Assessment of efficient sampling designs for urban stormwater monitoring

Monitoring programs for urban runoff have not been assessed for effectiveness or efficiency in estimating mass emissions. In order to determine appropriate designs for stormwater, total suspended solids (TSS) and flow information from the Santa Ana River was collected nearly every 15 min for every storm of the 1998 water year. All samples were used to calculate the "true load" and then three within-storm sampling designs (flow-interval, time-interval, and simple random) and five among-storm sampling designs (stratified by size, stratified by season, simple random, simple random of medium and large storms, and the first m storms of the season) were simulated. Using these designs, we evaluated three estimators for storm mass emissions (mean, volume-weighted, and ratio) and three estimators for annual mass emissions (median, ratio, and regular). Designs and estimators were evaluated with respect to accuracy and precision. The optimal strategy was used to determine the appropriate number of storms to sample annually based upon confidence interval width for estimates of annual mass emissions and concentration. The amount of detectable trend in mass emissions and concentration was determined for sample sizes 3 and 7. Single storms were most efficiently characterized (small bias and standard error) by taking 12 samples following a flow-interval schedule and using a volume-weighted estimator of mass emissions. The ratio estimator, when coupled with the simple random sample of medium and large storms within a season, most accurately estimated concentration and mass emissions; and had low bias over all of the designs. Sampling seven storms is the most efficient method for attaining small confidence interval width for annual concentration. Sampling three storms per year allows a 20% trend to be detected in mass emissions or concentration over five years. These results are decreased by 10% by sampling seven storms per year.     

Sampling frequency and accuracy of SPM flux estimates in two contrasted drainage basins

The present paper is based on discharges and suspended particulate matter concentrations from a 9-years high-resolution database for the Garonne River (large plain river) covering contrasted hydrologic years, and a 12-months high frequency sampling for the Nivelle River (small mountainous river). Annual SPM fluxes in the Garonne River range from 0.6 x 10(6) t year(-1) (1997) to 3.9 x 10(6) t year(-1) (1996). In contrast, the Nivelle River transported 11 x 10(3) t year(-1) from December 1995 to December 1996. From the long-term observation of the Garonne River an empirical relation between SPM* (discharge-weighted mean annual SPM concentrations) and annual discharge was established. This relation allows estimating annual SPM fluxes for the Garonne River with less than 30% deviation from reference values for the whole range of mean annual discharge observed during the past decade. Specific (=area-normalized) annual SPM fluxes (YSPM) range from 11 to 74 t km(-2) year(-1) for the Garonne River. Comparison of these results with YSPM of the Nivelle River (69 t km(-2) year(-1) in 1996) suggests that interannual hydrological variations may have a greater impact on fluvial SPM transport than basin-specific parameters. By extracting individual SPM concentrations and corresponding discharge values from the database, different sampling frequencies were simulated and resulting SPM fluxes were then compared to reference fluxes derived from the complete database. If a deviation of simulated flux estimates from reference fluxes lower than +/-20% is accepted, the Garonne River (large plain river) must be sampled at least every 3 days (10 samples per month) and the Nivelle River every 7 h (approx. 100 samples per month). For the Garonne River this minimum sampling frequency is valid for all contrasted hydrologic years of the observation period. Below these minimum sampling frequencies, annual SPM flux estimates may greatly differ from reference fluxes (up to 200%) and there is high probability of systematic underestimation. Consequently, annual SPM flux estimates for the Garonne River derived from the empirical relation (SPM*-annual discharge) are likely to be more satisfactory (errors <30%) than estimates based on sampling frequencies lower than the minimum frequency. These findings underline the need of adapted sampling strategies for erosion assessment, reliable chemical (e.g. nutrients and pollutants) mass balances and characterisation of fluvial transport mechanisms in the world's contrasted watersheds.     

Statistical models of river loadings of nitrogen and phosphorus in the Lough Neagh system

To establish nutrient budgets of Lough Neagh in N. Ireland, and provide strategies for the reduction of nitrogen and phosphorus it became necessary to obtain estimates of their inputs to the lake. On the six major rivers entering the lake continuous flow metering was available but chemical concentrations were only available every 8 or 15 days. To associate river chemical concentrations and loadings with flows for these observed dates, and hence predict from their relation the loads at the unobserved dates a computer program using eight possible statistical relations was used. Those methods examined included various regressions with adjustments, higher order (polynomial) fits, logarithmic and other transforms, and different rising and falling flow relations. Results produced by the various methods with discussion of their relative merits are presented. Reasons are given for the final selection of a simple log load on log flow relation for rivers derived from terrestrial catchments.     

基于Bayes理论的Logistic增长曲线模型参数估计方法研究

Logistic增长曲线模型是一种广泛应用的近＂S＂型的增长曲线模型,其3个参数不能用常规的最小二乘法来求解。本文将该模型参数视为随机变量,根据贝叶斯理论结合参数的先验信息和观测数据推断参数的后验分布,然后构造基于Gibbs抽样的MCMC数值计算过程并进行工程实例分析。数据分析结果表明,与其它估计方法相比,本文所提出的Bayes方法得到的是参数的分布且估计的结果优于其它方法,在给出参数估计值的同时还给出参数估计值的置信区间,使得工程决策可以考虑预测值的可靠性,在实际工程应用中具有一定的参考价值。     

Water quality surveys: A statistical method based on determinism, quantiles and the binomial distribution

A statistical method for surveying water quality and analysing the results in terms of quantiles is described. The value of a water quality variable in a grab-sample is taken as a deterministic function of the temporal and spatial coordinates of the sampling point. Quantiles can then be defined for any specified region in time and space as unique, fixed values, and randomly located grab-samples may be used to estimate them for the purposes of describing or regulating water quality. Robust statistical inferences are possible using the binomial distribution. Properties of the quantiles, confidence limits, comparisons with fixed values or between regions, assessment of trends, simultaneous inferences and estimation of sample sizes are discussed. Two examples of water quality surveys, one of Port Phillip Bay, the other of the Maribyrnong River, Victoria, are used to illustrate the theory, paying particular attention to practical problems which arose. The proposed method is compared with others based on stochastic models, and is claimed to be simpler and more reliable.     

Multi-scale strategies for the monitoring of freshwater cyanobacteria: reducing the sources of uncertainty

Cyanobacterial blooms are a frequent phenomenon in eutrophic freshwaters worldwide and are considered potential hazards to ecosystems and human health. Monitoring strategies based on conventional sampling often fail to cover the marked spatial and temporal variations in cyanobacterial distribution and fluctuating toxin concentrations inherent to cyanobacterial blooms. To deal with these problems, we employed a multi-scale approach for the study of a massive Microcystis bloom in Tajo River (Spain) utilizing 1) remote sensing techniques, 2) conventional water sampling and 3) analysis of chemotypical subpopulations. Tajo River at the study area is influenced by high temperatures waters diverted upstream from a nuclear power plant, the presence of a dam downstream and a high nutrient load, which provide optimal conditions for massive cyanobacterial proliferation. MERIS imagery revealed high Chl-a concentrations that rarely fell below 20 μg L⁻¹ and moderate spatiotemporal variations throughout the study period (March-November 2009). Although the phytoplanktonic community was generally dominated by Microcystis, sampling points highly differed in cyanobacterial abundance and community composition. Microcystin (MC) concentrations were highly heterogeneous, varying up to 3 orders of magnitude among sampling points, exceeding in some cases WHO guideline values for drinking and also for recreational waters. The analysis of single colonies by MALDI-TOF MS revealed differences in the proportion of MC-producing colonies among points. The proportion of toxic colonies showed a highly significant linear correlation with total MC: biovolume ratio (r² = 0.9; p < 0.001), evidencing that the variability in toxin concentrations can be efficiently addressed by simple analysis of subpopulations. We propose implementing a multi-scale monitoring strategy that allows covering the spatiotemporal heterogeneities in both cyanobacterial distribution (remote sensing) and MC concentrations (subpopulation analysis) and thereby reduce the main sources of uncertainty in the assessment of the risks associated to bloom events.     

Feedback simulation of duct design for alkali exhaust system in a semiconductor factory

Duct design for an exhaust system must not only considers the demand of volume flow rate, but also takes into consideration a number of issues including system pressure balance, velocity constraint, space limitation and energy conservation. Conventional duct design methods either fail to achieve pressure equilibrium or offer poor control of flow velocity or duct diameter. A new design method that comprises two major calculation procedures: system sizing and rating is proposed. Duct system sizing problem is solved by the initial design from the conventional design methods. Feedback simulation provides the rating procedure for system actual operating process. An example is presented in this study to understand the characteristics of the proposed method. It demonstrates that the new duct design method contains a simple computation procedure and considers the pressure equilibrium under certain limits on space or flow velocity. It also provides the energy conservation strategies for the actual operating process during the design stage.     

Solution of a class of load combination problems by directional simulation

The load combination problem of Ferry Borges-Castanheta may be effectively handled by the Rackwitz-Fiessler algorithm provided the load pulses have absolutely continuous distribution function. However, realistic modelling of extraordinary actions requires the load pulse distributions to have a concentrated probability at zero. In principle this discontinuity may be handled by conditioning such that the combination problem reduces to several problems with absolutely continuous distribution functions. With just some few extraordinary actions taking part in the combination problem this method of conditioning becomes quite cumbersome and even impracticable.If it is assumed that the single load pulses are clipped normal random variables, i.e. of the form max{0, X} where X is normal, then a combination of the RF-algorithm and directional Monte Carlo simulation technique turns out to be useful. At any given argument the directional simulation method gives not only a confidence interval for the value of the distribution function but also a confidence interval for the value of the density function of a random variable defined as a sum of clipped dependent or independent normal variables. This is just what is needed in the RF-algorithm in order to apply the principle of normal tail approximation on the distribution of the sum.     

The influence of sampling interval on the accuracy of trail impact assessment

Trail impact assessment and monitoring (IA&M) programs have been growing in importance and application in recreation resource management at protected areas. This paper addresses a fundamental issue in designing trail IA&M surveys: the choice of sampling interval. Specifically, the influence of sampling interval on the accuracy of estimates for selected trail impact problems was examined using a resampling simulation method. A complete census of four impact-types on 70 backcountry trails in the Great Smoky Mountains National Park was utilized as the base dataset for the analyses. The census data were resampled at increasing intervals to create a series of simulated point datasets. At each sampling interval level, the accuracy of simulated datasets was evaluated by comparing the estimates of frequency of occurrence and lineal extent for each impact-type with actual census values. Simulation results indicate that increasing sampling intervals are associated with an overall increase in accuracy loss for all four impact-types. The direction of accuracy loss for lineal extent estimates is mixed, while frequency of occurrence estimates are consistently and substantially lower than the actual values. Responses of accuracy loss to increasing sampling intervals vary across impact-types on extent estimates, but are consistent on the frequency estimates. These findings suggest that systematic point sampling can be an appropriate method for estimating lineal extent but not the frequency of trail impacts. Sample intervals of less than 100 m appear to yield an excellent level of estimate accuracy for the four impact-types evaluated. The census-based trail survey and the resampling simulation method developed in this study can be a valuable first step in establishing long-term trail IA&M programs, in which an optimal sampling interval range with acceptable accuracy is determined before investing efforts in data collection.     

Bayesian model for flow-class dependent distributions of fecal-indicator bacterial concentration in surface waters

A Bayesian statistical water quality model is demonstrated to predict fecal-indicator bacterial concentrations for waterbodies without sufficient monitoring data for data-intensive modeling techniques. Using a truncated bivariate normal likelihood function and the readily available observations of flow and bacterial concentration, the Bayesian approach propagates the uncertainty in the model parameterization to the final predictions of in-stream bacterial concentration. The proposed model captures the variation in the magnitude of bacterial loading between dry and wet conditions by estimating separate sets of model parameters for different flow conditions, but also has the capability to pool the data among flow conditions. The model can be used in two ways: first, the model specifies the percent of time that the recreational season in-stream concentration is not in compliance with the relevant water quality standard, and second, the model estimates the necessary bacterial load reduction for multiple flow conditions to meet the relevant water quality standard. Using an eleven year monitoring record for a site sampled at a monthly frequency on the Youghiogheny River in southwestern Pennsylvania, USA, the model parameters are updated and posterior predictions are generated for each 2-year increment. After six years of sampling, the predicted percent of time that the recreational season in-stream bacterial concentration is not in compliance with the relevant water quality is 82% with 95% CI(80,85), and the bacterial load reductions required to meet the standard are 14.7 CI(14.6,14.8), 14.5 CI(14.3, 14.6), and 14.0 CI(13.9, 14.2) log₁₀(cfu/day) for the high, normal, and dry flow conditions, respectively. The change in estimated load reduction and percent exceedance resulting from additional monitoring for this site becomes small after six years of sampling, indicating that a decision does not need to be postponed for additional monitoring.     

小样本岩土参数的Bootstrap估计及边坡稳定分析

 针对岩土参数小样本下t分布法区间估计较宽将导致工程设计偏于保守的问题,根据描述土体固有变异性的c,?总体开展小样本随机取样勘察模拟,运用Bootstrap法进行数据重构得到区间估计和点估计结果,对比与t分布法所得参数估计的差异。基于充足次数重复抽样构建的参数估计空间,分析与之映射的边坡稳定安全系数离散特征。研究表明：对应于同一置信水平,能充分利用小样本经验分布信息的Bootstrap法可有效收窄c,?均值置信区间,保证率下限值较传统t分布法结果更接近真值;虽然2种方法得到点估计结果的均值和方差相同,即对应的边坡稳定可靠指标相等,但采用Bootstrap法保证率下限值计算的边坡稳定安全系数均值相对较大,离散性更小,且这种改善效果随参数变异水平上升愈加明显;在保证相同可靠度条件下,Bootstrap法能更合理地对小样本统计不确定性导致的边坡安全风险进行补偿。     

The assimilative capacity of Qiantang River watershed,China

The Qiantang River, located in Zhejiang Province, China, is a major water supplier to a highly populated region for multiple uses. With economic development, the received pollutants exceeded its assimilative capacity, leading to algal blooms or fish kills. This study was an up‐to‐date evaluation of the assimilative capacity of the Qiantang River, investigating the influence of stream flow. A confidence of 75 and 90% of instream flows were selected as the design flows, while the traditional one‐dimensional point discharge model and QUAL2K model were used to analyse biochemical oxygen demand (BOD) assimilative capacity. The results showed that the assimilative capacity of 75% confidence instream flow was larger than that of 90% confidence. The assimilative capacity based on QUAL2K model considered almost all rates of BOD gain and loss, which were larger than that of one‐dimensional point discharge model. The total amount of BOD discharged into Qiantang River was 17 1283 t·a^?1 in 2004. Under 75 and 90% confidence river flow conditions, the calculated total BOD reduction percentage of the whole river was 38.2 and 55.9%, respectively. Furthermore, the results were used as criteria for developing a BOD total maximum daily load (TMDL) in order to achieve the sustainable use of water resources derived from Qiantang River watershed.     

燃气日负荷影响因素的相关分析和偏相关分析

相关分析和偏相关分析是研究两个或两个以上变量之间密切程度的两种常用的统计方法。论述了相关系数和偏相关系数的计算方法。通过计算某城市燃气日负荷与其影响因素的相关系数和偏相关系数,分析了各影响因素对燃气日负荷的影响程度,指出了在进行能源消费影响因素的相关分析和偏相关分析时应注意的问题。     

A comparison of discrete and intensive sampling for measuring the loads of nitrogen and phosphorus in the river main, County Antrim

The River Main, County Antrim, was intensively monitored during November 1974 to May 1975 to obtain accurate measurements of the loads of nitrogen and phosphorus to compare with loads predicted by a statistical model from discrete sampling and continuous flow data. During the survey period 2-hourly samples were collected on 102 days. Flow data were available from continuous recording of river level. Depending on the prevailing flow conditions 2-hourly or composite 8-hourly samples were analysed for soluble reactive P, soluble unreactive P, total soluble P, particulate P, total P, nitrate N, Kjeldahl N and total N. For the discrete sampling programme grab samples were collected at 8-day intervals and analysed for soluble reactive P, total P and nitrate N.River flow data showed the “flashy” nature of the discharge and flow variation by two orders of magnitude. During intensive monitoring particulate P concentration varied by two orders of magnitude while all other fractions varied by about one order of magnitude. Flow was therefore more important in determining loads for all fractions except particulate P. The concentration of all fractions except soluble unreactive P were significantly related to flow. Loads and flows were generally best related by log load-log flow equations. The slopes of these equations indicated that soluble reactive P and nitrate N sources were diluted by low concentration water at high flows whereas particulate P sources increased at high flows due to erosion and surface run-off.Using log load-log flow equations developed from the discrete 8-day sampling data, loads were predicted and compared with loads for the same days as were intensively sampled. The predictive method based on discrete sampling overestimated soluble reactive P and nitrate N loads by 12 and 18% respectively but underestimated particulate P load by 43%. The error in predicted loads was due to discrete sampling frequencies being biased towards low flow conditions which prevail for the greatest proportion of the time. Since soluble reactive P and nitrate N concentrations decreased with increasing flow, predicted loads were therefore too high. The converse was true for particulate P whose concentration increased markedly with increased flow.Instead of designing a sampling programme based on a rigid time period between samples, it should be possible using river flow history for the months of the year to select sampling frequencies which would more closely approximate to flow-proportional sampling. For example, fixed-period 8-day sampling of the major rivers entering Lough Neagh might be replaced by monthly sampling in June, July and August, fortnightly sampling in April, May and September, and sampling every 5 days for the other 6 months.     

基于监测数据桥梁结构状态评估实用方法研究

监测系统测得的信号经处理后,以各指标的变化量为基准,提出一种围绕指标变化量这一新型评判参数的状态评估理论。从各指标变化量的近似统计分布规律着手,依据置信度和置信区间的概念,提出一种新的状态等级划分方法。由于监测数据与状态等级划分的标准均为区间数,采用区间可拓评价理论建立桥梁结构状态评估模型。引入集值统计和重心决策理论将权重分为主观权重和客观权重来分别计算。最后,以菜园坝长江大桥主桥作为工程实例,利用理论及相应监测数据进行评估分析,结果表明菜园坝大桥整体运营状态良好,评定结果与实际情况吻合较好,故可认为此种评定理论较为合理,具有较好的工程实用性。     

Analytical aspects of the CEEM soil project

In the past, exercises aiming at an assessment of data uncertainty in environmental analysis were usually restricted to the analysis step, while sampling and pre-analytical sample treatment was largely ignored. Collaborative studies on the quantification of sampling errors require, besides a suitable and well characterized test site, the availability of a reference laboratory for the analysis of all of the samples taken in the context of the study by all participants and also test methods which do not contribute large and variable uncertainties due to long and complex analytical methodologies. Here we summarize the major analytical aspects of a European project on the identification and quantification of sampling influences on the determination of lead, cadmium, copper and zinc in soil. The participant group included the leading soil analysis laboratories in Europe; the test site at Dornach (CH) was well suited for the purpose and showed high metal gradients and differentiated land use. The analytical methods (wavelength-dispersive X-ray fluorescence spectrometry and solid-state Zeeman AAS) used in the study showed stable performance characteristics within the confidence interval of the certified reference materials used for the measurement quality control over the entire project period. Additionally, double-blind tests on split samples showed agreement of data in very narrow limits thus demonstrating the reliability of the reference database.     

Estimation of heat-transfer characteristics on the hot surface of glass pane with down-flowing water film

A hybrid inverse scheme of the Laplace transform and finite-difference methods in conjunction with a sequential-in-time procedure, least-squares method and experimental temperature data is applied to solve a 2D transient inverse heat conduction problem in order to estimate the unknown transient total heat flux and overall heat-transfer coefficient on the hot surface of the glass pane with the down-flowing water film exposed to a fire environment. It can be difficult to estimate this overall heat-transfer coefficient because it mainly involves the convection and radiation heat-transfer coefficients and that due to the mass transfer. The functional form of the total heat flux is unknown a priori and is assumed to vary with time and space. Thus, a series of connected cubic polynomial function in space and a linear function in time can be introduced to approximate this unknown surface heat flux during a specific time interval before performing the inverse calculation. Later, the unknown surface heat flux, surface temperature and overall heat-transfer coefficient at a specific time can be estimated from the knowledge of experimental measured temperature data and the given heat-transfer coefficient on the cold surface of the glass pane obtained from the correlation between the local Nusselt number and Rayleigh number. The results show that the effect of the down-flowing water film flow rate on the present estimates cannot be negligible. The overall heat-transfer coefficient on the downstream region of the glass pane can be markedly higher than that on the upstream region.     

Eutrophication problems in Emilia Romagna,Italy: Monitoring the nutrient load discharged to the littoral zone of the Adriatic Sea

The deteriorating eutrophic state of the northern Adriatic Sea led to the commissioning of a study between 1977 and 1979 to identify the sources and forms of the nutrients phosphorus and nitrogen discharged from the basin of the river Savio. The study investigated the reduction in the phosphorus load in sewage per head of population caused by a reduction in the phosphorus content of detergents used in the basin and by the use of septic tanks. The flow and nutrient loads carried by the river were monitored during dry and wet weather to establish annual nutrient loads carried to the sea. An extensive sampling programme was carried out to quantify the principal sources of nutrients of which the most important were pig farming, Man and chemical fertilisers. An attempt was made to balance the nutrient loads discharged from the basin.     

长江流域居住建筑不同供暖模式下的负荷特性分析

通过分析长江流域冬季供暖特点,采用建筑环境动态负荷分析软件DeST-h对该地区典型城市重庆居住建筑在连续供暖和间歇供暖2种供暖模式下的冬季逐时热负荷进行了计算,分析了2种供暖模式下的负荷分布特性。连续供暖的热负荷总体水平较低,波动较小,且与室外空气温度呈负相关,而间歇供暖的热负荷波动较大,具体表现为开始阶段热负荷较大,而后迅速降低并稳定。据此进一步分析了该负荷特性对长江流域居住建筑的空气源热泵机组选型及运行调节的影响。分析得出:按照夏季供冷工况进行设备选型,机组名义工况下的制热量能满足连续供暖的最大热负荷需求和间歇供暖稳定阶段的热负荷需求;连续供暖条件下部分负荷率主要分布在25%~75%之间,机组的运行调节可采用定容量压缩机台数控制方式;间歇供暖条件下部分负荷率主要分布在50%~100%之间,建议采用变容量调节方式。     

Efficient calculation of the radiation heat flux surrounding a jet fire

The major objective of the paper is to address the main weakness of the reverse Monte-Carlo method applied to jet fire simulation; its slow convergence rate. This is done by replacing the use of a pseudo-random number generator for calculating ray orientations with a ray direction specification based on Sobol sequences. Sobol sequences produce sequences of points on the unit hemisphere that are not independent of each other in that new points in the sequence avoid previous points generated. This has the property that a more uniform pattern of rays on the unit hemisphere is produced, giving a ray convergence rate for the incident heat flux that is asymptotically equivalent to O(N_Ray⁻¹). The use of Sobol sequences to accelerate convergence of the Monte-Carlo method has been applied in mathematical physics and financial modelling but the results presented here are the first study of quasi-Monte-Carlo methods applied to the incident heat flux integral. The use of Sobol sequences to generate ray directions means that the Central Limit Theorem no longer holds. In its place, it has been demonstrated that it is possible to construct a Gaussian variable from the incident intensity distributions calculated using Sobol sequences. This means it is possible to calculate confidence limits for a prediction of incident heat flux and the confidence limits contract with ray number at a rate of O(N_Ray⁻¹ ln(N_Ray)).