AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.     

溶出伏安法中电极的操作技术

电极性能的优劣是完成溶出伏安分析的关键,本文就三电极体系中电极的选择、处理、安装、使用、维护方法等方面作了较详细的说明和探讨,提高了方法的精密度和准确度,使溶出伏安法在海水分析中得到更好的应用.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

Efficacy of created and restored nesting sites for the conservation of colonial Laridae in the South of France

By rapidly modifying key habitat components, habitat restoration is at risk of producing attractive cues for animals without providing habitats of sufficient quality. As such, individual fitness components, such as reproduction, could be reduced and restored habitats could become ecological traps. This risk notably appears by using artificial constructions in restoration projects, yet few studies have evaluated their efficacy in a robust way. We investigated this by analyzing 154 islets that were created or restored to improve the conservation status of 7 colonial Laridae species in the South of France. From 2007 to 2016, we compared occupancy dynamics and breeding parameters of these species between the restored sites and 846 unmanaged nesting sites. We also explored species’ preference for different nesting site characteristics and their respective effect on breeding parameters. Restored nesting sites were 2–9 times as attractive as unmanaged sites for all species except the Black-headed Gull (Chroicocephalus ridibundus). Colonization probability was up to 100 times higher in sites already used by other species the previous year and increased with distance to the shore until >0.2 when distance was over 250 m. Abandonment probability was 29–70% lower when breeding was successful the previous year in all species except the Sandwich Tern (Thalasseus sandvicensis). Productivity and breeding success probability were 2 times higher on managed sites. Distance from the shore was an important attractive characteristic of artificial nesting sites in all species. Other nesting site characteristics had species-specific effects on colonization, abandonment, and breeding success. Our results indicate that managed nesting sites are successful conservation tools for colonial Laridae in the Mediterranean and do not act as ecological traps. Our study showed that testing the ecological trap hypothesis is a robust way to evaluate the success of restoration projects of breeding habitats.     

罕见冬季降雨中人工增雨微物理过程分析研究

用Micaps实时资料、CPAS卫星反演分析资料、NCEP再分析资料、ECMWF再分析资料,多普勒雷达PUP产品资料,对2015年12月1日夜间至2日凌晨沈阳地区罕见冬季降雨过程,进行了天气学分析、及大气微物理人工增雨作业条件分析,并结合沈阳地区人工增雨作业指标,得出本次降雨过程在厄尔尼诺正在发生的背景下,为常见的高空槽转东北冷涡型,水汽、动力等微物理作业条件也适合于开展人工增雨作业,并给出了相应的作业指导参数,为沈阳地区今后在冬季降雨天气过程中开展人工增雨作业积累了宝贵经验.     

ABC算法优化SVR的磨损故障预测模型

目的为了提高故障预测的精度,针对支持向量回归SVR(Support vector machine for regression,SVR)参数选择困难的问题,提出一种采用人工蜂群(artificial bee colony,ABC)算法优化支持向量回归(SVR)的故障预测模型(ABC-SVR)。方法该模型先对样本数据进行重构,然后将故障预测误差(适应度)作为优化目标,通过ABC算法寻优找到最优的SVR参数,建立故障预测模型。最后通过实例仿真验证模型的优越性。结果采用ABC算法优化的SVR故障预测模型进行时间序列预测,能够较好地跟踪发动机滑油金属元素浓度的变化过程,并且能够提前2个取样时间预测异常情况的出现。结论 ABC-SVR模型有效解决了SVR参数选择难题,能够更加准确地表现故障变化规律,提高了故障预测精度。     

水体系中氧氟沙星的光化学降解研究

研究了高压汞灯和氙灯照射下氧氟沙星(OFLX)在蒸馏水、人工海水和天然海水中的光降解过程,探讨了光源、起始浓度、丙酮、表面活性剂等因素对OFLX光化学降解速率的影响.结果表明,OFLX在高压汞灯下的光反应速率比在氙灯下快得多,均符合一级反应动力学过程;在相同光源下,OFLX在海水中降解最快,其次是人工海水;当OFLX初始浓度为2、4、6mg.L-1时,其光解速率常数分别为0.163、0.140和0.132 min-1,随着OFLX初始浓度增大,其光解率降低;不同浓度的丙酮均能促进OFLX光降解的反应,其反应速率常数为0.084 2～0.102 min-1,且光敏效率与丙酮浓度呈正相关关系;然而当十六烷基三甲基溴化铵(CTAB)、十二烷基苯磺酸钠(SDBS)、吐温-20(TW-20)等表面活性剂的浓度为5 mg.L-1,它们均抑制了水体中OFLX光降解反应的进程.另外,利用金藻8701单种培养进行了OFLX光化学降解前后的毒性试验,表明OFLX光解过程产生风险较高的中间产物,随着光解进行,产物毒性降低.     

舰船海水管路腐蚀状态评估技术研究

目的研究建立舰船海水管路的腐蚀状态评估指标体系及评估方法。方法通过经验选择影响舰船海水管路腐蚀状态的重要指标,并确定相应评估方法、评价标准及权重。结果选择管材腐蚀程度、阴极保护状态、电绝缘保护状态、海水流速控制状态、密封材料密封状态5项参数组成海水管路系统腐蚀状态评估指标体系。结论可选用层次-模糊法对海水管路腐蚀状态进行评估,其中层次分析法(AHP)用来确定评价指标权重,模糊综合评判法用来处理评价指标值。     

海水重金属监测分析方法研究

总结国内外的海水水质重金属的监测分析方法,调查国内海水重金属分析方法,比较各种分析方法的优缺点.得到以下结论：海水中汞、砷、硒的主要分析方法为原子荧光法,此方法具有操作简单、灵敏度高等优点;铜、铅、锌、镉、镍的主要分析方法为原子吸收法,此方法比极谱法具有更好的灵敏度和重现性;总铬和六价铬的分析方法主要为二苯碳酰二肼分光光度法,方法操作简单、易于推广.     

海州湾海洋牧场人工鱼礁投放对营养盐的影响

为了解海州湾海洋牧场人工鱼礁投放对营养盐的影响,基于2008—2015年间共24个航次水质调查资料,分析了海州湾海洋牧场鱼礁区和对照区活性磷酸盐(PO_4~(3-)-P)、活性硅酸盐(SiO_3~(2-)-Si)和溶解无机氮(DIN)的浓度、组成及营养盐结构的变化.同时,比较了鱼礁区和对照区营养盐的变化,初步分析了人工鱼礁投放量与营养盐的相关性,尝试探索人工鱼礁投放对营养盐浓度与结构的影响.结果表明,鱼礁区和对照区PO_4~(3-)-P、SiO_3~(2-)-Si浓度均呈现出秋季夏季春季的特点,且鱼礁区高于对照区.DIN在鱼礁区和对照区也呈现出同样的季节变化特点,但鱼礁区的变化幅度显著大于对照区.海洋牧场人工鱼礁的投放使鱼礁区PO_4~(3-)-P和DIN浓度增加.受热力学平衡的影响,对照区DIN浓度也出现了增加,而PO_4~(3-)-P受人工鱼礁投放的影响小.鱼礁区和对照区SiO_3~(2-)-Si受人工鱼礁投放影响均不明显.另外,海洋牧场DIN组成也发生了改变,2012年前NO_3~--N为DIN主要组成,之后为NH_4~+-N.营养盐结构分析显示,海州湾海洋牧场营养盐对浮游植物主要表现为磷限制.