3D model for a secondary facultative pond

This paper describes a comprehensive model of wastewater treatment in secondary facultative ponds, which combines 3D hydrodynamics with a mechanistic water quality model. The hydrodynamics are based on the Navier-Stokes equation for incompressible fluids under shallow water and Boussinesq assumptions capturing the flow dynamics along length, breadth and depth of the pond. The water quality sub model is based on the Activated Sludge Model (ASM) concept, describing COD and nutrient removal as function of bacterial growth following Monod kinetics, except for Escherichia coli removal, which was modelled as first order decay. The model was implemented in the Delft3D software and was used to evaluate the effect of wind and the addition of baffles on the water flow pattern, temperature profiles in the pond and treatment efficiency. In contrast to earlier models reported in the literature, our simulation results did not show any significant improvement in COD removal (based on the ASM concept) with addition of baffles or under intermittent wind-induced mixing. However, E. coli removal efficiency, based on a first order decay approach, showed a fair improvement in the presence of baffles or intermittent wind-induced mixing. Furthermore, simulations with continuous wind effect showed a decrease in removal efficiency for COD but a further increase in E. coli removal efficiency. Such contrasting results for two different approaches in modelling could indicate that the first order decay concept might not be appropriate to describe all the interactions between biochemical processes in a pond. However, these interpretations remain theoretical, as the model needs validation with field data.     

Artificial neural network modeling of the river water quality—A case study

The paper describes the training, validation and application of artificial neural network (ANN) models for computing the dissolved oxygen (DO) and biochemical oxygen demand (BOD) levels in the Gomti river (India). Two ANN models were identified, validated and tested for the computation of DO and BOD concentrations in the Gomti river water. Both the models employed eleven input water quality variables measured in river water over a period of 10 years each month at eight different sites. The performance of the ANN models was assessed through the coefficient of determination (R²) (square of the correlation coefficient), root mean square error (RMSE) and bias computed from the measured and model computed values of the dependent variables. Goodness of the model fit to the data was also evaluated through the relationship between the residuals and model computed values of DO and BOD. The model computed values of DO and BOD by both the ANN models were in close agreement with their respective measured values in the river water. Relative importance and contribution of the input variables to the model output was evaluated through the partitioning approach. The identified ANN models can be used as tools for the computation of water quality parameters.     

A bio-inspired computing model as a new tool for modeling ecosystems: The avian scavengers as a case study

The models used for ecosystems modeling are generally based on differential equations. However, in recent years new computational models based on biological processes, or bioinspired models, have arisen, among which are P systems. These are inspired by the functions of cells and present important advantages with respect to traditional models, such as a high computational efficiency, modularity and their ability to work in parallel. They are simple, individual-based models that use biological parameters that can be obtained experimentally. In this work, we present the framework for a model based on P systems applied to the study of an ecosystem in which three avian scavengers (predators) interact with 10 wild and domestic ungulates (preys). The computation time for 100 repetitions, corresponding to 14 simulation years each, with an initial population composed of 385,422 individuals, was 30 min. Our results suggest that the model presented, based on P systems, correctly simulates the population dynamics in the period of time analyzed. We discuss the usefulness of this tool in simulating complex ecosystems dynamics to aid managers, conservationists and policy-makers in making appropriate decisions for the improvement of management and conservation programs.     

Multiple-pattern parameter identification and uncertainty analysis approach for water quality modeling

This paper presents a multiple-pattern parameter identification and uncertainty analysis approach for robust water quality modeling using a neural network (NN) embedded genetic algorithm (GA). The modeling approach uses an adaptive NN–GA framework to inversely solve the governing equations in a water quality model for multiple parameter patterns, along with an alternating fitness method to maintain solution diversity. The procedure was demonstrated through a coupled 2D hydrodynamic and eutrophication model for Loch Raven Reservoir in Maryland. The inverse problem was formulated as a nonlinear optimization problem minimizing the degree of misfit (DOM) between model results and observed data. A set of NN models was developed to approximate the input-output response relationship of the Loch Raven Reservoir model and was incorporated into a GA framework in an adaptive fashion to search for near-optimal solutions minimizing the DOM. The numerical example showed that the adaptive NN–GA approach is capable of identifying multiple parameter patterns that reproduce the observed data equally well. The resulting parameter patterns were incorporated into the numerical model, and a multiple-pattern robust water quality modeling analysis, along with a compound margin of safety (CMOS) method, was proposed and applied to analyze the parameter pattern uncertainty.     

Modeling linkages between sediment resuspension and water quality in a shallow,eutrophic, wind-exposed lake

The interactions between bed sediments and the water column in shallow, eutrophic lakes have tremendous implications for the fate and transport of nutrients in those water bodies. This has resulted in the development of water quality models for lakes incorporating the processes of sediment resuspension. Reliable resuspension models are thus needed to accurately represent this phenomenon. In this paper, three different sediment-resuspension models are combined with a hydrodynamic and water quality model, dynamic lake model-water quality (DLM-WQ), and the resulting models are used to simulate nutrient distributions in the highly eutrophic Salton Sea, California, USA. One of the resuspension formulas is based upon sediment characteristics as well as the bed shear stress exerted by wind-induced waves and currents, while the other two are standard, power-law-type formulas for cohesive sediments with two different exponents. The outputs for water quality variables, such as temperature, chlorophyll a, dissolved oxygen and nutrients, obtained from the three resulting models and from an earlier DLM-WQ run with a simple empirical sediment-resuspension model are compared with measured data. The level of agreement between the simulations and the measured data is assessed by using both statistical and graphical model evaluation methods, including measures of residual errors, sample autocorrelations, t-tests, and box plots. Based on these assessments, DLM-WQ with an extended version of the García and Parker [García, M.H., Parker, G., 1993. Experiments on the entrainment of sediment into suspension by a dense bottom current. J. Geophys. Res.-Oceans 98, 4793–4807] relationship gave the best results for water quality in the Salton Sea, confirming that the use of formulas with more information on the sediment characteristics yields more accurate results. To the best of our knowledge, this is the first effort to combine water quality models for lakes and reservoirs with a sediment-resuspension model which was originally intended for open-channel flows. The simulations confirm that sediment resuspension is the most dominant process in the Salton Sea's nutrient cycling. The effect of proposed physical changes to the Salton Sea on water quality characteristics is also addressed.     

浅水流动有限体积法/Osher格式的二维水流-水质模拟

应用无结构网格有限体积法 /Osher格式的二维水流 -水质耦合数值模型 ,采用黎曼近似解计算模拟区域水量、动量及污染物输送通量。通过对长江南京八卦洲江段浓度场的模拟计算 ,其结果与遥感卫星图片确定的污染带分布相吻合 ,证实了模型的合理性和模拟能力     

Region of influence method improves macroinvertebrate predictive models in Maryland

Stream biological assessment reflects not just conventional water quality, but an environmental quality that represents the integrity of the stream ecosystem. In Britain, Australia and the United States, macroinvertebrate predictive models were built and applied to stream assessment by employing multivariate analysis. There were variations in these models, where adaptations were made for different regions, but the philosophy underlying the models was similar: employ site classification to predict expected assemblage. Taxon assemblage is predicted from reference groups with similar stream features; these resulting models are RIVPACS-style models. Because every site has to belong to one group in the classification process, each reference group might include some dissimilar sites, and their dissimilarity in taxon assemblage impaired the results of taxon predictions from these models. To avoid this limitation, this study employed a Region-of-Influence-style (ROI-style) modeling method, selecting only similar reference sites and allowing each site to build its own reference group.Three different Region-of-Influence selection schemes were applied to improve the macroinvertebrate predictive model in Maryland: the Assessment by Nearest Neighbour Analysis (ANNA), the Burn's Region of Influence (BROI), and the New Datum Region of Influence (NROI) predictive schemes. The prediction results from ANNA, BROI, and NROI were compared, and the reference selections of each predictive scheme were examined. The comparison showed no preference for the total number of reference sites used by either predictive scheme. The number of reference sites did not correlate to the quality of reference sites used and thus does not control the predictability. The ROI-style model in Maryland had better prediction performance than the RIVPACS-style models, and could improve the bioassessment of streams.     

Rank regression analysis of correlated water quality data from South East Queensland

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.     

Three-Dimensional Modelling of Concentration Fluctuations in Complicated Geometry

The strong fluctuating component in the measured concentration time series of a dispersing gaseous pollutant in the atmospheric boundary layer, and the hazard level associated to short-term concentration levels, demonstrate the necessity of calculating the magnitude of turbulent fluctuations of concentration using computational simulation models. Moreover the computation of concentration fluctuations in cases of dispersion in realistic situations, such as built-up areas or street canyons, is of special practical interest for hazard assessment purposes. In this paper, the formulation and evaluation of a model for concentration fluctuations, based on a transport equation, are presented. The model is applicable in cases of complex geometry. It is included in the framework of a computational code, developed for simulating the dispersion of buoyant pollutants over complex geometries. The experimental data used for the model evaluation concerned the dispersion of a passive gas in a street canyon between 4 identical rectangular buildings performed in a wind tunnel. The experimental concentration fluctuations data have been derived from measured high frequency concentrations. The concentration fluctuations model is evaluated by comparing the model's predictions with the observations in the form of scatter plots, quantile-quantile plots, contour plots and statistical indices as the fractional bias, the geometrical mean variance and the factor-of-two percentage. From the above comparisons it is concluded that the overall model performance in the present complex geometry case is satisfactory. The discrepancies between model predictions and observations are attributed to inaccuracies in prescribing the actual wind tunnel boundary conditions to the computational code.     

Application of various mathematical models to data from the uptake of methyl mercury in bluegill sunfish (Lepomis macrochirus)

Evaluated and compared are the results of various mathematical models to data from the uptake of methyl mercury in bluegill sunfish (Lepomis macrochirus). Data were obtained from the direct uptake of methyl mercury from water in bluegill at 9°C and at a CH₃HgCl concentration of 0.2 ppb. The models considered are: (1) linear uptake relationship; (2) first-order kinetics, one-compartment or single-exponential model; (3) combination of first-order kinetics and the linear uptake relationship, designated as slope-exponential model; (4) two-compartment or double-exponential model; (5) three-compartment model, including a storage compartment for the build up of contaminant, designated as storage model; (6) three-compartment model, allowing two routes of elimination, designated the “Y” model; (7) an empirical uptake relationship having the form of a rectangular hyperbola.A comparison of the nonlinear models showed that the empirical model had fewer convergence problems in obtaining parameter estimates and its parameter values had less variation. The best fit was made by the “Y” model, the empirical model gave one of the smaller values of the residual mean squares, and other nonlinear models had computational convergence difficulties. The lack of computational problems and the comparitively small residual mean squares resulted in the selection of and the preference for the empirical model for use in describing the individual and interactive effects of temperature and methyl mercury concentration on the direct uptake of methyl mercury from water by bluegill.     

Simulation of water quality in a flood detention area using models of different spatial discretization

Detention areas provide a means to lower peak discharges in rivers by temporarily storing excess water. In the case of extreme flood events, the storage effect reduces the risk of dike failures or extensive inundations for downstream reaches and near the site of abstraction. Due to the large amount of organic matter contained in the river water and the inundation of terrestrial vegetation in the detention area, a deterioration of water quality may occur. In particular, decay processes can cause a severe depletion of dissolved oxygen (DO) in the temporary water body. In this paper, we studied the potential of a water quality model to simulate the DO dynamics in a large but shallow detention area to be built at the Elbe River (Germany). Our focus was on examining the impact of spatial discretization on the model’s performance and usability. Therefore, we used a zero-dimensional (0D) and a two-dimensional (2D) modeling approach in parallel. The two approaches solely differ in their spatial discretization, while conversion processes, parameters, and boundary conditions were kept identical. The dynamics of DO simulated by the two models are similar in the initial flooding period but diverge when the system starts to drain. The deviation can be attributed to the different spatial discretization of the two models, leading to different estimates of flow velocities and water depths. Only the 2D model can account for the impact of spatial variability on the evolution of state variables. However, its application requires high efforts for pre- and post-processing and significantly longer computation times. The 2D model is, therefore, not suitable for investigating various flood scenarios or for analyzing the impact of parameter uncertainty. For practical applications, we recommend to firstly set up a fast-running model of reduced spatial discretization, e.g. a 0D model. Using this tool, the reliability of the simulation results should be checked by analyzing the parameter uncertainty of the water quality model. A particular focus may be on those parameters that are spatially variable and, therefore, believed to be better represented in a 2D approach. The benefit from the application of the more costly 2D model should be assessed, based on the analyses carried out with the 0D model. A 2D model appears to be preferable only if the simulated detention area has a complex topography, flow velocities are highly variable in space, and the parameters of the water quality model are well known.     

中国自来水行业市场化战略的经济学分析

我国自来水行业长期以来实行国家经营,由于缺乏竞争以及行业监管不足,致使供水不足、行业经营效率低下、成本较高,因此,采取市场化模式势在必行.对此,我国自来水行业从1992年开始实施以打破垄断、提高效率与改善服务质量为目标的市场化改革,并取得了一定的成效,但是还是存在许多不足.在介绍了我国自来水产业市场化模式的发展历程,并运用经济学的相关理论和实证方法,来分析中国自来水市场化模式.     

Towards carrying capacity assessment for aquaculture in the Bolinao Bay, Philippines: A numerical study of tidal circulation

The increase in intensive aquaculture production in the Bolinao Bay, Philippines reached the point of harmful influence to production stock. Up to the present, there has been no estimation of aquaculture carrying capacity which is based on quantification of processes responsible for (a) water quality inside the units, (b) impact to the seabed and (c) water quality in the whole Bolinao Bay. The numerical estimation of tidal circulation, which is the most dominant part of the hydrodynamical regime in the Bolinao Bay, represents an unavoidable step in the carrying capacity determination considering points (a), (b) and (c). The hydrodynamical model we apply is a free surface, 3D finite element tidal model, forced with sea elevation dynamics at three open boundaries. It incorporates an increase in bottom stress drag coefficients in the coral areas and advanced transport corrected advection scheme. The model simulations of water flow show good agreement with measured currents in the central part of the Bolinao Bay, southern and northeastern channel, while agreement in the areas in vicinity of northern channel is not as tight. In order to provide an insight into the water exchange in aquaculture units, to support local water quality models and seabed deposition models (points (a) and (b)), the area is mapped with neap tide mean, spring tide mean and 14-day mean current velocity contours. The highest 14-day mean velocities are attained in the southern channel (>17 cm s⁻¹), while the mean velocities characteristic for northern part (<6 cm s⁻¹) and shallow areas of coral reefs (<2 cm s⁻¹) are much lower. Area-mean difference between spring tide and 14-day mean velocities is estimated to be 18.32% (std=7.31%), while difference between neap tide and 14-day mean velocities is 17.62 % (std=11.19%). To support global basin-wide water quality models (point (c)), retention of water in the bay is estimated by Lagrangian and Eulerian calculation procedure of mean residence time field. Both calculations estimate the highest (no-wind) residence times (Lan: 25.4 days, Eul: 21.03 days) in the central northern part, but most of the area (Lan: 73.11%, Eul: 79.31%) is characterized by residence time values significantly lower than 15 days. The results are readily applicable for upcoming implementation in the models of local (aquaculture units, seabed) and basin-wide (Bolinao Bay) nutrient dynamics, primary and secondary production, organic matter decomposition and oxygen dynamics.     

Efficient Markov chain Monte Carlo sampling for hierarchical hidden Markov models

Traditional Markov chain Monte Carlo (MCMC) sampling of hidden Markov models (HMMs) involves latent states underlying an imperfect observation process, and generates posterior samples for top-level parameters concurrently with nuisance latent variables. When potentially many HMMs are embedded within a hierarchical model, this can result in prohibitively long MCMC runtimes. We study combinations of existing methods, which are shown to vastly improve computational efficiency for these hierarchical models while maintaining the modeling flexibility provided by embedded HMMs. The methods include discrete filtering of the HMM likelihood to remove latent states, reduced data representations, and a novel procedure for dynamic block sampling of posterior dimensions. The first two methods have been used in isolation in existing application-specific software, but are not generally available for incorporation in arbitrary model structures. Using the NIMBLE package for R, we develop and test combined computational approaches using three examples from ecological capture–recapture, although our methods are generally applicable to any embedded discrete HMMs. These combinations provide several orders of magnitude improvement in MCMC sampling efficiency, defined as the rate of generating effectively independent posterior samples. In addition to being computationally significant for this class of hierarchical models, this result underscores the potential for vast improvements to MCMC sampling efficiency which can result from combinations of known algorithms.     

Temporal dimension and water quality control in an emission trading scheme based on water environmental functional zone

Emission trading is one of the most effective alternatives to controlling water pollution. Water environmental functional zone (WEFZ) is used to determine the water quality standard and identify the zone boundary for each river or reach. In this study, a new emission trading scheme was addressed based on WEFZ, accounting for both the temporal dimension and water quality control. A temporal factor of emission trading was proposed based on variations in the environmental capacity within a year by dividing the year into three periods, including high, normal, and low periods of environmental capacity. During each period, emission trading was implemented exclusively. A water quality-control scheme was suggested based on the water quality requirement in the water functional zone, in which the water quality at the downstream boundary of the zone was required to meet the water standard following auto-purification in the stream. Two methods of calculating water quality control are addressed for point-source pollution and non-point-source pollution. The calculated temporal dimension and water quality control were located in Dongxi River of the Daning Watershed in the Three Gorges Watershed. The high period was during June, July, and August, the normal period was during April, May, September, and October, and the low period was during January, February, March, November, and December. The results from the water quality calculation demonstrated that the discharge of point-source and non-point-source pollutions led to an excess of common contaminants at the downstream boundary of WEFZ. The temporal and spatial factors above should be incorporated into the emission trading scheme based on WEFZ.     

Development of a rotorcraft dust-emission parameterization using a CFD model

Flights of rotorcraft over the desert floor can result in significant entrainment of particulate matter into the atmospheric boundary layer. Continuous or widespread operation can lead to local and regional impacts on visibility and air quality. To account for this pollutant source in air quality models, a parameterization scheme is needed that addresses the complex vertical distribution of dust ejected from the rotorcraft wake into the atmospheric surface layer. A method to parameterize the wind and turbulence fields and shear stress at the ground is proposed here utilizing computational fluid dynamics and a parameterized rotor model. Measurements taken from a full scale experiment of rotorcraft flight near the surface are compared to the simulation results in a qualitative manner. The simulation is shown to adequately predict the forward detachment length of the induced ground jet compared to the measured detachment lengths. However, the simulated ground vortex widths and vorticity deviate substantially from the measured values under a range of flight speeds. Results show that the method may be applicable for air quality modeling assuming slow airspeeds of the rotorcraft, with advance ratios of 0.005–0.02.     

Modelling transpiration and growth in salinity-stressed tomato under different climatic conditions

Models aiming to simulate growth under salinity stress and varied climatic conditions must rely on accurate methods for predicting transpiration and photosynthesis. Traditionally, models have described salinity stress as a decrease in water uptake caused by a low osmotic potential in the soil; however, many physiological studies suggest that reduced plant growth observed under saline conditions could be caused by increased respiration. Explicit calculation of photosynthesis and respiration enables both approaches to be tested and compared in a simulation model. We used an integrated ecosystems model (the CoupModel) to simulate photosynthesis and transpiration over a range of salinities. The model was calibrated and tested on two sets of data (two different seasons) on saline water, drip-irrigated tomato from lysimeter trials in the Arava Valley, Israel. Yields for the spring season were significantly lower than during the first autumn season even though transpiration was higher. As a result, water use efficiency differed by a factor of two between seasons. The model was successful in capturing this large variation, which was caused primarily by high levels of radiation and vapour pressure deficits during spring. For autumn the salinity stress approach in which water uptake was reduced performed well, whereas during spring the increased respiration approach correlated better with measurements. The concept of water use efficiency was found to be a useful tool for interpreting the accumulated effects of climatic and environmental conditions on particular agricultural systems. An attempt to simulate tomatoes grown in production beds indicated that the model set-up was also able to describe conventional cropping systems.     

Super-individuals a simple solution for modelling large populations on an individual basis

Modelling populations on an individual-by-individual basis has proven to be a fruitful approach. Many complex patterns that are observed on the population level have been shown to arise from simple interactions between individuals. However, a major problem with these models is that the typically large number of individuals needed requires impractically large computation times. The common solution, reduction of the number of individuals in the model, can lead to loss of variation, irregular dynamics, and large sensitivity to the value of random generator seeds. As a solution to these problems, we propose to add an extra variable feature to each model individual, namely the number of real individuals it actually represents. This approach allows zooming from a real individual-by-individual model to a cohort representation or ultimately an all-animals-are-equal view without changing the model formulation. Therefore, the super-individual concept offers easy possibilities to check whether the observed behaviour is an artifact of following a limited number of individuals or of lumping individuals, and also to verify whether individual variability is indeed an essential ingredient for the observed behaviour. In addition the approach offers arbitrarily large computational advantages. As an example the super-individual approach is applied to a generic model of the dynamics of a size-distributed consumer cohort as well as to an elaborate applied simulation model of the recruitment of striped bass.     

水资源供需平衡动态模拟分析方法

本文根据多水源供水系统的特点，从优化利用水资源，改善与保护水环境质量出发，建立限水资源供需平衡的动态分析模型，该模型较为客观地反映了需水量与可供水量之间的时空矛盾，可为供水系统的运行管理提供较为精确的决策依据。模型已在台山市区环境规划中得到了应用，效果良好。