Scale Effects on Spatially Varying Relationships Between Urban Landscape Patterns and Water Quality

Scientific interpretation of the relationships between urban landscape patterns and water quality is important for sustainable urban planning and watershed environmental protection. This study applied the ordinary least squares regression model and the geographically weighted regression model to examine the spatially varying relationships between 12 explanatory variables (including three topographical factors, four land use parameters, and five landscape metrics) and 15 water quality indicators in watersheds of Yundang Lake, Maluan Bay, and Xinglin Bay with varying levels of urbanization in Xiamen City, China. A local and global investigation was carried out at the watershed-level, with 50 and 200 m riparian buffer scales. This study found that topographical features and landscape metrics are the dominant factors of water quality, while land uses are too weak to be considered as a strong influential factor on water quality. Such statistical results may be related with the characteristics of land use compositions in our study area. Water quality variations in the 50 m buffer were dominated by topographical variables. The impact of landscape metrics on water quality gradually strengthen with expanding buffer zones. The strongest relationships are obtained in entire watersheds, rather than in 50 and 200 m buffer zones. Spatially varying relationships and effective buffer zones were verified in this study. Spatially varying relationships between explanatory variables and water quality parameters are more diversified and complex in less urbanized areas than in highly urbanized areas. This study hypothesizes that all these varying relationships may be attributed to the heterogeneity of landscape patterns in different urban regions. Adjustment of landscape patterns in an entire watershed should be the key measure to successfully improving urban lake water quality.     

STREAM HEALTH RANKINGS PREDICTED BY SATELLITE DERIVED LAND COVER METRICS1

ABSTRACT: Land cover and land use change have long been known to influence the chemical, physical, and biological characteristics of streams. This study makes use of land cover maps derived from fine resolution satellite imagery and an extensive stream quality dataset to determine the relationship between small watershed health rankings and land cover composition and configuration. Landscape metrics were derived from digital impervious surface area (ISA), tree cover (percent), and agricultural crop maps within Montgomery County, Maryland. Watershed rankings were developed by state and county collaborators (MD‐DNR and MCDEP) using extensive biological and chemical measurements. In stepwise logistic regression models the factors accounting for the most variation in stream health ranking were the percent ISA, followed by the percent of tree cover. Riparian buffer zone tree cover was also a significant predictor. Of the metrics that considered the spatial configuration of the landscape, a contagion index and the percent of ISA in the flow path from the ISA to the stream were also found to be significant predictors of stream health. Despite limited ability to characterize landscape configuration or narrow riparian buffer zone vegetation with coarser resolution imagery (from Landsat), model results were not significantly different from those based on the use of fine‐resolution ISA information, suggesting that broader area applications of the approach are possible. The results indicate that management practices designed to improve stream water quality should focus on the amount of ISA and tree cover in both the watershed and within the buffer zone.     

Landscape Planning for Agricultural Nonpoint Source Pollution Reduction III: Assessing Phosphorus and Sediment Reduction Potential

Riparian buffers have the potential to improve stream water quality in agricultural landscapes. This potential may vary in response to landscape characteristics such as soils, topography, land use, and human activities, including legacies of historical land management. We built a predictive model to estimate the sediment and phosphorus load reduction that should be achievable following the implementation of riparian buffers; then we estimated load reduction potential for a set of 1598 watersheds (average 54 km²) in Wisconsin. Our results indicate that land cover is generally the most important driver of constituent loads in Wisconsin streams, but its influence varies among pollutants and according to the scale at which it is measured. Physiographic (drainage density) variation also influenced sediment and phosphorus loads. The effect of historical land use on present-day channel erosion and variation in soil texture are the most important sources of phosphorus and sediment that riparian buffers cannot attenuate. However, in most watersheds, a large proportion (approximately 70%) of these pollutants can be eliminated from streams with buffers. Cumulative frequency distributions of load reduction potential indicate that targeting pollution reduction in the highest 10% of Wisconsin watersheds would reduce total phosphorus and sediment loads in the entire state by approximately 20%. These results support our approach of geographically targeting nonpoint source pollution reduction at multiple scales, including the watershed scale.     

WATER QUALITY IN AGRICULTURAL,URBAN, AND MIXED LAND USE WATERSHEDS1

ABSTRACT: Water quality and nonpoint source (NPS) pollution are important issues in many areas of the world, including the Inner Bluegrass Region of Kentucky where urban development is changing formerly rural watersheds into urban and mixed use watersheds. In watersheds where land use is mixed, the relative contributions of NPS pollution from rural and urban land uses can be difficult to separate. To better understand NPS pollution sources in mixed use watersheds, surface water samples were taken at three sites that varied in land use to examine the effect of land use on water quality. Within the group of three watersheds, one was predominately agriculture (Agricultural), one was predominately urban (Urban), and a third had relatively equal representation of both types of land uses (Mixed). Nitrogen (N), phosphorus (P), total suspended solids (TSS), turbidity, pH, temperature, and streamflow were measured for one year. Comparisons are made among watersheds for concentration and fluxes of water quality parameters. Nitrate and orthophosphate concentrations were found to be significantly higher in the Agricultural watershed. Total suspended solids, turbidity, temperature, and pH, were found to be generally higher in the Urban and Mixed watersheds. No differences were found for streamflow (per unit area), total phosphorus, and ammonium concentrations among watersheds. Fluxes of orthophosphate were greater in the Agricultural watershed that in the Urban watershed while fluxes of TSS were greater in the Mixed watershed when compared to the Agricultural watershed. Fluxes of nitrate, ammonium, and total phosphorus did not vary among watersheds. It is apparent from the data that Agricultural land uses are generally a greater source of nutrients than the Urban land uses while Urban land uses are generally a greater source of suspended sediment.     

Linking Nitrogen Export to Landscape Heterogeneity: The Role of Infrastructure and Storm Flows in a Mediterranean Urban System

Urban ecosystems are often sources of nonpoint source (NPS) nitrogen (N) pollution to aquatic ecosystems. However, N export from urban watersheds is highly variable. Examples of densely urbanized watersheds are not well studied, and these may have comparatively low export rates. Commonly used metrics of landscape heterogeneity may obscure our ability to discern relationships among landscape characteristics that can explain these lower export rates. We expected that differences not often captured by these metrics in the relative cover of vegetation, structures, and impervious surfaces would better explain observed variation in N export. We examined these relationships during storms in residential watersheds. Contrary to expectations, land cover did not directly predict variation in N or water export. Instead, N export was strongly linked to drainage infrastructure density. Our research highlights the role of fine‐scaled landscape attributes, mainly infrastructure, in explaining patterns of N export from densely urbanized watersheds. Changes to hydrologic flow paths by infrastructure explained more variation in N export than land cover. Our findings support further development of landscape ecological models of urban N export that focus on hydrologic modification by infrastructure rather than traditional landscape measures such as land use, as indicators for evaluating patterns of NPS nitrogen pollution in densely urbanized watersheds.     

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.     

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.     

PREDICTABILITY OF SURFACE WATER POLLUTION LOADING IN PENNSYLVANIA USING WATERSHED‐BASED LANDSCAPE MEASUREMENTS1

ABSTRACT: We formally evaluated the relationship between landscape characteristics and surface water quality in the state of Pennsylvania (USA) by regressing two different types of pollutant responses on landscape variables that were measured for whole watersheds. One response was the monthly exported mass of nitrogen estimated from field measurements, while the other response was a GIS‐modeled pollution potential index. Regression models were built by the stepwise selection protocol, choosing an optimal set of landscape predictors. After factoring out the effect of physiography, the dominant predictors were the proportion of “annual herbaceous” land and “total herbaceous” land for the nitrogen loading and pollution potential index, respectively. The strength of these single predictors is encouraging because the marginal land cover proportions are the simplest landscape measurements to obtain once a land cover map is in hand; however, the optimal set of predictors also included several measurements of spatial pattern. Thus, for watersheds at this general hierarchical scale, gross landscape pattern may be an important influence on instream pollution loading. Overall, there is strong evidence that using landscape measurements alone, obtained solely from remotely sensed data, can explain most of the water quality variability (R²= approx. 0.75) within these watersheds.     

Effects of watershed configuration and composition on downstream lake water quality

We evaluated the relationships between landscape characteristics and lake water quality in receiving waters by regressing four water quality responses on landscape variables that were measured for whole watersheds and three different buffer distances (30, 60, and 120 m). Classical percolation theory was used to conceptualize nutrient pathways and to explain nonlinear responses. The response variables were total nitrogen (TN), total phosphorus (TP), chlorophyll-a (Chl-a), and Secchi transparency (SD). Landscape data were obtained from satellite image-derived maps of 130 watersheds in Iowa using geographic information systems software. We developed regression models with a stepwise protocol selecting the optimal number of significant explanatory variables. Configuration variables such as contagion, the cohesion of cropland and urban land, and the aggregation index of forest were very important and more important than variables assessing landscape composition (e.g., percentage farmland). Whole watershed models predicted between 15 and 67% of the variability in TN, TP, Chl-a, and SD. Proximity-explicit data offered only slightly improved statistical power over land cover data derived from the entire watershed for variables TN, Chl-a. and SD, but not for TP.     

Statistical and Spatial Analysis of Land Cover Impact on Selected Metro Vancouver, British Columbia Watersheds

The Greater Vancouver area has undergone significant land use and land cover (LULC) change over the past several decades, often adversely affecting stream health and water quality, particularly in those areas that have undergone the most urbanization. In this study 30 years of historical LULC and water quality data were examined using GIS and statistical analysis to better understand these impacts and to help build a broader understanding of cause and effect relationships of changing LULC, especially since urbanization is increasingly occurring within sensitive watersheds at greater distances from the City of Vancouver. Urban, agriculture, and disturbed LULC data from 1976, 1986, and 2000 were examined within a number of watersheds and related to historical water quality data sampled from streams during similar time frames. Additional higher resolution 2006 LULC data from a smaller number of watersheds were then examined and compared to stream health data to investigate the sensitivity of LULC data resolution on monitoring watershed impact. While LULC impact can be clearly seen at both high and lower resolutions, issues of ambiguous land cover and land use designations can potentially affect the magnitude of the relationship.     

Impact of Urban Sprawl on Water Quality in Eastern Massachusetts,USA

A study of water quality, land use, and population variations over the past three decades was conducted in eastern Massachusetts to examine the impact of urban sprawl on water quality using geographic information system and statistical analyses. Since 1970, eastern Massachusetts has experienced pronounced urban sprawl, which has a substantial impact on water quality. High spatial correlations are found between water quality indicators (especially specific conductance, dissolved ions, including Ca, Mg, Na, and Cl, and dissolved solid) and urban sprawl indicators. Urbanized watersheds with high population density, high percentage of developed land use, and low per capita developed land use tended to have high concentrations of water pollutants. The impact of urban sprawl also shows clear spatial difference between suburban areas and central cities: The central cities experienced lower increases over time in specific conductance concentration, compared to suburban and rural areas. The impact of urban sprawl on water quality is attributed to the combined effects of population and land-use change. Per capita developed land use is a very important indicator for studying the impact of urban sprawl and improving land use and watershed management, because inclusion of this indicator can better explain the temporal and spatial variations of more water quality parameters than using individual land use or/and population density.     

URBAN IMPACTS ON PHYSICAL STREAM CONDITION: EFFECTS OF SPATIAL SCALE,CONNECTIVITY, AND LONGITUDINAL TRENDS1

ABSTRACT: An assessment of physical conditions in urban streams of the Puget Sound region, coupled with spatially explicit watershed characterizations, demonstrates the importance of spatial scale, drainage network connectivity, and longitudinal downstream trends when considering the effects of urbanization on streams. A rapid stream assessment technique and a multimetric index were used to describe the physical conditions of multiple reaches in four watersheds. Watersheds were characterized using geographic information system (GIS) derived landscape metrics that represent the magnitude of urbanization at three spatial scales and the connectivity of urban land. Physical conditions, as measured by the physical stream conditions index (PSCI), were best explained for the watersheds by two landscape metrics: quantity of intense and grassy urban land in the subwatershed and quantity of intense and grassy urban land within 500 m of the site (R²= 0.52, p > 0.0005). A multiple regression of PSCI with these metrics and an additional connectivity metric (proximity of a road crossing) provided the best model for the three urban watersheds (R²= 0.41, p > 0.0005). Analyses of longitudinal trends in PSCI within the three urban watersheds showed that conditions improved when a stream flowed through an intact riparian buffer with forest or wetland vegetation and without road crossings. Results demonstrate that information on spatial scale and patterns of urbanization is essential to understanding and successfully managing urban streams.     

Effects of Impervious Cover at Multiple Spatial Scales on Coastal Watershed Streams1

Abstract: The spatial scale and location of land whose development has the strongest influence on aquatic ecosystems must be known to support land use decisions that protect water resources in urbanizing watersheds. We explored impacts of urbanization on streams in the West River watershed, New Haven, Connecticut, to identify the spatial scale of watershed imperviousness that was most strongly related to water chemistry, macroinvertebrates, and physical habitat. A multiparameter water quality index was used to characterize regional urban nonpoint source pollution levels. We identified a critical level of 5% impervious cover, above which stream health declined. Conditions declined with increasing imperviousness and leveled off in a constant state of impairment at 10%. Instream variables were most correlated (0.77 ≤ |r| ≤ 0.92, p < 0.0125) to total impervious area (TIA) in the 100‐m buffer of local contributing areas (～5‐km² drainage area immediately upstream of each study site). Water and habitat quality had a relatively consistent strong relationship with TIA across each of the spatial scales of investigation, whereas macroinvertebrate metrics produced noticeably weaker relationships at the larger scales. Our findings illustrate the need for multiscale watershed management of aquatic ecosystems in small streams flowing through the spatial hierarchies that comprise watersheds with forest‐urban land use gradients.     

Mitigating the Effects of Landscape Development on Streams in Urbanizing Watersheds

This collaborative study examined urbanization and impacts on area streams while using the best available sediment and erosion control (S&EC) practices in developing watersheds in Maryland, United States. During conversion of the agricultural and forested watersheds to urban land use, land surface topography was graded and vegetation was removed creating a high potential for sediment generation and release during storm events. The currently best available S&EC facilities were used during the development process to mitigate storm runoff water quality, quantity, and timing before entering area streams. Detailed Geographic Information System (GIS) maps were created to visualize changing land use and S&EC practices, five temporal collections of LiDAR (light detection and ranging) imagery were used to map the changing landscape topography, and streamflow, physical geomorphology, and habitat data were used to assess the ability of the S&EC facilities to protect receiving streams during development. Despite the use of the best available S&EC facilities, receiving streams experienced altered flow, geomorphology, and decreased biotic community health. These impacts on small streams during watershed development affect sediment and nutrient loads to larger downstream aquatic ecosystems such as the Chesapeake Bay.     

In search of effective scales for stream management: does agroecoregion,watershed, or their intersection best explain the variance in stream macroinvertebrate communities?

Our lack of understanding of relationships between stream biotic communities and surrounding landscape conditions makes it difficult to determine the spatial scale at which management practices are best assessed. We investigated these relationships in the Minnesota River Basin, which is divided into major watersheds and agroecoregions which are based on soil type, geologic parent material, landscape slope steepness, and climatic factors affecting crop productivity. We collected macroinvertebrate and stream habitat data from 68 tributaries among three major watersheds and two agroecoregions. We tested the effectiveness of the two landscape classification systems (i.e., watershed, agroecoregion) in explaining variance in habitat and macroinvertebrate metrics, and analyzed the relative influence on macroinvertebrates of local habitat versus regional characteristics. Macroinvertebrate community composition was most strongly influenced by local habitat; the variance in habitat conditions was best explained at the scale of intersection of major watershed and agroecoregion (i.e., stream habitat conditions were most homogeneous within the physical regions of intersection of these two landscape classification systems). Our results are consistent with findings of other authors that most variation in macroinvertebrate community data from large agricultural catchments is attributable to local physical conditions. Our results are the first to test the hypothesis and demonstrate that the scale of intersection best explains these variances. The results suggest that management practices adjusted for both watershed and ecoregion characteristics, with the goal of improving physical habitat characteristics of local streams, may lead to better basin-wide water quality conditions and stream biological integrity.     

EFFECTS OF MULTI‐SCALE ENVIRONMENTAL CHARACTERISTICS ON AGRICULTURAL STREAM BIOTA IN EASTERN WISCONSIN1

ABSTRACT: The U.S. Geological Survey examined 25 agricultural streams in eastern Wisconsin the determine relations between fish, invertebrate, and algal metrics and multiple spatial scales of land cover, geologic setting, hydrologic, aquatic habitat, and water chemistry data. Spearman correlation and redundancy analyses were used to examine relations among biotic metrics and environmental characteristics. Riparian vegetation, geologic, and hydrologic conditions affected the response of biotic metrics to watershed agricultural land cover but the relations were aquatic assemblage dependent. It was difficult to separate the interrelated effects of geologic setting, watershed and buffer land cover, and base flow. Watershed and buffer land cover, geologic setting, reach riparian vegetation width, and stream size affected the fish IBI, invertebrate diversity, diatom IBI, and number of algal taxa; however, the invertebrate FBI, percentage of EPT, and the diatom pollution index were more influenced by nutrient concentrations and flow variability. Fish IBI scores seemed most sensitive to land cover in the entire stream network buffer, more so than watershed‐scale land cover and segment or reach riparian vegetation width. All but one stream with more than approximately 10 percent buffer agriculture had fish IBI scores of fair or poor. In general, the invertebrate and algal metrics used in this study were not as sensitive to land cover effects as fish metrics. Some of the reach‐scale characteristics, such as width/depth ratios, velocity, and bank stability, could be related to watershed influences of both land cover and geologic setting. The Wisconsin habitat index was related to watershed geologic setting, watershed and buffer land cover, riparian vegetation width, and base flow, and appeared to be a good indicator of stream quality Results from this study emphasize the value of using more than one or two biotic metrics to assess water quality and the importance of environmental characteristics at multiple scales.     

Spatial and Temporal Evaluation of Hydrological Response to Climate and Land Use Change in Three South Dakota Watersheds

This study analyzed changes in hydrology between two recent decades (1980s and 2010s) with the Soil and Water Assessment Tool (SWAT) in three representative watersheds in South Dakota: Bad River, Skunk Creek, and Upper Big Sioux River watersheds. Two SWAT models were created over two discrete time periods (1981‐1990 and 2005‐2014) for each watershed. National Land Cover Datasets 1992 and 2011 were, respectively, ingested into 1981‐1990 and 2005‐2014 models, along with corresponding weather data, to enable comparison of annual and seasonal runoff, soil water content, evapotranspiration (ET), water yield, and percolation between these two decades. Simulation results based on the calibrated models showed that surface runoff, soil water content, water yield, and percolation increased in all three watersheds. Elevated ET was also apparent, except in Skunk Creek watershed. Differences in annual water balance components appeared to follow changes in land use more closely than variation in precipitation amounts, although seasonal variation in precipitation was reflected in seasonal surface runoff. Subbasin‐scale spatial analyses revealed noticeable increases in water balance components mostly in downstream parts of Bad River and Skunk Creek watersheds, and the western part of Upper Big Sioux River watershed. Results presented in this study provide some insight into recent changes in hydrological processes in South Dakota watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

UTILIZATION OF LANDSCAPE INDICATORS TO MODEL POTENTIAL PATHOGEN IMPAIRED WATERS1

ABSTRACT: Many water bodies within the United States are contaminated by non‐point source (NPS) pollution, which is defined as those materials posing a threat to water quality arising from a number of individual sources and diffused through hydrologic processes. One such NPS pollutant that is of critical concern are pathogens derived from animal wastes, including humans. The potential presence of pathogens is identified by testing the water for fecal conform, a bacteria also associated with animal wastes. Water contaminated by animal wastes are most often associated with urban and agricultural areas, thus it is postulated that by utilizing land cover indicators, those water bodies that may be at risk of fecal coliform contamination may be identified. This study utilizes land cover information derived from the Multi‐Resolution Land Characterization (MRLC) project to analyze fecal coliform contamination in South Carolina. Also utilized are 14 digit hydro‐logic unit code (HUC) watersheds of the state, a digital elevation model, and test point data stating whether fecal coliform levels exceeded State Water Quality Standards. Proportions of the various land covers are identified within the individual watersheds and then analyzed using a logistic regression. The results reveal that watersheds with large proportions of urban land cover and agriculture on steep slopes had a very high probability of being impaired. (KEY TERMS: Geographic Information Systems; land use planning; nonpoint source pollution; statistical analysis; water quality; watershed management.)     

WATERSHED SCALING EFFECT ON BASE FLOW NITRATE,VALLEY AND RIDGE PHYSIOGRAPHIC PROVINCE1

ABSTRACT: A study of stream base flow and NO₃‐N concentration was conducted simultaneously in 51 subwatersheds within the 116‐square‐kilometer watershed of East Mahantango Creek near Klingerstown, Pennsylvania. The study was designed to test whether measurable results of processes and observations within the smaller watersheds were similar to or transferable to a larger scale. Ancillary data on land use were available for the small and large watersheds. Although the source of land‐use data was different for the small and large watersheds, comparisons showed that the differences in the two land‐use data sources were minimal. A land use‐based water‐quality model developed for the small‐scale 7.3‐square‐kilometer watershed for a previous study accurately predicted NO₃‐N concentrations from sampling in the same watershed. The water‐quality model was modified and, using the imagery‐based land use, was found to accurately predict NO₃‐N concentrations in the subwatersheds of the large‐scale 116‐square‐kilometer watershed as well. Because the model accurately predicts NO₃‐N concentrations at small and large scales, it is likely that in second‐order streams and higher, discharge of water and NO₃‐N is dominated by flow from smaller first‐order streams, and the contribution of ground‐water discharge to higher order streams is minimal at the large scale.     

Spatial Variations in the Relationships between Land Use and Water Quality across an Urbanization Gradient in the Watersheds of Northern Georgia, USA

A spatial statistical technique, Geographically Weighted Regression (GWR) is applied to study the spatial variations in the relationships between four land use indicators, including percentages of urban land, forest, agricultural land, and wetland, and eight water quality indicators including specific conductance (SC), dissolved oxygen, dissolved nutrients, and dissolved organic carbon, in the watersheds of northern Georgia, USA. The results show that GWR has better model performance than ordinary least squares regression (OLS) to analyze the relationships between land use and water quality. There are great spatial variations in the relationships affected by the urbanization level of watersheds. The relationships between urban land and SC are stronger in less-urbanized watersheds, while those between urban land and dissolved nutrients are stronger in highly-urbanized watersheds. Percentage of forest is an indicator of good water quality. Agricultural land is usually associated with good water quality in highly-urbanized watersheds, but might be related to water pollution in less-urbanized watersheds. This study confirms the results obtained from a similar study in eastern Massachusetts, and so suggest that GWR technique is a very useful tool in water environmental research and also has the potential to be applied to other fields of environmental studies and management in other regions.