A genetic algorithm for optimizing off-farm irrigation scheduling

This paper examines the use of genetic algorithm (GA) optimization to identify water delivery schedules for an open-channel irrigation system. Significant objectives and important constraints are identified for this system, and suitable representations of these within the GA framework are developed. Objectives include maximizing the number of orders that are scheduled to be delivered at the requested time and minimizing variations in the channel flow rate. If, however, an order is to be shifted, the irrigator preference for this to be by ±24 h rather than ±12 h is accounted for. Constraints include avoiding exceedance of channel capacity. The GA approach is demonstrated for an idealized system of five irrigators on a channel spur. In this case study, the GA technique efficiently identified the optimal schedule that was independently verified using full enumeration of the entire search space of possible order schedules. Results have shown great promise in the ability of GA techniques to identify good irrigation order schedules.J. B. Nixon, G. C. Dandy and A. R. Simpso

Attitudes towards asylum seekers: Evaluating a mature-aged community education programme

The arrival of asylum seekers and refugees across a nation’s border is often the subject of contested debate in many Western nations. Australian research finds unacceptable levels of community prejudice against asylum seekers (e.g., Klocker, 2004; Suhnan et al., in press). Compared to other Western nations, Australia receives relatively few asylum seekers. For example, the UNHCR (2011) finds that of the top 15 receiving Western countries, Australia is ranked 13th. Despite Australia’s comparatively small number of asylum applications, those who arrive unauthorised (i.e., without a valid visa) are subject to mandatory detention whereby they are held in an immigration detention centre until they receive a visa and security clearance; sometimes this can take years (Briskman et al., 2008). There is considerable evidence showing that mandatory detention has an extremely detrimental effect on asylum seekers’ mental health (e.g., Davidson et al., 2008; The Australian Psychological Society, 2011)

ANALISIS DAYA DUKUNG LAHAN DALAM PENGEMBANGAN PERMUKIMAN DI KOTA TOMOHON

Peningkatan jumlah penduduk kawasan perkotaan di Kota Tomohon mengakibatkan peningkatan kebutuhan masyarakat seperti Kawasan permukiman. Seiring dengan adanya pertumbuhan jumlah penduduk, menyebabkan penambahan jumlah kawasan terbangun, untuk itu perlu diidentifikasi daya dukung lahan di Kota Tomohon. Tujuan penelitian untuk menganalisis daya dukung lahan dan menganalisis arahan pengembangan permukiman berdasarkan daya dukung lahan di Kota Tomohon. Teknik pengumpulan data dalam penelitian ini dilakukan dengan cara survey langsung untuk melihat kondisi eksisting dan pengambilan data sekunder di instansi yang berkaitan. Metode analisis yang digunakan adalah metode analisis spasial dan analisis proyeksi geometri guna mendapat hasil proyeksi 20 tahun kedepan. Dari hasil analisis didapatkan hasil daya dukung lahan kelas 1 (kawasan pengembangan) memiliki luas ratio tutupan lahan eksisitng 99.42% atau 535.97 Ha, kelas 2 (kawasan kendala I) 8.48% atau 291.76 Ha, kelas 3 (kawasan kendala II) 7.63% atau 551.52 Ha, kelas 4 untuk ratio tutupan lahannya 0%, ditetapkan sebagai kawasan lindung dan limitasi. Diketahui kebutuhan luas lahan permukiman pada tahun 2039 di Kota Tomohon adalah 48.04 Ha dan luas daya dukung lahan yang masih dapat dikembangkan sebagai kawasan permukiman ada pada kelas 2 dan kelas 3 dengan total luasanya adalah 2320.12 Ha sehingga Kota Tomohon masih dapat memenuhi kebutuhan lahan untuk pengembangan permukiman

A framework for using ant colony optimization to schedule environmental flow management alternatives for rivers, wetlands, and floodplains

[1] Rivers, wetlands, and floodplains are in need of management as they have been altered from natural conditions and are at risk of vanishing because of river development. One method to mitigate these impacts involves the scheduling of environmental flow management alternatives (EFMA); however, this is a complex task as there are generally a large number of ecological assets (e.g., wetlands) that need to be considered, each with species with competing flow requirements. Hence, this problem evolves into an optimization problem to maximize an ecological benefit within constraints imposed by human needs and the physical layout of the system. This paper presents a novel optimization framework which uses ant colony optimization to enable optimal scheduling of EFMAs, given constraints on the environmental water that is available. This optimization algorithm is selected because, unlike other currently popular algorithms, it is able to account for all aspects of the problem. The approach is validated by comparing it to a heuristic approach, and its utility is demonstrated using a case study based on the Murray River in South Australia to investigate (1) the trade-off between plant recruitment (i.e., promoting germination) and maintenance (i.e., maintaining habitat) flow requirements, (2) the trade-off between flora and fauna flow requirements, and (3) a hydrograph inversion case. The results demonstrate the usefulness and flexibility of the proposed framework as it is able to determine EFMA schedules that provide optimal or near-optimal trade-offs between the competing needs of species under a range of operating conditions and valuable insight for managers.J.M. Szemis, H.R. Maier and G.C. Dand

Improved validation framework and R-package for artificial neural network models

Validation is a critical component of any modelling process. In artificial neural network (ANN) modelling, validation generally consists of the assessment of model predictive performance on an independent validation set (predictive validity). However, this ignores other aspects of model validation considered to be good practice in other areas of environmental modelling, such as residual analysis (replicative validity) and checking the plausibility of the model in relation to a priori system understanding (structural validity). In order to address this shortcoming, a validation framework for ANNs is introduced in this paper that covers all of the above aspects of validation. In addition, the validann R-package is introduced that enables these validation methods to be implemented in a user-friendly and consistent fashion. The benefits of the framework and R-package are demonstrated for two environmental modelling case studies, highlighting the importance of considering replicative and structural validity in addition to predictive validity

Optimal division of data for neural network models in water resources applications

The way that available data are divided into training, testing, and validation subsets can have a significant influence on the performance of an artificial neural network (ANN). Despite numerous studies, no systematic approach has been developed for the optimal division of data for ANN models. This paper presents two methodologies for dividing data into representative subsets, namely, a genetic algorithm (GA) and a self-organizing map (SOM). These two methods are compared with the conventional approach commonly used in the literature, which involves an arbitrary division of the data. A case study is presented in which ANN models developed using each data division technique are used to forecast salinity in the River Murray at Murray Bridge (South Australia) 14 days in advance. When tested on a validation data set from July 1992 to March 1998, the models developed using the GA and SOM data division techniques resulted in a reduction in RMS error of 24.2% and 9.9%, respectively, over the conventional data division method. It was found that a SOM could be used to diagnose why an ANN model has performed poorly, given that the poor performance is primarily related to the data themselves and not the choice of the ANN's parameters or architecture.Gavin J. Bowden, Holger R. Maier and Graeme C. Dand

An integrated dynamic modeling framework for investigating the impact of climate change and variability on irrigated agriculture

Many hydrologic systems are likely to be affected by climate change. This is of particular importance given that agricultural production systems are inextricably linked to the hydrologic systems they rely upon. Although irrigation is often employed as a method to dampen the effect of short-term variation in climatic inputs to agricultural production, sources of irrigation water are not immune to long-term climatic change. Irrigation water use decisions are most often made at the farm level. It is at this scale that the economic and social impacts of climate change will be manifest. This paper presents an integrated stochastic dynamic modeling framework that can be used to investigate the viability of irrigated farms under alternative climate change scenarios. The framework is applied to a theoretical farm in the Murray Darling Basin, Australia, under four potential future climate scenarios. It is found that neglecting interannual variability in climatic inputs to agriculture consistently underestimates the reduction in farm viability caused by climate change and that multiyear sequences of climate states strongly influence estimates of farm profitability.Timothy S. C. Rowan, Holger R. Maier, Jeff Connor and Graeme C. Dand

Microsurgical third ventriculocisternostomy as an alternative to ETV: report of two cases

OBJECTIVE: To describe a microsurgical alternative to endoscopic third ventriculocisternostomy. METHODS: Two children with shunt-dependent hydrocephalus and multiple shunt revisions were considered candidates for third ventriculocisternostomy (TVS). Because of slit ventricles, an endoscopic approach was not possible and, therefore, both patients received a microsurgical TVS by a supraorbital approach. RESULTS: In both cases, microsurgical TVS was successful and the patients became shunt free. CONCLUSION: Microsurgical TVS by a supraorbital craniotomy is a viable alternative to endoscopic TVS in selected cases

Counting carbon fibres by electrical resistance measurement

AbstractElectrical Impedance Measurement has been used to measure the diameter of single carbon fibres to within 3% of the actual value measured by Scanning Electron Microscopy (SEM). The precision of the technique developed also allows for the accurate determination of the number of fibres present in a carbon fibre bundle, such data are important for the calculation of fibre tensile strength from the tensile force applied to carbon fibre bundles. The impedance of a single carbon fibre and carbon fibre bundles of up to 20 fibres have been measured, with results showing good agreement with theoretical values. The impedance of multiple lengths of carbon fibres ranging from 80 to 300mm has also been studied, with the impedance being directly proportional to the fibre length, as per electrical theory. This technique will be suitable for determining the number of fibres in a virgin or recycled carbon fibre bundle