940 resultados para Mathematical modeling of water quality


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Caption title.

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Красимир Йорджев, Христина Костадинова - В работата се разглежда една релация на еквивалентност в множеството от всички квадратни бинарни матрици. Обсъдена е комбинаторната задача за намиране мощността и елементите на фактормножеството относно тази релация. Разгледана е и възможността за получаване на някои специални елементи на това фактормножество. Предложен е алгоритъм за решаване на поставените задачи. Получените в статията резултати намират приложение при описанието топологията на различните тъкачни структури.

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The major objectives of this dissertation were to develop optimal spatial techniques to model the spatial-temporal changes of the lake sediments and their nutrients from 1988 to 2006, and evaluate the impacts of the hurricanes occurred during 1998–2006. Mud zone reduced about 10.5% from 1988 to 1998, and increased about 6.2% from 1998 to 2006. Mud areas, volumes and weight were calculated using validated Kriging models. From 1988 to 1998, mud thicknesses increased up to 26 cm in the central lake area. The mud area and volume decreased about 13.78% and 10.26%, respectively. From 1998 to 2006, mud depths declined by up to 41 cm in the central lake area, mud volume reduced about 27%. Mud weight increased up to 29.32% from 1988 to 1998, but reduced over 20% from 1998 to 2006. The reduction of mud sediments is likely due to re-suspension and redistribution by waves and currents produced by large storm events, particularly Hurricanes Frances and Jeanne in 2004 and Wilma in 2005. Regression, kriging, geographically weighted regression (GWR) and regression-kriging models have been calibrated and validated for the spatial analysis of the sediments TP and TN of the lake. GWR models provide the most accurate predictions for TP and TN based on model performance and error analysis. TP values declined from an average of 651 to 593 mg/kg from 1998 to 2006, especially in the lake’s western and southern regions. From 1988 to 1998, TP declined in the northern and southern areas, and increased in the central-western part of the lake. The TP weights increased about 37.99%–43.68% from 1988 to 1998 and decreased about 29.72%–34.42% from 1998 to 2006. From 1988 to 1998, TN decreased in most areas, especially in the northern and southern lake regions; western littoral zone had the biggest increase, up to 40,000 mg/kg. From 1998 to 2006, TN declined from an average of 9,363 to 8,926 mg/kg, especially in the central and southern regions. The biggest increases occurred in the northern lake and southern edge areas. TN weights increased about 15%–16.2% from 1988 to 1998, and decreased about 7%–11% from 1998 to 2006.

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Altered freshwater inflows have affected circulation, salinity, and water quality patterns of Florida Bay, in turn altering the structure and function of this estuary. Changes in water quality and salinity and associated loss of dense turtle grass and other submerged aquatic vegetation (SAV) in Florida Bay have created a condition in the bay where sediments and nutrients have been regularly disturbed, frequently causing large and dense phytoplankton blooms. These algal and cyanobacterial blooms in turn often cause further loss of more recently established SAV, exacerbating the conditions causing the blooms. Chlorophyll a (CHLA) was selected as an indicator of water quality because it is an indicator of phytoplankton biomass, with concentrations reflecting the integrated effect of many of the water quality factors that may be altered by restoration activities. Overall, we assessed the CHLA indicator as being (1) relevant and reflecting the state of the Florida Bay ecosystem, (2) sensitive to ecosystem drivers (stressors, especially nutrient loading), (3) feasible to monitor, and (4) scientifically defensible. Distinct zones within the bay were defined according to statistical and consensual information. Threshold levels of CHLA for each zone were defined using historical data and scientific consensus. A presentation template of condition of the bay using these thresholds is shown as an example of an outreach product.

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Limestone-based (karstic) freshwater wetlands of the Everglades, Belize, Mexico, and Jamaica are distinctive in having a high biomass of CaCO3-rich periphyton mats. Diatoms are common components of these mats and show predictable responses to environmental variation, making them good candidates for assessing nutrient enrichment in these naturally ultraoligotrophic wetlands. However, aside from in the Everglades of southern Florida, very little research has been done to document the diatoms and their environmental preferences in karstic Caribbean wetlands, which are increasingly threatened by eutrophication. We identified diatoms in periphyton mats collected during wet and dry periods from the Everglades and similar freshwater karstic wetlands in Belize, Mexico, and Jamaica. We compared diatom assemblage composition and diversity among locations and periods, and the effect of the limiting nutrient, P, on species composition among locations. We used periphyton-mat total P (TP) as a metric of availability. A total of 176 diatom species in 45 genera were recorded from the 4 locations. Twenty-three of these species, including 9 that are considered indicative of Everglades diatom flora, were found in all 4 locations. In Everglades and Caribbean sites, we identified assemblages and indicator species associated with low and high periphyton-mat TP and calculated TP optima and tolerances for each indicator species. TP optima and tolerances of indicator species differed between the Everglades and the Caribbean, but weighted averaging models predicted periphyton-mat TP concentrations from diatom assemblages at Everglades (R2  =  0.56) and Caribbean (R2  =  0.85) locations. These results show that diatoms can be effective indicators of water quality in karstic wetlands of the Caribbean, but application of regionally generated transfer functions to distant sites provides less reliable estimates than locally developed functions.

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In perifusion cell cultures, the culture medium flows continuously through a chamber containing immobilized cells and the effluent is collected at the end. In our main applications, gonadotropin releasing hormone (GnRH) or oxytocin is introduced into the chamber as the input. They stimulate the cells to secrete luteinizing hormone (LH), which is collected in the effluent. To relate the effluent LH concentration to the cellular processes producing it, we develop and analyze a mathematical model consisting of coupled partial differential equations describing the intracellular signaling and the movement of substances in the cell chamber. We analyze three different data sets and give cellular mechanisms that explain the data. Our model indicates that two negative feedback loops, one fast and one slow, are needed to explain the data and we give their biological bases. We demonstrate that different LH outcomes in oxytocin and GnRH stimulations might originate from different receptor dynamics. We analyze the model to understand the influence of parameters, like the rate of the medium flow or the fraction collection time, on the experimental outcomes. We investigate how the rate of binding and dissociation of the input hormone to and from its receptor influence its movement down the chamber. Finally, we formulate and analyze simpler models that allow us to predict the distortion of a square pulse due to hormone-receptor interactions and to estimate parameters using perifusion data. We show that in the limit of high binding and dissociation the square pulse moves as a diffusing Gaussian and in this limit the biological parameters can be estimated.

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Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Dissertation, 2016

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This fact sheet summarizes the water quality data collected as part of the Iowa Department of Natural Resources ambient lake monitoring program.

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Knowledge of how biota can be used to monitor ecosystem health and assess impacts by human alterations such as land use and management measures taken at different spatial scales is critical for improving the ecological quality of aquatic ecosystems. This knowledge in Uganda is very limited or unavailable yet it is needed to better understand the relationship between environmental factors at different spatial scales, assemblage structure and taxon richness of aquatic ecosystems. In this study, benthic invertebrate community patterns were sampled between June 2001 and April 2002 and analysed in relation to water quality and catchment land use patterns from three shallow near-shore bays characterized by three major land uses patterns: urban (Murchison Bay); semi-urban (Fielding Bay); rural (Hannington Bay). Variations in density and guild composition of benthic macro-invertebrates communities were evaluated using GIS techniques along an urban-rural gradient of land use and differences in community composition were related to dissolved oxygen and conductivity variation. Based on numerical abundance and tolerance values, Hilsenhoff's Biotic Index ofthe invertebrates was determined in order to evaluate the relative importance of water quality in the three bays. Murchison Bay supported a relatively taxa-poor invertebrate assemblage mainly comprising stenotopic and eurytopic populations of pollution-tolerant groups such as worms and Chironomus sp. with an overall depression in species diversity. On the contrary, the communities in Fielding and Hannington bays were quite similar and supported distinct and diverse assemblages including pollution-intolerant forms such as Ephemeroptera (mayflies), Odonata (dragonflies). The Hilsenhoff Biotic Index in Murchison Bay was 6.53. (indicating poor water quality) compared to 6.34 for Fielding Bay and 5.78 for Hannington Bay (both indicating fair water quality). The characterization of maximum taxa richness balanced among taxa groups with good representation of intolerant individuals in Hannington Bay relative to Fielding and Murchison bays concludes that the bay is the cleanest in terms of water quality. Contrary, the dominance of few taxa with many tolerant iqdividuals present in Murchison Bay indicates that the bay is degraded in terms of water quality. These result are ofimportance when planning conservation and management measures, implementing large-scale biomonitoring programs, and predicting how human alterations (e.g nutrient loading) affect water ecosystems. Therefore, analysis of water quality in relation to macro-invertebrate community composition patterns as bio-indicators can lead to further understanding of their responses to environmental manipulations and perturbations.

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Some physiochemical properties of water quality of Otamiri-oche River which runs through Imeh, Edegelem and Chokocho Communities in Etche ethnic nationality of Rivers State, Nigeria were investigated. Samples were collected in triplicate from the three different locations along the river in both rainy and dry seasons. Each sampling points is located 500m away from the successive one, and the samples were taken from the open river at the zone extending beyond the shoreline. Samples were stored in ice packs and immediately taken to the laboratory to investigate some selected physico-chemical characteristics. Also, bacteriological study was carried out on the samples. The laboratory results of the selected physico-chemical parameters when compared with the world health organization (WHO) standard showed that all the selected physico-chemical parameters were within the world health organization (WHO) permissible in both rainy and dry season except pH. For rainy season, the pH values were 5.00±0.00, 5.40 ±0.40, and 5.40± 0.30 for Imeh, Edegelem and Chokocho respectively. For the dry season, the pH values were 5.83± 0.01, 5.56±0.01, 5.90±0.01 for Imeh, Edegelem and Chokocho respectively. Also magnesium hardness exceeded the World Health Organization (WHO) permissible limit in rainy season only. The results of bacteriological study showed that all the sampling locations contained high numbers of coliform bacteria in both rainy and dry seasons. The number of coliform bacteria during rainy season was 25.00±0.00, 25.00±0.00, and 35.00±0.00 for Imeh, Edegelem and Chokocho respectively. Those of dry season were 93.00±3.55, 56.66±4.49, and 35.60±4.17 for Imeh, Edegelem and Chokocho respectively. The difference between the rainy and dry season was tested statistically using the t-test. The results of the statistical analyses showed a significant difference (p<0.05) between the rainy and dry seasons.

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The purpose of this research was to present the principles for the implementation of a future water body classification program at the UGRHI-1 (Management Unit of Water Resources-1/São Paulo, Brazil) using qualitative and quantitative water modeling. Our study area was in Campos do Jordão, a city in the state of São Paulo, specifically in the Perdizes river watershed, which is included in the UGRHI-1. The water quality assessment used a modeling mehtodology that can support a future study for the classification of water bodies in the region. The behavior of DO and BOD parameters was assessed in the water quality scenarios, considering the variations of flows, loads, reductions in withdrawals and different efficiencies in sewage treatment. The model used was QUAL2E developed by USEPA (United States Environmental Protection Agency) that received a new graphic interface named QUAL2R model. The reference flows Q7,10, Q95% and Qm used were obtained through the DAEE (Department of Water and Electric Energy) hydrologic regionalization method. It was noted that of the 9 proposed scenarios, only scenario 6 that was predicted in the flow regime Qm with the existence of a treatment system capable of removing 93% of the BOD, in the Perdizes River remained 67.5% of the time in class 2. Scenario 8 predicted a 50% reduction in In scenario 8 a reduction of 50% in the flow captured in CA-04, associated with the efficiency of 93% of BOD removal keeping the river in class 2. In scenario 9 the minimum required efficiency in sewage treatment in the flow regime Q95% for keeping the river in class 2 was also calculated and the value of 94.7% was obtained.

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Deterministic models have been widely used to predict water quality in distribution systems, but their calibration requires extensive and accurate data sets for numerous parameters. In this study, alternative data-driven modeling approaches based on artificial neural networks (ANNs) were used to predict temporal variations of two important characteristics of water quality chlorine residual and biomass concentrations. The authors considered three types of ANN algorithms. Of these, the Levenberg-Marquardt algorithm provided the best results in predicting residual chlorine and biomass with error-free and ``noisy'' data. The ANN models developed here can generate water quality scenarios of piped systems in real time to help utilities determine weak points of low chlorine residual and high biomass concentration and select optimum remedial strategies.

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Background: The quality of stormwater runoff from ports is significant as it can be an important source of pollution to the marine environment. This is also a significant issue for the Port of Brisbane as it is located in an area of high environmental values. Therefore, it is imperative to develop an in-depth understanding of stormwater runoff quality to ensure that appropriate strategies are in place for quality improvement, where necessary. To this end, the Port of Brisbane Corporation aimed to develop a port specific stormwater model for the Fisherman Islands facility. The need has to be considered in the context of the proposed future developments of the Port area. ----------------- The Project: The research project is an outcome of the collaborative Partnership between the Port of Brisbane Corporation (POBC) and Queensland University of Technology (QUT). A key feature of this Partnership is that it seeks to undertake research to assist the Port in strengthening the environmental custodianship of the Port area through ‘cutting edge’ research and its translation into practical application. ------------------ The project was separated into two stages. The first stage developed a quantitative understanding of the generation potential of pollutant loads in the existing land uses. This knowledge was then used as input for the stormwater quality model developed in the subsequent stage. The aim is to expand this model across the yet to be developed port expansion area. This is in order to predict pollutant loads associated with stormwater flows from this area with the longer term objective of contributing to the development of ecological risk mitigation strategies for future expansion scenarios. ----------------- Study approach: Stage 1 of the overall study confirmed that Port land uses are unique in terms of the anthropogenic activities occurring on them. This uniqueness in land use results in distinctive stormwater quality characteristics different to other conventional urban land uses. Therefore, it was not scientifically valid to consider the Port as belonging to a single land use category or to consider as being similar to any typical urban land use. The approach adopted in this study was very different to conventional modelling studies where modelling parameters are developed using calibration. The field investigations undertaken in Stage 1 of the overall study helped to create fundamental knowledge on pollutant build-up and wash-off in different Port land uses. This knowledge was then used in computer modelling so that the specific characteristics of pollutant build-up and wash-off can be replicated. This meant that no calibration processes were involved due to the use of measured parameters for build-up and wash-off. ---------------- Conclusions: Stage 2 of the study was primarily undertaken using the SWMM stormwater quality model. It is a physically based model which replicates natural processes as closely as possible. The time step used and catchment variability considered was adequate to accommodate the temporal and spatial variability of input parameters and the parameters used in the modelling reflect the true nature of rainfall-runoff and pollutant processes to the best of currently available knowledge. In this study, the initial loss values adopted for the impervious surfaces are relatively high compared to values noted in research literature. However, given the scientifically valid approach used for the field investigations, it is appropriate to adopt the initial losses derived from this study for future modelling of Port land uses. The relatively high initial losses will reduce the runoff volume generated as well as the frequency of runoff events significantly. Apart from initial losses, most of the other parameters used in SWMM modelling are generic to most modelling studies. Development of parameters for MUSIC model source nodes was one of the primary objectives of this study. MUSIC, uses the mean and standard deviation of pollutant parameters based on a normal distribution. However, based on the values generated in this study, the variation of Event Mean Concentrations (EMCs) for Port land uses within the given investigation period does not fit a normal distribution. This is possibly due to the fact that only one specific location was considered, namely the Port of Brisbane unlike in the case of the MUSIC model where a range of areas with different geographic and climatic conditions were investigated. Consequently, the assumptions used in MUSIC are not totally applicable for the analysis of water quality in Port land uses. Therefore, in using the parameters included in this report for MUSIC modelling, it is important to note that it may result in under or over estimations of annual pollutant loads. It is recommended that the annual pollutant load values given in the report should be used as a guide to assess the accuracy of the modelling outcomes. A step by step guide for using the knowledge generated from this study for MUSIC modelling is given in Table 4.6. ------------------ Recommendations: The following recommendations are provided to further strengthen the cutting edge nature of the work undertaken: * It is important to further validate the approach recommended for stormwater quality modelling at the Port. Validation will require data collection in relation to rainfall, runoff and water quality from the selected Port land uses. Additionally, the recommended modelling approach could be applied to a soon-to-be-developed area to assess ‘before’ and ‘after’ scenarios. * In the modelling study, TSS was adopted as the surrogate parameter for other pollutants. This approach was based on other urban water quality research undertaken at QUT. The validity of this approach should be further assessed for Port land uses. * The adoption of TSS as a surrogate parameter for other pollutants and the confirmation that the <150 m particle size range was predominant in suspended solids for pollutant wash-off gives rise to a number of important considerations. The ability of the existing structural stormwater mitigation measures to remove the <150 m particle size range need to be assessed. The feasibility of introducing source control measures as opposed to end-of-pipe measures for stormwater quality improvement may also need to be considered.

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This paper describes the experimental evaluation of a novel Autonomous Surface Vehicle capable of navigating complex inland water reservoirs and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran is capable of collecting water column profiles whilst in motion. It is also directly integrated with a reservoir scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper describes the onboard vehicle navigation and control algorithms as well as obstacle avoidance strategies. Experimental results are shown demonstrating its ability to maintain track and avoid obstacles on a variety of large-scale missions and under differing weather conditions, as well as its ability to continuously collect various water quality parameters complimenting traditional manual monitoring campaigns.

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With growing population and fast urbanization in Australia, it is a challenging task to maintain our water quality. It is essential to develop an appropriate statistical methodology in analyzing water quality data in order to draw valid conclusions and hence provide useful advices in water management. This paper is to develop robust rank-based procedures for analyzing nonnormally distributed data collected over time at different sites. To take account of temporal correlations of the observations within sites, we consider the optimally combined estimating functions proposed by Wang and Zhu (Biometrika, 93:459-464, 2006) which leads to more efficient parameter estimation. Furthermore, we apply the induced smoothing method to reduce the computational burden. Smoothing leads to easy calculation of the parameter estimates and their variance-covariance matrix. Analysis of water quality data from Total Iron and Total Cyanophytes shows the differences between the traditional generalized linear mixed models and rank regression models. Our analysis also demonstrates the advantages of the rank regression models for analyzing nonnormal data.