Monitoring nutrient transport in large rivers

The problem of estimating nutrient transport in large rivers and the uncertainty of such load estimates was studied both empirically and theoretically. In the empirical part of the study, time series of data from the Rhine, Meuse, Vistula and Oder Rivers were examined. The results of this data analysis justify the use of linear interpolation to estimate concentrations prevailing between sampling occasions. A special study of the spatial variation of concentrations within different cross-sections of the Vistula river showed that such variation can contribute substantially to the uncertainty of load estimates. In general, however, sampling at one point in the cross-section did not result in biased load estimates. In the theoretical part of the study, simple ARMA (autoregressive-moving average) models were used to derive generally applicable formulas for the expected mean square error of load estimates based on serially dependent concentration data. These formulas were then used to estimate the uncertainty of calculated nutrient loads in the Rhine and the Vistula, respectively.     

Assessing uncertainty in annual nitrogen,phosphorus, and suspended sediment load estimates in three agricultural streams using a 21-year dataset

Accurate estimation of constituent loads is important for studies of ecosystem mass balance or total maximum daily loads. In response, there has been an effort to develop methods to increase both accuracy and precision of constituent load estimates. The relationship between constituent concentration and stream discharge is often complicated, potentially leading to high uncertainty in load estimates for certain constituents, especially at longer-term (annual) scales. We used the loadflex R package to compare uncertainty in annual load estimates from concentration vs. discharge relationships in constituents of interest in agricultural systems, including ammonium as nitrogen (NH₄-N), nitrate as nitrogen (NO₃-N), soluble reactive phosphorus (SRP), and suspended sediments (SS). We predicted that uncertainty would be greatest in NO₃-N and SS due to complex relationships between constituent concentration and discharge. We also predicted lower uncertainty with a composite method compared to regression or interpolation methods. Contrary to predictions, we observed the lowest uncertainty in annual NO₃-N load estimates (relative error 1.5–23%); however, uncertainty was greatest in SS load estimates, consistent with predictions (relative error 19–96%). For all constituents, we also generally observed reductions in uncertainty by up to 34% using the composite method compared to regression and interpolation approaches, as predicted. These results highlight differences in uncertainty among different constituents and will aid in model selection for future studies requiring accurate and precise estimates of constituent load.     

Sampling Considerations for Establishment of Baseline Loadings from Forested Watersheds for TMDL Application

Five methods for estimating maximum daily and annual nitrate (NO3) and suspended sediment loads using periodic sampling of varying intensities were compared to actual loads calculated from intensive stormflow and baseflow sampling from small, forested watersheds in north central West Virginia to determine if the less intensive sampling methods were accurate and could be utilized in TMDL development. There were no significant differences between the annual NO3 load estimates using non-intensive sampling methods and the actual NO3 loads. However, maximum daily NO3 loads were estimated less accurately than annual loads. The ability to estimate baseline NO3 loads fairly accurately with non-intensive concentration data is attributed to the small fluctuation in NO3 concentrations over flow and time, particularly during storms. By contrast, suspended sediment exports determined by any of the non-intensive methods varied significantly and widely from and compared poorly to the actual exports for both daily and annual methods. Weekly sampling better approximated actual annual exports, but there were no significant statistical differences among weekly, monthly, and quarterly estimates. Suspended sediment concentrations varied widely within and among storm events, so that accurate estimates of total annual or maximum daily loads could not be obtained from infrequent sampling.     

Influence of different nitrate–N monitoring strategies on load estimation as a base for model calibration and evaluation

Model-based predictions of the impact of land management practices on nutrient loading require measured nutrient flux data for model calibration and evaluation. Consequently, uncertainties in the monitoring data resulting from sample collection and load estimation methods influence the calibration, and thus, the parameter settings that affect the modeling results. To investigate this influence, we compared three different time-based sampling strategies and four different load estimation methods for model calibration and compared the results. For our study, we used the river basin model Soil and Water Assessment Tool on the intensively managed loess-dominated Parthe watershed (315 km²) in Central Germany. The results show that nitrate–N load estimations differ considerably depending on sampling strategy, load estimation method, and period of interest. Within our study period, the annual nitrate–N load estimation values for the daily composite data set have the lowest ranges (between 9.8% and 15.7% maximum deviations related to the mean value of all applied methods). By contrast, annual estimation results for the submonthly and the monthly data set vary in greater ranges (between 24.9% and 67.7%). To show differences between the sampling strategies, we calculated the percentage deviation of mean load estimations of submonthly and monthly data sets as related to the mean estimation value of the composite data set. For nitrate–N, the maximum deviation is 64.5% for the submonthly data set in the year 2000. We used average monthly nitrate–N loads of the daily composite data set to calibrate the model to achieve satisfactory simulation results [Nash–Sutcliffe efficiency (NSE) 0.52]. Using the same parameter settings with submonthly and monthly data set, the NSE dropped to 0.42 and 0.31, respectively. Considering the different results from the monitoring strategy and the load estimation method, we recommend both the implementation of optimized monitoring programs and the use of multiple load estimation methods to improve water quality characterization and provide appropriate model calibration and evaluation data.     

Longitudinal variability in streamwater chemistry and carbon and nitrogen fluxes in restored and degraded urban stream networks

Stream restoration has increasingly been used as a best management practice for improving water quality in urbanizing watersheds, yet few data exist to assess restoration effectiveness. This study examined the longitudinal patterns in carbon and nitrogen concentrations and mass balance in two restored (Minebank Run and Spring Branch) and two unrestored (Powder Mill Run and Dead Run) stream networks in Baltimore, Maryland, USA. Longitudinal synoptic sampling showed that there was considerable reach-scale variability in biogeochemistry (e.g., total dissolved nitrogen (TDN), dissolved organic carbon (DOC), cations, pH, oxidation/reduction potential, dissolved oxygen, and temperature). TDN concentrations were typically higher than DOC in restored streams, but the opposite pattern was observed in unrestored streams. Mass balances in restored stream networks showed net uptake of TDN across subreaches (mean ± standard error net uptake rate of TDN across sampling dates for Minebank Run and Spring Branch was 420.3 ± 312.2 and 821.8 ± 570.3 mg m(-2) d(-1), respectively). There was net release of DOC in the restored streams (1344 ± 1063 and 1017 ± 944.5 mg m(-2) d(-1) for Minebank Run and Spring Branch, respectively). Conversely, degraded streams, Powder Mill Run and Dead Run showed mean net release of TDN across sampling dates (629.2 ± 167.5 and 327.1 ± 134.5 mg m(-2) d(-1), respectively) and net uptake of DOC (1642 ± 505.0 and 233.7 ± 125.1 mg m(-2) d(-1), respectively). There can be substantial C and N transformations in stream networks with hydrologically connected floodplain and pond features. Assessment of restoration effectiveness depends strongly on where monitoring is conducted along the stream network. Monitoring beyond the stream-reach scale is recommended for a complete perspective of evaluation of biogeochemical function in restored and degraded urban streams.     

The effects of subsampling and sampling frequency on the use of surface-floating pupal exuviae to measure Chironomidae (Diptera) communities in wadeable temperate streams

Community, diversity, and biological index metrics for chironomid surface-floating pupal exuviae (SFPE) were assessed at different subsample sizes and sampling frequencies from wadeable streams in Minnesota (USA). Timed collections of SFPE were made using a biweekly sampling interval in groundwater-dominated (GWD) and surface-water-dominated (SWD) streams. These two types of stream were sampled because they support different Chironomidae communities with different phenologies which could necessitate sampling methodologies specific to each stream type. A subsample size of 300 individuals was sufficient to collect on average 85% of total taxa richness and to estimate most metrics with an error of about 1% relative to 1,000 count samples. SWD streams required larger subsample sizes to achieve similar estimates of taxa richness and metric error compared to GWD streams, but these differences were not large enough to recommend different subsampling methods for these stream types. Analysis of sample timing determined that 97% of emergence occurred from April through September. We recommend in studies where estimation of winter emergence is not important that sampling be limited to this period. Sampling frequency also affected the proportion of the community collected. To maximize the portion of the community, collected samples should be taken across seasons although no specific sampling interval is recommended. Subsampling and sampling frequency was also assessed simultaneously. When using a 300-count subsample, a 4-week sampling interval from April through September was required to collect on average 71% of the community. Due to differences in elements of the chironomid community evaluated by different studies (e.g., biological condition, phenology, and taxonomic composition), richness estimates are documented for five sampling intervals (2, 4, 6, 8, 10, and 12 weeks) and five subsample sizes (100, 200, 300, 500, and 1,000 counts). This research will enhance future studies by providing guidelines for tailoring SFPE methods to study specific goals and resources.     

An urban observatory for quantifying phosphorus and suspended solid loads in combined natural and stormwater conveyances

Water quality in urban streams and stormwater systems is highly dynamic, both spatially and temporally, and can change drastically during storm events. Infrequent grab samples commonly collected for estimating pollutant loadings are insufficient to characterize water quality in many urban water systems. In situ water quality measurements are being used as surrogates for continuous pollutant load estimates; however, relatively few studies have tested the validity of surrogate indicators in urban stormwater conveyances. In this paper, we describe an observatory aimed at demonstrating the infrastructure required for surrogate monitoring in urban water systems and for capturing the dynamic behavior of stormwater-driven pollutant loads. We describe the instrumentation of multiple, autonomous water quality and quantity monitoring sites within an urban observatory. We also describe smart and adaptive sampling procedures implemented to improve data collection for developing surrogate relationships and for capturing the temporal and spatial variability of pollutant loading events in urban watersheds. Results show that the observatory is able to capture short-duration storm events within multiple catchments and, through inter-site communication, sampling efforts can be synchronized across multiple monitoring sites.     

Determining storm sampling requirements for improving precision of annual load estimates of nutrients from a small forested watershed

This study sought to determine the lowest number of storm events required for adequate estimation of annual nutrient loads from a forested watershed using the regression equation between cumulative load (∑L) and cumulative stream discharge (∑Q). Hydrological surveys were conducted for 4 years, and stream water was sampled sequentially at 15-60-min intervals during 24 h in 20 events, as well as weekly in a small forested watershed. The bootstrap sampling technique was used to determine the regression (∑L-∑Q) equations of dissolved nitrogen (DN) and phosphorus (DP), particulate nitrogen (PN) and phosphorus (PP), dissolved inorganic nitrogen (DIN), and suspended solid (SS) for each dataset of ∑L and ∑Q. For dissolved nutrients (DN, DP, DIN), the coefficient of variance (CV) in 100 replicates of 4-year average annual load estimates was below 20% with datasets composed of five storm events. For particulate nutrients (PN, PP, SS), the CV exceeded 20%, even with datasets composed of more than ten storm events. The differences in the number of storm events required for precise load estimates between dissolved and particulate nutrients were attributed to the goodness of fit of the ∑L-∑Q equations. Bootstrap simulation based on flow-stratified sampling resulted in fewer storm events than the simulation based on random sampling and showed that only three storm events were required to give a CV below 20% for dissolved nutrients. These results indicate that a sampling design considering discharge levels reduces the frequency of laborious chemical analyses of water samples required throughout the year.     

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

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

Streamwater acid-base chemistry and critical loads of atmospheric sulfur deposition in Shenandoah National Park, Virginia

A modeling study was conducted to evaluate the acid-base chemistry of streams within Shenandoah National Park, Virginia and to project future responses to sulfur (S) and nitrogen (N) atmospheric emissions controls. Many of the major stream systems in the park have acid neutralizing capacity (ANC) less than 20 μeq/L, levels at which chronic and/or episodic adverse impacts on native brook trout are possible. Model hindcasts suggested that none of these streams had ANC less than 50 μeq/L in 1900. Model projections, based on atmospheric emissions controls representative of laws already enacted as of 2003, suggested that the ANC of those streams simulated to have experienced the largest historical decreases in ANC will increase in the future. The levels of S deposition that were simulated to cause streamwater ANC to increase or decrease to three specified critical levels (0, 20, and 50 μeq/L) ranged from less than zero (ANC level not attainable) to several hundred kg/ha/year, depending on the selected site and its inherent acid-sensitivity, selected ANC endpoint criterion, and evaluation year for which the critical load was calculated. Several of the modeled streams situated on siliciclastic geology exhibited critical loads <0 kg/ha/year to achieve ANC >50 μeq/L in the year 2040, probably due at least in part to base cation losses from watershed soil. The median modeled siliciclastic stream had a calculated critical load to achieve ANC >50 μeq/L in 2100 that was about 3 kg/ha/year, or 77% lower than deposition in 1990, representing the time of model calibration.     

Evaluation of phosphorus loads from Ontario municipal wastewater treatment plants

Results are presented from an evaluation of the nature and accuracy of phosphorus loads discharged by Ontario municipal wastewater treatment plants into the Great Lakes. Data were examined for the 96 plants treating flows in excess of 4546 m³d^-1 for the period 1981 to 1985. For the Lake Erie, Lake Ontario/St. Lawrence River and Upper Great Lakes basins, total basin phosphorus loads were classified according to type of wastewater treatment system, the type of chemical added for phosphorus removal, plant capacity, and sampling frequency. Load estimation techniques were compared using the 1985 daily data from three representative treatment plants. Annual phosphorus loads were compared using the complete data records for the plants and using Monte Carlo techniques to simulate an incomplete data record typical of once per week effluent phosphorus sampling. Potential sources of bias were identified in annual phosphorus load estimates from municipal treatment plants.     

Deposition in boreal forests in relation to type, size, number and placement of collectors

Open precipitation and throughfall was collected at a Norway spruce stand in Finland using funnel-type collectors and at a black spruce stand in Canada using trough-type collectors. The presence or absence of a rim on the funnel, funnel diameter (9, 14 and 20 cm) and length of sampling period (1, 2 and 4 weeks) on monthly values were evaluated at the Norway spruce stand, and the number of collectors required for defined levels of accuracy and precision of throughfall loads to be reached and the influence of the spatial arrangement of collectors on solute concentrations was studied at both stands. The presence of a rim had no significant effect on open precipitation and throughfall amounts, but did on throughfall DOC, Ca²⁺, Mg²⁺, K⁺, Na⁺ and Cl⁻ ion loads. Deposition loads increased with decreasing funnel diameter; for open precipitation, this was due to increased catch efficiency while for throughfall the increase was attributed to canopy interaction and leaching of litter trapped in the collectors. Calculated monthly H⁺ loads decreased and those for all other constituents increased with collection period length. Using 15 collectors at the Norway spruce stand would allow throughfall loads to be determined to within 20% of the true mean weekly value with a confidence level of 95% for most solute, but not for NH₄ ⁺–N, NO₃ ⁻–N, Mg²⁺ and SO₄ ²⁻-S. Using 15 trough collectors, the same confidence level at the more heterogeneous black spruce stand would only be achieved for H⁺, Cl⁻, DOC and SO₄ ²⁻-S loads. In both stands, using either random or systematic placements of throughfall collectors gave similar results.     

Carbon Tetrachloride Marine Risk Assessment with Special Reference to the Osparcom Region: North Sea

Accurate estimates of stressor levels in unsampled streams would provide valuable information for managing these resources over large regions. Spatial interpolation of stream characteristics have rarely been attempted, partly because defining separation distances between distinct stream samples is not straightforward. That is, conventional Eulerian definitions of separation distance may not apply to stream networks where information flows along distinct paths. A two-stage model for estimating stressor levels in unsampled streams is presented. Mean characteristics within streams are predicted usign a generalized additive model and residual variation is estimated using a conventional application of spatial statistics. The model is developed and tested using stream survey data collected in the state of Maryland, USA. Model efficiency is compared for three stream variables (nitrate concentration, sulfate concentration, and epifaunal substrate score) known to be associated with biological impairments in streams. Accounting for spatial autocorrelation in the residual variation improved model R2 from 0.71 to 0.81 for nitrate, from 0.29 to 0.63 for sulfate, and from 0.21 to 0.31 for epifaunal substrate score.     

Acidification reversal in low mountain range streams of Germany

This study evaluates the acidification status and trends in streams of forested mountain ranges in Germany in consequence of reduced anthropogenic deposition since the mid 1980s. The analysis is based on water quality data for 86 long-term monitored streams in the Ore Mountains, the Bavarian Forest, the Fichtelgebirge, the Harz Mountains, the Spessart, the Black Forest, the Thuringian Forest, and the Rheinisches Schiefergebirge of Germany and the Vosges of France. Within the observation period, which starts for the individual streams between 1980 and 2001 and ends between 1990 and 2009, trends in chemical water quality were calculated with the Seasonal Mann Kendall Test. About 87% of the streams show significant (p < 0.05) negative trends in sulfate. The general reduction in acid deposition resulted in increased pH values (significant for 66% of the streams) and subsequently decreased base cation concentrations in the stream water (for calcium significant in 58% and magnesium 49% of the streams). Reaction products of acidification such as aluminum (significant for 50%) or manganese (significant for 69%) also decreased. Nitrate (52% with significant decrease) and chloride (38% with significant increase) have less pronounced trends and more variable spatial patterns. For the quotient of acidification, which is the ratio of the sum of base cations and the sum of acid anions, no clear trend is observed: in 44% of the monitored streams values significantly decreased and in 23% values significantly increased. A notable observation is the increasing DOC concentration, which is significant for 55% of the observed streams.     

Estimation of riverine loads of nitrogen and phosphorus to the Baltic Sea, 1970–1993

This article presents the results of the first critical examination of time series of riverine nutrient-load data for the entire Baltic Sea drainage area. Water quality data collected by or for the different national environmental agencies were compiled and analysed statistically to identify and remove inconsistent or obviously incorrect observations. Moreover, sampling tours were undertaken to acquire additional information about the present nutrient concentrations in the largest rivers in the study area. Gaps in the time series of approved data were then filled in by employing statistical interpolation and extrapolation methods. Thereafter, the concentration and runoff data were combined to obtain estimates of monthly nutrient loads for the time period 1970–93. The results of the calculations showed that although there had been substantial changes in land use, atmospheric deposition and wastewater treatment in many parts of the study area, the total riverine loads of nitrogen (N) and phosphorus (P) to the Baltic Sea have been fairly constant since 1980, and most likely also since 1970. Moreover, the interannual variation was clearly correlated to the runoff. The mean annual loads for the time period 1980–93 were found to be about 825 000 tonnes N and 41 000 tonnes P, respectively. This implies that (i) several other investigators have strongly underestimated the riverine loads of nutrients, especially the nitrogen, and that (ii) the riverine loads by far exceed the input to the Baltic Sea from other sources, {i.e.} atmospheric deposition, direct emissions from cities and industries along the Baltic Sea coast and nitrogen fixation by marine algae.     

Selenium in surface and irrigation water in the Kendrick irrigation district, Wyoming

High selenium (Se) concentrations have been found in surface waters in the Kendrick Reclamation Project, Wyoming. Precipitation and irrigation water moving over seleniferous soils are contributing causes, and drought may exacerbate this. This study surveyed Se concentrations and discharges in local surface streams, irrigation drains, and the delivery canal. Sites were sampled monthly and analyzed for Se and total suspended solids (TSS). A completely randomized design with two factors (soil parent material and location, inside or outside irrigation district) was used. Mean Se concentrations were 64 μg L^???1 inside the irrigation district on shale soils, 17 μg L^???1 inside the district off shale soils, 5 μg L^???1 outside the district on shale soils, and 3 μg L^???1 outside the district off shale soils. Correlations between discharge and Se concentrations were generally negative, while correlations between discharge and Se load were generally positive. There was little correlation between load and concentration, and little correlation between TSS and Se. A comparison of Se concentrations in streams and drains showed Se concentrations were significantly higher (p?<?0.001) in streams during the irrigation season, but not in the off-season (p?=?0.515). We conclude that higher discharges decrease Se concentration, but increase load. Conversion from flood to sprinkle irrigation may increase Se concentrations by reducing discharge, but decrease Se loads going into the N. Platte River, and will likely alter the timing and magnitude of flows. Both load and concentration should be considered when implementing Se regulations and standards.     

Siting analyses for water quality sampling in a catchment

Pollution loads discharged from upstream development or human activities significantly degrade the water quality of a reservoir. The design of an appropriate water quality sampling network is therefore important for detecting potential pollution events and monitoring pollution trends. However, under a limited budgetary constraint, how to site an appropriate number of sampling stations is a challenging task. A previous study proposed a method applying the simulated annealing algorithm to design the sampling network based on three cost factors including the number of reaches, bank length, and subcatchment area. However, these factors are not directly related to the distribution of possible pollution. Thus, this study modified the method by considering three additional factors, i.e. total phosphorus, nitrogen, and sediment loads. The larger the possible load, the higher the probability of a pollution event may occur. The study area was the Derchi reservoir catchment in Taiwan. Pollution loads were derived from the AGNPS model with rainfall intensity estimated using the Thiessen method. Analyses for a network with various numbers of sampling sites were implemented. The results obtained based on varied cost factors were compared and discussed. With the three additional factors, the chosen sampling network is expected to properly detect pollution events and monitor pollution distribution and temporal trends.     

EMAP Design and River Reach File 3 (RF3) as a Sample Frame in the Central Valley, California

The Central Valley, California, R-EMAP project assessed the effects of highly modified, agriculturally dominated landuse on the aquatic resources of the lower portion of the Central Valley watersheds. The focus of this paper is to assess the utility of the EMAP design and the River Reach File version 3 (RF3) 1:100,000 scale Digital Line Graph (DLG) as a sampling frame. The study area is 34,099 mi²(88,316 km²) and comprises the lower reaches of the Sacramento River and San Joaquin River watersheds to the 1000 ft. (305 m) elevation. Sampling sites are selected using a tessellation stratified design to represent the two main populations of interest: natural streams and man-made waterways. Sites are selected to represent 13,226 miles of streams and sloughs, and 14,648 miles of irrigation canals, ditches and drains. To achieve an approximately equal sample size across stream orders and basins, the sample design was weighted by Strahler order categories to ensure sampling occurred in the higher order streams. Based on office and field reconnaissance, the study provided information on the quality of RF3 as a sampling frame. Site selection using RF3 had a success rate of approximately 44%. The RF3 database has an error rate of approximately 7%. When human influence factors were included, the error rate increased to 16%. There was an 11% error rate when selecting sites for natural streams, and approximately a 14% error rate for man-made waterways. The reconnaissance information indicated that presence or absence of irrigation ditches and return drains depends on changing agricultural uses. Some of the error in the RF3 for natural streams and man-made waterways can be attributed to rapid urban expansion, especially in the San Joaquin basin.     

Predicting Water Quality Impaired Stream Segments using Landscape-Scale Data and a Regional Geostatistical Model: A Case Study in Maryland

In the United States, probability-based water quality surveys are typically used to meet the requirements of Section 305(b) of the Clean Water Act. The survey design allows an inference to be generated concerning regional stream condition, but it cannot be used to identify water quality impaired stream segments. Therefore, a rapid and cost-efficient method is needed to locate potentially impaired stream segments throughout large areas. We fit a set of geostatistical models to 312 samples of dissolved organic carbon (DOC) collected in 1996 for the Maryland Biological Stream Survey using coarse-scale watershed characteristics. The models were developed using two distance measures, straight-line distance (SLD) and weighted asymmetric hydrologic distance (WAHD). We used the Corrected Spatial Akaike Information Criterion and the mean square prediction error to compare models. The SLD models predicted more variability in DOC than models based on WAHD for every autocovariance model except the spherical model. The SLD model based on the Mariah autocovariance model showed the best fit (r² = 0.72). DOC demonstrated a positive relationship with the watershed attributes percent water, percent wetlands, and mean minimum temperature, but was negatively correlated to percent felsic rock type. We used universal kriging to generate predictions and prediction variances for 3083 stream segments throughout Maryland. The model predicted that 90.2% of stream kilometers had DOC values less than 5 mg/l, 6.7% were between 5 and 8 mg/l, and 3.1% of streams produced values greater than 8 mg/l. The geostatistical model generated more accurate DOC predictions than previous models, but did not fit the data equally well throughout the state. Consequently, it may be necessary to develop more than one geostatistical model to predict stream DOC throughout Maryland. Our methodology is an improvement over previous methods because additional field sampling is not necessary, inferences about regional stream condition can be made, and it can be used to locate potentially impaired stream segments. Further, the model results can be displayed visually, which allows results to be presented to a wide variety of audiences easily.     

Critical Sampling Points Methodology: Case Studies of Geographically Diverse Watersheds

Only with a properly designed water quality monitoring network can data be collected that can lead to accurate information extraction. One of the main components of water quality monitoring network design is the allocation of sampling locations. For this purpose, a design methodology, called critical sampling points (CSP), has been developed for the determination of the critical sampling locations in small, rural watersheds with regard to total phosphorus (TP) load pollution. It considers hydrologic, topographic, soil, vegetative, and land use factors. The objective of the monitoring network design in this methodology is to identify the stream locations which receive the greatest TP loads from the upstream portions of a watershed. The CSP methodology has been translated into a model, called water quality monitoring station analysis (WQMSA), which integrates a geographic information system (GIS) for the handling of the spatial aspect of the data, a hydrologic/water quality simulation model for TP load estimation, and fuzzy logic for improved input data representation. In addition, the methodology was purposely designed to be useful in diverse rural watersheds, independent of geographic location. Three watershed case studies in Pennsylvania, Amazonian Ecuador, and central Chile were examined. Each case study offered a different degree of data availability. It was demonstrated that the developed methodology could be successfully used in all three case studies. The case studies suggest that the CSP methodology, in form of the WQMSA model, has potential in applications world-wide.