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.)     

LAND COVER AS A FRAMEWORK FOR ASSESSING RISK OF WATER POLLUTION1

ABSTRACT: A survey of numerous field studies shows that nitrogen and phosphorous export coefficients are significantly different across forest, agriculture, and urban land‐cover types. We used simulations to estimate the land‐cover composition at which there was a significant risk of nutrient loads representative of watersheds without forest cover. The results suggest that at between 20 percent and 30 percent nonforest cover, there is a 10 percent or greater chance of N or P nutrient loads being equivalent to the median values of predominantly agricultural or urban watersheds. The methods apply to environmental management for assessing the risk to increased nonpoint nutrient pollution. Interpretation of the risk measures are discussed relative to their application for a single watershed and across a region comprised of several watersheds.     

Weighting Nitrogen and Phosphorus Pixel Pollutant Loads to Represent Runoff and Buffering Likelihoods

Watershed models often estimate annual nitrogen (N) or phosphorus (P) pollutant loads in rural areas with export coefficient (EC) (kg/ha/yr) values based on land cover, and in urban areas as the product of spatially uniform event mean concentration (EMC) (mg/L) values and runoff volume. Actual N and P nonpoint source (NPS) pollutant loading has more spatial complexity due to watershed variation in runoff likelihood and buffering likelihood along surface and subsurface pathways, which can be represented in a contributing area dispersal area (CADA) NPS model. This research develops a CADA NPS model to simulate how watershed properties of elevation, land cover, and soils upslope and downslope of each watershed pixel influence nutrient loading. The model uses both surface and subsurface runoff indices (RI), and surface and subsurface buffer indices (BI), to quantify the runoff and buffering likelihood for each watershed pixel, and generate maps of weighted EC and EMC values that identify NPS pollutant loading hotspots. The research illustrates how CADA NPS model maps and pixel loading values are sensitive to the spatial resolution and accuracy of elevation and land cover data, and model predictions can represent the lower and upper bounds of NPS loading. The model provides managers with a tool to rapidly visualize, rank, and investigate likely areas of high nutrient export.     

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.     

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.     

MODELING THE DISTRIBUTION OF DIFFUSE NITROGEN SOURCES AND SINKS IN THE NEUSE RIVER BASIN OF NORTH CAROLINA,USA1

This study quantified nonpoint source nitrogen (NPS‐N) sources and sinks across the 14,582 km² Neuse River Basin (NRB) located in North Carolina, to provide tabular data summaries and graphic overlay products to support the development of management approaches to best achieve established N reduction goals. First, a remote sensor derived, land cover classification was performed to support modeling needs. Modeling efforts included the development of a mass balance model to quantify potential N sources and sinks, followed by a precipitation event driven hydrologic model to effectively transport excess N across the landscape to individual stream reaches to support subsequent labeling of transported N values corresponding to source origin. Results indicated that agricultural land contributed 55 percent of the total annual NPS‐N loadings, followed by forested land at 23 percent (background), and urban areas at 21 percent. Average annual N source contributions were quantified for agricultural (1.4 kg/ha), urban (1.2 kg/ha), and forested cover types (0.5 kg/ha). Nonpoint source‐N contributions were greatest during the winter (40 percent), followed by spring (32 percent), summer (28 percent), and fall (0.3 percent). Seasonal total N loadings shifted from urban dominated and forest dominated sources during the winter, to agricultural sources in the spring and summer. A quantitative assessment of the significant NRB land use activities indicated that high (greater than 70 percent impervious) and medium (greater than 35 percent impervious) density urban development were the greatest contributors of NPS‐N on a unit area basis (1.9 and 1.6 kg/ha/yr, respectively), followed by row crops and pasture/hay cover types (1.4 kg/ha/yr).     

Assessing the Relationship Between Landscape Patterns and Nonpoint‐Source Pollution in the Danjiangkou Reservoir Basin in China1

Abstract: The constrained ordination method from quantitative ecology was utilized to assess the relationship between landscape patterns and nonpoint‐source (NPS) pollution for the purpose of identifying effective water‐quality improvement practices in Danjiangkou Reservoir (DJKR) basin, China. The soil and water assessment tool (SWAT) was applied to simulate NPS pollution and the Fragstats model was applied to calculate the landscape metrics. The study concluded that organic nutrients formed the main NPS pollutant in the DJKR basin and that most of the NPS pollution occurred along with soil loss. Based on partial redundancy analysis, the conclusion that landscape metrics were significantly correlated to NPS pollution indices was obtained. Specifically, the composition of LULC (land use/land cover) was the most effective factor to estimate NPS pollution. Dry cultivated land was identified as the main source of NPS pollution, and paddy fields were characterized with the most intensive soluble nutrients loss. In addition, the reason that fragmented and complex landscape patterns exacerbate NPS pollution was that natural landscape composed most of this area. Moreover, the fragmented natural landscape indicated intensive agricultural activities that were the crucial trigger for NPS pollution. Combined with the economic condition in China, Conversion of Cropland to Forests Program (CCFP) should be conducted selectively and gradually in the DJKR basin.     

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.     

Dissolved organic nitrogen regulation in freshwaters

Dissolved organic nitrogen (DON) has been hypothesized to play a major role in N cycling in a variety of ecosystems. Our aim was to assess the seasonal and concentration relationships between dissolved organic carbon (DOC), DON, and NO3- within 102 streams and 16 lakes within catchments of differing complexity situated in Wales. Further, we aimed to assess whether patterns of land use, soil type, and vegetation gave consistent trends in DON and dissolved inorganic nitrogen (DIN) relationships over a diverse range of catchments. Our results reinforce that DON constitutes a significant component of the total dissolved N pool typically representing 40 to 50% of the total N in streams and lakes but sometimes representing greater than 85% of the total dissolved N. Generally, the levels of DON were inversely correlated with the concentration of DIN. In contrast to DIN concentrations, which showed distinct seasonality, DON showed no consistent seasonal trend. We hypothesize that this reflects differences in the bioavailability of these two N types. The amount of DON, DOC, and DIN was significantly related to soil type with higher DON export from Histosol-dominated catchments in comparison with Spodosol-dominated watersheds. Vegetation cover also had a significant effect on DON concentrations independent of soil type with a nearly twofold decrease in DON export from forested catchments in comparison with nonforested watersheds. Due to the diversity in catchment DON behavior, we speculate that this will limit the adoption of DON as a broad-scale indicator of catchment condition for use in monitoring and assessment programs.     

THE MISUSE OF HYDROLOGIC UNIT MAPS FOR EXTRAPOLATION,REPORTING, AND ECOSYSTEM MANAGEMENT1

ABSTRACT: The use of watersheds to conduct research on land/water relationships has expanded recently to include both extrapolation and reporting of water resource information and ecosystem management. More often than not, hydrologic units (HUs) are used for these purposes, with the implication that hydrologic units are synonymous with watersheds. Whereas true topographic watersheds are areas within which apparent surface water drains to a particular point, generally only 45 percent of all hydrologic units, regardless of their hierarchical level, meet this definition. Because the area contributing to the downstream point in many hydrologic units extends far beyond the unit boundaries, use of the hydrologic unit framework to show regional and national patterns of water quality and other environmental resources can result in incorrect and misleading illustrations. In this paper, the implications of this misuse are demonstrated using four adjacent HUs in central Texas. A more effective way of showing regional patterns in environmental resources is by using data from true watersheds representative of different ecological regions containing particular mosaics of geographical characteristics affecting differences in ecosystems and water quality.     

GIS‐BASED HYIROLOGIC MODELING OF RIPARIAN AREAS: IMPLICATIONS FOR STREAM WATER QUALITY1

ABSTRACT: Riparian buffers have potential for reducing excess nutrient levels in surface water. Spatial variation in riparian buffer effectiveness is well recognized, yet researchers and managers still lack effective general tools for understanding the relevance of different hydrologic settings. We present several terrain‐based GIS models to predict spatial patterns of shallow, subsurface hydrologic flux and riparian hydrology. We then link predictions of riparian hydrology to patterns of nutrient export in order to demonstrate potential for augmenting the predictive power of land use/land cover (LU/LC) maps. Using predicted hydrology in addition to LUILC, we observed increases in the explained variation of nutrient exports from 290 sites across Lower Michigan. The results suggest that our hydrologic predictions relate more strongly to patterns of nutrient export than the presence or absence of wetland vegetation, and that in fact the influence of vegetative structure largely depends on its hydrologic context. Such GIS models are useful and complimentary tools for exploring the role of hydrologic routing in riparian ecosystem function and stream water quality. Modeling efforts that take a similar GIS approach to material transport might be used to further explore the causal implications of riparian buffers in heterogeneous watersheds.     

Denitrification potential in urban riparian zones

Denitrification, the anaerobic microbial conversion of nitrate (NO3-) to nitrogen (N) gases, is an important process contributing to the ability of riparian zones to function as "sinks" for NO3- in watersheds. There has been little analysis of riparian zones in urban watersheds despite concerns about high NO3- concentrations in many urban streams. Vegetation and soils in urban ecosystems are often highly disturbed, and few studies have examined microbial processes like denitrification in these ecosystems. In this study, we measured denitrification potential and a suite of related microbial parameters (microbial biomass carbon [C] and N content, potential net N mineralization and nitrification, soil inorganic N pools) in four rural and four urban riparian zones in the Baltimore, MD metropolitan area. Two of the riparian zones were forested and two had herbaceous vegetation in each land use context. There were few differences between urban and rural and herbaceous and forest riparian zones, but variability was much higher in urban than rural sites. There were strong positive relationships between soil moisture and organic matter content and denitrification potential. Given the importance of surface runoff in urban watersheds, the high denitrification potential of the surface soils that we observed suggests that if surface runoff can be channeled through areas with high denitrification potential (e.g., stormwater detention basins with wetland vegetation), these areas could function as important NO3- sinks in urban watersheds.     

Recent Land Cover History and Nutrient Retention in Riparian Wetlands

Wetland ecosystems are profoundly affected by altered nutrient and sediment loads received from anthropogenic activity in their surrounding watersheds. Our objective was to compare a gradient of agricultural and urban land cover history during the period from 1949 to 1997, with plant and soil nutrient concentrations in, and sediment deposition to, riparian wetlands in a rapidly urbanizing landscape. We observed that recent agricultural land cover was associated with increases in Nitrogen (N) and Phosphorus (P) concentrations in a native wetland plant species. Conversely, recent urban land cover appeared to alter receiving wetland environmental conditions by increasing the relative availability of P versus N, as reflected in an invasive, but not a native, plant species. In addition, increases in surface soil Fe content suggests recent inputs of terrestrial sediments associated specifically with increasing urban land cover. The observed correlation between urban land cover and riparian wetland plant tissue and surface soil nutrient concentrations and sediment deposition, suggest that urbanization specifically enhances the suitability of riparian wetland habitats for the invasive species Japanese stiltgrass [Microstegium vimenium (Trinius) A. Camus].     

Impact of Changing Climate and Land Cover on Flood Magnitudes in the Delaware River Basin,USA

Changing climate and land cover are expected to impact flood hydrology in the Delaware River Basin over the 21st Century. HEC‐HMS models (U.S. Army Corps of Engineers Hydrologic Engineering Center‐Hydrologic Modeling System) were developed for five case study watersheds selected to represent a range of scale, soil types, climate, and land cover. Model results indicate that climate change alone could affect peak flood discharges by ?6% to +58% a wide range that reflects regional variation in projected rainfall and snowmelt and local watershed conditions. Land cover changes could increase peak flood discharges up to 10% in four of the five watersheds. In those watersheds, the combination of climate and land cover change increase modeled peak flood discharges by up to 66% and runoff volumes by up to 44%. Precipitation projections are a key source of uncertainty, but there is a high likelihood of greater precipitation falling on a more urbanized landscape that produces larger floods. The influence of climate and land cover changes on flood hydrology for the modeled watersheds varies according to future time period, climate scenario, watershed land cover and soil conditions, and flood frequency. The impacts of climate change alone are typically greater than land cover change but there is substantial geographic variation, with urbanization the greater influence on some small, developing 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.     

EXAMINING LAND USE INFLUENCES ON STREAM HABITATS AND MACROINVERTEBRATES: A GIS APPROACH1

ABSTRACT: Geographic Information Systems (GIS) were used to assess the relationships between land use patterns and the physical habitat and macroinvertebrate fauna of streams within similar sized watersheds. Eleven second or third order watersheds ranging from highly urbanized to heavily forested were selected along Lake Superior's North Shore. Land use patterns within the watersheds were quantified using readily available digital land use/land cover information, with a minimum mapping resolution of 16 ha. Physical habitat features, describing substrate characteristics and stream morphology, were characterized at sample points within each stream. Principle component and correlation analyses were used to identify relationships between macroinvertebrates and stream physical habitat, and between habitat and land use patterns. Substrate characteristics and presence of coarse woody debris were found to have the strongest correlations with macreinvertebrate assemblage richness and composition. Agricultural and urban land use was correlated with substrate characteristics. Algal abundance, associated with macroinvertebrate compositional differences, was correlated with housing density and non-forest land covers. The use of readily available spatial data, even at this relatively coarse scale, provides a means to detect the primary relationships between land use and stream habitat quality; finer-resolution GIS databases are needed to assess more subtle influences, such as those due to riparian conditions.     

An assessment of landscape characteristics affecting estuarine nitrogen loading in an urban watershed

Exploring the quantitative association between landscape characteristics and the ecological conditions of receiving waters has recently become an emerging area for eco-environmental research. While the landscape-water relationship research has largely targeted on inland aquatic systems, there has been an increasing need to develop methods and techniques that can better work with coastal and estuarine ecosystems. In this paper, we present a geospatial approach to examine the quantitative relationship between landscape characteristics and estuarine nitrogen loading in an urban watershed. The case study site is in the Pensacola estuarine drainage area, home of the city of Pensacola, Florida, USA, where vigorous urban sprawling has prompted growing concerns on the estuarine ecological health. Central to this research is a remote sensor image that has been used to extract land use/cover information and derive landscape metrics. Several significant landscape metrics are selected and spatially linked with the nitrogen loading data for the Pensacola bay area. Landscape metrics and nitrogen loading are summarized by equal overland flow-length rings, and their association is examined by using multivariate statistical analysis. And a stepwise model-building protocol is used for regression designs to help identify significant variables that can explain much of the variance in the nitrogen loading dataset. It is found that using landscape composition or spatial configuration alone can explain most of the nitrogen loading variability. Of all the regression models using metrics derived from a single land use/cover class as the independent variables, the one from the low density urban gives the highest adjusted R-square score, suggesting the impact of the watershed-wide urban sprawl upon this sensitive estuarine ecosystem. Measures towards the reduction of non-point source pollution from urban development are necessary in the area to protect the Pensacola bay ecosystem and its ecosystem services.     

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.     

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.     

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to Central Plains stream conditions

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use-land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite-nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use-land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.