942 resultados para water quality model
Resumo:
This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.
Resumo:
Process variability in pollutant build-up and wash-off generates inherent uncertainty that affects the outcomes of stormwater quality models. Poor characterisation of process variability constrains the accurate accounting of the uncertainty associated with pollutant processes. This acts as a significant limitation to effective decision making in relation to stormwater pollution mitigation. The study undertaken developed three theoretical scenarios based on research findings that variations in particle size fractions <150µm and >150µm during pollutant build-up and wash-off primarily determine the variability associated with these processes. These scenarios, which combine pollutant build-up and wash-off processes that takes place on a continuous timeline, are able to explain process variability under different field conditions. Given the variability characteristics of a specific build-up or wash-off event, the theoretical scenarios help to infer the variability characteristics of the associated pollutant process that follows. Mathematical formulation of the theoretical scenarios enables the incorporation of variability characteristics of pollutant build-up and wash-off processes in stormwater quality models. The research study outcomes will contribute to the quantitative assessment of uncertainty as an integral part of the interpretation of stormwater quality modelling outcomes.
Resumo:
Purpose The purpose of this paper is to explore the concept of service quality for settings where several customers are involved in the joint creation and consumption of a service. The approach is to provide first insights into the implications of a simultaneous multi‐customer integration on service quality. Design/methodology/approach This conceptual paper undertakes a thorough review of the relevant literature before developing a conceptual model regarding service co‐creation and service quality in customer groups. Findings Group service encounters must be set up carefully to account for the dynamics (social activity) in a customer group and skill set and capabilities (task activity) of each of the individual participants involved in a group service experience. Research limitations/implications Future research should undertake empirical studies to validate and/or modify the suggested model presented in this contribution. Practical implications Managers of service firms should be made aware of the implications and the underlying factors of group services in order to create and manage a group experience successfully. Particular attention should be given to those factors that can be influenced by service providers in managing encounters with multiple customers. Originality/value This article introduces a new conceptual approach for service encounters with groups of customers in a proposed service quality model. In particular, the paper focuses on integrating the impact of customers' co‐creation activities on service quality in a multiple‐actor model.
Resumo:
Concentrations of several pesticides were monitored in a paddy block and in the Kose river, which drains a paddy catchment in Fukuoka prefecture, Japan. Detailed water management in the block was also monitored to evaluate its effect on the pesticide contamination. The concentrations of applied pesticides in both block irrigation channel and drainage canal increased to tens of μg/L shortly after their applications. The increase in pesticide concentrations was well correlated with the open of irrigation and drainage gates in the pesticide-applied paddy plots only 1–3 days after pesticide application. High concentration of other pesticides, mainly herbicides, was also observed in the inflow irrigation and drainage waters, confirming the popularity of early irrigation and drainage after pesticide application in the area. The requirement of holding water after pesticide application (as a best management practice) issued by the authority was thus not properly followed. In a larger scale of the paddy catchment, the concentration of pesticides also increased significantly to several μg/L in the water of the Kose river shortly after the start of the pesticide application period either in downstream or mid–upstream areas, confirming the effect of current water management to the water quality. More extension and enforcement on water management should be done in order to control pesticide pollution from rice cultivation in Japan.
Resumo:
Pesticide use in paddy rice production may contribute to adverse ecological effects in surface waters. Risk assessments conducted for regulatory purposes depend on the use of simulation models to determine predicted environment concentrations (PEC) of pesticides. Often tiered approaches are used, in which assessments at lower tiers are based on relatively simple models with conservative scenarios, while those at higher tiers have more realistic representations of physical and biochemical processes. This chapter reviews models commonly used for predicting the environmental fate of pesticides in rice paddies. Theoretical considerations, unique features, and applications are discussed. This review is expected to provide information to guide model selection for pesticide registration, regulation, and mitigation in rice production areas.
Resumo:
We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.
Resumo:
There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.
Resumo:
Records of shrimp growth and water quality made during 12 crops from each of 48 ponds, over a period of 6.5 years, were provided by a Queensland, Australia, commercial shrimp farm, These data were analysed with a new growth model derived from the Gompertz model. The results indicate that water temperature, mortality and pond age significantly affect growth rates. After 180 days, shrimp reach 34 g at constant 30 degrees C, but only 15 g after the same amount of time at 20 degrees C. Mortality, through thinning the density of shrimp in the ponds, increased the growth rate, but the effect is small. With continual production, growth rates at first remained steady, then appeared to decrease for the sixth and seventh crop, after which they have increased steadily with each crop. It appears that conservative pond management, together with a gradual improvement in husbandry techniques, particularly feed management, brought about this change. This has encouraging implications for the long-term sustainability of the farming methods used. The growth model can be used to predict productivity, and hence, profitability, of new aquaculture locations or new production strategies.
Resumo:
In open-cut strip mining, waste material is placed in-pit to minimise operational mine costs. Slope failures in these spoil piles pose a significant safety risk to personnel, along with a financial risk from loss of equipment and scheduling delays. It has been observed that most spoil pile failures occur when the pit has been previously filled with water and then subsequently dewatered. The failures are often initiated at the base of spoil piles where the material can undergo significant slaking (disintegration) over time due to overburden pressure and water saturation. It is important to understand how the mechanical properties of base spoil material are affected by slaking when designing safe spoil pile slope angles, heights, and dewatering rates. In this study, fresh spoil material collected from a coal mine in Brown Basin Coalfield of Queensland, Australia was subjected to high overburden pressure (0 – 900 kPa) under saturated condition and maintained over a period of time (0 – 6 months) allowing the material to slake. To create the above conditions, laboratory designed pressure chambers were used. Once a spoil sample was slaked under certain overburden pressure over a period of time, it was tested for classification, permeability, and strength properties. Results of this testing program suggested that the slaking of saturated coal mine spoil increase with overburden pressure and the time duration over which the overburden pressure was maintained. Further, it was observed that shear strength and permeability of spoil decreased with increase in spoil slaking.
Resumo:
The Great Barrier Reef (GBR) is the largest reef system in the world; it covers an area of approximately 2,225,000 km² in the northern Queensland continental shelf. There are approximately 750 reefs that exist within 40 km of the Queensland coast. Recent research has identified that poor water quality is having negative impacts on the GBR (Haynes et al. 2007). The Fitzroy Basin covers 143,000 km² and is the largest catchment draining into the GBR as well as being one of the largest catchments in Australia (Karfs et al. 2009). The Burdekin Catchment is the second largest catchment entering into the GBR and covers 133,432 km².The prime determinant for the changes in water quality entering into the GBR have been attributed to grazing, with beef production the largest single land use industry comprising 90% of the land area (Karfs et al. 2009). Extensive beef production contributes over $1 billion dollars to the national economy annually and employs over 9000 people, many in rural communities (Gordon 2007). ‘Economic modelling of grazing systems in the Fitzroy and Burdekin catchments’ was a joint project with the Fitzroy Basin Association and the Queensland Department of Employment Economic Development and Innovation. The project was formed under the federally funded Caring For Our Country and the Reef Rescue programs. The project objectives were as follows; * Quantifying the costs of over-utilising available pasture and the resulting sediment leaving a representative farm for four of the major land systems in the Burdekin or Fitzroy catchments and identifying economically optimal pasture utilisation rates * Estimating the cost of reducing pasture utilisation rates below the determined optimal * Using this information, guide the selection of appropriate tools to achieve reduced utilisation rates e.g. extension process versus incentive payments or a combination of both * Model the biophysical and economic impacts of altering grazing systems to restore land condition e.g. from C condition to B condition for four land systems in the Burdekin or Fitzroy catchments.
Resumo:
A case study was undertaken to determine the economic impact of a change in management class as detailed in the A, B, C and D management class framework. This document focuses on the implications of changing from D to C, C to B and B to A class management in the Burdekin River irrigation area (BRIA) and if the change is worthwhile from an economic perspective. This report provides a guide to the economic impact that may be expected when undertaking a particular change in farming practices and will ultimately lead to more informed decisions being made by key industry stakeholders. It is recognised that these management classes have certain limitations and in many cases the grouping of practices may not be reflective of the real situation. The economic case study is based on the A, B, C and D management class framework for water quality improvement developed in 2007/2008 for the Burdekin natural resource management region. The framework for the Burdekin is currently being updated to clarify some issues and incorporate new knowledge since the earlier version of the framework. However, this updated version is not yet complete and so the Paddock to Reef project has used the most current available version of the framework for the modelling and economics. As part of the project specification, sugarcane crop production data for the BRIA was provided by the APSIM model. The information obtained from the APSIM crop modelling programme included sugarcane yields and legume grain yield (legume grain yield only applies to A class management practice). Because of the complexity involved in the economic calculations, a combination of the FEAT, PiRisk and a custom made spreadsheet was used for the economic analysis. Figures calculated in the FEAT program were transferred to the custom made spreadsheet to develop a discounted cash flow analysis. The marginal cash flow differences for each farming system were simulated over a 5-year and 10-year planning horizon to determine the net present value of changing across different management practices. PiRisk was used to test uncertain parameters in the economic analysis and the potential risk associated with a change in value.
Resumo:
A case study was undertaken to determine the economic impact of a change in management class as detailed in the A, B, C and D management class framework. This document focuses on the implications of changing from D to C, C to B and B to A class management in the Burdekin Delta region and if the change is worthwhile from an economic perspective. This report provides a guide to the economic impact that may be expected when undertaking a particular change in farming practices and will ultimately lead to more informed decisions being made by key industry stakeholders. It is recognised that these management classes have certain limitations and in many cases the grouping of practices may not be reflective of the real situation. The economic case study is based on the A, B, C and D management class framework for water quality improvement developed in 2007/2008 for the Burdekin natural resource management region. The framework for the Burdekin is currently being updated to clarify some issues and incorporate new knowledge since the earlier version of the framework. However, this updated version is not yet complete and so the Paddock to Reef project has used the most current available version of the framework for the modelling and economics. As part of the project specification, sugarcane crop production data for the Burdekin Delta region was provided by the APSIM model. The information obtained from the APSIM crop modelling programme included sugarcane yields and legume grain yield (legume grain yield only applies to A class management practice). Because of the complexity involved in the economic calculations, a combination of the FEAT, PiRisk and a custom made spreadsheet was used for the economic analysis. Figures calculated in the FEAT program were transferred to the custom made spreadsheet to develop a discounted cash flow analysis. The marginal cash flow differences for each farming system were simulated over a 5-year and 10-year planning horizon to determine the Net Present Value of changing across different management practices. PiRisk was used to test uncertain parameters in the economic analysis and the potential risk associated with a change in value.
Resumo:
A case study was undertaken to determine the economic impact of a change in management class as detailed in the A, B, C and D management class framework. This document focuses on the implications of changing from D to C, C to B and B to A class management in the Tully region and if the change is worthwhile from an economic perspective. This report provides a guide to the economic impact that may be expected when undertaking a particular change in farming practices and will ultimately lead to more informed decisions being made by key industry stakeholders. It is recognised that these management classes have certain limitations and in many cases the grouping of practices may not be reflective of the real situation. The economic case study is based on the A, B, C and D management class framework for water quality improvement developed in 2007/2008 by the wet tropics natural resource management region. The framework for wet tropics is currently being updated to clarify some issues and incorporate new knowledge since the earlier version of the framework. However, this updated version is not yet complete and so the Paddock to Reef project has used the most current available version of the framework for the modelling and economics. As part of the project specification, sugarcane crop production data for the Tully region was provided by the APSIM model. Because of the complexity involved in the economic calculations, a combination of the FEAT, PiRisk and a custom made spreadsheet was used for the economic analysis. Figures calculated in the FEAT program were transferred to the custom made spreadsheet to develop a discounted cash flow analysis. The marginal cash flow differences for each farming system were simulated over a 5-year and 10-year planning horizon to determine the Net Present Value of changing across different management practices. PiRisk was used to test uncertain parameters in the economic analysis and the potential risk associated with a change in value.
Resumo:
Cyanobacterial mass occurrences, also known as water blooms, have been associated with adverse health effects of both humans and animals. They can also be a burden to drinking water treatment facilities. Risk assessments of the blooms have generally focused on the cyanobacteria themselves and their toxins. However, heterotrophic bacteria thriving among cyanobacteria may also be responsible for many of the adverse health effects, but their role as the etiological agents of these health problems is poorly known. In addition, studies on the water purification efficiency of operating water treatment plants during cyanobacterial mass occurrences in their water sources are rare. In the present study, over 600 heterotrophic bacterial strains were isolated from natural freshwater, brackish water or from treated drinking water. The sampling sites were selected as having frequent cyanobacterial occurrences in the water bodies or in the water sources of the drinking water treatment plants. In addition, samples were taken from sites where cyanobacterial water blooms were surmised to have caused human health problems. The isolated strains represented bacteria from 57 different genera of the Gamma-, Alpha- or Betaproteobacteria, Actinobacteria, Flavobacteria, Sphingobacteria, Bacilli and Deinococci classes, based on their partial 16S rRNA sequences. Several isolates had no close relatives among previously isolated bacteria or cloned 16S rRNA genes of uncultivated bacteria. The results show that water blooms are associated with a diverse community of cultivable heterotrophic bacteria. Chosen subsets of the isolated strains were analysed for features such as their virulence gene content and possible effect on cyanobacterial growth. Of the putatively pathogenic haemolytic strains isolated in the study, the majority represented the genus Aeromonas. Therefore, the Aeromonas spp. strains isolated from water samples associated with adverse health effects were screened for the virulence gene types encoding for enterotoxins (ast, alt and act/aerA/hlyA), flagellin subunits (flaA/flaB), lipase (lip/pla/lipH3/alp-1) and elastase (ahyB) by PCR. The majority (90%) of the Aeromonas strains included one or more of the six screened Aeromonas virulence gene types. The most common gene type was act, which was present in 77% of the strains. The fla, ahyB and lip genes were present in 30 37% of the strains. The prevalence of the virulence genes implies that the Aeromonas may be a factor in some of the cyanobacterial associated health problems. Of the 183 isolated bacterial strains that were studied for possible effects on cyanobacterial growth, the majority (60%) either enhanced or inhibited growth of cyanobacteria. In most cases, they enhanced the growth, which implies mutualistic interactions. The results indicate that the heterotrophic bacteria have a role in the rise and fall of the cyanobacterial water blooms. The genetic and phenotypic characteristics and the ability to degrade cyanobacterial hepatotoxins of 13 previously isolated Betaproteobacteria strains, were also studied. The strains originated from Finnish lakes with frequent cyanobacterial occurrence. Tested strains degraded microcystins -LR and -YR and nodularin. The strains could not be assigned to any described bacterial genus or species based on their genetic or phenotypic features. On the basis of their characteristics a new genus and species Paucibacter toxinivorans was proposed for them. The water purification efficiency of the drinking water treatment processes during cyanobacterial water bloom in water source was assessed at an operating surface water treatment plant. Large phytoplankton, cyanobacterial hepatotoxins, endotoxins and cultivable heterotrophic bacteria were efficiently reduced to low concentrations, often below the detection limits. In contrast, small planktonic cells, including also possible bacterial cells, regularly passed though the water treatment. The passing cells may contribute to biofilm formation within the water distribution system, and therefore lower the obtained drinking water quality. The bacterial strains of this study offer a rich source of isolated strains for examining interactions between cyanobacteria and the heterotrophic bacteria associated with them. The degraders of cyanobacterial hepatotoxins could perhaps be utilized to assist the removal of the hepatotoxins during water treatment, whereas inhibitors of cyanobacterial growth might be useful in controlling cyanobacterial water blooms. The putative pathogenicity of the strains suggests that the health risk assessment of the cyanobacterial blooms should also cover the heterotrophic bacteria.
Resumo:
Phosphorus is a nutrient needed in crop production. While boosting crop yields it may also accelerate eutrophication in the surface waters receiving the phosphorus runoff. The privately optimal level of phosphorus use is determined by the input and output prices, and the crop response to phosphorus. Socially optimal use also takes into account the impact of phosphorus runoff on water quality. Increased eutrophication decreases the economic value of surface waters by Deteriorating fish stocks, curtailing the potential for recreational activities and by increasing the probabilities of mass algae blooms. In this dissertation, the optimal use of phosphorus is modelled as a dynamic optimization problem. The potentially plant available phosphorus accumulated in soil is treated as a dynamic state variable, the control variable being the annual phosphorus fertilization. For crop response to phosphorus, the state variable is more important than the annual fertilization. The level of this state variable is also a key determinant of the runoff of dissolved, reactive phosphorus. Also the loss of particulate phosphorus due to erosion is considered in the thesis, as well as its mitigation by constructing vegetative buffers. The dynamic model is applied for crop production on clay soils. At the steady state, the analysis focuses on the effects of prices, damage parameterization, discount rate and soil phosphorus carryover capacity on optimal steady state phosphorus use. The economic instruments needed to sustain the social optimum are also analyzed. According to the results the economic incentives should be conditioned on soil phosphorus values directly, rather than on annual phosphorus applications. The results also emphasize the substantial effects the differences in varying discount rates of the farmer and the social planner have on optimal instruments. The thesis analyzes the optimal soil phosphorus paths from its alternative initial levels. It also examines how erosion susceptibility of a parcel affects these optimal paths. The results underline the significance of the prevailing soil phosphorus status on optimal fertilization levels. With very high initial soil phosphorus levels, both the privately and socially optimal phosphorus application levels are close to zero as the state variable is driven towards its steady state. The soil phosphorus processes are slow. Therefore, depleting high phosphorus soils may take decades. The thesis also presents a methodologically interesting phenomenon in problems of maximizing the flow of discounted payoffs. When both the benefits and damages are related to the same state variable, the steady state solution may have an interesting property, under very general conditions: The tail of the payoffs of the privately optimal path as well as the steady state may provide a higher social welfare than the respective tail of the socially optimal path. The result is formalized and an applied to the created framework of optimal phosphorus use.