Assessing the ecological condition of streams in a southeastern Brazilian basin using a probabilistic monitoring design

Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodiversity and habitat. We assessed the ecological condition of streams in a southeastern Brazilian basin. We quantified the percentage of stream length in good, fair, and poor ecological condition according to benthic macroinvertebrate assemblage. We assessed the risk of finding degraded ecological condition associated with degraded aquatic riparian physical habitat condition, watershed condition, and water quality. We describe field sampling and implementation issues encountered in our survey and discuss design options to remedy them. Survey sample sites were selected using a spatially balanced, stratified random design, which enabled us to put confidence bounds on the ecological condition estimates derived from the stream survey. The benthic condition index indicated that 62 % of stream length in the basin was in poor ecological condition, and 13 % of stream length was in fair condition. The risk of finding degraded biological condition when the riparian vegetation and forests in upstream catchments were degraded was 2.5 and 4 times higher, compared to streams rated as good for the same stressors. We demonstrated that the GRTS statistical sampling method can be used routinely in Brazilian rain forests and other South American regions with similar conditions. This survey establishes an initial baseline for monitoring the condition and trends of streams in the region.     

Predicting Water Quality Impaired Stream Segments using Landscape-Scale Data and a Regional Geostatistical Model: A Case Study in Maryland

In the United States, probability-based water quality surveys are typically used to meet the requirements of Section 305(b) of the Clean Water Act. The survey design allows an inference to be generated concerning regional stream condition, but it cannot be used to identify water quality impaired stream segments. Therefore, a rapid and cost-efficient method is needed to locate potentially impaired stream segments throughout large areas. We fit a set of geostatistical models to 312 samples of dissolved organic carbon (DOC) collected in 1996 for the Maryland Biological Stream Survey using coarse-scale watershed characteristics. The models were developed using two distance measures, straight-line distance (SLD) and weighted asymmetric hydrologic distance (WAHD). We used the Corrected Spatial Akaike Information Criterion and the mean square prediction error to compare models. The SLD models predicted more variability in DOC than models based on WAHD for every autocovariance model except the spherical model. The SLD model based on the Mariah autocovariance model showed the best fit (r² = 0.72). DOC demonstrated a positive relationship with the watershed attributes percent water, percent wetlands, and mean minimum temperature, but was negatively correlated to percent felsic rock type. We used universal kriging to generate predictions and prediction variances for 3083 stream segments throughout Maryland. The model predicted that 90.2% of stream kilometers had DOC values less than 5 mg/l, 6.7% were between 5 and 8 mg/l, and 3.1% of streams produced values greater than 8 mg/l. The geostatistical model generated more accurate DOC predictions than previous models, but did not fit the data equally well throughout the state. Consequently, it may be necessary to develop more than one geostatistical model to predict stream DOC throughout Maryland. Our methodology is an improvement over previous methods because additional field sampling is not necessary, inferences about regional stream condition can be made, and it can be used to locate potentially impaired stream segments. Further, the model results can be displayed visually, which allows results to be presented to a wide variety of audiences easily.     

A Framework for Comprehensive,Integrated, Watershed Monitoring in New York City

The International Life SciencesInstitute (ILSI) Risk Science Institute (RSI) convenedan expert panel of scientists to developrecommendations for a comprehensive monitoring programfor the Croton and Catskill/Delaware watersheds, whichprovide drinking water to New York City's residents. This effort was conducted as part of efforts topreserve and enhance the quality of New York City'sreservoir system through a watershed protectionprogram. The panel developed recommendations for astrategic framework on which to construct a monitoringprogram. As part of this activity, the paneldetermined whether existing monitoring activities weredeficient and, where activities were deficient, thepanel developed recommendations for additionalinformation that should be collected.The panel recommended the development and use of anintegrated approach to watershed monitoring, whichdraws on modeling, risk-based planning and analysis,statistical sampling and design, and basic compliancemonitoring. The approach should be designed toprovide an assessment of natural and anthropogenicsources of stress to the system as well as anassessment of water quality trends in response tostresses acting in concert, both over the long termand over the five-year New York City Memorandum ofAgreement (MOA) assessment time frame. It should alsoprovide an assessment of the human health andenvironmental risks posed by a variety of stressors,and the impact of management actions implemented toameliorate stressors.     

Integrating probabalistic and targeted compliance monitoring for comprehensive watershed assessment

Environmental monitoring typically falls into one of two broad categories. Targeted designs, utilizing fixed stations, focus on describing and quantifying impacts, tracking trends, and assessing compliance with regulatory guidelines or limits. Probabilistic designs, in contrast, draw sampling stations at random from an area or region, and the stations are used to describe conditions in the region of interest based on a subpopulation of sites. These two design approaches are usually viewed as mutually exclusive, with randomized designs used for broader regional assessments of overall ambient condition and targeted designs for demonstrating regulatory compliance and/or characterizing specific, localized impacts. Combining elements of both approaches into a single design provides benefits not available from either design alone. Embedding targeted monitoring within the framework of a probabilistic design enables data from targeted stations to be viewed in a more accurate regional context and provides a consistent background against which to identify characteristic regional patterns of contamination and impact. We use the San Gabriel River Regional Monitoring Program, recently implemented in southern California, to illustrate the structure of a hybrid design and how it enables data analyses and assessments that provide a more complete picture of conditions in the watershed. For example, the hybrid design showed that approximately 80% of the metals levels at compliance sites were below the 25th percentile of the overall watershed condition as indicated by the probabilistic sampling.     

Probabilistic risk assessment of insecticide concentrations in agricultural surface waters: a critical appraisal

Due to the specific modes of action and application patterns of agricultural insecticides, the insecticide exposure of agricultural surface waters is characterized by infrequent and short-term insecticide concentration peaks of high ecotoxicological relevance with implications for both monitoring and risk assessment. Here, we apply several fixed-interval strategies and an event-based sampling strategy to two generalized and two realistic insecticide exposure patterns for typical agricultural streams derived from FOCUS exposure modeling using Monte Carlo simulations. Sampling based on regular intervals was found to be inadequate for the detection of transient insecticide concentrations, whereas event-triggered sampling successfully detected all exposure incidences at substantially lower analytical costs. Our study proves that probabilistic risk assessment (PRA) concepts in their present forms are not appropriate for a thorough evaluation of insecticide exposure. Despite claims that the PRA approach uses all available data to assess exposure and enhances risk assessment realism, we demonstrate that this concept is severely biased by the amount of insecticide concentrations below detection limits and therefore by the sampling designs. Moreover, actual insecticide exposure is of almost no relevance for PRA threshold level exceedance frequencies and consequential risk assessment outcomes. Therefore, we propose a concept that features a field-relevant ecological risk analysis of agricultural insecticide surface water exposure. Our study quantifies for the first time the environmental and economic consequences of inappropriate monitoring and risk assessment concepts used for the evaluation of short-term peak surface water pollutants such as insecticides.     

瓯江源头区龙泉溪底栖大型无脊椎动物多样性和群落特征

源头区溪流是河流生态系统最脆弱的部分,也是淡水底栖大型无脊椎动物(简称底栖动物)集中分布的热点区域,在流域物种库的形成和生态系统的多样性维持过程中具有不可忽视的作用。然而,目前国内对源头区溪流底栖动物多样性的系统调查研究较少。笔者对位于浙江省丽水市瓯江源头区的龙泉溪进行了底栖动物多样性调查研究,分别于2021年丰水期和平水期在覆盖龙泉溪主要山溪河流的18个样点采样,共采集获得底栖动物标本3 700余号。通过联合使用传统形态分类和DNA条形码技术,共鉴定出底栖动物165种,隶属5门、9纲、19目、68科、124属。联合使用DNA条形码可使底栖动物科、种水平的分辨力提升28.3%和34.1%。调查研究表明:龙泉溪底栖动物多样性丰富,物种组成以节肢动物为主(占比高达87.9%,145种),其中水生昆虫占绝大多数(共计8目、48科、140种,占84.8%),主要优势种为鞘翅目的狭溪泥甲属1种Stenelmis sp.1、毛翅目的纹石蛾属Hydorpsyche和短脉纹石蛾属Cheumatopsyche各1种;底栖动物群落多样性丰富,且在丰水期和平水期均维持在较高的水平;海拔和底质类型等微生境条件对底栖动物多样性分布的影响分析显示,底质类型对底栖动物分布密度的影响显著。对水生态状况的生物评估结果显示:Biotic Index污染生物指数更适合龙泉溪流域的水质健康状况评估,龙泉溪流域整体的水生态状况健康,水质属清洁或极清洁。该研究使用传统形态学和DNA条形码技术相结合的鉴定方式,提高了底栖动物物种鉴定的精度,所获得的多样性调查和水质评价结果为瓯江源头区溪流乃至整个流域的生态保护和长期监测提供了本底基础资料。     

Impact of sampling strategy on stream load estimates in till landscape of the Midwest

Accurately estimating various solute loads in streams during storms is critical to accurately determine maximum daily loads for regulatory purposes. This study investigates the impact of sampling strategy on solute load estimates in streams in the US Midwest. Three different solute types (nitrate, magnesium, and dissolved organic carbon (DOC)) and three sampling strategies are assessed. Regardless of the method, the average error on nitrate loads is higher than for magnesium or DOC loads, and all three methods generally underestimate DOC loads and overestimate magnesium loads. Increasing sampling frequency only slightly improves the accuracy of solute load estimates but generally improves the precision of load calculations. This type of investigation is critical for water management and environmental assessment so error on solute load calculations can be taken into account by landscape managers, and sampling strategies optimized as a function of monitoring objectives.     

Determining Ecoregions for Environmental and GMO Monitoring Networks

A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.     

Using variance components to estimate power in a hierarchically nested sampling design

We used variance components to assess allocation of sampling effort in a hierarchically nested sampling design for ongoing monitoring of early life history stages of the federally endangered Devils Hole pupfish (DHP) (Cyprinodon diabolis). Sampling design for larval DHP included surveys (5 days each spring 2007–2009), events, and plots. Each survey was comprised of three counting events, where DHP larvae on nine plots were counted plot by plot. Statistical analysis of larval abundance included three components: (1) evaluation of power from various sample size combinations, (2) comparison of power in fixed and random plot designs, and (3) assessment of yearly differences in the power of the survey. Results indicated that increasing the sample size at the lowest level of sampling represented the most realistic option to increase the survey’s power, fixed plot designs had greater power than random plot designs, and the power of the larval survey varied by year. This study provides an example of how monitoring efforts may benefit from coupling variance components estimation with power analysis to assess sampling design.     

我国流域水生态完整性评价方法构建

流域水生态完整性评价是指通过对水生态系统中不同水生态指标(生物和非生物)的监测以及由数学方法综合形成的综合评价指数,来反映水生态系统完整性状况。近年来,世界各国水环境管理政策发生了变化,开始强调生态保护,重视水体的生态质量。中国现行的常规理化监测指标(如COD、氨氮、BOD5)很难满足水环境管理的需求,难以全面准确地反映水环境质量变化的趋势。因此,在借鉴欧美发达国家流域水生态完整性评价方法的基础上,结合中国目前监测现状以及流域水环境管理需求,构建了包括物理生境指标、理化指标、水生生物指标在内的流域水生态完整性监测与评价方法,以期为中国流域水质目标管理技术体系的业务化运行提供可资借鉴的技术支撑,实现从单一的化学指标监测转向综合的水生态系统监测,实现流域水生态完整性的监测与评价。     

Addressing statistical and operational challenges in designing large-scale stream condition surveys

Implementing a statistically valid and practical monitoring design for large-scale stream condition monitoring and assessment programs can be difficult due to factors including the likely existence of a diversity of ecosystem types such as ephemeral streams over the sampling domain; limited resources to undertake detailed monitoring surveys and address knowledge gaps; and operational constraints on effective sampling at monitoring sites. In statistical speak, these issues translate to defining appropriate target populations and sampling units; designing appropriate spatial and temporal sample site selection methods; selection and use of appropriate indicators; and setting effect sizes with limited ecological and statistical information about the indicators of interest. We identify the statistical and operational challenges in designing large-scale stream condition surveys and discuss general approaches for addressing them. The ultimate aim in drawing attention to these challenges is to ensure operational practicality in carrying out future monitoring programs and that the resulting inferences about stream condition are statistically valid and relevant.     

水生态环境质量评价体系研究

流域水生态环境质量评价体系是为流域环境管理提供基础数据,协助管理者开展流域保护措施的重要技术支持。该文深入剖析了发达国家典型水生态环境质量评价体系,归纳分析了其体系框架、构成特点、方法适用性和借鉴意义。结合前期研究基础,对评价体系的技术内容进行了完善和补充,明确了参照点位的选择原则,补充了评价方法选择的技术路线,提出了增设和实施不同监测计划的方案,最终提出生态环境质量评价技术体系框架。     

Application of the probability-based Maryland Biological Stream Survey to the state’s assessment of water quality standards

The Clean Water Act presents a daunting task for states by requiring them to assess and restore all their waters. Traditional monitoring has led to two beliefs: (1) ad hoc sampling (i.e., non-random) is adequate if enough sites are sampled and (2) more intensive sampling (e.g., collecting more organisms) at each site is always better. We analyzed the 1,500 Maryland Biological Stream Survey (MBSS) random sites sampled in 2000–2004 to describe the variability of Index of Biotic Integrity (IBI) scores at the site, reach, and watershed scales. Average variability for fish and benthic IBI scores increased with increasing spatial scale, demonstrating that single site IBI scores are not representative at watershed scales and therefore at best 25% of a state’s stream length can be representatively sampled with non-random designs. We evaluated the effects on total taxa captured and IBI precision of sampling for twice as many benthic macroinvertebrates at 73 MBSS sites with replicate samples. When sampling costs were fixed, the precision of the IBI decreased as the number of sites had to be reduced by 15%. Only 1% more taxa were found overall when the 73 sites where combined. We concluded that (1) comprehensive assessment of a state’s waters should be done using probability-based sampling that allows the condition across all reaches to be inferred statistically and (2) additional site sampling effort should not be incorporated into state biomonitoring when it will reduce the number of sites sampled to the point where overall assessment precision is lower.     

A Water Quality Monitoring Network Design Methodology for the Selection of Critical Sampling Points: Part I

The principal instrument to temporally and spatially manage water resources is a water quality monitoring network. However, to date in most cases, there is a clear absence of a concise strategy or methodology for designing monitoring networks, especially when deciding upon the placement of sampling stations. Since water quality monitoring networks can be quite costly, it is very important to properly design the monitoring network so that maximum information extraction can be accomplished, which in turn is vital when informing decision-makers. This paper presents the development of a methodology for identifying the critical sampling locations within a watershed. Hence, it embodies the spatial component in the design of a water quality monitoring network by designating the critical stream locations that should ideally be sampled. For illustration purposes, the methodology focuses on a single contaminant, namely total phosphorus, and is applicable to small, upland, predominantly agricultural-forested watersheds. It takes a number of hydrologic, topographic, soils, vegetative, and land use factors into account. In addition, it includes an economic as well as logistical component in order to approximate the number of sampling points required for a given budget and to only consider the logistically accessible stream reaches in the analysis, respectively. The methodology utilizes a geographic information system (GIS), hydrologic simulation model, and fuzzy logic.     

Integrating sentinel watershed-systems into the monitoring and assessment of Minnesota’s (USA) waters quality

Section 303(d) of the Clean Water Act requires States and Tribes to list waters not meeting water quality standards. A total maximum daily load must be prepared for waters identified as impaired with respect to water quality standards. Historically, the management of pollution in Minnesota has been focused on point-source regulation. Regulatory effort in Minnesota has improved water quality over the last three decades. Non-point source pollution has become the largest driver of conventional 303(d) listings in the 21st century. Conventional pollutants, i.e., organic, sediment and nutrient imbalances can be identified with poor land use management practices. However, the cause and effect relationship can be elusive because of natural watershed-system influences that vary with scale. Elucidation is complex because the current water quality standards in Minnesota were designed to work best with water quality permits to control point sources of pollution. This paper presents a sentinel watershed-systems approach (SWSA) to the monitoring and assessment of Minnesota waterbodies. SWSA integrates physical, chemical, and biological data over space and time using advanced technologies at selected small watersheds across Minnesota to potentially improve understanding of natural and anthropogenic watershed processes and the management of point and non-point sources of pollution. Long-term, state-of-the-art monitoring and assessment is needed to advance and improve water quality standards. Advanced water quality or ecologically-based standards that integrate physical, chemical, and biological numeric criteria offer the potential to better understand, manage, protect, and restore Minnesota’s waterbodies.     

Critical Sampling Points Methodology: Case Studies of Geographically Diverse Watersheds

Only with a properly designed water quality monitoring network can data be collected that can lead to accurate information extraction. One of the main components of water quality monitoring network design is the allocation of sampling locations. For this purpose, a design methodology, called critical sampling points (CSP), has been developed for the determination of the critical sampling locations in small, rural watersheds with regard to total phosphorus (TP) load pollution. It considers hydrologic, topographic, soil, vegetative, and land use factors. The objective of the monitoring network design in this methodology is to identify the stream locations which receive the greatest TP loads from the upstream portions of a watershed. The CSP methodology has been translated into a model, called water quality monitoring station analysis (WQMSA), which integrates a geographic information system (GIS) for the handling of the spatial aspect of the data, a hydrologic/water quality simulation model for TP load estimation, and fuzzy logic for improved input data representation. In addition, the methodology was purposely designed to be useful in diverse rural watersheds, independent of geographic location. Three watershed case studies in Pennsylvania, Amazonian Ecuador, and central Chile were examined. Each case study offered a different degree of data availability. It was demonstrated that the developed methodology could be successfully used in all three case studies. The case studies suggest that the CSP methodology, in form of the WQMSA model, has potential in applications world-wide.     

Agriculture and elevation are the main factors for Pampasic stream habitat and water quality

Streams of the Pampasic plain in Southeastern South America are ecosystems affected by both water pollution and habitat alteration mainly due to agricultural activity. Water quality is influenced by the quality of habitats and both depend on land use and watershed morphology. The objective of this study was to determine the relationship between the variables of four factors: (1) the morphology of the watershed, (2) land use in the watershed, (3) river habitat, and (4) water quality of wadeable streams in Uruguay, as well as to determine the most representative variables to quantify such factors. We studied 28 watersheds grouped into three ecoregions and four principal activities, which generated seven zones with three to five streams each. Correlations between the variables of each factor allowed reducing the total number of variables from 57 to 32 to perform principal component analyses (PCA) by factor, reducing the number of variables to 18 for a general PCA. The first component was associated with water quality and elevation. The second was associated with the stream and watershed size, the third with habitat quality, and the fourth to the use of neighboring soils and objects in the channel. Our results indicate that agricultural intensity and elevation are the main factors associated with the habitat and water quality of these lowland streams. These factors must be especially considered in the development of water quality monitoring programs.     

美国EPA地表水质监测与评估的点位设计介绍

介绍了美国EPA地表水质监测与评估的点位设计。首先,指导性文件《基本水质监测方案》中的环境监测计划要求建立1个不少于1 000个点位的国家地表水质环境监测网,并提出了点位设计的标准,包括4点基本要求和针对每一类水域的具体要求。其次,另一指导性文件《准备州综合水质评估(305b报告)和电子升级:报告内容的准则》提出了1种新的对水质的综合性评估技术,要求在传统的判断点位设计的基础上增加概率统计点位设计方法。最后,全国一致的概率统计点位设计是相当有效的获知全国范围的水质情况及变化趋势的方法,EPA完全支持通过这种概率统计点位设计的方法来评估更多的水质状况。概率统计点位设计是EPA地表水质监测与评估的点位设计的发展趋势。     

水环境监测信息集成、共享与决策支持平台构建

以水环境监测数据可靠传输交换与集成、信息规范化处理分析、高效共享与决策支持为应用主线,对水环境监测信息集成、共享与决策支持平台的建设目标、总体架构、主要功能进行了研究,设计了平台的总体架构及主要功能,以实现涉水部门水环境信息的采集、传输、交换、存储、分析、发布、共享、展现等,为环境管理与决策人员、为公众、为各级(国家级流域级省级地市级县级)环境监测业务人员提供信息支撑。     

Evaluating Integrated Watershed Management using multiple criteria analysis—a case study at Chittagong Hill Tracts in Bangladesh

Criteria and indicators assessment is one of the ways to evaluate management strategies for mountain watersheds. One framework for this, Integrated Watershed Management (IWM), was employed at Chittagong Hill Tracts region of Bangladesh using a multi-criteria analysis approach. The IWM framework, consisting of the design and application of principles, criteria, indicators, and verifiers (PCIV), facilitates active participation by diverse professionals, experts, and interest groups in watershed management, to explicitly address the demands and problems to measure the complexity of problems in a transparent and understandable way. Management alternatives are developed to fulfill every key component of IWM considering the developed PCIV set and current situation of the study area. Different management strategies, each focusing on a different approach (biodiversity conservation, flood control, soil and water quality conservation, indigenous knowledge conservation, income generation, watershed conservation, and landscape conservation) were assessed qualitatively on their potential to improve the current situation according to each verifier of the criteria and indicator set. Analytic Hierarchy Process (AHP), including sensitivity analysis, was employed to identify an appropriate management strategy according to overall priorities (i.e., different weights of each principle) of key informants. The AHP process indicated that a strategy focused on conservation of biodiversity provided the best option to address watershed-related challenges in the Chittagong Hill Tracts, Bangladesh.