TESTING FOR TREND IN LAKE AND GROUND WATER QUALITY TIME SERIES1

ABSTRACT: The detection of gradual trends in water quality time series is increasing in importance as concern grows for diffuse sources of pollution such as acid precipitation and agricultural non-point sources. A significant body of literature has arisen dealing with trend detection in water quality variables that exhibit seasonal patterns. Much of the literature has dealt with seasonality of the first moment. However, little has been mentioned about seasonality in the variance, and its effect upon the performance of trend detection techniques. In this paper, eight methods of trend detection that arise from both the statistical literature as well as the water quality literature have been compared by means of a simulation study. Varying degrees of seasonality in both the variances and the means have been introduced into the artificial data, and the performances of these procedures are analyzed. Since the focus is on lake and ground water quality monitoring, quarterly sampling and short to moderate record lengths are examined.     

TEMPORAL VARIABILITY OF WATER QUALITY IN THE ST. LUCIE ESTUARY,SOUTH FLORIDA1

ABSTRACT: Four years of monthly freshwater discharge and constituent concentration data from three tributaries were related to a concurrent series of data for three segments of the St. Lucie Estuary in South Florida using multiple regression and time-series analysis techniques. Water quality parameters examined were dissolved inorganic and total nitrogen and phosphorus, chlorophyll a, total suspended solids, turbidity, and color. On monthly time scales, a multiple regression, which included freshwater discharge, freshwater constituent concentration, and dilution with ocean water (salinity) as independent variables, explained 50 percent or less of the variability in estuarine constituents. No single independent variable explained more variation than another. By contrast, on seasonal (wet, dry) time scales, freshwater discharge explained the bulk of variation in estuarine water quality (up to 93 percent). On monthly time scales, variability in concentrations of nutrients and other constituents may be largely controlled by processes internal to the system. At seasonal time scales, freshwater discharge appears to drive variability in most estuarine water quality parameters examined. Results indicate that management of tributary input on a seasonal basis, with the expectation of achieving seasonal concentration goals in the estuary, would have a higher probability of success than managing on a monthly basis.     

Spatial and temporal variation in nutrient parameters in stream water in a rural-urban catchment, Shikoku, Japan: effects of land cover and human impact

Seasonal and spatial variations in major ion chemistry and isotope composition in the rural-urban catchment of the Shigenobu River were monitored to determine the influences of agricultural and urban sewage systems on water quality. Temporal patterns of biochemical oxygen demand (BOD), total nitrogen (TN), total phosphorus (TP), and suspended sediment (SS) were examined at four sites in the rural-urban catchment. Urban land cover, incorporating the effects of increased population, domestic water use, and industrial wastewater, was positively associated with increases in water pollution and was included as an important explanatory variable for the variations in all water quality parameters. Significant trends were found in each parameter. BOD concentrations ranged widely, and were high in urban regions, due to the presence of a waste water treatment plant. TN and SS showed various trends, but did not vary widely, unlike TP. TP concentrations varied greatly, with high concentrations in cultivated areas, due to fertilizer use. Local water quality management or geology could further explain some of the variations in water quality. Non-point-source pollution exhibited strong positive spatial autocorrelation, indicating that incorporating spatial dimensions into water quality assessment enhances our understanding of spatial patterns of water quality. Data from the Ministry of Land Infrastructure and Transport (MLIT) and Environment Ministry (EM) were used to investigate trends in land management. Stepwise regression analysis was used to test the correlation between specific management practises and substance concentrations in surface water and sediment. MLIT and EM data for 1981-2003 showed an increase in TN, TP, and SS concentrations in surface water. High levels of fertilizer in dormant sprays and domestic water use were associated with high pesticide concentrations in water and sediment. This paper presents a novel method of studying the environmental impact of various agricultural management practises and recommends a management strategy that combines the use of reduced-risk pesticides with irrigation and non-irrigation periods in paddy fields.     

Water quality trends at inflows to Everglades National Park, 1977-2005

Restoration of the Florida Everglades is important for the health of the natural system, including both the "River of Grass" and its downstream estuaries. Water quality improvement is one indicator of successful restoration in this complex ecosystem. Using the period of record of 1977 through 2005, we evaluated data from seven inflow sites to the Everglades National Park (ENP) for temporal trends of various forms of phosphorus (P) and nitrogen (N) and analyzed them using principal component analysis and factor analysis without flow adjustments. Locally estimated scatter plot smoothing (LOESS) trend lines identified two inflection points (three time periods) of changing trend in total P (TP) concentration at the seven sites. Results indicated that overall water quality in ENP inflow improved from 1977 to 2005, with significant downward trends in TP concentration. The overall trend ofTP is probably mediated by hydrology, which is evident by a negative relationship between flow and annual average TP concentration at the majority of stations within the available data, although additional changes in vegetation due to hydroperiod may have some effects. Total N (TN), total Kjeldahl N, and total organic N concentrations also generally decreased at inflow sites. Water quality standards for TP, TN, and NH4+ -N were exceeded at selected sites during the study period. Principle component analysis and factor analysis detected a grouping of sampling sites related to the water delivery system that could be used as indicators to better manage monitoring resources. Study results suggest that water quality data analyses could provide additional insight into the success of a restoration management plan and on how monitoring may be modified for more efficient use ofresources.     

From agricultural intensification to conservation: sediment transport in the Raccoon River, Iowa, 1916-2009

Fluvial sediment is a ubiquitous pollutant that negatively affects surface water quality and municipal water supply treatment. As part of its routine water supply monitoring, the Des Moines Water Works (DMWW) has been measuring turbidity daily in the Raccoon River since 1916. For this study, we calibrated daily turbidity readings to modern total suspended solid (TSS) concentrations to develop an estimation of daily sediment concentrations in the river from 1916 to 2009. Our objectives were to evaluate long-term TSS patterns and trends, and relate these to changes in climate, land use, and agricultural practices that occurred during the 93-yr monitoring period. Results showed that while TSS concentrations and estimated sediment loads varied greatly from year to year, TSS concentrations were much greater in the early 20th century despite drier conditions and less discharge, and declined throughout the century. Against a backdrop of increasing discharge in the Raccoon River and widespread agricultural adaptations by farmers, sediment loads increased and peaked in the early 1970s, and then have slowly declined or remained steady throughout the 1980s to present. With annual sediment load concentrated during extreme events in the spring and early summer, continued sediment reductions in the Raccoon River watershed should be focused on conservation practices to reduce rainfall impacts and sediment mobilization. Overall, results from this study suggest that efforts to reduce sediment load from the watershed appear to be working.     

Characterization and prediction of highway runoff constituent event mean concentration

Highway stormwater runoff quality data were collected from throughout California during 2000-2003. Samples were analyzed for conventional pollutants (pH, conductivity, hardness, and temperature); aggregates (TSS, TDS, TOC, DOC); total and dissolved metals (As, Cd, Cr, Cu, Ni, Pb, and Zn); and nutrients (NO(3)-N, TKN, total P, and ortho-P). Storm event and site characteristics for each sampling site were recorded. A statistical summary for chemical characteristics of highway runoff is provided based on statewide urban and non-urban highways. Constituent event mean concentrations (EMCs) were generally higher in urban highways than in non-urban highways. The chemical characteristics of highway runoff in California were compared with national highway runoff chemical characterization data. The results obtained in California were generally similar to those found in other states. The median EMC for Pb measured in studies conducted in previous decades was much higher than the current median Pb EMC in California. The lower Pb EMC in California compared to previous highway runoff monitoring is believed to be due to the elimination of leaded gasoline. An attempt was also made to identify surrogate constituents within a general family of water quality categories using Spearman correlations and selected pairs with Spearman coefficients greater than 0.8. The strongest correlations were observed among parameters associated with dissolved minerals (EC, TDS, and chloride); organic carbon (TOC and DOC); petroleum hydrocarbons (TPH and O & G); and particulate matter (TSS and turbidity). Within the metals category, total iron concentration was highly correlated with most total metal concentrations. The correlations between total and dissolved concentrations were all less than 0.8, even between total and dissolved concentrations of the same metals. Multiple linear regression (MLR) analyses were performed to evaluate the impact of various site and storm event variables on highway runoff constituent EMCs. Parameters found to have significant impacts on highway runoff constituent EMCs include: total event rainfall (TER); cumulative seasonal rainfall (CSR); antecedent dry period (ADP); contributing drainage area (DA); and annual average daily traffic (AADT). Surrounding land use and geographic regions were also determined to have a significant impact on runoff quality. The MLR model was also used to predict constituent EMCs. Model performance determined by comparing predicted and measured values showed good agreement for most constituents.     

Precipitation Amount and Intensity Trends Across Southwest Saudi Arabia

This study examines precipitation accumulation and intensity trends across a region in southwest Saudi Arabia characterized by distinct seasonal weather patterns and mountainous terrain. The region is an example of an arid/semiarid area faced with maintaining sustainable water resources with a growing population. Annual and seasonal trends in precipitation amount were examined from 29 rain gages divided among four geographically unique regions from 1945/1946 to 2009. Two of the regions displayed significantly declining annual trends over the time series using a Mann‐Kendall test modified for autocorrelation (α < 0.05). Seasonal analysis revealed insignificant declining trends in at least two of the regions during each season. The largest and most consistent declining trends occurred during wintertime where all regions experienced negative trends. Several intensity metrics were examined in the study area from four additional stations containing daily data from 1985 to 2011. Intensity metrics included total precipitation, wet day count, simple intensity index, maximum daily annual rainfall, and upper/lower precipitation distribution changes. In general, no coherent trends were found among the daily stations suggesting precipitation is intensifying across the study area. The work represents the first of its size in the study area, and one of few in the region due to the lack of available long‐term data needed to properly examine precipitation changes.     

Modeling Variability and Trends in Pesticide Concentrations in Streams1

Abstract: A parametric regression model was developed for assessing the variability and long‐term trends in pesticide concentrations in streams. The dependent variable is the logarithm of pesticide concentration and the explanatory variables are a seasonal wave, which represents the seasonal variability of concentration in response to seasonal application rates; a streamflow anomaly, which is the deviation of concurrent daily streamflow from average conditions for the previous 30 days; and a trend, which represents long‐term (inter‐annual) changes in concentration. Application of the model to selected herbicides and insecticides in four diverse streams indicated the model is robust with respect to pesticide type, stream location, and the degree of censoring (proportion of nondetections). An automatic model fitting and selection procedure for the seasonal wave and trend components was found to perform well for the datasets analyzed. Artificial censoring scenarios were used in a Monte Carlo simulation analysis to show that the fitted trends were unbiased and the approximate p‐values were accurate for as few as 10 uncensored concentrations during a three‐year period, assuming a sampling frequency of 15 samples per year. Trend estimates for the full model were compared with a model without the streamflow anomaly and a model in which the seasonality was modeled using standard trigonometric functions, rather than seasonal application rates. Exclusion of the streamflow anomaly resulted in substantial increases in the mean‐squared error and decreases in power for detecting trends. Incorrectly modeling the seasonal structure of the concentration data resulted in substantial estimation bias and moderate increases in mean‐squared error and decreases in power.     

Seasonal Flushing of Pollutant Concentrations and Loads in Urban Stormwater1

Schiff, Kenneth C. and Liesl L. Tiefenthaler, 2011. Seasonal Flushing of Pollutant Concentrations and Loads in Urban Stormwater. Journal of the American Water Resources Association (JAWRA) 47(1):136‐142. DOI: 10.1111/j.1752‐1688.2010.00497.x Abstract: Despite broad observations of first flush within storms, the scientific understanding of seasonal flushing remains incomplete. Seasonal flushing occurs when initial storms of the season have greater concentrations or loads than storms later in the season. The goal of this study was to census stormwater concentrations and loads from an arid, urban watershed to quantify seasonal flushing. Samples were collected every 15 min during the 1997‐1998 wet season from the Santa Ana River and analyzed for total suspended solids. Initial storms of the season generated event mean concentrations 3‐10 times the event mean concentration of storms later in the season. Cumulative flow‐weighted mean concentrations were calculated as the season progressed. Early season storms discharged only 6% of the annual volume, but influenced flow‐weighted mean concentrations well past the midpoint of the wet season. Mass‐based estimates also indicated a disproportionate load in the early portion of the year; over 52% of the annual load was discharged in the first 30% of the annual volume from the highly urbanized lower watershed. Other stormwater pollutants, including six trace metals (Cd, Cr, Cu, Pb, Ni, Zn), were highly correlated with total suspended solids and also exhibited a significant seasonal flush.     

TRENDS IN PRECIPITATION AND STREAM CHEMISTRY IN A PRISTINE OLD-GROWTH FOREST WATERSHED,OLYMPIC NATIONAL PARK,WASHINGTON1

ABSTRACT: Human induced long-term changes in precipitation and stream chemistry have been observed in eastern North America and Europe, but few long-term studies have been conducted in coastal western North America. The objectives of this research were to determine: (1) time trends in precipitation and stream chemistry in a pristine old-growth forest watershed, and (2) seasonal patterns in precipitation and stream chemistry. It was conducted in 58 ha West Twin Creek Watershed, Hoh River Valley, Olympic National Park, Washington from 1984 to 1993. Vegetation consists of old-growth forest, with western hemlock, Douglas-fir, western redcedar, Pacific silver fir, and Sitka spruce being the dominant tree species. Annual precipitation varied from 2336 to 4518 mm during the study period with the majority of the rain falling between October and May. Chemistry of precipitation was strongly dominated by oceanic influences with Na and Cl being the dominant ions. The chemistry of the stream was influenced by bedrock weathering and was dominated by Ca, HCO₃, and SO₄ and was not strongly related to precipitation chemistry. The pH of precipitation averaged 5.3 over time and ranged from 4.3 to 7.1, while the stream pH averaged 7.5 and ranged from 5.5 to 9.0. There were few long-term trends in the chemical constituents of bulk precipitation or stream water with the exception of a slight decrease in NO₃ in precipitation and an increase of SO₄ in stream water. A trend of decreasing concentrations of Ca, Mg and Na in precipitation also occurred. There were no significant seasonal patterns in precipitation although the highest SO₄ concentrations usually occurred in late spring and summer perhaps due marine algal activity. Strong seasonal trends occurred in concentrations of HCO₃, SO₄, Ca, Mg, and Na in stream water resulting from weathering and stream flow patterns, with highest ion concentrations occurring just before the onset of the rainy season. Pulses of NO₃ in the stream were observed during fall and early winter resulting from the release of NO₃ which had accumulated in soils or sediments.     

SAMPLING FREQUENCY SELECTION FOR REGULATORY WATER QUALITY MONITORING1

ABSTRACT: The selection of sampling frequencies in order to achieve reasonably small and uniform confidence interval widths about annual sample means or sample geometric means of water quality constituents is suggested as a rational approach to regulatory monitoring network design. Methods are presented for predicting confidence interval widths at specified sampling frequencies while considering both seasonal variation and serial correlation of the quality time series. Deterministic annual cycles are isolated and serial dependence structures of the autoregressive, moving average type are identified through time series analysis of historic water quality records. The methods are applied to records for five quality constituents from a nine-station network in Illinois. Confidence interval widths about annual geometric means are computed over a range of sampling frequencies appropriate in regulatory monitoring. Results are compared with those obtained when a less rigorous approach, ignoring seasonal variation and serial correlation, is used. For a monthly sampling frequency the error created by ignoring both seasonal variation and serial correlation is approximately 8 percent. Finally, a simpler technique for evaluating serial correlation effects based on the assumption of AR(1) type dependence is examined. It is suggested that values of the parameter p₁, in the AR(1) model should range from 0.75 to 0.90 for the constituents and region studied.     

VIRGINIA USA WATER QUALITY, 1978 TO 1995: REGIONAL INTERPRETATION1

ABSTRACT: Nine surface water‐quality variables were analyzed for trend at 180 Virginia locations over the 1978 to 1995 period. Median values and seasonal Kendall's tau, a trend indicator statistic, were generated for dissolved oxygen saturation (DO), biochemical oxygen demand (BOD), pH (PH), total residue (TR), nonfilterable residue (NFR), nitrate‐nitrite nitrogen (NN), total Kjeldahl nitrogen (TKN), total phosphorus (TP), and fecal coliform (FC) at each location. Each location was assigned to one of four physiographic regions, and mean state and regional medians and taus were calculated. Widespread BOD and NFR improvements were detected and FC improvements occurred in the state's western regions. TR and TKN exhibited predominantly increasing trends at locations throughout the state. BOD, TKN, NFR, and TR medians were higher at coastal locations than in other regions. NN, TKN, and TR exhibited predominantly increasing trends in regions with high median concentrations, while declining trends predominated in regions with relatively high BOD, FC, and NFR medians. Appalachian locations exhibited the greatest regional water‐quality improvements for BOD, FC, NFR, and TKN. Factors responsible for regional differences appear to include geology, land use, and landscape features; these factors vary regionally.     

Surrogate Measures for Providing High Frequency Estimates of Total Suspended Solids and Total Phosphorus Concentrations1

Spackman Jones, Amber, David K. Stevens, Jeffery S. Horsburgh, and Nancy O. Mesner, 2010. Surrogate Measures for Providing High Frequency Estimates of Total Suspended Solids and Total Phosphorus Concentrations. Journal of the American Water Resources Association (JAWRA) 1‐15. DOI: 10.1111/j.1752‐1688.2010.00505.x Abstract: Surrogate measures like turbidity, which can be observed with high frequency in situ, have potential for generating high frequency estimates of total suspended solids (TSS) and total phosphorus (TP) concentrations. In the semiarid, snowmelt‐driven, and irrigation‐regulated Little Bear River watershed of northern Utah, high frequency in situ water quality measurements were recorded in conjunction with periodic chemistry sampling. Site‐specific relationships were developed using turbidity as a surrogate for TP and TSS at two monitoring locations. Methods are presented for employing censored data and for investigating categorical explanatory variables (e.g., hydrologic conditions). Turbidity was a significant explanatory variable for TP and TSS at both sites, which differ in hydrologic and water quality characteristics. The relationship between turbidity and TP was stronger at the upper watershed site where TP is predominantly particulate. At both sites, the relationships between turbidity and TP varied between spring snowmelt and base flow conditions while the relationships between TSS and turbidity were consistent across hydrological conditions. This approach enables the calculation of high frequency time series of TP and TSS concentrations previously unavailable using traditional monitoring approaches. These methods have broad application for situations that require accurate characterization of fluxes of these constituents over a range of hydrologic conditions.     

Evaluation of regression methodology with low-frequency water quality sampling to estimate constituent loads for ephemeral watersheds in Texas

Water quality regulation and litigation have elevated the awareness and need for quantifying water quality and source contributions in watersheds across the USA. In the present study, the regression method, which is typically applied to large (perennial) rivers, was evaluated in its ability to estimate constituent loads (NO(3)-N, total N, PO(4)-P, total P, sediment) on three small (ephemeral) watersheds with different land uses in Texas. Specifically, regression methodology was applied with daily flow data collected with bubbler stage recorders in hydraulic structures and with water quality data collected with four low-frequency sampling strategies: random, rise and fall, peak, and single stage. Estimated loads were compared with measured loads determined in 2001-2004 with an autosampler and high-frequency sampling strategies. Although annual rainfall and runoff volumes were relatively consistent within watersheds during the study period, measured annual nutrient and sediment concentrations and loads varied considerably for the cultivated and mixed watersheds but not for the pasture watershed. Likewise, estimated loads were much better for the pasture watershed than the cultivated and mixed landuse watersheds because of more consistent land management and vegetation type in the pasture watershed, which produced stronger correlations between constituent loads and mean daily flow rates. Load estimates for PO(4)-P were better than for other constituents possibly because PO(4)-P concentrations were less variable within storm events. Correlations between constituent concentrations and mean daily flow rate were poor and not significant for all watersheds, which is different than typically observed in large rivers. The regression method was quite variable in its ability to accurately estimate annual nutrient loads from the study watersheds; however, constituent load estimates were much more accurate for the combined 3-yr period. Thus, it is suggested that for small watersheds, regression-based annual load estimates should be used with caution, whereas long-term estimates can be much more accurate when multiple years of concentration data are available. The predictive ability of the regression method was similar for all of the low-frequency sampling strategies studied; therefore, single-stage or random strategies are recommended for low-frequency storm sampling on small watersheds because of their simplicity.     

Water Quality Changes as a Result of Coalbed Methane Development in a Rocky mountain Watershed1

Abstract: Coalbed methane (CBM) development raises serious environmental concerns. In response, concerted efforts have been made to collect chemistry, salinity, and sodicity data on CBM produced water. However, little information on changes of stream water quality resulting from directly and/or indirectly received CBM produced water is available in the literature. The objective of this study was to examine changes instream water quality, particularly sodicity and salinity, due to CBM development in the Powder River watershed, which is located in the Rocky Mountain Region and traverses the states of Wyoming and Montana. To this end, a retrospective analysis of water quality trends and patterns was conducted using data collected from as early as 1946 up to and including 2002 at four U.S. Geological Survey gauging stations along the Powder River. Trend analysis was conducted using linear regression and Seasonal Kendall tests, whereas, Tukey’s test for multiple comparisons was used to detect changes in the spatial pattern. The results indicated that the CBM development adversely affected the water quality in the Powder River. First, the development elevated the stream sodicity, as indicated by a significant increase trend of the sodium adsorption ratio. Second, the development tended to shrink the water quality differences among the three downstream stations but to widen the differences between these stations and the farthest upstream station. In contrast, the development had only a minor influence on stream salinity, as indicated by that the stream electrical conductivity exhibited either no trend or a marginally significant positive trend. Hence, the CBM development is likely an important factor that can be managed to lower the stream sodicity. The management may need to take into account that the effects of the CBM development were different from one location to another along the Powder River.     

Comparison of Two Parametric Methods to Estimate Pesticide Mass Loads in California’s Central Valley1

Saleh, Dina K., David L. Lorenz, and Joseph L. Domagalski, 2010. Comparison of Two Parametric Methods to Estimate Pesticide Mass Loads in California’s Central Valley. Journal of the American Water Resources Association (JAWRA) 00(0):1‐11. DOI: 10.1111/j.1752‐1688.2010.00506.x Abstract: Mass loadings were calculated for four pesticides in two watersheds with different land uses in the Central Valley, California, by using two parametric models: (1) the Seasonal Wave model (SeaWave), in which a pulse signal is used to describe the annual cycle of pesticide occurrence in a stream, and (2) the Sine Wave model, in which first‐order Fourier series sine and cosine terms are used to simulate seasonal mass loading patterns. The models were applied to data collected during water years 1997 through 2005. The pesticides modeled were carbaryl, diazinon, metolachlor, and molinate. Results from the two models show that the ability to capture seasonal variations in pesticide concentrations was affected by pesticide use patterns and the methods by which pesticides are transported to streams. Estimated seasonal loads compared well with results from previous studies for both models. Loads estimated by the two models did not differ significantly from each other, with the exceptions of carbaryl and molinate during the precipitation season, where loads were affected by application patterns and rainfall. However, in watersheds with variable and intermittent pesticide applications, the SeaWave model is more suitable for use on the basis of its robust capability of describing seasonal variation of pesticide concentrations.     

Targeted Application of Seasonal Load Duration Curves Using Multivariate Analysis in Two Watersheds Flowing Into Lake Houston1

Teague, Aarin, Philip B. Bedient, and Birnur Guven, 2011. Targeted Application of Seasonal Load Duration Curves Using Multivariate Analysis in Two Watersheds Flowing Into Lake Houston. Journal of the American Water Resources Association (JAWRA) 47(3):620‐634. DOI: 10.1111/j.1752‐1688.2011.00529.x Abstract: Water quality is a problem in Lake Houston, the primary source of drinking water for the City of Houston, Texas, due to pollutant loads coming from the influent watersheds, including Spring Creek and Cypress Creek. Statistical analysis of the historic water quality data was developed to understand the source characterization and seasonality of the watershed. Multivariate analysis including principal component, cluster, and discriminant analysis provided a custom seasonal assessment of the watersheds so that loading curves may be targeted for season specific pollutant source characterization. The load duration curves have been analyzed using data collected by the U.S. Geologic Survey with corresponding City of Houston water quality data at the sites to characterize the behavior of the pollutant sources and watersheds. Custom seasons were determined for Spring Creek and Cypress Creek watersheds and pollutant source characterization compared between the seasons and watersheds.     

Dissolved organic nitrogen regulation in freshwaters

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

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log₁₀ streamflow regressor provided the best model to predict monthly mean log₁₀ suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log₁₀ streamflow versus log₁₀ suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log₁₀ streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.     

Changes in Patterns of Streamflow From Unregulated Watersheds in Idaho,Western Wyoming,and Northern Nevada1

Clark, Gregory M., 2010. Changes in Patterns of Streamflow From Unregulated Watersheds in Idaho, Western Wyoming, and Northern Nevada. Journal of the American Water Resources Association (JAWRA) 46(3):486-497. DOI: 10.1111/j.1752-1688.2009.00416.x Abstract: Recent studies have identified a pattern of earlier spring runoff across much of North America. Earlier spring runoff potentially poses numerous problems, including increased risk of flooding and reduced summer water supply for irrigation, power generation, and migratory fish passage. To identify changing runoff patterns in Idaho streams, streamflow records were analyzed for 26 U.S. Geological Survey gaging stations in Idaho, western Wyoming, and northern Nevada, each with a minimum of 41 years of record. The 26 stations are located on 23 unregulated and relatively pristine streams that drain areas ranging from 28 to >35,000 km². Four runoff parameters were trend tested at each station for both the period of historical record and from 1967 through 2007. Parameters tested were annual mean streamflow, annual minimum daily streamflow, and the dates of the 25th and 50th percentiles of the annual total streamflow. Results of a nonparametric Mann-Kendall trend test revealed a trend toward lower annual mean and annual minimum streamflows at a majority of the stations, as well as a trend toward earlier snowmelt runoff. Significant downward trends over the period of historical record were most prevalent for the annual minimum streamflow (12 stations) and the 50th percentile of streamflow (11 stations). At most stations, trends were more pronounced during the period from 1967 through 2007. A regional Kendall test for water years 1967 through 2007 revealed significant regional trends in the percent change in the annual mean and annual minimum streamflows (0.67% less per year and 0.62% less per year, respectively), the 25th percentile of streamflow (12.3 days earlier), and the 50th percentile of streamflow (11.5 days earlier).