Assessment of Nonpoint Source Pollution from Inactive Mines Using a Watershed-Based Approach

/ A watershed-based approach for screening-level assessment of nonpoint source pollution from inactive and abandoned metal mines was developed and illustrated. The methodology was designed to use limited stream discharge and chemical data from synoptic surveys to derive key information required for targeting impaired waterbodies and critical source areas for detailed investigation and remediation. The approach was formulated based on the required attributes of an assessment methodology, information goals for targeting, attributes of data that are typical of basins with inactive mines, and data analysis methods that were useful for the case study. The methodology is presented as steps in a framework including evaluation of existing data/information and identification of data gaps; definition of assessment information goals for targeting and monitoring design; data collection, management, and analysis; and information reporting and use for targeting. Information generated includes the type and extent of and critical conditions for water-quality impairment, concentrations in and loadings to streams, differences between concentrations in and loadings to streams, and risks of exceeding target concentrations and loadings. Data from the Cement Creek Basin, located in the San Juan Mountains of southwestern Colorado, USA, were used to help develop and illustrate application of the methodology. The required information was derived for Cement Creek and used for preliminary targeting of locations for detailed investigation and remediation. Application of the approach to Cement Creek was successful in terms of cost-effective generation of information and use for targeting.KEY WORDS: Water quality assessment; Nonpoint source pollution; Inactive mines; Watershed     

Assessing Land-Use Impacts on Natural Resources

/ Much information is available on changes that occur in natural resources from both spatially-explicit data on environmental conditions and models of the interactions of these conditions and resources with human activities. The strategy for assessing land-use impacts on natural resources developed in this paper provides a framework for using relevant data and models to address questions of how management practices can promote both use and protection of resources. This assessment strategy integrates spatially explicit environmental data using geographic information systems (GIS) with computer models that simulate changes in land cover in response to land-use impacts. The computer models also simulate susceptibility of species to changes in habitat suitability and landscape patterns. The approach is applied to management of limestone barrens on the Oak Ridge Reservation in East Tennessee. Potential limestone barrens habitats are identified by overlaying appropriate soils, geology, slope, and land-use/land-cover conditions. Their validity is tested against known sites containing rare species that occur in these habitats. The location of habitats at risk in the aftermath of human activities is determined by using an available area model that identifies the size and proximity of sites that particular types of species can no longer use as habitat. The resulting risk map can be used in land management planning. The approach uses readily available in situ and remotely sensed data and is applicable to a wide range of locations and land-use scenarios. This approach can be refined based on needs identified by land managers and on the sensitivity of the results to the resolution of available resource information.KEY WORDS: Land management; Assessment; Habitat characterization; Limestone barrens; Ecological modeling; Geographic information systems     

Relationships Between Landscape Characteristics and Nonpoint Source Pollution Inputs to Coastal Estuaries

The model can help in examining the relative sensitivity of water-quality variables to alterations in land use made at varying distances from the stream channel. The model also shows the importance of streamside management zones, which are key to maintenance of stream water quality. The linkage model can be considered a first step in the integration of GIS and ecological models. The model can then be used by local and regional land managers in the formulation of plans for watershed-level management.     

A Watershed-Scale Model for Predicting Nonpoint Pollution Risk in North Carolina

The Southeastern United States is a global center of freshwater biotic diversity, but much of the regions aquatic biodiversity is at risk from stream degradation. Nonpoint pollution sources are responsible for 70% of that degradation, and controlling nonpoint pollution from agriculture, urbanization, and silviculture is considered critical to maintaining water quality and aquatic biodiversity in the Southeast. We used an ecological risk assessment framework to develop vulnerability models that can help policymakers and natural resource managers understand the impact of land cover changes on water quality in North Carolina. Additionally, we determined which landscape characteristics are most closely associated with macroinvertebrate community tolerance of stream degradation, and therefore with lower-quality water. The results will allow managers and policymakers to weigh the risks of management and policy decisions to a given watershed or set of watersheds, including whether streamside buffer protection zones are ecologically effective in achieving water quality standards. Regression analyses revealed that landscape variables explained up to 56.3% of the variability in benthic macroinvertebrate index scores. The resulting vulnerability models indicate that North Carolina watersheds with less forest cover are at most risk for degraded water quality and steam habitat conditions. The importance of forest cover, at both the watershed and riparian zone scale, in predicting macrobenthic invertebrate community assemblage varies by geographic region of the state.     

Headwater Influences on Downstream Water Quality

We investigated the influence of riparian and whole watershed land use as a function of stream size on surface water chemistry and assessed regional variation in these relationships. Sixty-eight watersheds in four level III U.S. EPA ecoregions in eastern Kansas were selected as study sites. Riparian land cover and watershed land use were quantified for the entire watershed, and by Strahler order. Multiple regression analyses using riparian land cover classifications as independent variables explained among-site variation in water chemistry parameters, particularly total nitrogen (41%), nitrate (61%), and total phosphorus (63%) concentrations. Whole watershed land use explained slightly less variance, but riparian and whole watershed land use were so tightly correlated that it was difficult to separate their effects. Water chemistry parameters sampled in downstream reaches were most closely correlated with riparian land cover adjacent to the smallest (first-order) streams of watersheds or land use in the entire watershed, with riparian zones immediately upstream of sampling sites offering less explanatory power as stream size increased. Interestingly, headwater effects were evident even at times when these small streams were unlikely to be flowing. Relationships were similar among ecoregions, indicating that land use characteristics were most responsible for water quality variation among watersheds. These findings suggest that nonpoint pollution control strategies should consider the influence of small upland streams and protection of downstream riparian zones alone is not sufficient to protect water quality.     

Classification and spatial mapping of riparian habitat with applications toward management of streams impacted by nonpoint source pollution

Management of riparian habitats has been recognized for its importance in reducing instream effects of agricultural nonpoint source pollution. By serving as a buffer, well structured riparian habitats can reduce nonpoint source impacts by filtering surface runoff from field to stream. A system has been developed where key characteristics of riparian habitat, vegetation type, height, width, riparian and shoreline bank slope, and land use are classified as discrete categorical units. This classification system recognizes seven riparian vegetation types, which are determined by dominant plant type. Riparian and shoreline bank slope, in addition to riparian width and height, each consist of five categories. Classification by discrete units allows for ready digitizing of information for production of spatial maps using a geographic information system (GIS). The classification system was tested for field efficiency on Tom Beall Creek watershed, an agriculturally impacted third-order stream in the Clearwater River drainage, Nez Perce County, Idaho, USA. The classification system was simple to use during field applications and provided a good inventory of riparian habitat. After successful field tests, spatial maps were produced for each component using the Professional Map Analysis Package (pMAP), a GIS program. With pMAP, a map describing general riparian habitat condition was produced by combining the maps of components of riparian habitat, and the condition map was integrated with a map of soil erosion potential in order to determine areas along the stream that are susceptible to nonpoint source pollution inputs. Integration of spatial maps of riparian classification and watershed characteristics has great potential as a tool for aiding in making management decisions for mitigating off-site impacts of agricultural nonpoint source pollution.     

Use of a geographic information system for storm runoff prediction from small urban watersheds

The use of computer-assisted map analysis techniques for prediction of storm runoff from a small urban watershed in the United States is investigated. An automated procedure for calculating input parameters for the US Soil Conservation Service (SCS) method of predicting storm runoff volume and peak timing is presented. Advanced techniques of spatial analysis are used to characterize spatial coincidence, surface configuration and effective hydrologic distance. A limited verification of the automated procedure indicates that the model reasonably characterizes water flow. A sensitivity analysis of basin disaggregation suggests that the SCS method yields increased volume and peak discharge predictions as the watershed is divided into smaller and smaller subunits. As a means to demonstrate the practical application of the automated procedure, a simulation of the effects on surface runoff for a potential residential development is presented.     

Long-Term Impacts of Land-Use Change on Non-Point Source Pollutant Loads for the St. Louis Metropolitan Area, USA

A land-use-change simulation model (LEAM) and a non-point-source (NPS) water quality model (L-THIA) were closely coupled as LEAMwq in order to determine the long-term implications of various degree of urbanization on NPS total nitrogen (TN), total suspended particles (TSP), and total phosphorus (TP) loads. A future land-use projection in the St. Louis metropolitan area from 2005 to 2030 using three economic growth scenarios (base, low, and high) and a long-term precipitation dataset were used to predict the mean annual surface runoff and mean annual NPS pollutant loads in the region. Results show mean annual TN increases of 0.21%, 0.13%, and 0.14% by 2030 compared to 2000 under the base, high, and low scenarios, respectively. TSP and TP showed similar trends with different magnitudes. Corresponding changes in annual mean surface runoff were shown to be lower than expected, which might be attributed to the small-scale conversion pattern of land uses. In the most dramatic change (high growth) scenario, the runoff would increase across time but at varying rates, and temporal pollutant loads would result in a more complicated pattern than in the other scenarios. This is attributed to the complex interactions between event mean concentrations of pollutants and the magnitude of changes in land-use acreages. By integrating L-THIA with LEAM, LEAMwq was found to be a useful planning tool to illustrate in a quick and simple manner how future water quality is connected to decision-making on future land-use change.     

Setting Priorities for Research on Pollution Reduction Functions of Agricultural Buffers

The success of buffer installation initiatives and programs to reduce nonpoint source pollution of streams on agricultural lands will depend the ability of local planners to locate and design buffers for specific circumstances with substantial and predictable results. Current predictive capabilities are inadequate, and major sources of uncertainty remain. An assessment of these uncertainties cautions that there is greater risk of overestimating buffer impact than underestimating it. Priorities for future research are proposed that will lead more quickly to major advances in predictive capabilities. Highest priority is given for work on the surface runoff filtration function, which is almost universally important to the amount of pollution reduction expected from buffer installation and for which there remain major sources of uncertainty for predicting level of impact. Foremost uncertainties surround the extent and consequences of runoff flow concentration and pollutant accumulation. Other buffer functions, including filtration of groundwater nitrate and stabilization of channel erosion sources of sediments, may be important in some regions. However, uncertainty surrounds our ability to identify and quantify the extent of site conditions where buffer installation can substantially reduce stream pollution in these ways. Deficiencies in predictive models reflect gaps in experimental information as well as technology to account for spatial heterogeneity of pollutant sources, pathways, and buffer capabilities across watersheds. Since completion of a comprehensive watershed-scale buffer model is probably far off, immediate needs call for simpler techniques to gage the probable impacts of buffer installation at local scales.     

Comparative Analysis of New Zealand and US Approaches for Agricultural Nonpoint Source Pollution Management

The role of the central government in New Zealand is generally limited to research and policy development, and regional councils are responsible for most monitoring and management of the problem. The role of the federal government in the United States includes research and monitoring, policy development, and regulation. States also have a significant management role. Both countries rely on voluntary approaches for NPS pollution management. Very few national water quality standards exist in New Zealand, whereas standards are widely used in the United States. Loading estimates and modeling are often used in the United States, but not in New Zealand. A wide range of best management practices (BMPs) are used in the United States, including buffer strips and constructed/engineered wetlands. Buffer strips and riparian management have been emphasized and used widely in New Zealand. Many approaches are common to both countries, but management of the problem has only been partly successful. The primary barriers are the inadequacy of the voluntary approach and the lack of scientific tools that are useful to decision-makers. More work needs to be performed on the evaluation of approaches developed in both countries that could be applied in the other countries. In addition, more cooperation and information/technology transfer between the two countries should be encouraged in the future.     

Development and Adoption of a Simple Nonpoint Source Pollution Model for Port Phillip Bay,Australia

New computing tools and approaches allow tailored development of software to meet the needs of environmental managers. The processes required for such tailoring fit well with adaptive management concepts where, as knowledge and system understanding develop among managers, the software can be developed or replaced to match. This paper reports on development and adoption of a simple nonpoint source pollution modeling tool, including technical aspects of data support for modeling and social aspects of software design. The software, named FILTER, used a unit load model to generate expected pollutant loads from subcatchments of Port Phillip Bay, Australia. Monitoring data were used for calibration to modify the delivery of generated pollutants to receiving waters. Spatial, tabular, and charting software components were used to provide alternative forms of output visualization. FILTER was developed using a process that resulted in manager-stakeholders taking responsibility for setting of model parameter values and operation of the user interface, thereby encouraging uptake. The inclusive development process, tailoring of the software to manager needs and styles of usage, and matching of model complexity to data and knowledge, resulted in a successful application that has become the current agreed system representation among disparate stakeholder organizations.     

Land use change in California,USA: Nonpoint source water quality impacts

California’s population increased 25% between 1980 and 1990, resulting in rapid and extensive urbanization. Of a total 123,000 ha urbanized in 42 of the state’s 58 counties between 1984 and 1990, an estimated 13% occurred on irrigated prime farmland, and 48% on wildlands or fallow marginal farmlands. Sixty-six percent of all new irrigated farmland put into production between 1984 and 1990 was of lesser quality than the prime farmland taken out of production by urbanization. Factors dictating the agricultural development of marginal farmlands include the availability and price of water and land, agricultural commodity prices, and technical innovations such as drip irrigation systems that impact the feasibility and costs of production. The increasing amount of marginal farmland being put into production could have significant water quality consequences because marginal lands are generally steeper, have more erodible soils, poorer drainage, and require more fertilizer than prime farmlands. Although no data exist to test our hypothesis, and numerous variables preclude definitive predictions, the evidence suggests that new irrigated marginal lands can increase nonpoint source (NPS) pollution for a given size area by an order of magnitude in some cases.     

A Conceptual Model for Defining and Assessing Land Management Units Using a Fuzzy Modeling Approach in GIS Environment

Appropriate land management decisions are important for current and future use of the land to ensure its sustainability. This requires that land management units (LMUs) be specified to enable the identification of specific parameters employed in decision making processes. This paper presents the development of a conceptual model, within geographic information systems (GIS), for defining and assessing LMUs from available biophysical information. The model consists of two main components (sub-models): land quality-based suitability analysis and soil erosion estimation. Using a fuzzy set methodology, the first sub-model was constructed to derive a land suitability index (LSI) for a cropping land utilization type. The LSI thus highlights the suitability grades of every pixel in the study area on a continuous basis. A sub-model of soil erosion was established based on the Revised Universal Soil Loss Equation (RUSLE) utilising the same spatial data bases employed for structuring the LSI. Using a soil loss tolerance principle, a fuzzy membership function of average annual soil loss (called soil loss index, SLI) was established, leading to compatibility between LSI and SLI for data integration. LMUs were then derived from various combinations of LSI and SLI. The methodology developed shows the significance of the model for refining available land suitability evaluation systems, which take no account of expected land degradation (from erosion) due to a nominated land use. It also provides a valuable guideline for cost-effective GIS applications in the identification and assessment of homogeneous land units, using available spatial information sets, at a finer scale.     

Assessment of Economic and Water Quality Impacts of Land Use Change Using a Simple Bioeconomic Model

The objective of this study is to assess the economic and water quality impact of land use change in a small watershed in the Wiregrass region of Alabama. The study compares changes in water quality and revenue from agricultural and timber production due to changes in land use between years 1992 and 2001. The study was completed in two stages. In the first stage, a biophysical model was used to estimate the effect of land use change on nitrogen and phosphorus runoff and sediment deposition in the main channel; in the second stage, farm enterprise budgeting tools were used to estimate the economic returns for the changes in land use condition. Both biophysical and economic results are discussed, and a case for complex optimization to develop a decision support system is presented.     

The Relative Importance of Road Density and Physical Watershed Features in Determining Coastal Marsh Water Quality in Georgian Bay

We used a GIS-based approach to examine the influence of road density and physical watershed features (watershed size, wetland cover, and bedrock type) on water quality in coastal marshes of Georgian Bay, Ontario. We created a GIS that included landscape information and water-quality data from a 9-year synoptic survey of 105 coastal marshes covering 28 quaternary watersheds. Multiple regressions and partial correlations were used to discern confounding effects of human-induced (road density) versus natural physical watershed determinants of water quality. Road density was the dominant factor influencing many water quality variables, showing positive correlations with specific conductivity (COND), total suspended solids (TSS), and inorganic suspended solids (ISS) and a negative correlation with overall Water Quality Index scores. Road density also showed positive correlations with total nitrate nitrogen (TNN) and total phosphorus (TP). By comparison, larger watershed area was the main factor leading to elevated TP concentrations. The proportion of the watershed occupied by wetlands explained the largest amount of variation in TNN concentrations (negative correlation) and was also negatively correlated with COND and positively correlated with TSS and ISS when we controlled for road density. Bedrock type did not have a significant effect in any of the models. Our findings suggest that road density is currently the overriding factor governing water quality of coastal marshes in Georgian Bay during the summer low-flow period. We recommend that natural variation in physical watershed characteristics be considered when developing water quality standards and management practices for freshwater coastal areas.     

Comparing Environmental Conditions Using Indicators of Pollution Hazard

/ Land use/land cover classifications for 1973 and 1991, derived from the interpretation of satellite imagery, are quantified on the basis of biophysical land units in a study area in southeastern Australia. Nutrient export potentials are estimated for each land unit based on their composition of land use/land cover classes. Spatial and temporal comparisons are made of the land units based on the calculated pollution hazard indicators to provide an insight into changes in the state of the environment and the regional significance of land use changes. For example, one ecosystem, unique to the study, showed a large increase in pollution hazard over the study period as a manifestation of an 11-fold rise in cleared area and an expansion of cropping activities. The benefits to environmental management in general are discussed.KEY WORDS: Land cover change; Nutrient export; Environmental condition; Pollution hazard; Agricultural pollution; Nonpoint source pollution; Diffuse pollution; Environmental degradation     

Quantitative Assessment of Agricultural Runoff and Soil Erosion Using Mathematical Modeling: Applications in the Mediterranean Region

Three mathematical models, the runoff curve number equation, the universal soil loss equation, and the mass response functions, were evaluated for predicting nonpoint source nutrient loading from agricultural watersheds of the Mediterranean region. These methodologies were applied to a catchment, the gulf of Gera Basin, that is a typical terrestrial ecosystem of the islands of the Aegean archipelago. The calibration of the model parameters was based on data from experimental plots from which edge-of-field losses of sediment, water runoff, and nutrients were measured. Special emphasis was given to the transport of dissolved and solid-phase nutrients from their sources in the farmers' fields to the outlet of the watershed in order to estimate respective attenuation rates. It was found that nonpoint nutrient loading due to surface losses was high during winter, the contribution being between 50% and 80% of the total annual nutrient losses from the terrestrial ecosystem. The good fit between simulated and experimental data supports the view that these modeling procedures should be considered as reliable and effective methodological tools in Mediterranean areas for evaluating potential control measures, such as management practices for soil and water conservation and changes in land uses, aimed at diminishing soil loss and nutrient delivery to surface waters. Furthermore, the modifications of the general mathematical formulations and the experimental values of the model parameters provided by the study can be used in further application of these methodologies in watersheds with similar characteristics.     

Landscape Planning for Agricultural Non–Point Source Pollution Reduction. II. Balancing Watershed Size,Number of Watersheds,and Implementation Effort

Agricultural non–point source (NPS) pollution poses a severe threat to water quality and aquatic ecosystems. In response, tremendous efforts have been directed toward reducing these pollution inputs by implementing agricultural conservation practices. Although conservation practices reduce pollution inputs from individual fields, scaling pollution control benefits up to the watershed level (i.e., improvements in stream water quality) has been a difficult challenge. This difficulty highlights the need for NPS reduction programs that focus efforts within target watersheds and at specific locations within target watersheds, with the ultimate goal of improving stream water quality. Fundamental program design features for NPS control programs—i.e., number of watersheds in the program, total watershed area, and level of effort expended within watersheds—have not been considered in any sort of formal analysis. Here, we present an optimization model that explores the programmatic and environmental trade-offs between these design choices. Across a series of annual program budgets ranging from $2 to $200 million, the optimal number of watersheds ranged from 3 to 27; optimal watershed area ranged from 29 to 214 km²; and optimal expenditure ranged from $21,000 to $35,000/km². The optimal program configuration was highly dependent on total program budget. Based on our general findings, we delineated hydrologically complete and spatially independent watersheds ranging in area from 20 to 100 km². These watersheds are designed to serve as implementation units for a targeted NPS pollution control program currently being developed in Wisconsin.     

Evaluation of a Collaborative Model: A Case Study Analysis of Watershed Planning in theIntermountain West

Collaborative planning processes have become increasingly popular for addressing environmental planning issues, resulting in a number of conceptual models for collaboration. A model proposed by Selin and Chavez suggests that collaboration emerges from a series of antecedents and then proceeds sequentially through problem-setting, direction-setting, implementation, and monitoring and evaluation phases. This paper summarizes an empirical study to evaluate if the Selin and Chavez model encompasses the range of factors important for the establishment and operation of collaboration in watershed planning from the perspective of the planning coordinator. Analysis of three case studies of watershed based planning efforts in the Intermountain West suggests the model realistically describes some of the fundamental collaborative elements in watershed planning. Particularly important factors include the involvement of stakeholders in data collection and analysis and the establishment of measurable objectives. Informal face-to-face dialog and watershed field tours were considered critical for identifying issues and establishing trust among stakeholders. Group organizational structure also seems to play a key role in facilitating collaboration. From this analysis, suggestions for refining the model are proposed.     

Modeling Flow and Sediment Transport in a River System Using an Artificial Neural Network

A river system is a network of intertwining channels and tributaries, where interacting flow and sediment transport processes are complex and floods may frequently occur. In water resources management of a complex system of rivers, it is important that instream discharges and sediments being carried by streamflow are correctly predicted. In this study, a model for predicting flow and sediment transport in a river system is developed by incorporating flow and sediment mass conservation equations into an artificial neural network (ANN), using actual river network to design the ANN architecture, and expanding hydrological applications of the ANN modeling technique to sediment yield predictions. The ANN river system model is applied to modeling daily discharges and annual sediment discharges in the Jingjiang reach of the Yangtze River and Dongting Lake, China. By the comparison of calculated and observed data, it is demonstrated that the ANN technique is a powerful tool for real-time prediction of flow and sediment transport in a complex network of rivers. A significant advantage of applying the ANN technique to model flow and sediment phenomena is the minimum data requirements for topographical and morphometric information without significant loss of model accuracy. The methodology and results presented show that it is possible to integrate fundamental physical principles into a data-driven modeling technique and to use a natural system for ANN construction. This approach may increase model performance and interpretability while at the same time making the model more understandable to the engineering community.