A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

Analysis of behavioral changes of zebrafish (Danio rerio) in response to formaldehyde using Self-organizing map and a hidden Markov model

Two computational methods were applied to classification of movement patterns of zebrafish (Danio rerio) to elucidate Markov processes in behavioral changes before and after treatment of formaldehyde (0.1 mg/L) in semi-natural conditions. The complex data of the movement tracks were initially classified by the Self-organizing map (SOM) to present different behavioral states of test individuals. Transition probabilities between behavioral states were further evaluated to fit Markov processes by using the hidden Markov model (HMM). Emission transition probability was also obtained from the observed variables (i.e., speed) for training with the HMM. Experimental transition and emission probability matrices were successfully estimated with the HMM for recognizing sequences of behavioral states with accuracy rates in acceptable ranges at central and boundary zones before (77.3-81.2%) and after (70.1-76.5%) treatment. A heuristic algorithm and a Markov model were efficiently combined to analyze movement patterns and could be a means of in situ behavioral monitoring tool.     

Knowledge gain and behavioral change in citizen-science programs

Citizen-science programs are often touted as useful for advancing conservation literacy, scientific knowledge, and increasing scientific-reasoning skills among the public. Guidelines for collaboration among scientists and the public are lacking and the extent to which these citizen-science initiatives change behavior is relatively unstudied. Over two years, we studied 82 participants in a three-day program that included education about non-native invasive plants and collection of data on the occurrence of those plants. Volunteers were given background knowledge about invasive plant ecology and trained on a specific protocol for collecting invasive plant data. They then collected data and later gathered as a group to analyze data and discuss responsible environmental behavior with respect to invasive plants. We tested whether participants without experience in plant identification and with little knowledge of invasive plants increased their knowledge of invasive species ecology, participation increased knowledge of scientific methods, and participation affected behavior. Knowledge of invasive plants increased on average 24%, but participation was insufficient to increase understanding of how scientific research is conducted. Participants reported increased ability to recognize invasive plants and increased awareness of effects of invasive plants on the environment, but this translated into little change in behavior regarding invasive plants. Potential conflicts between scientific goals, educational goals, and the motivation of participants must be considered during program design.     

基于ADuC824的环境监测系统设计与实现

介绍了一种对环境情况进行监测的系统软硬件设计方案.以ADI公司的ADuC824单片机为核心芯片,结合各类传感器和外围元器件构建,系统集成了环境信息采集、信息识别转换、双机通信和微电子电路等多种新技术,采用多通道实时采集数据,并解决了环境参数复杂难数字化的问题,实现了对环境参数全面高效的监测.     

泥石流危险度测试模型与多传感器监测系统

为较准确地预测泥石流的发生,达到防灾减灾的目的,建立一种将多种传感器感知的动态监测信息与地质环境信息相结合的泥石流危险度预测模型。根据泥石流的形成条件和演化机理,量化研究发生泥石流的临界降雨强度、临界倾斜角和临界泥砂堆积层高度。基于该模型,设计并制作由雨量、倾斜、物位3种传感器组成的多传感器监控系统。分析和试验结果表明:该模型和监控系统具有预测泥石流危险度的功能,摄取的信息较全面,准确性更高,时效性更强,置信度较高。     

危险化学品道路运输安全管理现状及发展趋势研究

为降低危化品运输风险,从危化品运输风险评价、道路选线模型、技术应用、应急联动机制及平台建设、统一联控监管平台等方面进行研究分析。通过对微观视角与宏观视角、单一应用与综合应用的归类和对比,进行分析并指出存在的问题。分析表明,获取精确连续数据,考虑多种外在变量来完善评估模型,注重理论、技术和监管资源的综合应用,发展大区域联控平台将是今后研究的发展趋势。     

单兵用主动式听力保护技术研究现状分析

战场噪声是造成单兵听力损伤的重要原因,通常要求单兵处于大于85dBA的噪声环境中需佩戴听力保护装置。听力保护装置通常包括耳罩式和耳塞式。新型单兵用耳塞式听力保护装置具有听力保护、环境声音的监听、持续及脉冲噪声抑制、通信接入等多种功能。     

宝钢环境信息化系统建设探索

系统介绍了宝钢环境信息化系统建设架构、功能、特点,以及对污染减排、环境自动监测及信息化技术进行有效融合后的应用实践,并对该信息化系统在提高环境监控能力,完善系统建设上提出扩展监控范围、提升功能等构想.     

中美固定源烟气排放连续监测系统对比浅析

简述了我国烟气排放连续监测系统(CEMS)概况;介绍了美国CEMS体系及先进的管理经验,并从CEMS运营责任主体、管理依据、审核与管理模式以及数据应用等方面对中美CEMS体系进行了对比分析,在此基础上,提出了我国CEMS存在的问题和相应的对策建议.     

若尔盖湿地生态安全监测方案研究

若尔盖湿地是黄河上游重要的水源涵养地,在涵养水源、调节径流和维持生物多样性等方面具有重要作用,是流域乃至国家生态安全的关键地区.近年来,由于全球气候变化和人类不合理的开发活动导致若尔盖湿地生态退化加剧,威胁区域和流域生态安全.在若尔盖湿地生态退化趋势与生态安全理论框架研究的基础上,对若尔盖湿地生态安全监测的主要内容进行...