有关有限边界岸边排放稳态二维混合模式的几个问题的探讨

针对目前我国环境影响评价领域普遍采用的有限边界岸边排放稳态二维混合模式的局限性和不精确性，本文对由河流二维稳态水质模型的基本方程推求出的有限边界岸边排放的二维稳态混合模式的解析解的各项进行分析比较。同时针对费休的混合长度公式进行了计算比较。     

去除叶绿素a影响的泥沙反演模型

通过遥感方法反演自然水体中泥沙浓度时,大量藻类的存在影响泥沙的反演精度,如何消除这种影响是提高水体中泥沙反演精度的关键.文章通过对一定叶绿素a浓度下不同浓度泥沙的光谱曲线研究,分析光谱曲线特征位置的漂移和数值变化,寻找去除叶绿素a影响的光谱范围和特征位置,通过相关性分析,建立多个模型,并从中选取最佳模型.     

基于多时相卫星数据的采砂场遥感调查研究——以青海省湟水流域为例

文章采用多源多时相高分辨率遥感影像作为数据源，以ArcGIS、Erdas、Envi等遥感地信软件为信息提取平台，对青海省湟水流域的采砂场进行遥感调查分析。结果显示：①采砂场主要分布在湟水流域城市周边，其中，在用采砂场分布较密集，如西宁、湟中、平安附近分布较集中，而停用采砂场分布相对比较均匀；②采砂场共305处，其中长期和临时采砂场占重要比例，达73%，经过平整或绿化的停用采砂场较少，而停用且无整改及整改中的采砂场数量仍较多，是已整改的2倍；③长期采砂场面积规模占所有类型总面积的比重最大，达三分之二，而经过平整或已绿化的规模仅0.75 km²。研究以期对环境监察管理提供技术支撑，为后续的研究和砂场的高效精准管理提供技术方法和科学依据。     

改进主成分分析与多元回归融合的汉丰湖水质评估及预测

基于2015—2017年汉丰湖水质监测数据,采用改进主成分分析和多元回归相融合的评价方法对水环境质量状况进行评价。先对水质主要影响因素采用改进主成分分析作降维处理并计算主成分得分值,再对选定的主成分作多元线性回归处理得到水质预测回归模型,并用于研究区水质的评估预测。结果表明:选出的4个主成分因子其累积方差贡献率达到87.3%,实现了数据结构的简化;同时,改进主成分回归预测值总体上更趋近于实测值,其预测结果的相对误差最大值4%,而常规方法预测结果的相对误差最大值接近10%,体现出该方法所建模型具有较高的预测精度。     

广佛珠江河网区石油类污染数值模拟研究

基于EFDC模型，构建了广佛珠江感潮河网区三维水动力模型；同时，通过耦合石油类污染物水力输运与悬沙吸附一沉降过程，构建石油类水质数学模型，从而更全面客观地模拟水体石油类污染物的迁移转化过程。通过2001年1月实例模拟及验证，表明模型能较好地模拟再现珠江水体石油类浓度变化过程，为日后珠江水环境质量监控与水质改善、城市河涌整治成果评价及预测等提供技术支持。     

青藏工程走廊水环境安全保护等级区划研究

采用模糊数学综合评判法和突变级数法对青藏工程水环境安全的保护等级进行分区评价与研究,结果表明:青藏工程走廊带沿线水环境分为一级、二级和三级保护区3个区域,其中一级区范围为青藏高速公路拉萨—安多段,二级区范围为青藏高速公路安多—茶错段,三级区范围为青藏高速公路茶错—格尔木段;青藏工程走廊水环境安全保护路段共计408.92 km,安全保护等级高,占路线全长的35.56%。建议拉萨—安多全段,以及安多—茶错段部分路(桥)面通过工程措施和非工程措施相结合的方式实现路(桥)面径流污染控制,有效降低路(桥)面径流对走廊带水环境的影响。     

水质GM（1，1）和Ae~（a（k－1））模型预测

水质ＧＭ（１，１）和Ａｅ~（ａ（ｋ－１））模型预测易江（中国环境监测总站，北京１０００１２）水环境质量变化，归纳起来受自然因素和人为因素的影响。自然因素发生着缓慢的变化，对水环境质量变化的作用是渐进、平稳和相对微弱的。人为因素则不然，当主要污染源得到?..     

水中乙醛、丙烯醛和丙烯腈3种测定方法的对比

对比研究了大体积直接进样填充柱气相色谱法、顶空-气相色谱法和吹扫捕集-气相色谱法等3种测定水中乙醛、丙烯醛和丙烯腈的方法.结果表明,大体积直接进样法设备简单,但手动进样耗力费时,且灵敏度低,精密度差,直接水样分析易影响色谱柱和检测器的使用寿命;顶空法稳定性好,线性范围宽,相关性和精密度好,适合较高浓度水样的分析;吹扫捕集法操作简便,峰形好,检出限低,回收率高,适合低浓度水样的分析.顶空法和吹扫捕集法自动化程度高,均适用于大批量样品分析.     

水环境中药品和个人护理用品污染现状及研究进展

综述了当前国内外药品和个人护理用品(PPCPs)在地表水、地下水和饮用水中的污染现状,介绍了水环境中PPCPs污染的危害及其预测、调查与检测方法。提出了我国水环境中PPCPs污染未来的研究方向,包括改进水处理工艺,提高PPCPs的去除效率;提升分析技术水平,拓宽PPCPs的检测种类;深入研究PPCPs产生的环境效应,重视其职业暴露的污染与危害;建立水环境中PPCPs的预测制度及风险评价体系。     

线性修正趋势分析技术在环境质量预警预测中的应用

线性修正趋势分析法根据历年数据建立线性模型并进行修正,预测年度、季环境要素污染物变化情况,可应用于空气质量、水环境质量、噪声环境质量、污染源污染物排放等预警预测数据统计分析评价,为环境决策提供技术支持。本文通过实例论述了该方法在实际工作中的应用。     

人工沙滩对海水入侵影响评价的数值模拟研究

以广东省珠海市2018年完工的唐家湾沙滩为研究对象，基于OpenGeoSys程序构建海水入侵数值模型，根据水文地质调查数据，建立沙滩修复前地下水运动的数学模型，利用地下水盐度历史数据进行参数率定与模型验证。在该模型基础上，根据填沙的水文地质参数，改变模型相应部分的属性，分析针对不同人工沙滩修复方案情景下的咸淡水界面运移规律。结果表明：人工填沙可加速海水入侵，填沙厚度对海水入侵程度影响较小；增加填沙宽度可以有效缓解海水入侵，当填沙宽度达到50 m时，可驱退咸淡水界面至沙滩修复前的状态。     

基于K-means聚类的沙尘天气快速识别技术研究

依据沙尘天气判定条件分析2018年春季（2—4月）陕西省西安市环境空气质量小时监测数据，共识别9 d受沙尘影响。研究基于K-means聚类沙尘天气分析方法，分析沙尘天气监测数据特征，并对沙尘识别聚类模型进行优化研究，识别的沙尘影响天气与传统方法一致。分析表明，聚类方法可用于沙尘天气监测数据的识别，与传统方法相比较，基于K-means聚类方法能够快速、准确识别沙尘影响天气。     

Water Quality Prediction of Water Sources Based on Meteorological Factors using the CA-NARX Approach

With the increasingly serious problem of surface water environmental safety, it is of great significance to study the changing trend of reservoir water quality, and it is necessary to establish a water quality prediction and early warning system for the management and maintenance of water resources. Aiming at the problem of water quality prediction in reservoirs, a CA-NARX algorithm is designed, which combines the improved dynamic clustering algorithm with the idea of machine learning and the forward dynamic regression neural network. The improved dynamic clustering algorithm is used to classify the eutrophication degree of waterbodies according to the total phosphorus and total nitrogen content. Considering four meteorological factors, air temperature, water temperature, water surface evaporation, and rainfall, synthetically for each water quality condition, the total phosphorus and total nitrogen in the waterbody are forecasted by an improved forward NARX dynamic regression neural network. Based on this, the CA-NARX prediction algorithm can realize short period water quality prediction. Compared with the traditional support vector regression machine model, improved GA-BP neural network, and exponential smoothing method, the CA-NARX model has the least prediction error.

     

Numerical modelling of the groundwater inflow to an advancing open pit mine: Kolahdarvazeh pit,Central Iran

The groundwater inflow into a mine during its life and after ceasing operations is one of the most important concerns of the mining industry. This paper presents a hydrogeological assessment of the Irankuh Zn-Pb mine at 20 km south of Esfahan and 1 km northeast of Abnil in west-Central Iran. During mine excavation, the upper impervious bed of a confined aquifer was broken and water at high-pressure flowed into an open pit mine associated with the Kolahdarvazeh deposit. The inflow rates were 6.7 and 1.4 m³/s at the maximum and minimum quantities, respectively. Permeability, storage coefficient, thickness and initial head of the fully saturated confined aquifer were 3.5?×?10^?4 m/s, 0.2, 30 m and 60 m, respectively. The hydraulic heads as a function of time were monitored at four observation wells in the vicinity of the pit over 19 weeks and at an observation well near a test well over 21 h. In addition, by measuring the rate of pumping out from the pit sump, at a constant head (usually equal to height of the pit floor), the real inflow rates to the pit were monitored. The main innovations of this work were to make comparison between numerical modelling using a finite element software called SEEP/W and actual data related to inflow and extend the applicability of the numerical model. This model was further used to estimate the hydraulic heads at the observation wells around the pit over 19 weeks during mining operations. Data from a pump-out test and observation wells were used for model calibration and verification. In order to evaluate the model efficiency, the modelling results of inflow quantity and hydraulic heads were compared to those from analytical solutions, as well as the field data. The mean percent error in relation to field data for the inflow quantity was 0.108. It varied between 1.16 and 1.46 for hydraulic head predictions, which are much lower values than the mean percent errors resulted from the analytical solutions (from 1.8 to 5.3 for inflow and from 2.16 to 3.5 for hydraulic head predictions). The analytical solutions underestimated the inflow compared to the numerical model for the time period of 2–19 weeks. The results presented in this paper can be used for developing an effective dewatering program.     

Coupling upland watershed and downstream waterbody hydrodynamic and water quality models (SWAT and CE-QUAL-W2) for better water resources management in complex river basins

Effective water resources management programs have always incorporated detailed analyses of hydrological and water quality processes in the upland watershed and downstream waterbody. We have integrated two powerful hydrological and water quality models (SWAT and CE-QUAL-W2) to simulate the combined processes of water quantity and quality both in the upland watershed and downstream waterbody. Whereas the SWAT model outputs water quality variables in its entirety, the CE-QUAL-W2 model requires inputs in various pools of organic matter contents. An intermediate program was developed to extract outputs from SWAT at required subbasin and reach outlets and converts them into acceptable CE-QUAL-W2 inputs. The CE-QUAL-W2 model was later calibrated for various hydrodynamic and water quality simulations in the Cedar Creek Reservoir, TX, USA. The results indicate that the two models are compatible and can be used to assess and manage water resources in complex watersheds comprised of upland watershed and downstream waterbodies.     

Impact of model parameterization on predictive uncertainty of regional groundwater models in the context of environmental impact assessment

Parameterization strategy impacts models' outputs and the associated uncertainty. This is particularly true for transient regional groundwater models where parameters can only be weakly constrained by insufficient observations. However, this is rarely investigated under any particular model structure. This study bridges this gap using a regional groundwater model developed to understand the impact of coal seam gas extraction on groundwater systems in a probabilistic framework. Two different parameterization schemes were implemented for hydraulic conductivity and specific storage. The first method solely relies on the relationship between hydraulic properties and burial depths. The second more complex strategy allows more spatial variations of hydraulic parameters using pilot points. The study provides new insights and practical guidance on the application of groundwater modelling for environmental impact assessment. The results suggest that the choice of model parameterization has a significant influence on predictive uncertainty. The model using the simple parameterization provides predictions with a much wider range than the model with a more sophisticated parameterization. This is because that the lowly parameterized model tends to generate more extreme effective hydraulic parameter fields unless the parameterization simplification converts the inverse problem to a (close to) well-posed problem that rarely exists for applied regional groundwater modelling. The potential impact of model parameterization should be discussed explicitly in groundwater modelling applications to support decision making to avoid misinterpretation of the modelling results.     

Hydrostratigraphy and hydrogeology of the western part of Maira area, Khyber Pakhtunkhwa, Pakistan: a case study by using electrical resistivity

Hydrostratigraphy and hydrogeology of the Maira vicinity is important for the characterization of aquifer system and developing numerical groundwater flow models to predict the future availability of the water resource. Conventionally, the aquifer parameters are obtained by the analysis of pumping tests data which provide limited spatial information and turn out to be costly and time consuming. Vertical electrical soundings and pump testing of boreholes were conducted to delineate the aquifer system at the western part of the Maira area, Khyber Pakhtun Khwa, Pakistan. Aquifer lithology in the eastern part of the study area is dominated by coarse sand and gravel whereas the western part is characterized by fine sand. An attempt has been made to estimate the hydraulic conductivity of the aquifer system by establishing a relationship between the pumping test results and vertical electrical soundings by using regression technique. The relationship is applied to the area along the resistivity profiles where boreholes are not drilled. Our findings show a good match between pumped hydraulic conductivity and estimated hydraulic conductivity. In case of sparse borehole data, regression technique is useful in estimating hydraulic properties for aquifers with varying lithology.     

Multipoint source method in air pollution modelling of cold start emission

The paper presents a new method of air pollution modelling on a micro scale. For estimation of concentration of car exhaust pollutants, each car is treated as an instantaneous moving emission source. This approach enables us to model time and spatial changes of emission, especially during cold and cool start of an engine. These stages of engine work are a source of significant pollution concentration in urban areas. In this work, two models are proposed: one for the estimation of emission after cold start of the engine and another for the prediction of pollutant concentration. The first model (defined for individual exhaust gas pollutants) enables us to calculate the emission as a function of time after the cold or cool start, ambient temperature and average speed of motion. This model uses the HBEFA database. The second mathematical model is developed in order to calculate the pollutant dispersion and concentrations. The finite volume method is applied to discretise the set of partial differential equations describing wind flow and pollutant dispersion in the domain considered. Models presented in this paper can be called short-term models on a small spatial scale. The results of numerical simulation of pollutant emission and dispersion are also presented.     

Modelling the Distribution and Quality of Sand and Gravel Resources in 3D: a Case Study in the Thames Basin,UK

Three-dimensional (3D) models are often utilised to assess the presence of sand and gravel deposits. Expanding these models to provide a better indication of the suitability of the deposit as aggregate for use in construction would be advantageous. This, however, leads to statistical challenges. To be effective, models must be able to reflect the interdependencies between different criteria (e.g. depth to deposit, thickness of deposit, ratio of mineral to waste, proportion of ‘fines’) as well as the inherent uncertainty introduced because models are derived from a limited set of boreholes in a study region. Using legacy borehole data collected during a systematic survey of sand and gravel deposits in the UK, we have developed a 3D model for a 2400 km² region close to Reading, southern England. In developing the model, we have reassessed the borehole grading data to reflect modern extraction criteria and explored the most suitable statistical modelling technique. The additive log-ratio transform and the linear model of coregionalization have been applied, techniques that have been previously used to map soil texture classes in two dimensions, to assess the quality of sand and gravel deposits in the area. The application of these statistical techniques leads to a model which can be used to generate thousands of plausible realisations of the deposit which fully reflect the extent of model uncertainty. The approach offers potential to improve regional-scale mineral planning by providing an enhanced understanding of sand and gravel deposits and the extent to which they meet current extraction criteria.

     

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.