Linear alkylbenzene sulfonate (LAS) in water of Lake Dianchi—spatial and seasonal variation, and kinetics of biodegradation

Agroforesty systems, which are recommended as a management option to lower the shallow groundwater level and to reuse saline subsurface drainage waters from the tile-drained croplands in the drainage-impacted areas of Jan Joaquin Valley of California, have resulted in excessive boron buildup in the soil root zone. To assess the efficacy of the long-term impacts of soil boron buildup in agroforesty systems, a mathematical model was developed to simulate non-conservative boron transport. The developed dynamic two-dimensional finite element model simulates water flow and boron transport in saturated–unsaturated soil system, including boron sorption and boron uptake by root-water extraction processes. The simulation of two different observed field data sets by the developed model is satisfactory, with mean absolute error of 1.5 mg/L and relative error of 6.5%. Application of the model to three different soils shows that boron adsorption is higher in silt loam soil than that in sandy loam and clay loam soils. This result agrees with the laboratory experimental observations. The results of the sensitivity analysis indicate that boron uptake by root-water extraction process influences the boron concentration distribution along the root zone. Also, absorption coefficient and maximum adsorptive capacity of a soil for boron are found to be sensitive parameters.     

Sequential extractions of selenium soils from Stewart Lake: total selenium and speciation measurements with ICP-MS detection

Different techniques have been employed in order to evaluate the most efficient procedure for the extraction of selenium from soil as required for speciation. Selenium contaminated sediments from Stewart Lake Wetland, California were used. A strong acid mineralization of the samples gives quantitative total selenium, which is then used to estimate recoveries for the milder extraction methods. The different extraction methodologies involve the sequential use of water, buffer (phosphate, pH 7) and either acid solution (e.g. HNO3 or HCl) or basic solutions (e.g. ammonium acetate, NaOH or TMAH). Pyrophosphate extraction was also evaluated and showed that selenium was not associated with humic acids. The extractants were subsequently analyzed by size exclusion chromatography (SEC) with UV (254 and 400 nm) and on-line ICP-MS detection; anion exchange chromatography, and ion-pair reversed phase chromatography with ICP-MS detection. For sequential extractions the extraction efficiencies showed that the basic extractions were more efficient than the acidic. The difference between the acidic and the basic extraction efficiency is carried to the sulfite extraction, suggesting that whatever is not extracted by the acid is subsequently extracted by the sulfite. The species identified with the different chromatographies were selenate, selenite, elemental selenium and some organic selenium.     

Highlighting the implications of selenium dispersion from disposal of Kahota Industrial Triangle area, Islamabad, Pakistan using three-dimension solute transport model

This study highlights the implications of selenium (Se) dispersion in groundwater flow regimes of Kahota Industrial Triangle area located adjacent to the Soan River, Islamabad. Initially, a regional groundwater 3-D flow model has been developed, calibrated to the known observed heads of 24 water wells, verified, and confirmed that convergence has actually arrived to satisfy the steady state condition. Later, the transient simulation was carried out adding in the known recharge, storage factor, porosity, and observed drawdown matched with the simulated drawdown that appears to fall in close agreement with a difference of 0.25 m. As such the steady state groundwater model has facilitated to understand the mechanism of groundwater flow regimes in reference to the implications of selenium dispersion from disposal of Kahota Industrial Triangle area. Thirty-five water samples were collected mainly from the industrial water wells for the evaluation of heavy metals. Selenium being the major contributor of pollution has been short listed to monitor its dispersion using a solute transport model modular three-dimensional transport model (MT3D). Chemical parameters related to selenium characteristics including horizontal and vertical transverse dispersivity/longitudinal dispersivity, effective molecular diffusion coefficient and bulk density of the porous medium of aquifers have been used in MT3D contaminant transport model. MT3D is run for 30 years in steady state condition. As usual first run did not produce the exact field conditions. Therefore, the contaminant transport model is calibrated against the 32 values of observed selenium concentrations in boreholes by minor adjustments in the chemical parameter values. The final calibration has been achieved with residual value of 3.88 × 10^???5 Kg/m³. Seven hypothetical observation wells are used to monitor the selenium concentrations over a long-term period of time.     

Assessing the influence of nutrient reduction on water quality using a three-dimensional model: case study in a tidal estuarine system

A coupled three-dimensional hydrodynamic and water quality model has been developed and applied to the Danshuei River estuarine system and adjacent coastal sea. The water quality model considers various species of nitrogen, phosphorus, organic carbon, and phytoplankton as well as dissolved oxygen and is driven by a three-dimensional hydrodynamic model. The hydrodynamic and water quality models were validated with observations of water surface elevation, velocity, salinity distribution, and water quality parameters. Statistical error analysis shows that predictions of hydrodynamics, salinity, dissolved oxygen, and nutrients from the model simulation quantitatively agreed with the observed data. The validated model was then applied to predict water quality conditions as a result of a reduction in nutrient loadings based on different engineering strategies. The simulated results revealed that the dissolved oxygen concentration would increase significantly and would be higher than 2 mg/L in the main stream and in three tributaries to meet the minimum statutory requirement for dissolved oxygen. Active estuarine management focused on the reduction of anthropogenic nutrient loads is needed for improvement in water quality.     

A Conceptual Nitrate Transport Model and Its Application at Different Scales

Groundwater and surface water pollution from nonpoint sources are problems of increasing concern. Nitrate transport is a crucial part in the whole process of nitrate loss. Previous methods for simulating the nitrate transport process usually involved solving complex advection–dispersion equations and required large amount of parameters and input data, which makes a model application expensive or invalid in terms of computation and data availability. The aim of this research is to develop a simple conceptual method to simulate the nitrate transport. In this paper, a simple conceptual method utilizing the distribution of nitrate loss against cumulative drainage to simulate the nitrate transport process is introduced. The concept and construction of this method are presented, and its applicability at different spatial scales is demonstrated. Results of model application at laboratory, pilot, and catchment scales show that this method has a good capability to simulate the transport of nitrate. Impact of spatial scales on parameters’ values is also discussed. Compared to conventional methods, this method requires fewer parameters, less computing time, and less input data.     

A Comprehensive Numerical Model Simulating Gas,Heat, and Moisture Transport in Sanitary Landfills and Methane Oxidation in Final Covers

A model to simulate gas, heat, and moisture transport through a sanitary landfill has been developed. The model not only considers the different processes that go on in a landfill but also the oxidation of methane in the final cover. The model was calibrated using published results and field data from a pilot scale landfill in Calgary. The model captures the physics of the different processes quite well. Simulations from the model show that waste permeability had a significant impact on the temperature, pressure distribution, and flux from a landfill. The presence of the final and intermediate covers enhanced the gas storage capacity of the landfill. Biodegradation of the waste was enhanced as the final cover minimized the atmospheric influences. In addition, the composition of landfill gas emitted to the atmosphere was significantly different from the composition of gas generated in landfill due to the presence of covers as some of the methane is oxidized to carbon dioxide. There was no significant benefit of using a final cover of higher depth. The presence and number of intermediate covers had an impact on gas flux and temperature distribution within a landfill.     

Development and Testing of 2D Finite Difference Model in Open Channels

This study develops a depth-averaged two-dimensional (2D) numerical model using a finite difference method (FDM) on a staggered grid. The governing equations were solved using the Marker and Cell method that was developed at the Los Alamos laboratories by Harlow and Welch in 1965. In the paper, an explicit FDM was used to solve the governing equations. A first-order approximation was used for the temporal derivative. Second-order central difference approximations were used for space discretization. The time step is limited by the Courant–Friedrichs–Lewy (CFL) condition. The time step used in this study depends on the grid spacing and velocity components in the x- and y-directions. The study is divided into two steps: the first step is to develop a depth-averaged 2D numerical model to simulate the flow process. The second constructs a module to calculate the bed load transport and simulate the river morphology in the areas that have steep slopes, torrents, and mountain rivers. Developed model was applied to the artificial channel and a flood event in the Asungjun River section of the mountainous Yangyang Namdae River (South Korea). General simulation results showed that the developed model was in good agreement with the observed data.     

Selenium in aquatic biota inhabiting agricultural drains in the Salton Sea Basin, California

Resource managers are concerned that water conservation practices in irrigated farmlands along the southern border of the Salton Sea, Imperial County, California, could increase selenium concentrations in agricultural drainwater and harm the desert pupfish (Cyprinodon macularius), a federally protected endangered species. As part of a broader attempt to address this concern, we conducted a 3-year investigation to collect baseline information on selenium concentrations in seven agricultural drains inhabited by pupfish. We collected water, sediment, selected aquatic food-chain taxa (particulate organic detritus, filamentous algae, net plankton, and midge [Chironomidae] larvae), and two poeciliid fishes (western mosquitofish Gambusia affinis and sailfin molly Poecilia latipinna) for selenium determinations. The two fish species served as ecological surrogates for pupfish, which we were not permitted to sacrifice. Dissolved selenium ranged from 0.70 to 32.8 μg/L, with selenate as the major constituent. Total selenium concentrations in other environmental matrices varied widely among drains, with one drain (Trifolium 18) exhibiting especially high concentrations in detritus, 5.98-58.0 μg Se/g; midge larvae, 12.7-50.6 μg Se/g; mosquitofish, 13.2-20.2 μg Se/g; and mollies, 12.8-30.4 μg Se/g (all tissue concentrations are based on dry weights). Although toxic thresholds for selenium in fishes from the Salton Sea are still poorly understood, available evidence suggests that ambient concentrations of this element may not be sufficiently elevated to adversely affect reproductive success and survival in selenium-tolerant poeciliids and pupfish.     

Implications and concerns of deep-seated disposal of hydrocarbon exploration produced water using three-dimensional contaminant transport model in Bhit Area, Dadu District of Southern Pakistan

A three-dimensional contaminant transport model has been developed to simulate and monitor the migration of disposal of hydrocarbon exploration produced water in Injection well at 2,100 m depth in the Upper Cretaceous Pab sandstone, Bhit area in Dadu district of Southern Pakistan. The regional stratigraphic and structural geological framework of the area, landform characteristics, meteorological parameters, and hydrogeological milieu have been used in the model to generate the initial simulation of steady-state flow condition in the underlying aquifer’s layers. The geometry of the shallow and deep-seated characteristics of the geological formations was obtained from the drilling data, electrical resistivity sounding surveys, and geophysical well-logging information. The modeling process comprised of steady-state simulation and transient simulation of the prolific groundwater system of contamination transport after 1, 10, 30 years of injection. The contaminant transport was evaluated from the bottom of the injection well, and its short- and long-term effects were determined on aquifer system lying in varying hydrogeological and geological conditions.     

2017年江苏省PM2.5数值模拟及内外源解析

根据江苏省72个国控点监测数据,采用了区域大气模式和多尺度空气质量模式系统(RAMS-CMAQ)模拟了2017年江苏省ρ(PM_2.5)的时空分布,耦合综合源追踪算法(ISAM)分析了不同地区排放源对ρ(PM_2.5)的贡献特征。结果表明,PM_2.5模拟与观测值的相关系数(r)=0.76,标准平均偏差(NMB)=5.2%,均方根误差(RMSE)=23.4μg/m₃,模拟结果落于观测结果0.5~2倍的比例(FAC2)=84.2%。源追踪模块结果显示,夏季主要受东南风控制,本地排放的贡献更大(省内贡献为52.34%),其他季节受偏北风输送影响,外源输送的影响较大(省外贡献为53.48%~56.84%);冬季苏北5市的排放贡献比沿江8市的更大,而春、夏季沿江8市排放贡献较大。     

AgInput: An Agricultural Nutrient and Pesticide Source Model

Agriculture can be a major nonpoint source (NPS) of nutrient and pesticide contamination in the environment. Available databases do not provide accurate and dynamic data on fertilizer and pesticide application, which limits the ability of complex watershed models to simulate contaminant loads into impaired water bodies. A model for estimating agricultural nutrient and pesticide input for watershed modeling has been developed. Climate, soils, and major agricultural operations are considered within the model, so that it can be adapted to any watershed or subregion within a watershed. The timing of the agricultural operations is a function of the weather data, providing realistic results at daily, monthly, or annual application rates. The model also predicts irrigation demand and biomass production, which can be used to calibrate the model. Model output can be used in any watershed model that considers agricultural land uses. Two case studies were evaluated, using grape vineyards in the Napa River and strawberry production in Newport Bay as examples. The predicted time to maturity corresponded well with actual data. Irrigation and fertilizer needs were very sensitive to weather input. Although the model can generate weather from long-term averages, the simulated results are best when at least observed precipitation and temperature are provided, to capture extreme events. The model has data for 98 crops and 126 pesticides, based on the California Department of Pesticide Regulation database. The databases are easily modifiable by the user to adapt them to local conditions. The output from AgInput is much needed for watershed modeling and for development of total maximum daily loads (TMDLs), based on realistic targets of irrigation, nutrient, and pesticide inputs. The model is available for free download at .     

基于GWLF模型的于桥水库入库河流水文模拟及氮磷负荷估算

流域模型技术应用是当前开展面源污染防治的重要工具,而水文过程的准确模拟是进行污染负荷估算的首要环节和关键步骤。为了弄清近年来于桥水库入库河流氮、磷输入负荷,选取GWLF模型对水平口子流域的水文过程进行模拟,首先利用2006—2018年气象、水文资料率定模型水文参数,然后将参数推广到整个流域,对2019—2020年3条主要入库河流流量进行模拟,最后乘以相应河流断面的总氮、总磷浓度估算氮磷输入负荷。结果显示：GWLF模型适用于研究区的水文过程模拟,校准期和验证期的纳氏系数分别为0.89和0.91,平均相对误差分别为12.2%和13.1%;2020年总氮入库负荷为3 977.0 t,其中引滦调水贡献占57.0%,3条入库河流共贡献43.0%;总磷入库负荷为48.8 t,其中引滦调水贡献占68.6%,3条入库河流共贡献31.4%。GWLF模型输入数据需求量较少,模型参数较少,模拟效果较好,适用于中小型流域的水资源和水环境管理,具有一定的推广应用前景。     

Particle release transport in Danshuei River estuarine system and adjacent coastal ocean: a modeling assessment

A three-dimensional hydrodynamic model was created to study the Danshuei River estuarine system and adjacent coastal ocean in Taiwan. The model was verified using measurements of the time-series water surface elevation, tidal current, and salinity from 1999. We conclude that our model is consistent with these observations. Our particle-tracking model was also used to explore the transport of particles released from the Hsin-Hai Bridge, an area that is heavily polluted. The results suggest that it takes a much longer time for the estuary to be flushed out under low freshwater discharge conditions than with high freshwater discharge. We conclude that the northeast and southwest winds minimally impact particle dispersion in the estuary. The particles fail to settle to the bottom in the absence of density-induced circulation. Our model was also used to simulate the ocean outfall at the Bali. Our experimental results suggest that the tidal current dominates the particle trajectories and influences the transport properties in the absence of a wind stress condition. The particles tend to move northeast or southwest along the coast when northeast or southwest winds prevail. Our data suggest that wind-driven currents and tidal currents play important roles in water movement as linked with ocean outfall in the context of the Danshuei River.     

Fate of selenium in a small urban watershed

A field study was conducted on a small urban watershed (residential and golf course dominated) in southern Nevada to assess the concentration and speciation of selenium (Se) in a series of drain lines and monitoring wells and to quantify the mass discharge of Se from the drain system. Water samples were collected on a monthly basis and analyzed for total Se, selenate (SeO₄ ⁼) and selenite (SeO₃ ⁼). In addition, where possible, flow was assessed as was, temperature, redox potential, pH, dissolved oxygen (DO) along with all major cations and anions. The data were then modeled with PhreeqC to identify selenium speciation. Results revealed a SeO₄ ⁼ dominated system with SeO₄ ⁼ concentrations ranging from 13 to 62 ppb. In the monitoring wells, 66 % of the variation in the total Se concentration could be described based on depth to groundwater, temperature and sulfate concentrations (P?<?0.001). In particular, higher total Se concentrations were predicted for shallower depth to groundwater, suggesting the solubilization of Se evapo-concentrates near the surface could be reduced by lowering water tables. The highest of all correlations was found between SeO₄ ⁼ concentrations (↑) and the sodium (↑) and DO (↑) concentrations in the monitoring wells (R ²?=?0.77, P?<?0.001). An excellent curvilinear relationship was found between total Se and the electrical conductivity in the water (R ²?=?0.73, P?<?0.001). Based on the Se data and time line identified in this study, high concentrations of Se could be expected to drain from this area for many years to come, with salinity acting as a good proxy for Se concentration. In the drain lines, Se concentrations were found to be invariant to flow (P?>?0.05). Flow discharge from the main drain system to the Las Vegas Wash was estimated at 559 acre feet during the 1 year study period. This flow was estimated to carry 4,203 Mg of salts 6.71 Mg of nitrate-N and 27.1 kg of total Se.     

郑州市PM2.5浓度时空分布特征及预测模型研究

利用统计学原理和GIS技术,对郑州市2013年8月17—12月31日期间PM2.5浓度时空分布特征进行分析,同时结合气象资料与前一日污染数据,建立人工神经网络反向传播算法模型(BP-ANN)和多元线性回归模型用于该市细颗粒物污染的短期预测。结果表明,郑州市PM2.5浓度日变化呈单峰模式,随逆温现象的发生和交通的密集于上午11:00达到峰值,午后逐步下降。在工作日、周末与国庆节的对比中,国庆节期间颗粒物污染浓度高出平日32.8%,表明人为活动的加剧影响PM2.5的排放;周末与工作日期间无显著差异。在空间分布上,金水区、管城回族区污染最为严重,工业燃煤、地铁施工等源排放是造成污染的主要原因;位于远郊的岗里水库,受秸秆焚烧和市区污染输送等影响,PM2.5浓度亦维持较高水平。最后,研究将所构建的BP-ANN预测模型和多元线性回归模型对比,结果发现两模型在建模阶段预测值与真实值的拟合一致性指标分别为0.944、0.918,均方根误差分别为59.788、70.611;验证阶段拟合一致性指标分别为0.854、0.794,平均绝对误差分别为25.298、32.775,表明BP-ANN模型在预测郑州市PM2.5污染过程中更具优势。     

Artificial neural network modeling of dissolved oxygen in reservoir

The water quality of reservoirs is one of the key factors in the operation and water quality management of reservoirs. Dissolved oxygen (DO) in water column is essential for microorganisms and a significant indicator of the state of aquatic ecosystems. In this study, two artificial neural network (ANN) models including back propagation neural network (BPNN) and adaptive neural-based fuzzy inference system (ANFIS) approaches and multilinear regression (MLR) model were developed to estimate the DO concentration in the Feitsui Reservoir of northern Taiwan. The input variables of the neural network are determined as water temperature, pH, conductivity, turbidity, suspended solids, total hardness, total alkalinity, and ammonium nitrogen. The performance of the ANN models and MLR model was assessed through the mean absolute error, root mean square error, and correlation coefficient computed from the measured and model-simulated DO values. The results reveal that ANN estimation performances were superior to those of MLR. Comparing to the BPNN and ANFIS models through the performance criteria, the ANFIS model is better than the BPNN model for predicting the DO values. Study results show that the neural network particularly using ANFIS model is able to predict the DO concentrations with reasonable accuracy, suggesting that the neural network is a valuable tool for reservoir management in Taiwan.     

Ecological study of river Suswa: modeling DO and BOD

In this paper limnological status of river Suswa was observed for a period of two years. A water quality Beck modified Khanna Bhutiani model (BMKB model) was developed to calculate DO (dissolved Oxygen) and BOD (biochemical oxygen demand). The model was developed to calculate DO and BOD by using DO/BOD of same place and upstream in previous season which results in Single output. This model gives the seasonal value on the basis of previously taken upstream and downstream observations/concentrations of DO and BOD. The model was calibrated and verified for the water quality data (Physico-chemical data) of samples collected from river Suswa in different seasons. The model gave good agreement between data observed by it and the data observed manually, thus substantiating the validity of the model. Only minor differences were observed in physical, chemical and heavy metals of all the four sampling stations during the course of study.     

New Unstructured Mesh Water Quality Model for Cooling Water Biocide Discharges

A new unstructured mesh coastal water and air quality model has been developed that includes species transport, nonlinear decay, by-product formation, and mass-exchange between sea and atmosphere. The model has been programmed with a graphical user interface and is applicable to coastal seawater, lakes, and rivers. Focused on species conversion and interaction with the atmosphere, the water and air quality model follows a modular approach. It is a compatible module which simulates distributions based on fluid dynamic field data of underlying existing hydrodynamic and atmospheric simulations. Nonlinear and spline approximations of decay and growth kinetics, by-product formation, and joint sea–atmosphere simulation have been embedded. The Windows application software includes functions allowing error analysis concerning mesh and finite volume approximation. In this work, a submerged residual chlorine cooling water discharge and halogenated matter by-product formation has been simulated. An error analysis has been carried out by varying vertical meshing, time-steps and comparing results based on explicit and implicit finite volume approximation. The new model has been named 3D Simulation for Marine and Atmospheric Reactive Transport, in short 3D SMART.     

Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China

Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl^?), calcium (Ca²⁺), total alkalinity, total hardness, nitrate nitrogen (NO₃-N), and ammonical nitrogen (NH₄-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO₃-N, NH₄-N, and Ca²⁺. Cl^? was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters.     

Impact of phosphorus load reduction on water quality in a stratified reservoir-eutrophication modeling study

Monitoring data collected from the Mingder Reservoir in Taiwan indicate that the water quality is between mesotrophic and eutrophic. Chlorophyll a concentration is higher in the summer and anoxic conditions occur in the bottom. The data also reveal that a pronounced vertical thermal gradient in summer and vertical mixing the end of fall. A vertical two-dimensional, laterally averaged hydrodynamic and water quality model (CE-QUAL-W2) was adopted to simulate the water surface elevation, water temperature, and water quality conditions in the water column. The modeling effort was supported with monitoring data collected in the field for a 2-year period in the reservoir. The hydrodynamic model reproduced the time series water surface elevation. Spatial and temporal distributions of temperature in the water column of the reservoir were also well reproduced by the hydrodynamic model. Model-calculated concentrations of key water quality constituents such as nutrients, dissolved oxygen, and algal biomass matched the measured values closely in the reservoir. The calibrated model was then applied to simulate water quality response to various nutrient reduction scenarios. Results of the model scenario runs reveal that a 20% and 80% reduction of the phosphorus loads will improve the water quality from eutrophic to mesotrophic and oligotrophic conditions, respectively. The modeling effort has yielded valuable information that can be used by decision makers for the evaluation of different management strategies of reducing watershed nutrient loads.