Integrating LiDAR data and multi-temporal aerial imagery to map wetland inundation dynamics using Google Earth Engine.

The Prairie Pothole Region of North America is characterized by millions of depressional wetlands, which provide critical habitats for globally significant populations of migratory waterfowl and other wildlife species. Due to their relatively small size and shallow depth, these wetlands are highly sensitive to climate variability and anthropogenic changes, exhibiting inter- and intra-annual inundation dynamics. Moderate-resolution satellite imagery (e.g., Landsat, Sentinel) alone cannot be used to effectively delineate these small depressional wetlands. By integrating fine spatial resolution Light Detection and Ranging (LiDAR) data and multi-temporal (2009-2017) aerial images, we developed a fully automated approach to delineate wetland inundation extent at watershed scales using Google Earth Engine. Machine learning algorithms were used to classify aerial imagery with additional spectral indices to extract potential wetland inundation areas, which were further refined using LiDAR-derived landform depressions. The wetland delineation results were then compared to the U.S. Fish and Wildlife Service National Wetlands Inventory (NWI) geospatial dataset and existing global-scale surface water products to evaluate the performance of the proposed method. We tested the workflow on 26 watersheds with a total area of 16,576 km2 in the Prairie Pothole Region. The results showed that the proposed method can not only delineate current wetland inundation status but also demonstrate wetland hydrological dynamics, such as wetland coalescence through fill-spill hydrological processes. Our automated algorithm provides a practical, reproducible, and scalable framework, which can be easily adapted to delineate wetland inundation dynamics at broad geographic scales.

Differing Modes of Biotic Connectivity within Freshwater Ecosystem Mosaics.

We describe a collection of aquatic and wetland habitats in an inland landscape, and their occurrence within a terrestrial matrix, as a "freshwater ecosystem mosaic" (FEM). Aquatic and wetland habitats in any FEM can vary widely, from permanently ponded lakes, to ephemerally ponded wetlands, to groundwater-fed springs, to flowing rivers and streams. The terrestrial matrix can also vary, including in its influence on flows of energy, materials, and organisms among ecosystems. Biota occurring in a specific region are adapted to the unique opportunities and challenges presented by spatial and temporal patterns of habitat types inherent to each FEM. To persist in any given landscape, most species move to recolonize habitats and maintain mixtures of genetic materials. Species also connect habitats through time if they possess needed morphological, physiological, or behavioral traits to persist in a habitat through periods of unfavorable environmental conditions. By examining key spatial and temporal patterns underlying FEMs, and species-specific adaptations to these patterns, a better understanding of the structural and functional connectivity of a landscape can be obtained. Fully including aquatic, wetland, and terrestrial habitats in FEMs facilitates adoption of the next generation of individual-based models that integrate the principles of population, community, and ecosystem ecology.

The Significant Surface-Water Connectivity of "Geographically Isolated Wetlands".

We evaluated the current literature, coupled with our collective research expertise, on surface-water connectivity of wetlands considered to be "geographically isolated" (sensu Tiner Wetlands 23:494-516, 2003a) to critically assess the scientific foundation of grouping wetlands based on the singular condition of being surrounded by uplands. The most recent research on wetlands considered to be "geographically isolated" shows the difficulties in grouping an ecological resource that does not reliably indicate lack of surface water connectivity in order to meet legal, regulatory, or scientific needs. Additionally, the practice of identifying "geographically isolated wetlands" based on distance from a stream can result in gross overestimates of the number of wetlands lacking ecologically important surface-water connections. Our findings do not support use of the overly simplistic label of "geographically isolated wetlands". Wetlands surrounded by uplands vary in function and surface-water connections based on wetland landscape setting, context, climate, and geographic region and should be evaluated as such. We found that the "geographically isolated" grouping does not reflect our understanding of the hydrologic variability of these wetlands and hence does not benefit conservation of the Nation's diverse wetland resources. Therefore, we strongly discourage use of categorizations that provide overly simplistic views of surface-water connectivity of wetlands fully embedded in upland landscapes.

Sediment delivery estimates in water quality models altered by resolution and source of topographic data.

Moderate-resolution (30-m) digital elevation models (DEMs) are normally used to estimate slope for the parameterization of non-point source, process-based water quality models. These models, such as the Soil and Water Assessment Tool (SWAT), use the Universal Soil Loss Equation (USLE) and Modified USLE to estimate sediment loss. The slope length and steepness factor, a critical parameter in USLE, significantly affects sediment loss estimates. Depending on slope range, a twofold difference in slope estimation potentially results in as little as 50% change or as much as 250% change in the LS factor and subsequent sediment estimation. Recently, the availability of much finer-resolution (∼3 m) DEMs derived from Light Detection and Ranging (LiDAR) data has increased. However, the use of these data may not always be appropriate because slope values derived from fine spatial resolution DEMs are usually significantly higher than slopes derived from coarser DEMs. This increased slope results in considerable variability in modeled sediment output. This paper addresses the implications of parameterizing models using slope values calculated from DEMs with different spatial resolutions (90, 30, 10, and 3 m) and sources. Overall, we observed over a 2.5-fold increase in slope when using a 3-m instead of a 90-m DEM, which increased modeled soil loss using the USLE calculation by 130%. Care should be taken when using LiDAR-derived DEMs to parameterize water quality models because doing so can result in significantly higher slopes, which considerably alter modeled sediment loss.

Hotspots of wetland loss to impervious surfaces in the conterminous United States.

In this study, a first wall-to-wall comparison between the National Wetlands Inventory (NWI) and the National Land Cover Database (NLCD) was conducted across the entire conterminous United States (CONUS) to evaluate U.S. wetland loss conditions. Annually, around 26 km2 of wetlands are lost to impervious surfaces across the CONUS. Spatially, wetland loss is not evenly distributed, with 90 % of losses occurring in only 9 % of the land area, forming hotspots around expanding urban regions such as Houston, Jacksonville, and Naples. Over the past few decades, Florida experienced the highest wetland loss (5.73 km2/year) among all states, while Houston had the most wetland loss (2.54 km2/year) among all metropolitan regions. Stepwise multiple regression models identified population growth and its associated demand for new housing as the major drivers for wetland loss. Wetland loss per population increase is the highest (>15 m2/person) in most metropolitan regions around the East Coast and Gulf of Mexico. Unfortunately, current wetland loss hotspots will likely suffer further losses in future decades due to projected population growth, with Houston, Cape Coral, and Miami metropolitan regions having the greatest projected wetland loss of 89.15 km2, 34.35 km2, and 28.20 km2, respectively. This study has identified wetland loss hotspots and their drivers across the U.S. that were not possible in previous sample-based studies. The findings are critical in wetland management and protection across the U.S.

Vulnerable Waters are Essential to Watershed Resilience.

Watershed resilience is the ability of a watershed to maintain its characteristic system state while concurrently resisting, adapting to, and reorganizing after hydrological (for example, drought, flooding) or biogeochemical (for example, excessive nutrient) disturbances. Vulnerable waters include non-floodplain wetlands and headwater streams, abundant watershed components representing the most distal extent of the freshwater aquatic network. Vulnerable waters are hydrologically dynamic and biogeochemically reactive aquatic systems, storing, processing, and releasing water and entrained (that is, dissolved and particulate) materials along expanding and contracting aquatic networks. The hydrological and biogeochemical functions emerging from these processes affect the magnitude, frequency, timing, duration, storage, and rate of change of material and energy fluxes among watershed components and to downstream waters, thereby maintaining watershed states and imparting watershed resilience. We present here a conceptual framework for understanding how vulnerable waters confer watershed resilience. We demonstrate how individual and cumulative vulnerable-water modifications (for example, reduced extent, altered connectivity) affect watershed-scale hydrological and biogeochemical disturbance response and recovery, which decreases watershed resilience and can trigger transitions across thresholds to alternative watershed states (for example, states conducive to increased flood frequency or nutrient concentrations). We subsequently describe how resilient watersheds require spatial heterogeneity and temporal variability in hydrological and biogeochemical interactions between terrestrial systems and down-gradient waters, which necessitates attention to the conservation and restoration of vulnerable waters and their downstream connectivity gradients. To conclude, we provide actionable principles for resilient watersheds and articulate research needs to further watershed resilience science and vulnerable-water management.

Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S.

Global trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from climate-driven variability in wetland extent. We present an approach to concurrently track land cover disturbance and inundation extent across the Mid-Atlantic region, United States, using the Landsat archive in Google Earth Engine. Disturbance was identified as a change in greenness, using a harmonic linear regression approach, or as a change in growing season brightness. Inundation extent was mapped using a modified version of the U.S. Geological Survey's Dynamic Surface Water Extent (DSWE) algorithm. Annual (2015-2018) disturbance averaged 0.32% (1095 km2 year-1) of the study area per year and was most common in forested areas. While inundation extent showed substantial interannual variability, the co-occurrence of disturbance and declines in inundation extent represented a minority of both change types, totaling 109 km2 over the four-year period, and 186 km2, using the National Wetland Inventory dataset in place of the Landsat-derived inundation extent. When the annual products were evaluated with permitted wetland and stream fill points, 95% of the fill points were detected, with most found by the disturbance product (89%) and fewer found by the inundation decline product (25%). The results suggest that mapping inundation alone is unlikely to be adequate to find and track anthropogenic wetland loss. Alternatively, remotely tracking both disturbance and inundation can potentially focus efforts to protect, manage, and restore wetlands.

Mapping landscape-level hydrological connectivity of headwater wetlands to downstream waters: A geospatial modeling approach - Part 1.

Headwater wetlands affect ecosystem integrity of downstream waters; however, many wetlands - particularly geographically isolated wetlands (GIWs) - continue to be at risk. A significant portion of US federal policy is based on the jurisdictional status of wetlands, which is partly determined by the relationship between wetlands and downstream waters, including the cumulative impact of wetlands on those waters. We present a novel multi-phase geospatial modeling method to help elucidate hydrological relationship between GIWs and downstream waters at the landscape scale. The presented approach in this study used inundation maps derived from time series remotely sensed data between 1985 and 2010, weather and hydrological records, and ancillary geospatial data including information from the US Fish and Wildlife Service National Wetlands Inventory (NWI). The study site was a headwater catchment (292 km2) of the Choptank River Basin, located in the Mid-Atlantic region of USA, which contained a large number of Delmarva bays. The results showed inundation extent within GIWs varied, in aggregate, in response to weather variability (r = 0.58; p-value = 0.05), and was well correlated with streamflow (r = 0.81; p-value < 0.01) and base flow (r = 0.57; p-value < 0.1) conditions. The relationship between inundation patterns and stream discharge also varied with NWI hydrologic modifiers. The GIWs with water regime characterized by longer durations of flooding exhibited stronger correlations with stream discharge, but those GIWs with shorter durations of flooding were less correlated with stream discharge. This analysis suggests the mutual reliance (i.e., connection) of wetlands and streams on groundwater. GIWs appeared to function in aggregate, and it is likely that the combined effect of these wetlands significantly influenced the functioning of downstream waters.

Mapping landscape-level hydrological connectivity of headwater wetlands to downstream waters: A catchment modeling approach - Part 2.

In Part 1 of this two-part manuscript series, we presented an effective assessment method for mapping inundation of geographically isolated wetlands (GIWs) and quantifying their cumulative landscape-scale hydrological connectivity with downstream waters using time series remotely sensed data (Yeo et al., 2018). This study suggested strong hydrological coupling between GIWs and downstream waters at the seasonal timescale via groundwater. This follow-on paper investigates the hydrological connectivity of GIWs with downstream waters and cumulative watershed-scale hydrological impacts over multiple time scales. Modifications were made to the representation of wetland processes within the Soil and Water Assessment Tool (SWAT). A version of SWAT with improved wetland function, SWAT-WET, was applied to Greensboro Watershed, which is located in the Mid-Atlantic Region of USA, to simulate hydrological processes over 1985-2015 under two contrasting land use scenarios (i.e., presence and absence of GIWs). Comparative analysis of simulation outputs elucidated how GIWs could influence partitioning of precipitation between evapotranspiration (ET) and terrestrial water storage, and affect water transport mechanisms and routing processes that generate streamflow. Model results showed that GIWs influenced the watershed water budget and stream flow generation processes over the long-term (30 year), inter-annual, and monthly time scales. GIWs in the study watershed increased terrestrial water storage during the wet season, and buffered the dynamics of shallow groundwater during the dry season. The inter-annual modeling analysis illustrated that densely distributed GIWs can exert strong hydrological influence on downstream waters by regulating surface water runoff, while maintaining groundwater recharge and ET under changing (wetter) climate conditions. The study findings highlight the hydrological connectivity of GIWs with downstream waters and the cumulative hydrological influence of GIWs as hydrologic sources to downstream ecosystems through different runoff processes over multiple time scales.

Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams.

Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous landscape-scale ecological functions, many of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field-validated, landscape-scale approaches for classifying wetlands on the basis of their expected degree of hydrologic connectivity with stream networks. This study quantified seasonal variability in surface hydrologic connectivity (SHC) patterns between forested Delmarva bay wetland complexes and perennial/intermittent streams at 23 sites over a full-water year (2014-2015). Field data were used to develop metrics to predict SHC using hypothesized landscape drivers of connectivity duration and timing. Connection duration was most strongly related to the number and area of wetlands within wetland complexes as well as the channel width of the temporary stream connecting the wetland complex to a perennial/intermittent stream. Timing of SHC onset was related to the topographic wetness index and drainage density within the catchment. Stepwise regression modelling found that landscape metrics could be used to predict SHC duration as a function of wetland complex catchment area, wetland area, wetland number, and soil available water storage (adj-R 2 = 0.74, p < .0001). Results may be applicable to assessments of forested depressional wetlands elsewhere in the U.S. Mid-Atlantic and Southeastern Coastal Plain, where climate, landscapes, and hydrological inputs and losses are expected to be similar to the study area.

A watershed-scale model for depressional wetland-rich landscapes.

Wetlands are often dominant features in low relief, depressional landscapes and provide an array of hydrologically driven ecosystem services. However, contemporary models do not adequately represent the role of spatially distributed wetlands in watershed-scale water storage and flows. Such tools are critical to better understand wetland hydrological, biogeochemical, and biological functions and predict management and policy outcomes at varying spatial scales. To develop a new approach for simulating depressional landscapes, we modified the Soil and Water Assessment Tool (SWAT) model to incorporate improved representations of depressional wetland structure and hydrological processes. Specifically, we refined the model to incorporate: (1) water storage capacity and surface flowpaths of individual wetlands and (2) local wetland surface and subsurface exchange. We utilized this model, termed SWAT-DSF (DSF for Depressional Storage and Flows), to simulate the ~289 km2 Greensboro watershed within the Delmarva Peninsula of the US Coastal Plain. Model calibration and verification used both daily streamflow observations and remotely sensed surface water extent data (ca. 2-week temporal resolution), allowing us to assess model performance with respect to both streamflow and watershed inundation patterns. Our findings demonstrate that SWAT-DSF can successfully replicate distributed wetland processes and resultant watershed-scale hydrology. SWAT-DSF provides improved temporal and spatial characterization of watershed-scale water storage and flows in depressional landscapes, providing a new tool to quantify wetland functions at broad spatial scales.

Estimating restorable wetland water storage at landscape scales.

Globally, hydrologic modifications such as ditching and subsurface drainage have significantly reduced wetland water storage capacity (i.e., volume of surface water a wetland can retain) and consequent wetland functions. While wetland area has been well documented across many landscapes and used to guide restoration efforts, few studies have directly quantified the associated wetland storage capacity. Here, we present a novel raster-based approach to quantify both contemporary and potential (i.e., restorable) storage capacities of individual depressional basins across landscapes. We demonstrate the utility of this method by applying it to the Delmarva Peninsula, a region punctuated by both depressional wetlands and drainage ditches. Across the entire peninsula, we estimated that restoration (i.e., plugging ditches) could increase storage capacity by 80%. Focusing on an individual watershed, we found that over 59% of restorable storage capacity occurs within 20 m of the drainage network, and that 93% occurs within 1 m elevation of the drainage network. Our demonstration highlights widespread ditching in this landscape, spatial patterns of both contemporary and potential storage capacities, and clear opportunities for hydrologic restoration. In Delmarva and more broadly, our novel approach can inform targeted landscape-scale conservation and restoration efforts to optimize hydrologically mediated wetland functions.

The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware.

The dependence of downstream waters on upstream ecosystems necessitates an improved understanding of watershed-scale hydrological interactions including connections between wetlands and streams. An evaluation of such connections is challenging when, (1) accurate and complete datasets of wetland and stream locations are often not available and (2) natural variability in surface-water extent influences the frequency and duration of wetland/stream connectivity. The Upper Choptank River watershed on the Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands. In this analysis, wetland/stream surface water connections were quantified using multiple wetland and stream datasets, including headwater streams and depressions mapped from a lidar-derived digital elevation model. Surface-water extent was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. The frequency of wetland/stream connections increased as a more complete and accurate stream dataset was used and surface-water extent was included, in particular when the spatial resolution of the imagery was finer (i.e., <10 m). Depending on the datasets used, 12% to 60% of wetlands by count (21% to 93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50% to 94% of the watershed contributing direct surface water runoff to streamflow. This finding suggests that our interpretation of the frequency and duration of wetland/stream connections will be influenced not only by the spatial and temporal characteristics of wetlands, streams and potential flowpaths, but also by the completeness, accuracy and resolution of input datasets.

Impacts of Watershed Characteristics and Crop Rotations on Winter Cover Crop Nitrate-Nitrogen Uptake Capacity within Agricultural Watersheds in the Chesapeake Bay Region.

The adoption rate of winter cover crops (WCCs) as an effective conservation management practice to help reduce agricultural nutrient loads in the Chesapeake Bay (CB) is increasing. However, the WCC potential for water quality improvement has not been fully realized at the watershed scale. This study was conducted to evaluate the long-term impact of WCCs on hydrology and NO3-N loads in two adjacent watersheds and to identify key management factors that affect the effectiveness of WCCs using the Soil and Water Assessment Tool (SWAT) and statistical methods. Simulation results indicated that WCCs are effective for reducing NO3-N loads and their performance varied based on planting date, species, soil characteristics, and crop rotations. Early-planted WCCs outperformed late-planted WCCs on the reduction of NO3-N loads and early-planted rye (RE) reduced NO3-N loads by ~49.3% compared to the baseline (no WCC). The WCCs were more effective in a watershed dominated by well-drained soils with increased reductions in NO3-N fluxes of ~2.5 kg N·ha-1 delivered to streams and ~10.1 kg N·ha-1 leached into groundwater compared to poorly-drained soils. Well-drained agricultural lands had higher transport of NO3-N in the soil profile and groundwater due to increased N leaching. Poorly-drained agricultural lands had lower NO3-N due to extensive drainage ditches and anaerobic soil conditions promoting denitrification. The performance of WCCs varied by crop rotations (i.e., continuous corn and corn-soybean), with increased N uptake following soybean crops due to the increased soil mineral N availability by mineralization of soybean residue compared to corn residue. The WCCs can reduce N leaching where baseline NO3-N loads are high in well-drained soils and/or when residual and mineralized N availability is high due to the cropping practices. The findings suggested that WCC implementation plans should be established in watersheds according to local edaphic and agronomic characteristics for reducing N leaching.

Metolachlor metabolite (MESA) reveals agricultural nitrate-N fate and transport in Choptank River watershed.

Over 50% of streams in the Chesapeake Bay watershed have been rated as poor or very poor based on the index of biological integrity. The Choptank River estuary, a Bay tributary on the eastern shore, is one such waterway, where corn and soybean production in upland areas of the watershed contribute significant loads of nutrients and sediment to streams. We adopted a novel approach utilizing the relationship between the concentration of nitrate-N and the stable, water-soluble herbicide degradation product MESA {2-[2-ethyl-N-(1-methoxypropan-2-yl)-6-methylanilino]-2-oxoethanesulfonic acid} to distinguish between dilution and denitrification effects on the stream concentration of nitrate-N in agricultural subwatersheds. The ratio of mean nitrate-N concentration/(mean MESA concentration * 1000) for 15 subwatersheds was examined as a function of percent cropland on hydric soil. This inverse relationship (R(2)=0.65, p<0.001) takes into consideration not only dilution and denitrification of nitrate-N, but also the stream sampling bias of the croplands caused by extensive drainage ditch networks. MESA was also used to track nitrate-N concentrations within the estuary of the Choptank River. The relationship between nitrate-N and MESA concentrations in samples collected over three years was linear (0.95 ≤ R(2) ≤ 0.99) for all eight sampling dates except one where R(2)=0.90. This very strong correlation indicates that nitrate-N was conserved in much of the Choptank River estuary, that dilution alone is responsible for the changes in nitrate-N and MESA concentrations, and more importantly nitrate-N loads are not reduced in the estuary prior to entering the Chesapeake Bay. Thus, a critical need exists to minimize nutrient export from agricultural production fields and to identify specific conservation practices to address the hydrologic conditions within each subwatershed. In well drained areas, removal of residual N within the cropland is most critical, and practices such as cover crops which sequester the residual N should be strongly encouraged. In poorly drained areas where denitrification can occur, wetland restoration and controlled drained structures that minimize ditch flow should be used to maximize denitrification.

Potential pollutant sources in a Choptank River (USA) subwatershed and the influence of land use and watershed characteristics.

Row-crop and poultry production have been implicated as sources of water pollution along the Choptank River, an estuary and tributary of the Chesapeake Bay. This study examined the effects of land use, subwatershed characteristics, and climatic conditions on the water quality parameters of a subwatershed in the Choptank River watershed. The catchments within the subwatershed were defined using advanced remotely-sensed data and current geographic information system processing techniques. Water and sediment samples were collected in May-October 2009 and April-June 2010 under mostly baseflow conditions and analyzed for select bacteria, nitrate-N, ammonium-N, total arsenic, total phosphorus (TP), orthophosphate (ortho-P), and particle-phase phosphorus (PP); n=96 for all analytes except for arsenic, n=136, and for bacteria, n=89 (aqueous) and 62 (sediment). Detections of Enterococci and Escherichia coli concentrations were ubiquitous in this subwatershed and showed no correlation to location or land use, however larger bacterial counts were observed shortly after precipitation. Nitrate-N concentrations were not correlated with agricultural lands, which may reflect the small change in percent agriculture and/or the similarity of agronomic practices and crops produced between catchments. Concentration data suggested that ammonia emission and possible deposition to surface waters occurred and that these processes may be influenced by local agronomic practices and climatic conditions. The negative correlation of PP and arsenic concentrations with percent forest was explained by the stronger signal of the head waters and overland flow of particulate phase analytes versus dissolved phase inputs from groundwater. Service roadways at some poultry production facilities were found to redirect runoff from the facilities to neighboring catchment areas, which affected water quality parameters. Results suggest that in this subwatershed, catchments with poultry production facilities are possible sources for arsenic and PP as compared to catchment areas where these facilities were not present.

Relating nutrient and herbicide fate with landscape features and characteristics of 15 subwatersheds in the Choptank River watershed.

Excess nutrients and agrochemicals from non-point sources contribute to water quality impairment in the Chesapeake Bay watershed and their loading rates are related to land use, agricultural practices, hydrology, and pollutant fate and transport processes. In this study, monthly baseflow stream samples from 15 agricultural subwatersheds of the Choptank River in Maryland USA (2005 to 2007) were characterized for nutrients, herbicides, and herbicide transformation products. High-resolution digital maps of land use and forested wetlands were derived from remote sensing imagery. Examination of landscape metrics and water quality data, partitioned according to hydrogeomorphic class, provided insight into the fate, delivery, and transport mechanisms associated with agricultural pollutants. Mean Nitrate-N concentrations (4.9 mg/L) were correlated positively with percent agriculture (R(2)=0.56) and negatively with percent forest (R(2)=0.60). Concentrations were greater (p=0.0001) in the well-drained upland (WDU) hydrogeomorphic region than in poorly drained upland (PDU), reflecting increased denitrification and reduced agricultural land use intensity in the PDU landscape due to the prevalence of hydric soils. Atrazine and metolachlor concentrations (mean 0.29 µg/L and 0.19 µg/L) were also greater (p=0.0001) in WDU subwatersheds than in PDU subwatersheds. Springtime herbicide concentrations exhibited a strong, positive correlation (R(2)=0.90) with percent forest in the WDU subwatersheds but not in the PDU subwatersheds. In addition, forested riparian stream buffers in the WDU were more prevalent than in the PDU where forested patches are typically not located near streams, suggesting an alternative delivery mechanism whereby volatilized herbicides are captured by the riparian forest canopy and subsequently washed off during rainfall. Orthophosphate, CIAT (6-chloro-N-(1-methylethyl)-1,3,5-triazine-2,4-diamine), CEAT (6-chloro-N-ethyl-1,3,5-triazine-2,4-diamine), and MESA (2-[(2-ethyl-6-methylphenyl) (2-methoxy-1-methylethyl)amino]-2-oxoethanesulfonic acid) were also analyzed. These findings will assist efforts in targeting implementation of conservation practices to the most environmentally-critical areas within watersheds to achieve water quality improvements in a cost-effective manner.