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.     

Pesticide Impact Rating Index – A Pesticide Risk Indicator for Water Quality

Pesticide users, natural resource managers, regulators, government agencies and many others are concerned about the off-site impact of pesticides on the environment. Systematic methods of the assessment of potential risk of pesticides to environmental components can serve as valuable tools in decision making and policy formulation. Simple risk indicators have been developed which cover a range of scenarios such as toxicity to organisms, health of farm workers, consumer health, and residues in harvested produce. The authors have developed a software package named Pesticide Impact Rating Index (PIRI) that outputs an improved pesticide risk indicator for water quality. PIRI is a standalone, user-friendly, platform-independent program. It can be used to (i) rank pesticides in terms of their relative pollution potential to groundwater or surface water, and (ii) to compare different land uses in a catchment or at a regional scale in terms of their relative impact on water quality. It is based on pesticides use; the pathway through which the pesticides are released to the water resources (drift, runoff, erosion, leaching) and the value of the water resources threatened. Each component is quantified using pesticide characteristics (including toxicity to organisms at different trophic levels, i.e. fish, daphnia, algae, etc.), environmental and site conditions (e.g. organic carbon content of soil, water input, slope of land, soil loss, recharge rate, depth of water table, etc.). This paper describes two case studies of the application of PIRI in Australia. The comparison of the risk assessment by PIRI on these revealed that PIRI correctly estimated the pollution potential of pesticides in greater than 80% of cases. A GIS version of PIRI is described in a companion paper in this volume. An erratum to this article is available at .     

垃圾焚烧飞灰中重金属的固化/稳定化处理实验研究

研究了城市生活垃圾焚烧-电灰的特性及飞灰中重金属的特性,对利用水泥作粘结剂进行飞灰固化/稳定化处理效果开展了系统的实验研究,分析了水泥固化/稳定化飞灰的工艺特点和最佳工艺参数,并讨论了粘结剂固化飞灰机理以及重金属浸出毒性,为进一步研究城市生活垃圾焚烧飞灰的无害化处理与利用提供了有重要价值的参考依据.     

污染物排放相关指标计算方法的研究

针对传统的污染排放数据指标计算方法存在的问题,提出污染物排放指标应根据排污强度和经济指标确定的新思路,同时提出污染物排放指标数据的快速测算模型设计.建议通过环境监测数据或物料衡算数据确定每个排污单位的平均排污强度,作为计算机处理的参数,再由该排污单位申报每月的经济指标(产量或产值),输入计算机计算其产污量、排污量和去除量.实施计算机管理的关键是选取适当的数据计算模型.新思路应该能够规范计算程序,建立污染源动态数据库,对排污数据实行有效的统计分析.     

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.     

Connecting the Dots: Public Engagement with Environmental Data

Air pollution and other environmental hazards are often imperceptible and need to be made publicly visible. The paper argues for the importance of visualizations in drawing public attention to imperceptible hazards and in providing the public with access to empirical data describing the risks. It also argues for critical inquiry into hazards’ selective visibility as it is produced by visualizations. The impact of visualizations and their selective visibility are considered through the example of a public art project called Particle Falls installed in 2014 in Pittsburgh, a city with a long history of both ignoring air pollution and working to ameliorate this problem. I examine the impact and selective visibility of Particle Falls by considering the underlying production of data, as well as context and support systems for this visualization, and by comparing it with other visualizations of local air quality.     

Conservation implications of physiological carry‐over effects in bats recovering from white‐nose syndrome

Although it is well documented that infectious diseases can pose threats to biodiversity, the potential long‐term consequences of pathogen exposure on individual fitness and its effects on population viability have rarely been studied. We tested the hypothesis that pathogen exposure causes physiological carry‐over effects with a pathogen that is uniquely suited to this question because the infection period is specific and time limited. The fungus Pseudogymnoascus destructans causes white‐nose syndrome (WNS) in hibernating bats, which either die due to the infection while hibernating or recover following emergence from hibernation. The fungus infects all exposed individuals in an overwintering site simultaneously, and bats that survive infection during hibernation clear the pathogen within a few weeks following emergence. We quantified chronic stress during the active season, when bats are not infected, by measuring cortisol in bat claws. Free‐ranging Myotis lucifugus who survived previous exposure to P. destructans had significantly higher levels of claw cortisol than naïve individuals. Thus, cryptic physiological carry‐over effects of pathogen exposure may persist in asymptomatic, recovered individuals. If these effects result in reduced survival or reproductive success, they could also affect population viability and even act as a third stream in the extinction vortex. For example, significant increases in chronic stress, such as those indicated here, are correlated with reduced reproductive success in a number of species. Future research should directly explore the link between pathogen exposure and the viability of apparently recovered populations to improve understanding of the true impacts of infectious diseases on threatened populations.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River,Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.     

制革废水和印染废水的综合毒性评估及鉴别

研究采用成组生物毒性试验(发光菌急性毒性、斑马鱼幼鱼急性毒性,斑马鱼胚胎发育毒性和小球藻急性毒性),结合理化指标,通过毒性单位、平均毒性(average toxicity,Av Tx)、毒性指数(toxic print,Tx Pr)、最敏感的测试(most sensitive test,MST)和潜在毒性效应指数(potential ecotoxic effects probe,PEEP)对不同工艺阶段印染及制革废水进行毒性削减评估.结果表明PEEP能兼顾废水排放量与毒性效应,更为客观地表征了废水综合毒性,PEEP评价结果显示制革废水和印染废水的毒性削减率分别达到36.8%和23.2%.最后,以发光菌作为受试生物,采用毒性鉴别评估(toxicity identification evaluation,TIE)技术,对印染废水进行毒性鉴别.结果表明,印染废水中主要的致毒物质为非极性有机污染,其次为可滤性化合物,然后是重金属、氧化性物质以及挥发性物质.