Soil quality at a national scale in New Zealand

New Zealand is a signatory to international conventions on environmental performance, and soil quality information is needed for reporting both at a national and regional level. Soil quality was measured at 222 sites in five regions of New Zealand (12 soil orders and 9 land-use categories). Topsoil (0-100 mm) properties measured were total carbon and nitrogen, potentially mineralizable N, pH, Olsen P, cation exchange capacity, bulk density, total porosity, macroporosity, and total available and readily available water. Our objectives were to gauge the representativeness of the sample, determine the contribution from land use or soil order to variability, rationalize the data set, and identify concerns for long-term sustainable land use. Soil and land use combinations were both under- or overrepresented in the data set compared with national distribution. Soil order and land-use categories explained 55 to 76% of the variance in soil properties. Total C contents of pastures were comparable with indigenous forest soils, but pastures were less acidic and with higher N and P contents. Plantation forests had characteristics similar to indigenous forests on comparable soils. Cropland soils comprised <1% of the national land cover and generally had high inorganic fertility and low organic matter, with evidence of compaction. Seven characteristics (total C, total N, mineralizable N, pH, Olsen P, bulk density, and macroporosity) explained 87% of the total variability. The findings are being used by monitoring agencies to raise awareness about soil quality in the wider community, set land management guidelines, and develop policies.     

Illinois redesigns its ambient water quality monitoring network

Illinois has been operating an ambient water quality network of almost 600 stations for several years. In 1977 changes in program emphasis toward intensive monitoring, the need for improved procedures and quality control in monitoring operations, and the desire to create a single data base of all Illinois State monitoring data, resulted in a redesign of the ambient monitoring program.A unique cooperative program between the Illinois Environmental Protection Agency and the US Geological Survey provides for their monitoring a portion of the network. The Survey provides flow data at most network stations as well as extensive manpower training, equipment, data processing, and program quality control. Informal agreements with other agencies have permitted a great reduction in the monitoring effort required by the Illinois Environmental Protection Agency.     

Determining regional water quality patterns and their ecological relationships

A multivariate statistical method for analyzing spatial patterns of water quality in Georgia and Kansas was tested using data in the US Environmental Protection Agency's STORET data system. Water quality data for Georgia and Kansas were organized by watersheds. We evaluated three questions: (a) can distinctive regional water quality patterns be detected and predicted using only a few water quality variables, (b) are regional water quality patterns correlated with terrestrial biotic regions, and (c) are regional water quality patterns correlated with fish distributions? Using existing data, this method can distinguish regions with water quality very different from the average conditions (as in Georgia), but it does not discriminate well between regions that do not have diverse water quality conditions (as in Kansas). Data that are spatially and temporally adequate for representing large regions and for multivariate statistical analysis are available for only a few common water quality parameters. Regional climate, lithology, and biotic regimes all have the potential to affect water quality, and terrestrial biotic regions and fish distributions do compare with regional water quality patterns, especially in a state like Georgia, where watershed characteristics are diverse. Thus, identifiable relationships between watershed characteristics and water quality should allow the development of an integrated landaquatic classification system that would be a valuable tool for resource management. Because geographical distributions of species may be limited by Zoogeographic and environmental factors, the recognition of patterns in fish distributions that correlate with regional water quality patterns could influence management strategies and aid regional assessments.     

Biodiversity Monitoring at the Tonle Sap Lake of Cambodia: A Comparative Assessment of Local Methods

This paper assesses local biodiversity monitoring methods practiced in the Tonle Sap Lake of Cambodia. For the assessment we used the following criteria: methodological rigor, perceived cost, ease of use (user friendliness), compatibility with existing activities, and effectiveness of intervention. Constraints and opportunities for execution of the methods were also considered. Information was collected by use of: (1) key informant interview, (2) focus group discussion, and (3) researcher's observation. The monitoring methods for fish, birds, reptiles, mammals and vegetation practiced in the research area have their unique characteristics of generating data on biodiversity and biological resources. Most of the methods, however, serve the purpose of monitoring biological resources rather than biodiversity. There is potential that the information gained through local monitoring methods can provide input for long-term management and strategic planning. In order to realize this potential, the local monitoring methods should be better integrated with each other, adjusted to existing norms and regulations, and institutionalized within community-based organization structures.     

山东省辖城市空气自动监测网运行监控及信息管理系统

研制了山东省环境空气自动监测网络运行监控及信息管理系统,实现了山东省全部省辖市所有点位环境空气自动监测统一数据实时采集与多级多目标传输,全过程跟踪的质量控制与保证,全省统一数据确认、在线信息化管理。     

Survey of state water quality monitoring programs

Budget changes, whether positive or negative, in water quality management agencies often mean a change in resources available for water quality monitoring. Many state agencies are currently facing monitoring budget cuts and, as a result, are reevaluating their monitoring programs. Such evaluations make use of a number of information sources, not the least of which are monitoring activities in other states. This article reports results of a survey of all fifty state water quality monitoring programs. Twenty questions were asked in the general areas of fixed-station monitoring, special studies, and biological monitoring. Each state was contacted by telephone at least twice during the survey. Fixed-station monitoring is conducted by 48 of 50 states. An average of 75 stations per state are sampled, generally on a monthly basis. There is a large variation in the way data are analyzed by the states; water quality indices and plots of concentration or loading over time are the most common methods. All but three states conduct special studies, but only seven repeat the studies on a regular basis. Special studies are generally problem specific as opposed to basin oriented. Biological monitoring is performed by 33 states; however, this is an area in which budget cuts are having a noticeable impact. In some cases, biological monitoring is being completely eliminated or suspended. Macroinvertebrate sampling is performed quarterly to biannualiy by 50% of the states; 75% of the states that sample macroinvertebrates do so annually. Periphyton sampling is performed by 33% of the states. Over 50% of the states are in the process of revising, or have revised, their monitoring program during the past five years. However, only four states had a detailed rationale and operating procedure for the entire monitoring system. Results of the survey are, therefore, averages of existing monitoring programs. Average results do not necessarily represent ideal situations, but do give an indication of how states are coping with their monitoring responsibilities.     

Long-Term Biological Monitoring of an Impaired Stream: Synthesis and Environmental Management Implications

The long-term ecological recovery of an impaired stream in response to an industrial facility’s pollution abatement actions and the implications of the biological monitoring effort to environmental management is the subject of this special issue of Environmental Management. This final article focuses on the synthesis of the biological monitoring program’s components and methods, the efficacy of various biological monitoring techniques to environmental management, and the lessons learned from the program that might be applicable to the design and application of other programs. The focus of the 25-year program has been on East Fork Poplar Creek, an ecologically impaired stream in Oak Ridge, Tennessee with varied and complex stressors from a Department of Energy facility in its headwaters. Major components of the long-term program included testing and monitoring of invertebrate and fish toxicity, bioindicators of fish health, fish contaminant accumulation, and instream communities (including periphyton, benthic macroinvertebrate, and fish). Key parallel components of the program include water chemistry sampling and data management. Multiple lines of evidence suggested positive ecological responses during three major pollution abatement periods. Based on this case study and the related literature, effective environmental management of impaired streams starts with program design that is consistent across space and time, but also adaptable to changing conditions. The biological monitoring approaches used for the program provided a strong basis for assessments of recovery from remedial actions, and the likely causes of impairment. This case study provides a unique application of multidisciplinary and quantitative techniques to address multiple and complex regulatory and programmatic goals, environmental stressors, and remedial actions.     

Integrating forage,wildlife, water,and fish projections with timber projections at the regional level: A case study in southern United States

The impact of timber management and land-use change on forage production, turkey and deer abundance, red-cockaded woodpecker colonies, water yield, and trout abundance was projected as part of a policy study focusing on the southern United States. The multiresource modeling framework used in this study linked extant timber management and land-area policy models with newly developed models for forage, wildlife, fish, and water. Resource production was integrated through a commonly defined land base that could be geographically partitioned according to individual resource needs. Resources were responsive to changes in land use, particularly human-related, and timber management, particularly the harvest of older stands, and the conversion to planted pine.     

Geographic information systems: a tool for strategic ground water quality management

Geographically‐related information is needed for several elements of an integrated ground water quality management programme, including ground water monitoring planning, prioritization of pollution sources, usage of permits and inspections for source control, and planning and completion of remedial actions. Geographic Information Systems (GISs) can be used to support these elements along with delineating wellhead protection areas (WHPAs), prioritizing existing contaminant sources and evaluating proposed changes in land usage in such areas. Eight case studies of the use of GISs in wellhead protection programmes are summarized, including examples from Rhode Island, Mississippi, New Jersey, New York, Pennsylvania, Kansas, Massachusetts and Texas. Six additional examples are mentioned relative to the use of GISs for evaluating ground water pollution potential, facilitating data analysis for environmental restoration of a large area with numerous waste sites, evaluating trends in ground water nitrate contamination, establishing a national database for ground water vulnerability to agricultural chemicals, simulating water table altitudes from stream and drainage basin locations, and selecting radioactive waste dump sites. The applicability of GISs and their associated advantages in wellhead protection and other ground water management studies are demonstrated via the case studies. The GIS technology provides a unique opportunity for analysing and visualizing spatial data. Contaminant and source prioritization within WHPAs is needed for both extant conditions and in the evaluation of proposed land use changes. The coupling of a GIS with contaminant/source prioritization would provide a strategic tool which could be used to plan targeted ground water monitoring programmes, to identify appropriate management or mitigation measures, minimize introduction of contaminants from existing sources into the subsurface environment, and to evaluate the potential of proposed land use activities for causing ground water contamination. GISs can be useful in providing current information for policy makers, planners and managers engaged in ground water quality decision making.     

RESEARCH: Comparison of Temporal Trends in Ambient and Compliance Trace Element and PCB Data in Pool 2 of the Mississippi River, USA, 1985–1995

6+ ), copper (Cu), lead (Pb), mercury (Hg), nickel (Ni), selenium (Se), zinc (Zn), and polychlorinated biphenyls (PCBs). Water-column, bed-sediment, and fish-tissue (fillets) data collected by five government agencies comprised the ambient data set; effluent data from five registered facilities comprised the compliance data set. The nonparametric Mann-Kendall trend test indicated that 33% of temporal trends in all data were statistically significant (P < 0.05). Possible reasons for this were low sample sizes, and a high percentage of samples below the analytical detection limit. Trends in compliance data were more distinct; most trace elements decreased significantly, probably due to improvements in wastewater treatment. Seven trace elements (Cr, Cd, Cu, Pb, Hg, Ni, and Zn) had statistically significant decreases in wastewater and portions of either or both ambient water and bed sediment. No trends were found in fish tissue. Inconsistency in trends between ambient and compliance data were often found for individual constituents, making overall similarity between the data sets difficult to determine. Logistical differences in monitoring programs, such as varying field and laboratory methods among agencies, made it difficult to assess ambient temporal trends.     

Modeling the spatial dynamics of regional land use: the CLUE-S model

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.     

Modeling wetland loss in coastal Louisiana: Geology,geography, and human modifications

Habitat change in coastal Louisiana from 1955/6 to 1978 was analyzed to determine the influence of geological and man-made changes on landscape patterns within 7.5 min quadrangle maps. Three quantitative analyses were used: principal components anlaysis, multiple regression analysis, and cluster analysis.Regional differences in land loss rates reflect variations in geology and the deltaic growth/decay cycles, man-induced chages in hydrology (principally canal dredging and spoil banking), and land-use changes (principally urbanization and agricultural expansion). The coastal zone is not homogeneous with respect to these variables and the interaction between causal factors leading to wetland loss is therefore locally variable and complex.The relationship between wetland loss, hydrologic changes, and geology can be described with statistically meaningful results, even though these data are insufficient to precisely quantify the relationship. However, these data support the hypothesis that the indirect impacts of man-induced changes (hydrologic and land use) may be as influential as the direct impacts resulting in converting wetlands to open water (canals) or modified (impounded) habitat.Three regions within the Louisiana coastal zone can be defined, based on the potential causal factors used in the analyses. The moderate (mean = 22%) wetland loss rates in region 1 are a result of relatively high canal density and developed area in marshes which overlie sediments of moderate age and depth; local geology acts, in this case, to lessen indirect impacts. On the other hand, wetland loss rates in region 2 are high (mean = 36%), despite fewer man-induced impacts; the potential for increased wetland loss due to both direct and indirect effects of man's activity in these areas is high. Conversely, wetland loss (mean = 20%) in region 3 is apparently least influenced by man's activity in the coastal zone because of sedimentary geology (old, thin sediments), even though these areas have already experienced significant direct habitat alteration and wetland loss.     

A minimum data set of water quality parameters to assess and compare treatment efficiency of stormwater facilities

Urban stormwater runoff is often of poor quality, impacting aquatic ecosystems and limiting the use of stormwater runoff for recreational purposes. Several stormwater treatment facilities (STFs) are in operation or at the pilot testing stage, but their efficiencies are neither well documented nor easily compared due to the complex contaminant profile of stormwater and the highly variable runoff hydrograph. On the basis of a review of available data sets on urban stormwater quality and environmental contaminant behavior, we suggest a few carefully selected contaminant parameters (the minimum data set) to be obligatory when assessing and comparing the efficiency of STFs. Consistent use of the minimum data set in all future monitoring schemes for STFs will ensure broad-spectrum testing at low costs and strengthen comparability among facilities. The proposed minimum data set includes: (i) fine fraction of suspended solids (<63 μm), (ii) total concentrations of zinc and copper, (iii) total concentrations of phenanthrene, fluoranthene, and benzo(b,k)fluoranthene, and (iv) total concentrations of phosphorus and nitrogen. Indicator pathogens and other specific contaminants (i.e., chromium, pesticides, phenols) may be added if recreational or certain catchment-scale objectives are to be met. Issues that need further investigation have been identified during the iterative process of developing the minimum data set.     

Cumulative environmental impacts and integrated coastal management: the case of Xiamen, China

This paper examines the assessment of cumulative environmental impacts and the implementation of integrated coastal management within the harbour of Xiamen, China, an urban region in which the coastal zone is under increasing pressure as a result of very rapid economic growth. The first stage of analysis incorporates components of a cumulative effects assessment, including (a) identification of sources of environmental impacts, notably industrial expansion, port development, shipping, waste disposal, aquaculture and coastal construction, (b) selection of a set of valued ecosystem components, focusing on circulation and siltation, water quality, sediment, the benthic community, and mangrove forests, and (c) use of a set of key indicators to examine cumulative impacts arising from the aggregate of human activities. In the second stage of analysis, the paper describes and assesses the development of an institutional framework for integrated coastal management in Xiamen, one that combines policy and planning (including legislative and enforcement mechanisms) with scientific and monitoring mechanisms (including an innovative 'marine functional zoning' system). The paper concludes that the integrated coastal management framework in Xiamen has met all relevant requirements for 'integration' as laid out in the literature, and has explicitly incorporated consideration of cumulative impacts within its management and monitoring processes.     

Using Satellite Fire Detection to Calibrate Components of the Fire Weather Index System in Malaysia and Indonesia

Vegetation fires have become an increasing problem in tropical environments as a consequence of socioeconomic pressures and subsequent land-use change. In response, fire management systems are being developed. This study set out to determine the relationships between two aspects of the fire problems in western Indonesia and Malaysia, and two components of the Canadian Forest Fire Weather Index System. The study resulted in a new method for calibrating components of fire danger rating systems based on satellite fire detection (hotspot) data. Once the climate was accounted for, a problematic number of fires were related to high levels of the Fine Fuel Moisture Code. The relationship between climate, Fine Fuel Moisture Code, and hotspot occurrence was used to calibrate Fire Occurrence Potential classes where low accounted for 3% of the fires from 1994 to 2000, moderate accounted for 25%, high 26%, and extreme 38%. Further problems arise when there are large clusters of fires burning that may consume valuable land or produce local smoke pollution. Once the climate was taken into account, the hotspot load (number and size of clusters of hotspots) was related to the Fire Weather Index. The relationship between climate, Fire Weather Index, and hotspot load was used to calibrate Fire Load Potential classes. Low Fire Load Potential conditions (75% of an average year) corresponded with 24% of the hotspot clusters, which had an average size of 30% of the largest cluster. In contrast, extreme Fire Load Potential conditions (1% of an average year) corresponded with 30% of the hotspot clusters, which had an average size of 58% of the maximum. Both Fire Occurrence Potential and Fire Load Potential calibrations were successfully validated with data from 2001. This study showed that when ground measurements are not available, fire statistics derived from satellite fire detection archives can be reliably used for calibration. More importantly, as a result of this work, Malaysia and Indonesia have two new sources of information to initiate fire prevention and suppression activities.     

Barriers to sharing water quality data: experiences from the Shale Network

The Shale Network is a group of stakeholders collating, publishing, and conducting research on water quality data collected in the northeastern United States experiencing natural gas extraction from shale using hydraulic fracturing. In developing the Shale Network, we have experienced reluctance to share data from all participating sectors. This paper explores this reluctance, identifying barriers to greater collaboration among multiple stakeholders in natural resource management projects. Findings are derived from participant observation of the Shale Network team, surveys conducted during Shale Network workshops, interviews with water quality stakeholders, and participant observation of water quality monitoring training sessions. The barriers identified include perceptions about data problems and quality, technical capacity, regulatory and legal limitations, competition for resources, and resource allocation decisions. This paper identifies strategies the Shale Network has used to overcome data-sharing barriers to expand a culture of data sharing that supports enhanced nature resource management and citizen engagement.     

Squaring the Circle? Combining Models, Indicators, Experts and End-Users in Integrated Land-Use Management Support Tools

The most important challenges faced in the field of integrated land-use management are (i) harmonizing and integrating different datasets, (ii) selecting appropriate indicators, (iii) fitting suitable models to adequate scales, and finally (iv) integrating data, indicators and models into systems that allow both a high level of participation and flexibility with the adaptation to a variety of questions and applications. The articles of this special issue “Squaring the Circle? Combining Models, Indicators, Experts and End-Users in Integrated Land-Use Management Support Tools” demonstrate the challenges that are related to this topic. The case studies present examples of such integrated systems in order to recommend best practices to support land-use management and to reveal existing shortcomings. As a conclusion, seven features of a successful applicable integrated land-use management support system are derived: (1) ability to deal with discontinuity in information and datasets, (2) contribution to solve the problem of indicator diversity, (3) structuring the decision-making process, (4) support of participation processes in generating decisions, (5) development, comparison and evaluation of land-use alternatives, (6) assessment of the efficiency and trade-offs of management options, and (7) assistance of stakeholders in group communication processes.     

Detecting acid precipitation impacts on lake water quality

The United States Environmental Protection Agency is planning to expand its long-term monitoring of lakes that are sensitive to acid deposition effects. Effective use of resources will require a careful definition of the statistical objectives of monitoring, a network design which balances spatial and temporal coverage, and a sound approach to data analysis. This study examines the monitoring objective of detecting trends in water quality for individual lakes and small groups of lakes. Appropriate methods of trend analysis are suggested, and the power of trend detection under seasonal (quarterly) sampling is compared to that of annual sampling. The effects of both temporal and spatial correlation on trend detection ability are described.     

Assessing Watershed-Scale, Long-Term Hydrologic Impacts of Land-Use Change Using a GIS-NPS Model

Land-use change, dominated by an increase in urban/impervious areas, has a significant impact on water resources. This includes impacts on nonpoint source (NPS) pollution, which is the leading cause of degraded water quality in the United States. Traditional hydrologic models focus on estimating peak discharges and NPS pollution from high-magnitude, episodic storms and successfully address short-term, local-scale surface water management issues. However, runoff from small, low-frequency storms dominates long-term hydrologic impacts, and existing hydrologic models are usually of limited use in assessing the long-term impacts of land-use change. A long-term hydrologic impact assessment (L-THIA) model has been developed using the curve number (CN) method. Long-term climatic records are used in combination with soils and land-use information to calculate average annual runoff and NPS pollution at a watershed scale. The model is linked to a geographic information system (GIS) for convenient generation and management of model input and output data, and advanced visualization of model results. The L-THIA/NPS GIS model was applied to the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana, USA. Historical land-use scenarios for 1973, 1984, and 1991 were analyzed to track land-use change in the watershed and to assess impacts on annual average runoff and NPS pollution from the watershed and its five subbasins. For the entire watershed between 1973 and 1991, an 18% increase in urban or impervious areas resulted in an estimated 80% increase in annual average runoff volume and estimated increases of more than 50% in annual average loads for lead, copper, and zinc. Estimated nutrient (nitrogen and phosphorus) loads decreased by 15% mainly because of loss of agricultural areas. The L-THIA/NPS GIS model is a powerful tool for identifying environmentally sensitive areas in terms of NPS pollution potential and for evaluating alternative land use scenarios for NPS pollution management.     

Impact of data quality and model complexity on prediction of pesticide leaching

Accurate input data for leaching models are expensive and difficult to obtain which may lead to the use of "general" non-site-specific input data. This study investigated the effect of using different quality data on model outputs. Three models of varying complexity, GLEAMS, LEACHM, and HYDRUS-2D, were used to simulate pesticide leaching at a field trial near Hamilton, New Zealand, on an allophanic silt loam using input data of varying quality. Each model was run for four different pesticides (hexazinone, procymidone, picloram and triclopyr); three different sets of pesticide sorption and degradation parameters (i.e., site optimized, laboratory derived, and sourced from the USDA Pesticide Properties Database); and three different sets of soil physical data of varying quality (i.e., site specific, regional database, and particle size distribution data). We found that the selection of site-optimized pesticide sorption (Koc) and degradation parameters (half-life), compared to the use of more general database derived values, had significantly more impact than the quality of the soil input data used, but interestingly also more impact than the choice of the models. Models run with pesticide sorption and degradation parameters derived from observed solute concentrations data provided simulation outputs with goodness-of-fit values closest to optimum, followed by laboratory-derived parameters, with the USDA parameters providing the least accurate simulations. In general, when using pesticide sorption and degradation parameters optimized from site solute concentrations, the more complex models (LEACHM and HYDRUS-2D) were more accurate. However, when using USDA database derived parameters, all models performed about equally.