Formulation,calibration, and validation of hybrid and coupled models for the design of upflow anaerobic filters in multiple separated stages for organic matter removal from sanitary landfill leachates

In this paper, the formulation, calibration, and validation of hybrid and coupled models for the design of upflow anaerobic filters in multiple separated stages were developed for organic matter removal from sanitary landfill leachates. Three novelties were presented, the type of reactor, design models, and kinetic coefficients. The upflow anaerobic filters were separated into two and three stages identified as UAF-2SS (DI-FAFS, in Spanish) and UAF-3SS (TRI-FAFS, in Spanish). The formulation, calibration, and validation of mathematical structures of hybrid models and five coupled models are proposed for each reactor. The hybrid models are based on the law of mass conservation, with the organic matter transformation component within the UAF-2SS and UAF-3SS reactors, being estimated from empirical equations that have been tested in aerobic culture reactors, adapted to the experimental factors, including among these, those under a non-stationary—advective conditions based on Velz's Law, Phelps's Law, and Monod's equation. The coupled models combine the components of the molecular transport by biosorption and molecular diffusion processes, with adaptations of the Stack's equation and Fick's Law, as well as transformation of organic substrates by biomass, whose kinetic coefficients contribute to explain the fraction, in which, the processes of mobility and biochemical transformation of the organic matter are occurring in the biomass within the bioreactors.     

Mathematical modelling and experimental validation of solar drying of mushrooms

This article presents two mathematical models for drying mushrooms considering the shrinkage effect. Both the models consider the physical changes of mushrooms during drying using the diffusion equation. A convective term is presented in the first model while, in the second model, the effective diffusion co-efficient is employed. Although the diffusion co-efficient is mainly dependent on the water content of the mushrooms, both models are suitable for analyzing the drying process. Moreover, in this study it has been demonstrated that both models are equivalent. The Genetic Algorithmic process was used to estimate the parameter values in different conditions. The information regarding the moisture content and the thickness evaluation taken from the models shows the best fit with the experimental data. The mathematical models developed to simulate the drying curve of mushroom have been evaluated and compared.     

ANNUAL EVAPOTRANSPIRATION OF NATWE VEGETATION IN A MEDITERRANEAN-TYPE CLIMATE1

ABSTRACT: Annual evapotranspiration from a watershed (ETws) is a function of annual precipitation (P) and fraction of the watershed covered by shrubs and trees (C). Other characteristics are not significant in explaining variance of ETws. A rational equation, ETws = (1-C) ETg + CETst, wherein ETg is the ET of herbaceous cover and ETst is the ET of shrubs and trees, is proposed. The equation has been calibrated for ET and P in inches for the watershed of Lake Cachuma on the Santa Ynez River. This equation, ETmax = 2.14(1-C)P^0.647+ 4.53 C^1.76 P^0.68, is recommended for estimating maximum annual ET demand for conceptual models. Where C is not known, the upper limit of ET = f (P) may be approximated by use of 0.65 for C. The equation has been derived for large unmanaged watersheds. Applicability for evaluation of contemporary multiple purpose vegetation management should be determined by studies of the hydrology of small openings in shrub and tree cover.     

EVAPOTRANSPIRATION MEASUREMENTS AND MODELING FOR THREE WETLAND SYSTEMS IN SOUTH FLORIDA1

ABSTRACT: At the Everglades Nutrient Removal project in south Florida, three lysimeters were installed to measure daily evapotranspiration (ET) rates from cattails (Typha domingensis), mixed marsh vegetation, and an open water/algae system. The cattail lysimeter began operation in February 1993. The mixed marsh vegetation lysimeter began operation in January 1994, and the open water lysimeter with occasional algae cover began operation in December 1993. The mean measured ET rate was 3.6 mm, 3.5 mm, and 3.7 mm per day for the cattail, mixed marsh vegetation, and open water/algae system, respectively. High resolution weather data were continuously measured at the site. Six models were applied to estimate daily ET rates of the three systems. The Penman-Monteith equation best estimated ET of cattail and mixed marsh vegetation, and the Penman Combination equation was most suitable for the open water/algae system. Empirical equations based on solar radiation and maximum temperature produced estimates of daily ET from the three systems that are comparable to models that require many more parameters. In cases where limited data is available, the calibrated simple models can be used to estimate ET from wetlands in south Florida.     

Personality, individual differences, and demographic antecedents of self-reported household waste management behaviours

The present study sought to extend recent conceptual frameworks of waste management behaviours by examining personality, individual differences, and socio-demographic antecedents of self-reported waste recycling, reuse, and reduction behaviours. A total of 203 participants from a British community sample completed a questionnaire consisting of measures of their self-reported waste management behaviour, Machiavellianism, political cynicism, the Big Five personality traits, and socio-demographics. The results of structural equation modelling showed that individuals who were less Machiavellian, less politically cynical, older, and more conscientious were more likely to report positive waste management behaviours. In combination, these predictors explained 22.0% of the variance in waste management behaviours. Thus, these variables may improve the predictive validity of existing conceptual models of waste management behaviours. The results are discussed in relation to those models.     

KALMAN FILTER ESTIMATION AND PREDICTION OF DAILY STREAM FLOWS: I. REVIEW,ALGORITHM, AND SIMULATION EXPERIMENTS1

An important class of models, frequently used in hydrology for the forecasting of hydrologic variables one or more time periods ahead, or for the generation of synthetic data sequences, is the class of autoregressive(AR) models. As the AR models belong to the family of linear stochastic difference equations, they have both a deterministic and a stochastic component. The stochastic component is often assumed to have a Gaussian distribution. It is well known that hydrologic observations (e.g., stream flows) are heavily affected by noise. To account explicitly for the observation noise, the linear stochastic difference equation is expressed in state variable form and an observation model is introduced. The discrete Kalman filter algorithm can then be used to obtain estimates of the state variable vector. Typically, in hydrologic systems, model parameters, system noise statistics and measurement noise statistics are unknown, and have to be estimated. In this study an adaptive algorithm is discussed which estimates these quantities simultaneously with the state variables. The performance of the algorithm is evaluated by using simulated data.     

吉东山区总辐射资源的地理空间分布特征

本文以地理纬度、经度和海拔高度为因子,采用二次趋势面函数,建立了描述吉林省东部长白山区年总辐射、5～9月总辐射和日平气温稳定通过10℃期间的总辐射资源的地理空间分布特征的数学模式。采用地理细网格场的分析方法,揭示了该山区总辐射资源的空间分布情况。     

NATURAL EROSION RATES AND THEIR PREDICTION IN THE IDAHO BATHOLITH1

ABSTRACT: Natural rates of surface erosion on forested granitic soils in central Idaho were measured in 40 m² bordered erosion plots over a period of four years. In addition, we measured a variety of site variables, soil properties, and summer rainstorm intensities in order to relate erosion rates to site attributes. Median winter erosion rates are approximately twice summer period rates, however mean summer rates are nearly twice winter rates because of infrequent high erosion caused by summer rainstorms. Regression equation models and regression tree models were constructed to explore relationships between erosion and factors that control erosion rates. Ground cover is the single factor that has the greatest influence on erosion rates during both summer and winter periods. Rainstorm intensity (erosivity index) strongly influences summer erosion rates, even on soils with high ground cover percentages. Few summer storms were of sufficient duration and intensity to cause rilling on the plots, and the data set was too small to elucidate differences in rill vs. interrill erosion. The regression tree models are relatively less biased than the regression equations developed, and explained 70 and 84 percent of the variability in summer and winter erosion rates, respectively.     

Modelling hydroenvironmental and health risk assessment parameters along the South Wales Coast

This paper highlights the increasing concerns relating to hydroenvironmetal issues and cites recent examples of the challenges now being regularly faced by hydroenvironmetal scientists and engineers. The limitations and restrictions of both physical (or laboratory) and numerical (or computer based) hydraulic models used in the planning and management of aquatic basins are discussed. General details are given of numerical models used for flow and water quality concentration predictions in estuarine waters, with particular application to the challenges occurring along the South Wales coast. A highly accurate and non-diffusive finite difference scheme that solves the transport equation for predicting water quality indicators and suspended sediment concentration distributions is also discussed. In particular, details are outlined of the extension of the water quality indicators of faecal coliforms, as required to comply with the EU Bathing Water Directive, to predict health risk assessment, in the form of predicting the risk of gastroenteritis. Three example research projects along the South Wales coast are described; the projects involve the application of two-dimensional and three-dimensional hydroenvironmetal models to predict flow patterns and water quality indicator organism distributions in the coastal receiving waters. These studies include: (i) a curvilinear finite difference approach to modelling flows in the Bristol Channel, (ii) coastal health risk predictions in Swansea Bay using combined water quality and epidemiological models, and (iii) combined sewer overflow discharges into Cardiff Bay.     

土地处理过程中主要污染物对地下水污染的数学模拟方法讨论

本文通过对地下水水质数学模拟方法讨论,介绍了主要污染物在土地处理系统中的迁移转化过程概况,根据不同类型污染物特性,边界条件及污水排放形式,建立起相应的模型解析方程,并确定有关参数值,试图从量上来预测污染物浓度在地下水流中的时空变化规律。     

OPEN CHANNEL INTERPOLATION OF CROSS SECTIONAL PROPERTIES1

ABSTRACT: This paper confirms the use of interpolated data to refine water surface profiles. Sources of error within these computations are due to truncation error, inaccuracies in geometric data, and improper modeling. Confirmation includes the development of an equation that models the effect of data measurement error on the computed water surface profile. A review of interpolation procedures includes a proposed method based upon geometric properties.     

An assessment of time series methods in metal price forecasting

The international price for metals is pivotal in the profitability equation for mining companies. If producer prices rise, assuming production levels and costs remain the same, profits are expected to increase. Accordingly, producers welcome any means by which price instability and unpredictability can be reduced. The paper analyses the ability of two user-friendly time series forecasting techniques to predict future lead and zinc prices. The conclusion is that price forecasting is difficult. It should, however, be acknowledged that whilst neither of the two models are definitive, they are useful for the mining company vis-à-vis its planning process. In particular, the results from the analysis in this paper suggest that ARIMA modelling provides marginally better forecast results than lagged forward price modelling. The methodologies employed in this paper have a broad based application to base metal forecasting by mining companies in general, that is, the applications are transferable.     

A SIMPLIFIED STREAM MODEL OF ACID MINE DRAINAGE EFFECTS1

ABSTRACT: Three methods of modeling acid mine drainage effects are discussed. A net alkalinity routing model is the simplest of these, but can be potentially misleading. It typically overestimates the effect of acid sources on pH by neglecting carbon dioxide transfer to the atmosphere. Inclusion of a simple carbon dioxide transfer function can substantially reduce errors in stream quality prediction. A plug flow reaeration equation, coupled with mass balancing at mixing points in a stream network provides modeling results comparable to those of more complex computerized solutions of chemical equilibrium equations. None of the models accounts for carbonate dissolution or oxidation and hydrolysis of ferrous iron.     

Limitations of model-fitting methods for kinetic analysis: Polystyrene thermal degradation

In this paper, some clarifications regarding the use of model-fitting methods of kinetic analysis are provided in response to the lack of plot linearity and dispersion in the activation energy values for the thermal degradation of polystyrene found in the literature and some results proposing an nth order model as the most suitable one. In the present work, two model-fitting methods based on the differential and integral forms of the general kinetic equation are evaluated using both simulated and experimental data, showing that the differential method is recommended due to its higher discrimination power. Moreover, the intrinsic limitations of model-fitting methods are highlighted: the use of a limited set of kinetic models to fit experimental data and the ideal nature of such models. Finally, it is concluded that a chain scission model is more appropriate than first order.     

Estimating turf pesticide volatilization from simple evapotranspiration models

A previously developed model by Haith et al. (2002) related pesticide volatilization from turf to evapotranspiration (ET) by scaling factors determined from vapor pressures and heats of vaporization. Although the model provided volatilization estimates that compared well with field measurements, it relied on the Penman ET equation, requiring hourly temperature, wind speed, and solar radiation data, none of which are routinely available at field sites. The current study determined that the volatilization model works equally well with a simpler ET equation requiring only daily temperatures. Three daily temperature-based ET models were evaluated as vehicles for estimating pesticide volatilization from turf: Hamon, Hargreaves-Samani, and a modified Priestley-Taylor. When compared with field volatilization measurements for eight pesticides, volatilization estimates produced from the Hargreaves-Samani model most closely approximated both the field observations and the previous estimates based on the more data-intensive Penman model. Mean estimated volatilization exceeded mean observations by 15% and the coefficient of variation (R2) between estimates and observations was 0.65. The comparable values based on Penman ET were 17% and 0.63, respectively.     

THE EFFECT OF DATA INDEPENDENCE IN MODEL CALIBRATION AND MODEL TESTING1

ABSTRACT: With the increased use of models in hydrologic design, there is an immediate need for a comprehensive comparison of hydrologic models, especially those intended for use at ungaged locations (i.e., where measured data are either not available or inadequate for model calibration). But some past comparisons of hydrologic models have used the same data base for both calibration and testing of the different models or implied that the results of model calibration are indicative of the accuracy at ungaged locations. This practice was examined using both the regression equation approach to peak discharge estimation and a unit hydrograph model that was intended for use in urban areas. The results suggested that the lack of data independence in the calibration and testing of regression equations may lead to both biased results and misleading statements about prediction accuracy. Additionally, although split-sample testing is recognized as desirable, the split-samples should be selected using a systematic-random sampling scheme, rather than random sampling, because random sampling with small samples may lead to a testing sample that is not representative of the population. A systematic-random sampling technique should lead to more valid conclusions about model reliability. For models like a unit hydrograph model, which are more complex and for which calibration is a more involved process, data independence is not as critical because the data fitting error variation is not as dominant as the error variation due to the calibration process and the inability of the model structure to conform with data variability.     

Optimizing organic fertilizer applications under steady-state conditions

Because organic N fertilizers must be mineralized before they become plant-available, application designs should consider time and temperature effects on N release as well as crop N requirements. This study presents deterministic (DOpt) and stochastic (SOpt) linear optimization models to determine sustainable land application schedules. The easily solved models minimize the amount of N that is applied while assuring than crop N demands are met as they develop. Temperature effects on N mineralization were included by using the Arrhenius equation to create a temperature-adjusted time series. Uncertainties associated with mineralization rates and the temperature-adjustment (Q10) factor are considered by SOpt. Examples are presented for a summer maize (Zea mays L.) and winter triticale (Triticum aestivum L. x Secale cereale L.) rotation operated by a hypothetical dairy operation in Stanislaus County, California. Monte Carlo simulations were used to test the models. A closed-form solution for estimating the time until steady state is presented and steady-state conditions were reached within 7 yr after applications were initiated. Because of temperature effects, DOpt solutions were 12% greater during the winter and 29% lower during the summer than a reference approach that applied liquid manure at 130% of the crop N demand. Stochastic linear optimization values were 1.7% greater than DOpt values in the summer and 6.2% greater in the winter. Surplus N estimates from Monte Carlo simulations averaged 104 kg ha(-1) for DOpt and 126 ka ha(-1) for SOpt, but SOpt was much less likely to result in crop N deficits. Linear optimization is a viable tool for scheduling organic N applications.     

DETERMINATION OF UNCONFINED AQUIFER HYDRAULIC PROPERTIES FROM RECOVERY TEST DATA1

ABSTRACT: This paper analyzes the sensitivity of drawdown to four hydraulic parameters in unconfined aquifers: horizontal and vertical hydraulic conductivity K_r and K_z, storage coefficient S, and specific yield S_y. Sensitivity coefficients indicate that the sensitivity vanes with time for each aquifer parameter, and K_r, K_z, S, and S_y are identifiable from recovery test data. An inverse method was used to calculate the four parameters from residual drawdowns. Results of application examples demonstrate that residual data provide valid information in the determination of unconfined aquifer hydraulic parameters.     

Development and Evaluation of Bankfull Hydraulic Geometry Relationships for the Physiographic Regions of the United States

Bankfull hydraulic geometry relationships are used to estimate channel dimensions for streamflow simulation models, which require channel geometry data as input parameters. Often, one nationwide curve is used across the entire United States (U.S.) (e.g., in Soil and Water Assessment Tool), even though studies have shown that the use of regional curves can improve the reliability of predictions considerably. In this study, regional regression equations predicting bankfull width, depth, and cross‐sectional area as a function of drainage area are developed for the Physiographic Divisions and Provinces of the U.S. and compared to a nationwide equation. Results show that the regional curves at division level are more reliable than the nationwide curve. Reliability of the curves depends largely on the number of observations per region and how well the sample represents the population. Regional regression equations at province level yield even better results than the division‐level models, but because of small sample sizes, the development of meaningful regression models is not possible in some provinces. Results also show that drainage area is a less reliable predictor of bankfull channel dimensions than bankfull discharge. It is likely that the regional curves can be improved using multiple regression models to incorporate additional explanatory variables.