterns with GIS and statistics. Six distinct forest land cover change trajectories were identified and these illustrate dynamic and heterogeneous nature of the forests. Closed forest cover has dominated throughout due to cyclical land use patterns, but over 70% of the land area has been continuously transforming between closed, semi-open and open land cover conditions. Land use turnover rates indicate that hardly any forest areas are left untouched from the forces, which remove and re-establish forest vegetation in the long run. Land cover and land use change trajectories are spatially fragmented in the studied landscape. Majority of forest loss-gain dynamics is caused by shifting cultivation, while forest losses are most dramatic along the coast, where traditional and new land uses meet and land uses pressures are highest. The study suggests that landscape change trajectory analyses, where contemporary and historical information on land uses and land cover changes are spatially linked, can provide valuable aspects into local level forest land use planning and management strategies. For the case study, the findings suggest the following key forest management strategies for consideration: (1) establishment of a protected forest/scrubland in participation with the local stakeholders, especially the farmers, (2) promotion of areas for permanent agricultural practices, while simultaneously introducing management controls in the traditional slash-and-burn farming areas, and (3) promoting new livelihood opportunities for the farmers, who have traditionally been dependent on forest resources, meanwhile introducing alternatives for fuel wood for cooking.     

Home-related injuries among under-five-year children and mothers' care regarding injury prevention in rural areas

This cross-sectional study was conducted in rural areas of Twiserkan (Toyserkan) County, in Iran, to assess factors associated with home-related injuries among under-five-year children and their mothers’ care regarding injury prevention. Mothers who had their under-five-year-old children injured within a 12-month period were identified from recorded information in Twiserkan Health Center. Then, data were gathered using pre-tested questionnaire and through interview with injured children's mothers. The questions were about characteristics of the children's injuries and their mothers’ care regarding injury prevention, using PRECEDE (Predisposing, Reinforcing, and Enabling Constructs in Educational/Environmental Diagnosis and Evaluation) model with focus on knowledge and attitude; enabling and reinforcing factors; and mothers' preventive behaviours. The study results showed that 197 out of 210 total identified mothers took part in the study. The reported injuries were 11.68%, 39.09%, and 49.24%, respectively, for severe, moderate, and mild cases. Fall was the most frequent injury with 35%. Among PRECEDE model constructs, there was a statistically significant correlation between mothers' knowledge and injury severity among children. Home-related injuries are an important health problem among study population and their prediction and prevention are necessary. Enhancement of mothers’ knowledge can be helpful to improve child injury prevention.     

Oil shocks and the dynamics of substitution adjustments of industrial fuels in the US

This paper investigates substitution among such alternate fuels as coal, natural gas, and electricity during the actual oil price increases of 1970s. These substitution adjustments are assumed to be dynamic and modelled by a partial adjustment structure. This dynamic structure is incorporated into a translog cost technology. Short- and long-run price elasticities are estimated by identifying inter- and intra-industry variations. The models are estimated with a sample of 88 pooled observations, including distillate and residual oils purchased by eleven 2-digit manufacturing groups (1974-81). Models are estimates are strictly negative. These own price elasticities range from (long-to short-run) –2.93 to –2.55 for distillate oil, –0.698 to – 1.53 for residual oil, –0.533 to 0.011 for coal, –0.235 to –0.213 for natural gas, to –0.888 to –0.845 for electricity. Estimastes of both short-run and long-run cross-price elasticities suggest that coal and electric energy are the prominent substitutes for fuel oils. While the relationship between the latter and natural gas remains largely complementary.     

Design-Operation of Multi-Hydropower Reservoirs: HBMO Approach

To illustrate and test the applicability and performance of the innovative honey-bee mating optimization (HBMO) algorithm in highly non-convex hydropower system design and operation, two problems are considered: single reservoir and multi-reservoir. Both hydropower problems are formulated to minimize the total present net cost of the system, while achieving the maximum possible ratio for generated power to installed capacity. The single hydropower reservoir problem is approached by the developed algorithm in 10 different runs. The first feasible solution was generated initially and later improved significantly and solutions converged to a near optimal solution very rapidly. In the application of the proposed algorithm to a five-reservoir hydropower system with 48 periods and a total of 230 decision variables, in early mating flights, the first feasible solution was identified and the results converged to a near optimal solution in later mating flights. In the case of the multi-reservoir problem, an efficient gradient-based nonlinear-programming solver (LINGO 8.0) failed to find a feasible solution and for the single hydropower reservoir design problem it performed much worse than the proposed algorithm.     

Dependence and Stability of the Demand for Money in a Small open Economy: The Case of Côte-d'Ivoire

Abstract: This paper investigates the effects of foreign variables on the demand for money in Côte-d'Ivoire during 1970. I-1986. IV. In the model specification, we consider that Côte-d'Ivoire is a member of the Franc zone. Within the zone, the CFA Franc is pegged to the French Franc, but outside the zone or with the generalized floating system, the CFA Franc espouses the form taken by the French Franc against other major currencies. The model satisfactorily explains behavioral relationships under these two regimes. Domestic determinants of the demand for real cash balances are the real GDP, the expected rate of inflation, the degree of credit restraint, and expectations of economic instability. International influences are captured by foreign interest and exchange rates. Stability and causality tests indicate that the money demand relation has been stable over time and is highly influenced by foreign interest rates. Résumé: Le présent document étudie les incidences des variables extérieures sur la demande de monnaie en Côte-d'Ivoire de 1970. I à 1986.IV. Dans la spécification du modéle, nous considérons que la COcte-d'Ivoire est membre de la Zone Franc, mais hors de la Zone ou avec le systéme flottant généralisé, le Franc CFA adopte les formes proses par le Franc Francais par rapport aux devise fortes. Le modéle explique de manié satisfaisante les rapprots aux devises fortes. Le modéle explique de manié satisfaisante les rapprots de comportement sous ces deux régimes. Les facteurs déterminants sur la demande de bilans de trésorerie réelle sont le PIB réel, le taus d'inflation prévisionnel, le degré de pénurie de crédit, les menaces d'instabilitééconomique. Les influences internationales sont représentées par les intéréts étrangers et les taux de change. Les tests de stabilité et der cause à effect indiquent que le rapport de la demande de monnaie a éaté stable au fil du temps et est fortement influencé par les taus d'intérét étrangers.     

Multiobjective Calibration of Reservoir Water Quality Modeling Using Multiobjective Particle Swarm Optimization (MOPSO)

Water resource management encounters large variety of multi objective problems that require powerful optimization tools in order to fully characterize the existing tradeoffs between various objectives that can be minimizing difference between forecasted physical, chemical, and biological behaviors of model and measured data. Calibration of complex water quality models for river and reservoir systems may include conflicting objectives addressed by various combinations of interacting calibration parameters. Calibration of the two dimensional CE-QUAL-W2 water quality and hydrodynamic model is an excellent example where the model must be calibrated for both hydrodynamic and water quality behavior. The aim of the present study is to show how multiobjective particle swarm optimization (MOPSO) can be implemented for automatic calibration of water quality and hydrodynamic parameters of a 2-dimensional, hydrodynamic, and water quality models (CEQUAL-W2) to predict physical, chemical, and biological behaviors of a water body, and then focus on a relevant case study. So MOPSO is utilized to generate Pareto optimal solutions for two conflicting calibration objectives. A combined measure of thermal and reservoir water level is considered as the first calibration objective. The second objective is formulated to forecast the best physical, chemical, and biological behavior of the model. Realizing the strong interactions between water quality and hydrodynamic issues of water bodies and their dependencies on the same set of calibration parameters, the proposed multiobjective approach may provide a wide version of all possible calibration solutions for better decision making to select best solution from pareto front.