Optimal design of rain gauge network in the Middle Yarra River catchment, Australia

Rainfall data are a fundamental input for effective planning, designing and operating of water resources projects. A well-designed rain gauge network is capable of providing accurate estimates of necessary areal average and/or point rainfall estimates at any desired ungauged location in a catchment. Increasing network density with additional rain gauge stations has been the main underlying criterion in the past to reduce error and uncertainty in rainfall estimates. However, installing and operation of additional stations in a network involves large cost and manpower. Hence, the objective of this study is to design an optimal rain gauge network in the Middle Yarra River catchment in Victoria, Australia. The optimal positioning of additional stations as well as optimally relocating of existing redundant stations using the kriging-based geostatistical approach was undertaken in this study. Reduction of kriging error was considered as an indicator for optimal spatial positioning of the stations. Daily rainfall records of 1997 (an El Niño year) and 2010 (a La Niña year) were used for the analysis. Ordinary kriging was applied for rainfall data interpolation to estimate the kriging error for the network. The results indicate that significant reduction in the kriging error can be achieved by the optimal spatial positioning of the additional as well as redundant stations. Thus, the obtained optimal rain gauge network is expected to be appropriate for providing high quality rainfall estimates over the catchment. The concept proposed in this study for optimal rain gauge network design through combined use of additional and redundant stations together is equally applicable to any other catchment

A new generic open pit mine planning process with risk assessment ability

Conventionally, mining industry relies on a deterministic view, where a unique mine plan is determined based on a single resource model. A major shortfall of this approach is the inability to assess the risk caused by the well-known geological uncertainty, i.e. the in situ grade and tonnage variability of the mineral deposit. Despite some recent attempts in developing stochastic mine planning models which have demonstrated promising results, the industry still remains sceptical about this innovative idea. With respect to unbiased linear estimation, kriging is the most popular and reliable deterministic interpolation technique for resource estimation and it appears to remain its popularity in the near future. This paper presents a new systematic framework to quantify the risk of kriging-based mining projects due to the geological uncertainties. Firstly, conditional simulation is implemented to generate a series of equally-probable orebody realisations and these realisations are then compared with the kriged resource model to analyse its geological uncertainty. Secondly, a production schedule over the life of mine is determined based on the kriged resource model. Finally, risk profiles of that production schedule, namely ore and waste tonnage production, blending grade and Net Present Value (NPV), are constructed using the orebody realisations. The proposed model was applied on a multi-element deposit and the result demonstrates that that the kriging-based mine plan is unlikely to meet the production targets. Especially, the kriging-based mine plan overestimated the expected NPV at a magnitude of 6.70% to 7.34% (135 M$to 151 M$). A new multivariate conditional simulation framework was also introduced in this paper to cope with the multivariate nature of the deposit. Although an iron ore deposit is used to prove the concepts, the method can easily be adapted to other kinds of mineral deposits, including surface coal mine

The spatial extent of tephra deposition and environmental impacts from the 1912 Novarupta eruption

The eruption of Novarupta within the Katmai Volcanic Cluster, south-west Alaska, in June 1912 was the most voluminous eruption of the twentieth century but the distal distribution of tephra deposition is inadequately quantified. We present new syntheses of published tephrostratigraphic studies and a large quantity of previously un-investigated historical records. For the first time, we apply a geostatistical technique, indicator kriging, to integrate and interpolate such data. Our results show evidence for tephra deposition across much of Alaska, Yukon, the northern Pacific, western British Columbia and northwestern Washington. The most distal tephra deposition was observed around 2,500 km downwind from the volcano. Associated with tephra deposition are many accounts of acid deposition and consequent impacts on vegetation and human health. Kriging offers several advantages as a means to integrate and present such data. Future eruptions of a scale similar to the 1912 event have the potential to cause widespread disruption. Historical records of tephra deposition extend far beyond the limit of deposition constrained by tephrostratigraphic records. The distal portion of tephra fallout deposits is rarely adequately mapped by tephrostratigraphy alone; contemporaneous reports of fallout can provide important constraints on the extent of impacts following large explosive eruptions

Area Disease Estimation Based on Sentinel Hospital Records

BACKGROUND: Population health attributes (such as disease incidence and prevalence) are often estimated using sentinel hospital records, which are subject to multiple sources of uncertainty. When applied to these health attributes, commonly used biased estimation techniques can lead to false conclusions and ineffective disease intervention and control. Although some estimators can account for measurement error (in the form of white noise, usually after de-trending), most mainstream health statistics techniques cannot generate unbiased and minimum error variance estimates when the available data are biased. METHODS AND FINDINGS: A new technique, called the Biased Sample Hospital-based Area Disease Estimation (B-SHADE), is introduced that generates space-time population disease estimates using biased hospital records. The effectiveness of the technique is empirically evaluated in terms of hospital records of disease incidence (for hand-foot-mouth disease and fever syndrome cases) in Shanghai (China) during a two-year period. The B-SHADE technique uses a weighted summation of sentinel hospital records to derive unbiased and minimum error variance estimates of area incidence. The calculation of these weights is the outcome of a process that combines: the available space-time information; a rigorous assessment of both, the horizontal relationships between hospital records and the vertical links between each hospital's records and the overall disease situation in the region. In this way, the representativeness of the sentinel hospital records was improved, the possible biases of these records were corrected, and the generated area incidence estimates were best linear unbiased estimates (BLUE). Using the same hospital records, the performance of the B-SHADE technique was compared against two mainstream estimators. CONCLUSIONS: The B-SHADE technique involves a hospital network-based model that blends the optimal estimation features of the Block Kriging method and the sample bias correction efficiency of the ratio estimator method. In this way, B-SHADE can overcome the limitations of both methods: Block Kriging's inadequacy concerning the correction of sample bias and spatial clustering; and the ratio estimator's limitation as regards error minimization. The generality of the B-SHADE technique is further demonstrated by the fact that it reduces to Block Kriging in the case of unbiased samples; to ratio estimator if there is no correlation between hospitals; and to simple statistic if the hospital records are neither biased nor space-time correlated. In addition to the theoretical advantages of the B-SHADE technique over the two other methods above, two real world case studies (hand-foot-mouth disease and fever syndrome cases) demonstrated its empirical superiority, as well

Incidence of oral cancer in relation to nickel and arsenic concentrations in farm soils of patients' residential areas in Taiwan

<p>Abstract</p> <p>Background</p> <p>To explore if exposures to specific heavy metals in the environment is a new risk factor of oral cancer, one of the fastest growing malignancies in Taiwan, in addition to the two established risk factors, cigarette smoking and betel quid chewing.</p> <p>Methods</p> <p>This is an observational study utilized the age-standardized incidence rates of oral cancer in the 316 townships and precincts of Taiwan, local prevalence rates of cigarette smoking and betel quid chewing, demographic factors, socio-economic conditions, and concentrations in farm soils of the eight kinds of heavy metal. Spatial regression and GIS (Geographic Information System) were used. The registration contained 22,083 patients, who were diagnosed with oral cancer between 1982 and 2002. The concentrations of metal in the soils were retrieved from a nation-wide survey in the 1980s.</p> <p>Results</p> <p>The incidence rate of oral cancer is geographically related to the concentrations of arsenic and nickel in the patients' residential areas, with the prevalence of cigarette smoking and betel quid chewing as controlled variables.</p> <p>Conclusions</p> <p>Beside the two established risk factors, cigarette smoking and betel quid chewing, arsenic and nickel in farm soils may be new risk factors for oral cancer. These two kinds of metal may involve in the development of oral cancer. Further studies are required to understand the pathways via which metal in the farm soils exerts its effects on human health.</p

Scenario of the spread of the invasive species Zaprionus indianus Gupta, 1970 (Diptera, Drosophilidae) in Brazil

Zaprionus indianus was first recorded in Brazil in 1999 and rapidly spread throughout the country. We have obtained data on esterase loci polymorphisms (Est2 and Est3), and analyzed them, using Landscape Shape Interpolation and the Monmonier Maximum Difference Algorithm to discover how regional invasion occurred. Hence, it was apparent that Z. indianus, after first arriving in São Paulo state, spread throughout the country, probably together with the transportation of commercial fruits by way of the two main Brazilian freeways, BR 153, to the south and the surrounding countryside, and the BR 116 along the coast and throughout the north-east

Effects of Particulate Air Pollution on Cardiovascular Health: A Population Health Risk Assessment

Particulate matter (PM) air pollution is increasingly recognized as an important and modifiable risk factor for adverse health outcomes including cardiovascular disease (CVD). However, there are still gaps regarding large population risk assessment. Results from the nationwide Behavioral Risk Factor Surveillance System (BRFSS) were used along with air quality monitoring measurements to implement a systematic evaluation of PM-related CVD risks at the national and regional scales. CVD status and individual-level risk factors were collected from more than 500,000 BRFSS respondents across 2,231 contiguous U.S. counties for 2007 and 2009. Chronic exposures to PM pollutants were estimated with spatial modeling from measurement data. CVD outcomes attributable to PM pollutants were assessed by mixed-effects logistic regression and latent class regression (LCR), with adjustment for multicausality. There were positive associations between CVD and PM after accounting for competing risk factors: the multivariable-adjusted odds for the multiplicity of CVD outcomes increased by 1.32 (95% confidence interval: 1.23–1.43) and 1.15 (1.07–1.22) times per 10 µg/m3 increase in PM2.5 and PM10 respectively in the LCR analyses. After controlling for spatial confounding, there were moderate estimated effects of PM exposure on multiple cardiovascular manifestations. These results suggest that chronic exposures to ambient particulates are important environmental risk factors for cardiovascular morbidity

Soil gas radon assessment and development of a radon risk map in Bolsena, Central Italy

Vulsini Volcanic district in Northern Latium (Central Italy) is characterized by high natural radiation background resulting from the high concentrations of uranium, thorium and potassium in the volcanic products. In order to estimate the radon radiation risk, a series of soil gas radon measurements were carried out in Bolsena, the principal urban settlement in this area NE of Rome. Soil gas radon concentration ranges between 7 and 176 kBq/m(3) indicating a large degree of variability in the NORM content and behavior of the parent soil material related in particular to the occurrence of two different lithologies. Soil gas radon mapping confirmed the existence of two different areas: one along the shoreline of the Bolsena lake, characterized by low soil radon level, due to a prevailing alluvial lithology; another close to the Bolsena village with high soil radon level due to the presence of the high radioactive volcanic rocks of the Vulsini volcanic district. Radon risk assessment, based on soil gas radon and permeability data, results in a map where the alluvial area is characterized by a probability to be an area with high Radon Index lower than 20 %, while probabilities higher than 30 % and also above 50 % are found close to the Bolsena village

History Shaped the Geographic Distribution of Genomic Admixture on the Island of Puerto Rico

Contemporary genetic variation among Latin Americans human groups reflects population migrations shaped by complex historical, social and economic factors. Consequently, admixture patterns may vary by geographic regions ranging from countries to neighborhoods. We examined the geographic variation of admixture across the island of Puerto Rico and the degree to which it could be explained by historic and social events. We analyzed a census-based sample of 642 Puerto Rican individuals that were genotyped for 93 ancestry informative markers (AIMs) to estimate African, European and Native American ancestry. Socioeconomic status (SES) data and geographic location were obtained for each individual. There was significant geographic variation of ancestry across the island. In particular, African ancestry demonstrated a decreasing East to West gradient that was partially explained by historical factors linked to the colonial sugar plantation system. SES also demonstrated a parallel decreasing cline from East to West. However, at a local level, SES and African ancestry were negatively correlated. European ancestry was strongly negatively correlated with African ancestry and therefore showed patterns complementary to African ancestry. By contrast, Native American ancestry showed little variation across the island and across individuals and appears to have played little social role historically. The observed geographic distributions of SES and genetic variation relate to historical social events and mating patterns, and have substantial implications for the design of studies in the recently admixed Puerto Rican population. More generally, our results demonstrate the importance of incorporating social and geographic data with genetics when studying contemporary admixed populations