Controls on Nutrients Across a Prairie Stream Watershed: Land Use and Riparian Cover Effects

Nutrient inputs generally are increased by human-induced land use changes and can lead to eutrophication and impairment of surface waters. Understanding the scale at which land use influences nutrient loading is necessary for the development of management practices and policies that improve water quality. The authors assessed the relationships between land use and stream nutrients in a prairie watershed dominated by intermittent stream flow in the first-order higher elevation reaches. Total nitrogen, nitrate, and phosphorus concentrations were greater in tributaries occupying the lower portions of the watershed, closely mirroring the increased density of row crop agriculture from headwaters to lower-elevation alluvial areas. Land cover classified at three spatial scales in each sub-basin above sampling sites (riparian in the entire catchment, catchment land cover, and riparian across the 2 km upstream) was highly correlated with variation in both total nitrogen (r² = 53%, 52%, and 49%, respectively) and nitrate (r² = 69%, 65%, and 56%, respectively) concentrations among sites. However, phosphorus concentrations were not significantly associated with riparian or catchment land cover classes at any spatial scale. Separating land use from riparian cover in the entire watershed was difficult, but riparian cover was most closely correlated with in-stream nutrient concentrations. By controlling for land cover, a significant correlation of riparian cover for the 2 km above the sampling site with in-stream nutrient concentrations could be established. Surprisingly, land use in the entire watershed, including small intermittent streams, had a large influence on average downstream water quality although the headwater streams were not flowing for a substantial portion of the year. This suggests that nutrient criteria may not be met only by managing permanently flowing streams.     

CORRELATION OF SELECTED WELL WATER QUALITY PARAMETERS WITH SOIL AND AQUIFER HYDROLOGIC PROPERTIES1

ABSTRACT: The geographical distribution of well water specific electrical conductivity and nitrate levels in a 932 km² ground water quality study area in the Fresno-Clovis, California, indicated that frequently areas of lower ground water salinity were also areas of relatively greater soil and aquifer permeability. From these observations and certain assumptions we hypothesized that the quality of the well water should be better in areas with permeable soils and geological formations. Correlation and multiple linear regression analysis supported this hypothesis for well water salinity. However, well water nitrate levels were significantly negatively correlated with only the estimated equivalent specific yield of the aquifer system. The multiple R² values of the most significant multiple linear regression models showed that only a fourth to a third of the variability in well water specific electric conductivity and nitrate levels could be ascribed to the effects of the hydrogeological parameters considered with more than 90 percent confidence. This indicates that three-fourths to two-thirds of the variability in ground water salinity and nitrate levels may be related to land use. Thus, there is considerable room for land use management techniques to improve ground water quality and reduce its variability.     

Linking Biological Integrity and Watershed Models to Assess the Impacts of Historical Land Use and Climate Changes on Stream Health

Land use change and other human disturbances have significant impacts on physicochemical and biological conditions of stream systems. Meanwhile, linking these disturbances with hydrology and water quality conditions is challenged due to the lack of high-resolution datasets and the selection of modeling techniques that can adequately deal with the complex and nonlinear relationships of natural systems. This study addresses the above concerns by employing a watershed model to obtain stream flow and water quality data and fill a critical gap in data collection. The data were then used to estimate fish index of biological integrity (IBI) within the Saginaw Bay basin in Michigan. Three methods were used in connecting hydrology and water quality variables to fish measures including stepwise linear regression, partial least squares regression, and fuzzy logic. The IBI predictive model developed using fuzzy logic showed the best performance with the R ² = 0.48. The variables that identified as most correlated to IBI were average annual flow, average annual organic phosphorus, average seasonal nitrite, average seasonal nitrate, and stream gradient. Next, the predictions were extended to pre-settlement (mid-1800s) land use and climate conditions. Results showed overall significantly higher IBI scores under the pre-settlement land use scenario for the entire watershed. However, at the fish sampling locations, there was no significant difference in IBI. Results also showed that including historical climate data have strong influences on stream flow and water quality measures that interactively affect stream health; therefore, should be considered in developing baseline ecological conditions.     

Application of best subset method for river water quality modeling: A study on Godavari River,India

The utilization of water quality analysis to inform optimal decision-making is imperative to achieve sustainable management of river water quality. A multitude of research works in the past has focused on river water quality modeling. Despite being a precise statistical regression technique that allows for fitting separate models for all potential combinations of predictors and selecting the optimal subset model, the application of best subset method in river water quality modeling is not widely adopted. The current research aims to validate the use of best subset method in evaluating the water quality parameters of the Godavari River, one of the largest rivers in India, by developing regression equations for different combinations of its physicochemical parameters. The study involves in formulating best subset regression equations to estimate the concentrations of river water quality parameters while also identifying and quantifying their variations. A total of 17 water quality parameters are analyzed at 13 monitoring sites using 13 years (1993–2005) of observed data for the monsoon (June–October) period and post-monsoon (November–February) period. The final subset model is selected among model combinations that are developed for each year's dataset through widely used statistical criteria such as R², F value, adjusted R²_a, AIC_c, and RSS. The final best subset model across all parameters exhibits R² values surpassing 0.8, indicating that the models possess the ability to account for over 80% of the variations in the concentrations of dependent parameters. Therefore, the findings demonstrated the appropriateness of this method in evaluating the water quality parameters in extensive rivers. This work is very useful for decision-making and in the management of river water quality for its sustainable use in the study area.     

Climatic and stream-flow controls on tree growth in a Western montane riparian forest

Humans have severely impacted riparian ecosystems through water diversions, impoundments, and consumptive uses. Effective management of these important areas is becoming an increasingly high priority of land managers, particularly as municipal, industrial, and recreational demands for water increase. We examined radial tree growth of four riparian tree species (Pinus jeffreyi, Populus trichocarpa, Betula occidentalis, and Pinus monophylla) along Bishop Creek, California, and developed models relating basal area increment (BAI) and relative basal area increment (RBAI) to climatic and stream flow variables. Between years 1995–1999, univariate regression analysis with stream flow explained 29 to 61% of the variation in BAI and RBAI among all species except P. trichocarpa; growth by P. trichocarpa was not significantly related to stream flows over this period. Stepwise linear regression indicated that species responded differently to climatic variables, and models based on these variables explained between 33 to 86% of variation in BAI and RBAI during the decade of the 1990s. We examined branch growth of P. trichocarpa for sensitivity to differences in stream flow regimes and found that annual branch growth did not vary between a high- and low-flow site, but that annual branch growth was significantly higher in wet years with greater stream flows. Our results support the establishment of site-specific management goals by land managers that take into account all of the important tree species present in riparian ecosystems and their differential responses to altered hydrologic condition. Instream flow requirements for maintaining tree growth and vigor are only one of the species-specific responses that need to be evaluated, and these assessments should attempt to separate experimentally stream-flow (managed) controls from climatic (unmanaged) controls on growth.     

Testing the Hydrological Landscape Unit Classification System and Other Terrain Analysis Measures for Predicting Low-Flow Nitrate and Chloride in Watersheds

Elevated nitrate concentrations in streamwater are a major environmental management problem. While land use exerts a large control on stream nitrate, hydrology often plays an equally important role. To date, predictions of low-flow nitrate in ungauged watersheds have been poor because of the difficulty in describing the uniqueness of watershed hydrology over large areas. Clearly, hydrologic response varies depending on the states and stocks of water, flow pathways, and residence times. How to capture the dominant hydrological controls that combine with land use to define streamwater nitrate concentration is a major research challenge. This paper tests the new Hydrologic Landscape Regions (HLRs) watershed classification scheme of Wolock and others (Environmental Management 34:S71-S88, 2004) to address the question: Can HLRs be used as a way to predict low-flow nitrate? We also test a number of other indexes including inverse-distance weighting of land use and the well-known topographic index (TI) to address the question: How do other terrain and land use measures compare to HLR in terms of their ability to predict low-flow nitrate concentration? We test this for 76 watersheds in western Oregon using the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program and Regional Environmental Monitoring and Assessment Program data. We found that HLRs did not significantly improve nitrate predictions beyond the standard TI and land-use metrics. Using TI and inverse-distance weighting did not improve nitrate predictions; the best models were the percentage land use—elevation models. We did, however, see an improvement of chloride predictions using HLRs, TI, and inverse-distance weighting; adding HLRs and TI significantly improved model predictions and the best models used inverse-distance weighting and elevation. One interesting result of this study is elevation consistently predicted nitrate better than TI or the hydrologic classification scheme.     

Air‐Water Temperature Relationships in the Trout Streams of Southeastern Minnesota's Carbonate‐Sandstone Landscape

Carbonate‐sandstone geology in southeastern Minnesota creates a heterogeneous landscape of springs, seeps, and sinkholes that supply groundwater into streams. Air temperatures are effective predictors of water temperature in surface‐water dominated streams. However, no published work investigates the relationship between air and water temperatures in groundwater‐fed streams (GWFS) across watersheds. We used simple linear regressions to examine weekly air‐water temperature relationships for 40 GWFS in southeastern Minnesota. A 40‐stream, composite linear regression model has a slope of 0.38, an intercept of 6.63, and R² of 0.83. The regression models for GWFS have lower slopes and higher intercepts in comparison to surface‐water dominated streams. Regression models for streams with high R² values offer promise for use as predictive tools for future climate conditions. Climate change is expected to alter the thermal regime of groundwater‐fed systems, but will do so at a slower rate than surface‐water dominated systems. A regression model of intercept vs. slope can be used to identify streams for which water temperatures are more meteorologically than groundwater controlled, and thus more vulnerable to climate change. Such relationships can be used to guide restoration vs. management strategies to protect trout streams.     

Linking Landscape Characteristics and High Stream Nitrogen in the Oregon Coast Range: Red Alder Complicates Use of Nutrient Criteria

Red alder (Alnus rubra), a nitrogen(N)‐fixing deciduous broadleaf tree, can strongly influence N concentrations in western Oregon and Washington. We compiled a database of stream N and GIS‐derived landscape characteristics in order to examine geographic variation in N across the Oregon Coast Range. Basal area of alder, expressed as a percent of watershed area, accounted for 37% and 38% of the variation in summer nitrate and total N (TN) concentrations, respectively. Relationships between alder and nitrate were strongest in winter when streamflow and landscape connections are highest. Distance to the coast and latitude, potential surrogates for sea salt inputs, and watershed area were also related to nitrate concentrations in an all‐subsets regression analysis, which accounted for 46% of the variation in summer nitrate concentrations. The model with the lowest Akaike's Information Criterion did not include developed or agricultural land cover, probably because few watersheds in our database had substantial levels of these land cover classes. Our results provide evidence, at a regional scale, that background sources and processes cause many Coast Range streams to exceed proposed nutrient criteria, and that the prevalence of a single tree species (N‐fixing red alder) exerts a dominant control over stream N concentrations across this region.     

Effects of Land Use and Sample Location on Nitrate‐Stream Flow Hysteresis Descriptors during Storm Events

The U.S. Geological Survey's New Jersey and Iowa Water Science Centers deployed ultraviolet‐visible spectrophotometric sensors at water‐quality monitoring sites on the Passaic and Pompton Rivers at Two Bridges, New Jersey, on Toms River at Toms River, New Jersey, and on the North Raccoon River near Jefferson, Iowa to continuously measure in‐stream nitrate plus nitrite as nitrogen (NO₃ + NO₂) concentrations in conjunction with continuous stream flow measurements. Statistical analysis of NO₃ + NO₂ vs. stream discharge during storm events found statistically significant links between land use types and sampling site with the normalized area and rotational direction of NO₃ + NO₂‐stream discharge (N‐Q) hysteresis patterns. Statistically significant relations were also found between the normalized area of a hysteresis pattern and several flow parameters as well as the normalized area adjusted for rotational direction and minimum NO₃ + NO₂ concentrations. The mean normalized hysteresis area for forested land use was smaller than that of urban and agricultural land uses. The hysteresis rotational direction of the agricultural land use was opposite of that of the urban and undeveloped land uses. An r² of 0.81 for the relation between the minimum normalized NO₃ + NO₂ concentration during a storm vs. the normalized NO₃ + NO₂ concentration at peak flow suggested that dilution was the dominant process controlling NO₃ + NO₂ concentrations over the course of most storm events.     

STREAM DISCHARGE PREDICTION VIA A GRID BASED SOIL WATER ROUTING WITH PADDY FIELDS1

ABSTRACT: A grid based daily hydrologic model for a watershed with paddy fields was developed to predict the stream discharge. ASCII formatted elevation, soil, and land use data supported by the GRASS Geographic Information System are used to generate distributed results such as surface runoff and subsurface flow, soil water content, and evapotranspiration. The model uses a single flow path algorithm and simulates a water balance at each grid element. A linear reservoir assumption was used to predict subsurface runoff components. The model was applied to a 75.6 km² watershed located in the middle of South Korea, and observed stream flow hydrographs from 1995 and 1996 were compared to model predictions. The stream flow predictions of 1995 and 1996 generally agreed with the observed flow, resulting in a Nash‐Sutcliffe efficiency R² of 0.60 and 0.62, respectively. The hydraulic conductivity for percolating water through the saturated layer affected baseflow generation. The levee height of the paddy influenced the time and magnitude of the surface runoff, depending on irrigation management. The model will be used for making low flow management decisions by evaluating the role of each land use to stream flow, especially in case of paddy decrease by gradual urbanization of a watershed.     

Stream Discharge and Riparian Land Use Influence In-Stream Concentrations and Loads of Phosphorus from Central Plains Watersheds

Total annual nutrient loads are a function of both watershed characteristics and the magnitude of nutrient mobilizing events. We investigated linkages among land cover, discharge and total phosphorus (TP) concentrations, and loads in 25 Kansas streams. Stream monitoring locations were selected from the Kansas Department of Health and Environment stream chemistry long-term monitoring network sites at or near U.S. Geological Survey stream gauges. We linked each sample with concurrent discharge data to improve our ability to estimate TP concentrations and loads across the full range of possible flow conditions. Median TP concentration was strongly linked (R ² = 76%) to the presence of cropland in the riparian zones of the mostly perennial streams. At baseflow, discharge data did not improve prediction of TP, but at high flows discharge was strongly linked to concentration (a threshold response occurred). Our data suggest that on average 88% of the total load occurred during the 10% of the time with the greatest discharge. Modeled reductions in peak discharges, representing increased hydrologic retention, predicted greater decreases in total annual loads than reductions of ambient concentrations because high discharge and elevated phosphorus concentrations had multiplicative effects. No measure of land use provided significant predictive power for concentrations when discharge was elevated or for concentration rise rates under increasing discharge. These results suggest that reductions of baseflow concentrations of TP in streams without wastewater dischargers may be managed by reductions of cropland uses in the riparian corridor. Additional measures may be needed to manage TP annual loads, due to the large percentage of the TP load occurring during a few high-flow events each year.     

DIN Retention‐Transport Through Four Hydrologically Connected Zones in a Headwater Catchment of the Upper Mississippi River1

Abstract: Dissolved inorganic nitrogen (DIN) retention‐transport through a headwater catchment was synthesized from studies encompassing four distinct hydrologic zones of the Shingobee River Headwaters near the origin of the Mississippi River. The hydrologic zones included: (1) hillslope ground water (ridge to bankside riparian); (2) alluvial riparian ground water; (3) ground water discharged through subchannel sediments (hyporheic zone); and (4) channel surface water. During subsurface hillslope transport through Zone 1, DIN, primarily nitrate, decreased from ～3 mg‐N/l to <0.1 mg‐N/l. Ambient seasonal nitrate:chloride ratios in hillslope flow paths indicated both dilution and biotic processing caused nitrate loss. Biologically available organic carbon controlled biotic nitrate retention during hillslope transport. In the alluvial riparian zone (Zone 2) biologically available organic carbon controlled nitrate depletion although processing of both ambient and amended nitrate was faster during the summer than winter. In the hyporheic zone (Zone 3) and stream surface water (Zone 4) DIN retention was primarily controlled by temperature. Perfusion core studies using hyporheic sediment indicated sufficient organic carbon in bed sediments to retain ground water DIN via coupled nitrification‐denitrification. Numerical simulations of seasonal hyporheic sediment nitrification‐denitrification rates from perfusion cores adequately predicted surface water ammonium but not nitrate when compared to 5 years of monthly field data (1989‐93). Mass balance studies in stream surface water indicated proportionally higher summer than winter N retention. Watershed DIN retention was effective during summer under the current land use of intermittently grazed pasture. However, more intensive land use such as row crop agriculture would decrease nitrate retention efficiency and increase loads to surface water. Understanding DIN retention capacity throughout the system, including special channel features such as sloughs, wetlands and floodplains that provide surface water‐ground water connectivity, will be required to develop effective nitrate management strategies.     

Impact of an Invasive Exotic Species on Stream Nitrogen Levels in Southern Illinois1

Abstract: Autumn‐olive (Elaeagnus umbellata Thunb.) is an invasive, exotic shrub that has become naturalized in the eastern United States. Autumn‐olive fixes nitrogen (N) via a symbiotic relationship with the actinomycete Frankia. At the plot scale, the presence of autumn‐olive has been related to elevated soil water nitrate‐N (NO₃^?‐N) concentrations. This study examined the relationship between autumn‐olive cover in a watershed and stream water quality. Stream water nitrate‐N (NO₃^?‐N) and ammonium‐N (NH₄⁺‐N) concentrations were measured in 12 first order ephemeral streams draining watersheds with mixed forest cover and a range of 0‐35% autumn‐olive cover. Percent autumn‐olive cover was positively correlated with mean stream NO₃^?‐N concentrations, but was not correlated with mean stream NH₄⁺‐N concentrations. While other studies have demonstrated a significant relationship between native N‐fixers and stream NO₃^?‐N, this is the first study to document a relationship for an invasive, exotic N‐fixing species. Results suggest that this exotic species can be an additional source of NO₃^? in local and regional water bodies and demonstrates an additional negative ecosystem consequence of invasion beyond losses in biodiversity.     

Relative Influence of Streamflows in Assessing Temporal Variability in Stream Habitat1

Abstract: The effects of streamflows on temporal variation in stream habitat were analyzed from the data collected 6‐11 years apart at 38 sites across the United States. Multiple linear regression was used to assess the variation in habitat caused by streamflow at the time of sampling and high flows between sampling. In addition to flow variables, the model also contained geomorphic and land use factors. The regression model was statistically significant (p < 0.05; R² = 0.31‐0.46) for 5 of 14 habitat variables: mean wetted stream depth, mean bankfull depth, mean wetted stream width, coefficient of variation of wetted stream width, and the percent frequency of bank erosion. High flows between samples accounted for about 16% of the total variation in the frequency of bank erosion. Streamflow at the time of sampling was the main source of variation in mean stream depth and contributed to the variation in mean stream width and the frequency of bank erosion. Urban land use (population change) accounted for over 20% of the total variation in mean bankfull depth, 15% of the total variation in the coefficient of variation of stream width, and about 10% of the variation in mean stream width.     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

GROUNDWATER DISCHARGE AND ITS IMPACT ON SURFACE WATER QUALITY IN A CHESAPEAKE BAY INLET1

ABSTRACT: Surface water, groundwater, and groundwater discharge quality surveys were conducted in Cherrystone Inlet, on Virginia's Eastern Shore. Shallow groundwater below agricultural fields had nitrate concentrations significantly higher than inlet surface waters and shallow groundwater underlying forested land. This elevated nitrate groundwater discharged to adjacent surface waters. Nearshore discharge rates of water across the sediment-water interface ranged from 0.02 to 3.69 liters·m^?2·hr^?1 during the surveys. The discharge was greatest nearshore at low tide periods, and decreased markedly with increasing distance offshore. Vertical hydraulic heads, E_h, and inorganic nitrogen flux in the sediments followed similar patterns. Nitrate was the predominant nitrogen species discharged nearshore adjacent to agricultural land use, changing to ammonium farther offshore. Sediment nitrogen fluxes were sufficient to cause observable impacts on surface water quality; nitrate concentrations were up to 20 times greater in areas of groundwater discharge than in the main stem inlet water. Based on DIN:DIP ratios, nitrogen contributions from direct groundwater discharge and tidal creek inputs appear to be of significant ecological importance. This groundwater discharge links land use activity and the quality of surface water, and therefore must be considered in selection of best management practices and water quality management strategies.     

TREE-RING RECONSTRUCTION OF UPPER GILA RWER DISCHARGE1

ABSTRACT: Effective planning for use of water resources requires accurate information on hydrologic variability induced by climatic fluctuations. Tree-ring analysis is one method of extending our knowledge of hydrologic variability beyond the relatively short period covered by gaged streamflow records. In this paper, a network of recently developed tree-ring chronologies is used to reconstruct annual river discharge in the upper Gila River drainage in southeastern Arizona and southwestern Arizona since A.D. 1663. The need for data on hydrologic variability for this semi-arid basin is accentuated because water supply is inadequate to meet current demand. A reconstruction based on multiple linear regression (R²=0.66) indicates that 20th century is unusual for clustering of high-discharge years (early 1900s), severity of multiyear drought (1950s), and amplification of low-frequency discharge variations. Periods of low discharge recur at irregular intervals averaging about 20 years. Comparison with other tree-ring reconstructions shows that these low-flow periods are synchronous from the Gila Basin to the southern part of the Upper Colorado River Basin.     

Spatiotemporal Variability in Water Sources Controls Chemical and Physical Properties of a Semi‐arid Urban River System

We conducted synoptic surveys over three seasons in one year to evaluate the variability in water sources and geochemistry of an urban river with complex water infrastructure in the state of Utah. Using stable isotopes of river water (δ¹⁸O and δ²H) within a Bayesian mixing model framework and a separate hydrologic mass balance approach, we quantified both the proportional inputs and magnitude of discharge associated with “natural” (lake, groundwater, and tributary inputs) and “engineered” (effluent and canal inflows) sources. The relative importance of these major contributors to streamflow varied both spatially and seasonally. Spatiotemporal patterns of dissolved oxygen, temperature, pH, calcium, chloride, nitrate, and orthophosphate indicated seasonal shifts in dominant sources of river water played an important role in determining water quality. We show although urban rivers are clearly influenced by novel water sources created by water infrastructure, they continue to reflect the imprint of “natural” water sources, including diffuse groundwater. Resource managers thus may need to account for the quantity of both surface waters and also historically overlooked groundwater inputs to address water quality concerns in urban rivers.     

Identifying relationships between baseflow geochemistry and land use with synoptic sampling and R-mode factor analysis

The relationship between land use and stream chemistry is often explored through synoptic sampling of rivers at baseflow conditions. However, baseflow chemistry is likely to vary temporally and spatially with land use. The purpose of our study is to examine the usefulness of the synoptic sampling approach for identifying the relationship between complex land use configurations and stream water quality. This study compares biogeochemical data from three synoptic sampling events representing the temporal variability of baseflow chemistry and land use using R-mode factor analysis. Separate R-mode factor analyses of the data from individual sampling events yielded only two consistent factors. Agricultural activity was associated with elevated levels of Ca2+, Mg2+, alkalinity, and frequently K+, SO4(2-), and NO3-. Urban areas were associated with higher concentrations of Na+, K+, and Cl-. Other retained factors were not consistent among sampling events, and some factors were difficult to interpret in the context of biogeochemical sources and processes. When all data were combined, further associations were revealed such as an inverse relationship between the proportion of wetlands and stream nitrate concentrations. We also found that barren lands were associated with elevated sulfate levels. This research suggests that an individual sampling event is unlikely to characterize adequately the complex processes controlling interactions between land use and stream chemistry. Combining data collected over two years during three synoptic sampling events appears to enhance our ability to understand processes linking stream chemistry and land use.