Comparative Water Quality of Lightly- and Moderately-Impacted Streams in the Southern Blue Ridge Mountains, USA

For less-developed regions like the Blue Ridge Mountains, data are limited that link basin-scale land use with stream quality. Two pairs of lightly-impacted (90–100% forested) and moderately-impacted (70–80% forested) sub-basins of the upper Little Tennessee River basin in the southern Blue Ridge were identified for comparison. The pairs contain physically similar stream reaches, chosen for the purpose of isolating forest conversion as a potential driver of any detected differences in water quality. Streams were sampled during baseflow conditions twice monthly over a six-month period from September 2003 through February 2004. Parametric t-tests were run for each parameter measured between the lightly-and moderately-impacted streams within each pair. Statistically significantly higher mean values of suspended and dissolved solids, nitrate, specific conductivity, turbidity, and temperature were observed in the moderately impacted streams versus the lightly impacted streams in both pairs, while dissolved oxygen levels were lower in the moderately-impacted streams. No significant differences were demonstrated in orthophosphate or ammonium concentration. A near-bankfull runoff event on February 6, 2004, was sampled for stormflow values, and the results support baseflow findings. The water quality of these streams is very good when compared with lower relief areas like the Piedmont, and none of the parameters measured in this study exceeds levels of known threat to stream biota. However, the demonstration that moderate reductions in forest cover are associated with stream water quality degradation carries important implications for stream management in this rapidly developing mountainous region.     

Lead forms in urban turfgrass and forest soils as related to organic matter content and pH

Identification of reference streams and human disturbance gradients are crucial steps in assessing the effects of human disturbances on stream health. We describe a process for identifying reference stream reaches and assessing disturbance gradients using readily available, geo-referenced stream and human disturbance databases. We demonstrate the utility of this process by applying it to wadeable streams in Michigan, USA, and use it to identify which human disturbances have the greatest impact on streams. Approximately 38% of cold-water and 16% of warm-water streams in Michigan were identified as being in least-disturbed condition. Conversely, approximately 3% of cold-water and 4% of warm-water streams were moderately to severely disturbed by landscape human disturbances. Anthropogenic disturbances that had the greatest impact on moderately to severely disturbed streams were nutrient loading and percent urban land use within network watersheds. Our process for assessing stream health represents a significant advantage over other routinely used methods. It uses inter-confluence stream reaches as an assessment unit, permits the evaluation of stream health across large regions, and yields an overall disturbance index that is a weighted sum of multiple disturbance factors. The robustness of our approach is linked to the scale of disturbances that affect a stream; it will be less robust for identifying less degraded or reference streams with localized human disturbances. With improved availability of high-resolution disturbance datasets, this approach will provide a more complete picture of reference stream reaches and factors contributing to degradation of stream health.     

Landscape changes as a factor affecting the course and consequences of extreme floods in the Otava river basin, Czech Republic

The paper presents the analysis of anthropogenical modifications of the landscape in relation to the course and consequences of floods. The research was conducted in the Otava river basin which represents the core zone of the extreme flood in August 2002 in Central Europe. The analysis was focused on the key indicators of landscape modification potentially affecting the runoff process - the long-term changes of land-use, changes of land cover structure, land drainage, historical shortening of the river network and the modifications of streams and floodplains. The information on intensity and spatial distribution of modifications was derived from different data sources - historical maps, available GIS data, remote sensing and field mapping. The results revealed a high level of spatial diversity of anthropogenical modifications in different parts of the river basin. The intensive modifications in most of indicators were concentrated in the lowland region of the river basin due to its agricultural use; however important changes were also recorded in the headwater region of the basin. The high spatial diversity of the modifications may result in their varying effect on the course and consequences of floods in different parts of the river basin. This effect is demonstrated by the cluster analysis based on the matrix of indicators of stream and floodplain modification, physiogeographical characteristics and geomorphological evidences of the flood in August 2002, derived from the individual thematic layers using GIS.     

Correspondence of biological condition models of California streams at statewide and regional scales

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California’s wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state (n?=?1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56 % of the variance in O/E values. Models for individual regions explained between 51 and 84 % of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes (n?≤?75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.     

Assessing Landscape Condition Relative to Water Resources in the Western United States: A Strategic Approach

The Environmental Monitoring and Assessment Program (EMAP) is proposing an ambitious agenda to assess the status of streams and estuaries in a 12-State area of the western United States by the end of 2003. Additionally, EMAP is proposing to access landscape conditions as they relate to stream and estuary conditions across the west. The goal of this landscape project is to develop a landscape model that can be used to identify the relative risks of streams and estuaries to potential declines due to watershed-scale, landscape conditions across the west. To do so, requires an understanding of quantitative relationships between landscape composition and pattern metrics and parameters of stream and estuary conditions. This paper describes a strategic approach for evaluating the degree to which landscape composition and pattern influence stream and estuary condition, and the development and implementation of a spatially-distributed, landscape analysis approach.     

Biological Integrity in Mid-Atlantic Coastal Plains Headwater Streams

The objective of this study was to assess the applicability of using landscape variables in conjunction with water quality and benthic data to efficiently estimate stream condition of select headwater streams in the Mid-Atlantic Coastal Plains. Eighty-two streams with riffle sites were selected from eight-two independent watersheds across the region for sampling and analyses. Clustering of the watersheds by landscape resulted in three distinct groups (forest, crop, and urban) which coincided with watersheds dominant land cover or use. We used non-parametric analyses to test differences in benthos and water chemistry between groups, and used regression analyses to evaluate responses of benthic communities to water chemistry within each of the landscape groups. We found that typical water chemistry measures associated with urban runoff such as specific conductance and dissolved chloride were significantly higher in the urban group. In the crop group, we found variables commonly associated with farming such as nutrients and pesticides significantly greater than in the other two groups. Regression analyses demonstrated that the numbers of tolerant and facultative macroinvertebrates increased significantly in forested watersheds with small shifts in pollutants, while in human use dominated watersheds the intolerant macroinvertebrates were more sensitive to shifts in chemicals present at lower concentrations. The results from this study suggest that landscape based clustering can be used to link upstream landscape characteristics, water chemistry and biotic integrity in order to assess stream condition and likely cause of degradation without the use of reference sites. Notice: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.     

Exploring the Relationship Between Hydrologic Parameters and Nutrient Loads Using Digital Elevation Model and GIS – A Case Study from Sugarcreek Headwaters, Ohio, U.S.A.

Ohio is typical among the Midwestern and Eastern United States with high levels of water pollutants, the main sources being from agriculture. In this study, we used a digital elevation model in conjunction with hydrological indices to determine the role of landscape complexity affecting the spatial and temporal variation in pollutant levels, in one of the most impaired headwater streams in Ohio. More than eighty five percent of the study area is dominated by agriculture. Spatial distribution of slope (S), altitude and wetness index along with other watershed parameters such as flow direction, flow accumulation, stream networks, flow stream orders and erosion index were used within a Geographic Information Systems framework to quantify variation in nitrate and phosphate loads to headwater streams. Stream monitoring data for nutrient loads were used to correlate the observed spatial and temporal patterns with hydrological parameters using multiple linear regressions. Results from the wetness index calculated from a digital elevation model suggested a range of 0.10–16.39, with more than 35% having values less than 4.0. A Revised Universal Soil Loss Equation (RUSLE) predicted soil loss in the range of 0.01–4.0 t/ha/yr. Nitrate nitrogen levels in the study area paralleled precipitation patterns over time, with higher nitrate levels corresponding to high precipitation. Atmospheric deposition through precipitation could explain approximately 35% of total nitrate levels observed in streams. Among the different topographic variables and hydrological indices, results from the step-wise multiple regression suggested the following best predictors, (1) elevation range and upstream flow length for nitrate, (2) flow direction and upstream flow length for ammonia-nitrogen and slope, and (3) elevation range for phosphate levels. Differences in the landscape models observed for nitrate, phosphate and ammonia-nitrogen in the surface waters were attributed partly to differences in the chemical activity and source strengths of the different forms of these nutrients through agricultural management practices. The results identify geomorphologic and landscape characteristics that influence pollutant levels in the study area.     

Linking stream and landscape trajectories in the southern Appalachians

A proactive sampling strategy was designed and implemented in 2000 to document changes in streams whose catchment land uses were predicted to change over the next two decades due to increased building density. Diatoms, macroinvertebrates, fishes, suspended sediment, dissolved solids, and bed composition were measured at two reference sites and six sites where a socioeconomic model suggested new building construction would influence stream ecosystems in the future; we label these "hazard sites." The six hazard sites were located in catchments with forested and agricultural land use histories. Diatoms were species-poor at reference sites, where riparian forest cover was significantly higher than all other sites. Cluster analysis, Wishart's distance function, non-metric multidimensional scaling, indicator species analysis, and t-tests show that macroinvertebrate assemblages, fish assemblages, in situ physical measures, and catchment land use and land cover were different between streams whose catchments were mostly forested, relative to those with agricultural land use histories and varying levels of current and predicted development. Comparing initial results with other regional studies, we predict homogenization of fauna with increased nutrient inputs and sediment associated with agricultural sites where more intense building activities are occurring. Based on statistical separability of sampled sites, catchment classes were identified and mapped throughout an 8,600 km(2) region in western North Carolina's Blue Ridge physiographic province. The classification is a generalized representation of two ongoing trajectories of land use change that we suggest will support streams with diverging biota and physical conditions over the next two decades.     

A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay Watershed

The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.     

Statistically Extracted Fundamental Watershed Variables for Estimating the Loads of Total Nitrogen in Small Streams

Accurate estimation of total nitrogen loads is essential for evaluating conditions in the aquatic environment. Extrapolation of estimates beyond measured streams will greatly expand our understanding of total nitrogen loading to streams. Recursive partitioning and random forest regression were used to assess 85 geospatial, environmental, and watershed variables across 636 small (<585 km²) watersheds to determine which variables are fundamentally important to the estimation of annual loads of total nitrogen. Initial analysis led to the splitting of watersheds into three groups based on predominant land use (agricultural, developed, and undeveloped). Nitrogen application, agricultural and developed land area, and impervious or developed land in the 100-m stream buffer were commonly extracted variables by both recursive partitioning and random forest regression. A series of multiple linear regression equations utilizing the extracted variables were created and applied to the watersheds. As few as three variables explained as much as 76 % of the variability in total nitrogen loads for watersheds with predominantly agricultural land use. Catchment-scale national maps were generated to visualize the total nitrogen loads and yields across the USA. The estimates provided by these models can inform water managers and help identify areas where more in-depth monitoring may be beneficial.