时域克里格方法在地表水水质预测中的应用

给出了纯时间域中普通克里格方法(TOK)的基本形式和其变异函数的性质,再依据扎龙湿地5年水体中BOD、DO、COD质量浓度的观测数据,利用该方法对2005—2009年的变化趋势进行了预测,在满足最小方差的条件下,使估计是无偏的。结果表明,这5年内湿地水体中DO和BOD质量浓度变化趋势不明显,但COD质量浓度却明显上升,说明湿地的水质正在发生变化,要减少进入湿地的污水量,加强污水处理,这样才能防止水质的进一步恶化。     

重金属迁移转化模型研究

大量重金属污染物迁移转化的现象和研究成果都表明重金属以泥沙颗粒为载体迁移转化,描述重金属在天然水体中的迁移转化必须紧紧抓住泥沙颗粒运动及重金属与泥沙之间的转化关系进行.为此在对现有的重金属迁移转化数学模型进行概括分类的基础上,根据水沙运动与污染物相互作用关系,分析了泥沙颗粒运动及重金属吸附解吸不平衡过程,并结合水沙数学模型,建立了重金属迁移转化的耦合模型.同时在模型合理性分析的基础上,对模型进行了计算分析,分析表明模型能够合理地反映重金属污染物在水体中的迁移转化过程.     

河流氮转化模型的应用

本文介绍有机氮、氨氮、亚硝酸盐氮和硝酸盐氮在细菌和水生物的作用下,因水体中溶解氧含量不同而互相转化,并由此建立了一元稳态顺序转化与逆向反应和溶解氧两者耦合的水质数学模型,同时用迭代法求出各反应率参数,经实测资料验证,成果精度达到基本要求,可在实际工作中应用。     

基于SPH方法的非饱和多孔介质相变耦合研究

在考虑相变的热能平衡方程和非饱和水分迁移质量控制方程的基础上,建立温度场-水分场的耦合模型,并采用一种无网格粒子算法（SPH）进行数值求解。其中,耦合方程中考虑了水流传热以及温度势对水流的直接驱动,在不考虑相变的情况下,该耦合模型可退化为常温下的水-热耦合模型,故可用于模拟冻融循环的相关问题。从求解热能平衡方程中的含冰量出发,实现解耦并对半无限单向冻结条件下介质内非稳态温度场和体积含水率分布场进行模拟,将耦合作用下的温度场与不耦合的解析解进行对比,反映出水分迁移对温度场存在较大影响。最后,求解了路基边坡在季节性周期温度边界下,温度场、水分场分布的演变规律,并评估了边坡阴阳面受热不均对水热两场分布的影响。计算结果基本能反映土冻结相变的实际物理过程,光滑粒子算法可以用于尝试解决冻土领域的其他相关问题。     

底泥原地稳定化过程中药剂对上覆水体的影响

采用底泥原地稳定化处理技术中的药剂投加方法,对苏州河底泥中投加零价铁(Fe0)、硝酸钙的上覆水体进行为期80 d研究比较.结果表明:投加Fe0后上覆水体的溶解氧(DO)被迅速消耗,体系易形成厌氧环境,而硝酸钙则减缓了上覆水体DO的消耗;投加零价铁或硝酸钙后都会使上覆水体的pH升高,Eh下降;投加Fe0后对上覆水体COD_Cr或TOC的影响较硝酸钙小;此外,两者上覆水体DO、pH和Eh与COD_Cr和TOC之间均具有一定的相关性.     

亚热带典型岩溶区地表溪流溶解无机碳昼夜变化特征及其影响因素

岩溶水体溶解无机碳(DIC)的转化过程是评价岩溶碳汇稳定性及效应的重要指标之一,为了解其在岩溶地下水补给的地表溪流中的变化特征和影响因素,于2013年7月8~14日对广西融安县官村地下河水补给的地表溪流进行7昼夜定位连续监测,利用高分辨率自动监测仪器每15分钟测定pH、溶解氧(DO)、水温(T)、电导率(SpC)等参数,人工每2小时采集水样用于测定常规离子和δ~(13)C_(DIC)等指标。结果表明溪流水体T,pH,DO,SpC,DIC(以HCO_3~-表示),Ca~(2+),δ~(13)C_(DIC),方解石饱和指数(SIc)以及水体二氧化碳分压(pCO_2)等水化学指标均表现出明显的昼夜变化过程。SpC,DIC,Ca~(2+)和pCO_2等指标白天降低,夜间升高;T,pH,DO,δ~(13)C_(DIC)和SIc等指标白天升高,夜间降低。SIc变化范围为0.70~0.89,表明溪流中可能发生了碳酸盐的沉积。通过热力学参数计算表明水温(昼夜变化幅度为5.8℃)对水体pCO_2的昼夜变化影响率为27.48%~54.88%。反映水体水生植物新陈代谢过程(光合作用和呼吸作用过程)的水体DO指标和水体δ~(13)C_(DIC)均在白天上升,夜间下降,而δ~(13)C_(DIC)和水体DIC呈明显负相关关系(R~2=0.71),这也证明溪流水体DIC的变化过程受到水生植物新陈代谢过程的影响,白天水生植物以光合作用为主,消耗DIC,释放O_2,水体δ~(13)C_(DIC)上升;晚上以呼吸作用为主,消耗O_2,释放CO_2,增加DIC,水体δ~(13)C_(DIC)下降,其对水体pCO_2的昼夜变化影响率为45.12%~72.52%。通过研究表明溪流溶解无机碳变化过程受到物理因素(太阳辐射和水温等)和生物作用(呼吸作用和光合作用)的共同影响,这为进一步了解岩溶地下水出露地表后溶解无机碳转化过程及岩溶碳汇稳定性评价提供了依据。     

考虑温度损伤的盐岩蠕变本构关系研究

根据统计力学原理,以分形岩石力学为桥梁,对盐岩在温度与应力耦合作用下蠕变特性进行了研究,导出了考虑围压效应的损伤变量表达式。综合前人的成果,推导出温度–应力耦合下的盐岩损伤方程。对盐岩在温度与三轴应力共同作用下的蠕变试验数据进行研究,分析了盐岩蠕变过程中衰减蠕变阶段、稳态蠕变阶段和加速蠕变阶段的各自特征。对于广义Bingham 蠕变模型在衰减和稳态蠕变阶段引入一非线性函数,在加速蠕变阶段引入损伤,建立了盐岩考虑温度损伤的蠕变本构关系。利用盐岩的三轴蠕变试验数据对新的蠕变损伤模型参数进行辩识与比较分析。结果表明,该模型能够很好地反映在不同温度作用下盐岩的衰减蠕变阶段、稳态蠕变阶段和加速蠕变阶段的规律,验证了该模型的合理性和正确性。     

黄浦江下游段水质参数BOD和DO计算方法初探

BOD和DO是衡量河流水质好坏的两个常用的参数,利用O’connor河口衰减模式,从溶解氧成因分析黄浦江下游吴泾至吴淞段DO与BOD和NOD的相关性,提出有别于Streeter-Phelps(S-P模式)的计算方法,计算结果与实测数据较符合,可以为黄浦江下游段水环境影响评价和容量的计算以及水质目标管理提供服务。     

深井巷道围岩地温场温度分布可视化模拟研究

根据地温场温度分布的数学模型,应用有限元法模拟了深井巷道围岩地温场中4种常见隧道断面的岩石温度分布特征规律,揭示出地温场内温度分布和地热学参数及时间、空间之间的本质关系,实现地温场内温度分布的二维动态等值线表征,直观地再现了地温场内温度分布非稳态变化的动态过程。     

基于热-流-固耦合模型的石油钻井施工过程数值分析

岩土介质多场耦合问题需考虑诸多因素,温度、渗流及应力之间的耦合关系复杂,试验条件不易控制,且难以实现,因此,辅以数值模拟手段具有重要的意义。基于混合物理论,推导出岩土介质温度、渗流和应力耦合的数学模型及其控制方程,提出该数学模型的求解方法,以MATLAB语言为平台,将Abaqus程序作为一个模块嵌入迭代算法程序中,编制了多场耦合分析程序,并给出了2个典型算例验证该方法的有效性和实用性。然后,将建立的多场耦合模型和计算程序应用于石油钻井施工过程的模拟,重点分析井壁围岩内温度场、渗流场和应力场的变化规律,以及钻井液温度的变化对井壁稳定性的影响。研究成果对我国地下石油、核废料储存等工程设计和施工具有一定的指导意义。     

Prediction of water quality parameters of Karoon River (Iran) by artificial intelligence-based models

This paper describes the application of multi-layer perceptron (MLP), radial basis network and adaptive neuro-fuzzy inference system (ANFIS) models for computing dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD) levels in the Karoon River (Iran). Nine input water quality variables including EC, PH, Ca, Mg, Na, Turbidity, PO₄, NO₃ and NO₂, which were measured in the river water, were employed for the models. The performance of these models was assessed by the coefficient of determination R ², root mean square error and mean absolute error. The results showed that the computed values of DO, BOD and COD using both the artificial neural network and ANFIS models were in close agreement with their respective measured values in the river water. MLP was also better than other models in predicting water quality variables. Finally, the sensitive analysis was done to determine the relative importance and contribution of the input variables. The results showed that the phosphate was the most effective parameters on DO, BOD and COD.     

Prediction of water quality from simple field parameters

Water quality parameters like temperature, pH, total dissolved solids (TDS), total suspended solids (TSS), dissolved oxygen (DO), oil and grease, etc., are calculated from the field while parameters like biological oxygen demand (BOD) and chemical oxygen demand (COD) are interpreted through the laboratory tests. On one hand parameters like temperature, pH, DO, etc., can be accurately measured with the exceeding simplicity, whereas on the other hand calculation of BOD and COD is not only cumbersome but also inaccurate many times. A number of previous researchers have tried to use different empirical methods to predict BOD and COD but these empirical methods have their limitations due to their less versatile application. In this paper, an attempt has been made to calculate BOD and COD from simple field parameters like temperature, pH, DO, TSS, etc., using Artificial Neural Network (ANN) method. Datasets have been obtained from analysis of mine water discharge of one of the mines in Jharia coalfield, Jharkhand, India. 73 data sets were used to establish ANN architecture out of which 58 datasets were used to train the network while 15 datasets for testing the network. The results show encouraging similarity between experimental and predicted values. The RMSE values obtained for the BOD and COD are 0.114 and 0.983 %, respectively.     

Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River

Accurate prediction of the chemical constituents in major river systems is a necessary task for water quality management, aquatic life well-being and the overall healthcare planning of river systems. In this study, the capability of a newly proposed hybrid forecasting model based on the firefly algorithm (FFA) as a metaheuristic optimizer, integrated with the multilayer perceptron (MLP-FFA), is investigated for the prediction of monthly water quality in Langat River basin, Malaysia. The predictive ability of the MLP-FFA model is assessed against the MLP-based model. To validate the proposed MLP-FFA model, monthly water quality data over a 10-year duration (2001–2010) for two different hydrological stations (1L04 and 1L05) provided by the Irrigation and Drainage Ministry of Malaysia are used to predict the biochemical oxygen demand (BOD) and dissolved oxygen (DO). The input variables are the chemical oxygen demand (COD), total phosphate (PO₄), total solids, potassium (K), sodium (Na), chloride (Cl), electrical conductivity (EC), pH and ammonia nitrogen (NH₄-N). The proposed hybrid model is then evaluated in accordance with statistical metrics such as the correlation coefficient (r), root-mean-square error, % root-mean-square error and Willmott’s index of agreement. Analysis of the results shows that MLP-FFA outperforms the equivalent MLP model. Also, in this research, the uncertainty of a MLP neural network model is analyzed in relation to the predictive ability of the MLP model. To assess the uncertainties within the MLP model, the percentage of observed data bracketed by 95 percent predicted uncertainties (95PPU) and the band width of 95 percent confidence intervals (d-factors) are selected. The effect of input variables on BOD and DO prediction is also investigated through sensitivity analysis. The obtained values bracketed by 95PPU show about 77.7%, 72.2% of data for BOD and 72.2%, 91.6% of data for DO related to the 1L04 and 1L05 stations, respectively. The d-factors have a value of 1.648, 2.269 for BOD and 1.892, 3.480 for DO related to the 1L04 and 1L05 stations, respectively. Based on the values in both stations for the 95PPU and d-factor, it is concluded that the neural network model has an acceptably low degree of uncertainty applied for BOD and DO simulations. The findings of this study can have important implications for error assessment in artificial intelligence-based predictive models applied for water resources management and the assessment of the overall health in major river systems.     

Water Quality Characteristics and Variations of Lake Dian

In order to understand the seasonal change tendencies of the water quality of the Lake Dian (Dianchi), the monitoring data from April to September 2015 at four sites distributed in the central part from North to south were analyzed, these data includes the profiles of the water temperature (Temperature or Temp.), Dissolved Oxygen content (DO), pH values, Chlorophyll-a (Chl-a), Phycocyanin (PC) and Conductivity (CD). At the same time, the Cyanophyte Relative Quantity Index (CRQI) was calculated based on the contents of Phycocyanin and Chlorophyll-a. The results demonstrate that along with the air temperature increase, the water temperature also increased step by step from April and May, and reach the maximum in June, from July to September, the water temperature kept relatively stable and decrease steadily. It also shows that the water temperature is not only various with different water depth, but also show that the temperature increase at different speed, even generally show that the surface temperature increase more rapidly than the deep water. The water temperature and its changes may adjust the air temperature of Kunming strongly and therefore, it is important for the forming of the Four Springs City of Kunming. We found that the amount of eukaryotes represented by Chlorophyll-a increased quickly and reach the highest level in the April, but the blue-green algae, which represented by the Phycocyanin is blooming in the September. This might imply that when the blue-green algae dominated the algae, the algae blooming occur. This is of great importance to understand the algae blooming processes in Lake Dian. We hope the further monitoring will provide us more detailed and useful information. Mean while, the changes of DO, pH and CD all have shown their unique that inspire us to continue the lake water monitoring. This monitoring work also proves that the single site measurements cannot provide any reliable and useful information about the lake water quality. More detailed and sustained monitoring works need to be done before we have a fully understanding on the changes of the lake water quality.     

溶解氧对零价铁去除水中六价铬的影响

六价铬Cr(Ⅵ)有巨毒性,对人类及生态环境有极大危害,运用纳米零价铁(nZVI)去除水中六价铬是一种快速高效的环境修复手段。前人的研究更多报道了pH值、温度、初始浓度等因素的影响,溶解氧(DO)的存在对于nZVI去除水体中Cr(Ⅵ)的作用却少有研究。在对比普通铁粉和纳米铁对六价铬去除的基础上,着重探讨了溶解氧(DO)对水中六价铬去除效果的影响及作用机制。批实验短期结果表明:由于纳米铁有较大的比表面积和更高的反应活性,导致nZVI的除Cr(Ⅵ)效率明显高于普通铁粉;溶解氧的存在促进了nZVI对Cr(Ⅵ)的去除,这是因为氧化作用产生较多的Fe2+,有利于Cr(Ⅵ)的去除,随着nZVI进一步氧化,产生的针铁矿、磁铁矿等铁氧化物能够进一步吸附Cr(Ⅵ),使得在有氧环境下Cr(Ⅵ)的去除效果好于无氧环境。     

A preliminary study on the environmental condition of the coral reef habitat

The present investigation was carried in coral reef areas of Palk Bay, Madapam. Palk Bay corals were found disturbed by human beings due to oil pollution, waste discharge from processing units and discharge of domestic household wastes from the nearby Mandapam town. Environmental conditions of the coral reef habitat in the Palk Bay, Mandapam was analyzed for a period of six months at fortnightly intervals for March to August 2001 on the coral reef areas. Temperature, pH, Dissolved Oxygen (DO), Biological Oxygen Demand (BOD) and Total Organic Carbon (TOC) were analyzed at five different stations of Palk Bay, Madapam. The maximum mean values of temperature, pH, DO, BOD and TOC for the four experimental and control stations were 32.6°C, 8.7, 7.02ppm, 8.29ppm and 2.13% and 31.5°C, 8.3, 7.98ppm, 5.71ppm and 0.48% respectively. The sampling stations were selected on the basis of their importance.     

Characterisation of the physicochemical qualities of a typical rural-based river: ecological and public health implications

The physicochemical qualities of a typical rural-based river were assessed over a 12-month period from August 2010 to July 2011 spanning the spring, summer, autumn and winter seasons. Water samples were collected from six sampling sites along Tyume River and analysed for total nitrogen, orthophosphate, biochemical oxygen demand (BOD), temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), total dissolved solids (TDS) and turbidity. BOD regimes did not differ significantly between seasons and between sampling points and ranged from 0.78 to 2.76 mg/L across seasons and sampling points, while temperature ranged significantly (P < 0.05) between 6 and 28 °C. Turbidity varied significantly (P < 0.05) from 6 to 281 nephelometric turbidity units while TDS (range 24–209 ppm) and conductivity (range 47.6–408 mg/L) also varied significantly (P < 0.05) across sampling points with a remarkable similarity in their trends. Orthophosphate concentrations varied from 0.06 to 2.72 mg/L across seasons and sampling points. Negative correlations were noted between temperature and the nutrients, DO and temperature (r = ?0.56), and TDS and DO (r = ?0.33). Positive correlations were noted between TDS and temperature (r = 0.41), EC and temperature (r = 0.15), and DO and pH (r = 0.55). All nutrients were positively correlated to each other. Most measured parameters were within prescribed safety guidelines. However, the general trend was that water quality tended to deteriorate as the river flows through settlements, moreso in rainy seasons.     

Water quality parameters along rivers

Water samples have been collected from a part of Surma River along different points and analyzed for various water quality parameters during dry and monsoon periods. Effects of industrial wastes, municipal sewage, and agricultural runoff on river water quality have been investigated. The study was conducted within the Chattak to Sunamganj portion of Surma River, which is significant due to the presence of two major industries-a paper mill and a cement factory. The other significant feature is the conveyors that travel from India to Chattak. This study involves determination of physical, biological and chemical parameters of surface water at different points. The river was found to be highly turbid in the monsoon season. But BOD and fecal coliform concentration was found higher in the dry season. The water was found slightly acidic. The mean values of parameters were Conductivity 84–805μs; DO: dry- 5.52 mg/L, monsoon-5.72 mg/L; BOD: dry-1 mg/L, monsoon-0.878 mg/L; Total Solid: dry-149.4 mg/L, monsoon- 145.7 mg/L. A model study was also conducted and values of different model parameters were estimated.     

2000-2014年蒙古高原植被覆盖时空变化特征及其对地表水热因子的响应

利用MODIS NDVI数据、同期地表水热组合数据和植被类型数据,对2000-2014年蒙古高原生长季和三季（春、夏、秋季）植被覆盖时空演变特征及其对地表水热因子响应模式进行分析。研究表明：这15 a来,蒙古高原生长季及三季归一化植被指数NDVI均呈增加趋势,且呈显著增加趋势区域主要集中在内蒙古地区,一定程度上反映了该地区生态恢复工程的有效性。研究区植被覆盖变化与地表水分指数LSWI有密切的关系,因此证明研究区植被覆盖的增加归因于自然和人为因素的共同作用。不同类型植被NDVI均呈增加趋势,其中荒漠植被NDVI增加最明显,森林植被增加平缓,且存在季节性差异。此外,不同类型植被NDVI受水热因子影响也存在季节性差异。     

北极斯瓦尔巴德群岛中部海域表层海水水质研究

掌握北极海水水质特征及地域分布等第一手数据对北极科考意义重大。该项研究工作是全国青少年北极科考子任务,于2017年夏季在北极斯瓦尔巴德群岛中部海域对表层海水水质特征、地域差异及相关控制因素进行了研究。选取了6个区域共40个采样点采集表层海水样本,从温度、酸碱度、电导率、溶解性总固体量、实际盐度和溶解氧饱和度等方面进行了水质特征测量分析,发现该海域6个区域在海水温度、电导率、溶解性总固体量、实际盐度及溶解氧饱和度等方面均有较大差异,而酸碱度差异不大: 北部冰区水温最低,溶解性总固体量最低,溶解氧含量较高; 西北部海湾溶解氧饱和度最高; 中部海峡溶解性总固体量最高,盐度和电导率最低; 南部海域水温最高,实际盐度和电导率最高,溶解氧饱和度最低; 东部沿海水温偏低。采样点地理位置、洋流情况、地形地貌等因素对表层海水水质均有影响。这些研究成果对补充我国在北极地区的第一手科考数据和进行深入的科考研究具有重要意义。