SPATIAL VARIABILITY IN WATER‐BALANCE MODEL PERFORMANCE IN THE CONTERMINOUS UNITED STATES1

ABSTRACT: A monthly water‐balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil‐moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R‐square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long‐term mean and standard deviation of annual precipitation; temperature and runoff; and low‐flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R‐square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.     

DESIGN CONSIDERATIONS FOR AMBIENT STREAM QUALITY MONITORING1

ABSTRACT: Existing ambient water quality monitoring programs have resulted in data which are often unsuitable for assessment of water quality trends. A primary concern in designing a stream quality monitoring network is the selection of a temporal sampling strategy. It is extremely important that data for trend assessment be collected uniformly in time. Greatly superior trend detection power results for such a strategy as compared to stratified sampling strategies. In general, it is desirable that sampling frequencies be at least monthly but not greater than biweekly; higher sampling frequencies usually result in little additional information. An upper limit on trend detectability exists such that for both five and ten year base periods it is often impossible to detect trends in time series where the ratio of the trend magnitude to time series standard deviation is less than about 0.5. For the same record lengths trends in records with trend to standard deviation ratios greater than about one can usually be detected with very high power when a uniform sampling strategy is followed.     

AN EVALUATION OF WEEKLY AND MONTHLY TIME SERIES FORECASTS OF MUNICIPAL WATER USE1

ABSTRACT: A cascade model for forecasting municipal water use one week or one month ahead, conditioned on rainfall estimates, is presented and evaluated. The model comprises four components: long term trend, seasonal cycle, autocorrelation and correlation with rainfall. The increased forecast accuracy obtained by the addition of each component is evaluated. The City of Deerfield Beach, Florida, is used as the application example with the calibration period from 1976–1980 and the forecast period the drought year of 1981. Forecast accuracy is measured by the average absolute relative error (AARE, the average absolute value of the difference between actual and forecasted use, divided by the actual use). A benchmark forecast is calculated by assuming that water use for a given week or month in 1981 is the same as the average for the corresponding period from 1976 to 1980. This method produces an AARE of 14.6 percent for one step ahead forecasts of monthly data and 15.8 percent for weekly data. A cascade model using trend, seasonality and autocorrelation produces forecasts with AARE of about 12 percent for both monthly and weekly data while adding a linear relationship of water use and rainfall reduces the AARE to 8 percent in both cases if it is assumed that rainfall is known during the forecast period. Simple rainfall predictions do not increase the forecast accuracy for water use so the major utility of relating water use and rainfall lies in forecasting various possible water use sequences conditioned on sequences of historical rainfall data.     

Water Quality and Land Use Changes in the Alafia and Hillsborough River Watersheds,Florida, USA1

Abstract: Spatial distribution of land use can have a substantial effect on surface and groundwater quality. Our objective was to test for trends in flow components and water quality related to changes in land use in the Alafia and Hillsborough River watersheds in Florida, USA, over the period 1974‐2007. In addition, water quality statistics were evaluated in the perspective of numeric water quality criteria and proposed reclassification of segments of the Alafia River. Trends in 10 water quality parameters and three discharge variables were evaluated using a nonparametric trend detection test. Results of land use analysis indicated substantial urbanization and loss of agricultural land in the study area. Discharge variables did not exhibit significant trends, whereas trends in the majority of water quality concentrations were negative or nonsignificant with total nitrogen and total Kjeldahl nitrogen as exceptions showing positive trends. Changes in nutrient pathways could not be clearly identified. Considering recently promulgated numeric nutrient criteria and standards for dissolved fluoride, much of the Alafia River was found to be out of compliance. While there were land use changes and changes in water quality over the study period, it was difficult to identify a direct cause‐effect relationship. Responses to regulatory efforts, such as the Clean Water Act and improvements in phosphate mining practices, may have had greater impacts on water quality than changes in land use.     

A MONTHLY TIME SERIES MODEL OF MUNICIPAL WATER DEMAND1

A multivariate time series model is formulated to study monthly variations in municipal water demand. The left hand side variable in the multivariate regression model is municipal water demand (gallons per connection per day) and the right hand side contains (explanatory) variables which include price (constant dollars), average temperature, total precipitation, and percentage of daylight hours. The application of the regression model to Salt Lake City Water Department data produced a high multiple correlation coefficient and F-statistic. The regression coefficients for the right hand side variables all have the appropriate sign. In an ex post forecast, the model accurately predicts monthly variations in municipal water demand. The proposed monthly multivariate model is not only found useful for forecasting water demand, but also useful for predicting and studying the impact of nonstructural management decisions such as the effect of price changes, peak load pricing methods, and other water conservation programs.     

Historical Groundwater Trends in Northern New England and Relations with Streamflow and Climatic Variables

Water‐level trends spanning 20, 30, 40, and 50 years were tested using month‐end groundwater levels in 26, 12, 10, and 3 wells in northern New England (Maine, New Hampshire, and Vermont), respectively. Groundwater levels for 77 wells were used in interannual correlations with meteorological and hydrologic variables related to groundwater. Trends in the contemporary groundwater record (20 and 30 years) indicate increases (rises) or no substantial change in groundwater levels in all months for most wells throughout northern New England. The highest percentage of increasing 20‐year trends was in February through March, May through August, and October through November. Forty‐year trend results were mixed, whereas 50‐year trends indicated increasing groundwater levels. Whereas most monthly groundwater levels correlate strongly with the previous month's level, monthly levels also correlate strongly with monthly streamflows in the same month; correlations of levels with monthly precipitation are less frequent and weaker than those with streamflow. Groundwater levels in May through August correlate strongly with annual (water year) streamflow. Correlations of groundwater levels with streamflow data and the relative richness of 50‐ to 100‐year historical streamflow data suggest useful proxies for quantifying historical groundwater levels in light of the relatively short and fragmented groundwater data records presently available.     

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.     

Long‐Term Streamflow Response to Climatic Variability in the Loess Plateau,China1

Abstract: The Loess Plateau region in northwestern China has experienced severe water resource shortages due to the combined impacts of climate and land use changes and water resource exploitation during the past decades. This study was designed to examine the impacts of climatic variability on streamflow characteristics of a 12‐km² watershed near Tianshui City, Gansu Province in northwestern China. Statistic analytical methods including Kendall’s trend test and stepwise regression were used to detect trends in relationship between observed streamflow and climatic variables. Sensitivity analysis based on an evapotranspiration model was used to detect quantitative hydrologic sensitivity to climatic variability. We found that precipitation (P), potential evapotranspiration (PET) and streamflow (Q) were not statistically significantly different (p > 0.05) over the study period between 1982 and 2003. Stepwise regression and sensitivity analysis all indicated that P was more influential than PET in affecting annual streamflow, but the similar relationship existed at the monthly scale. The sensitivity of streamflow response to variations of P and PET increased slightly with the increase in watershed dryness (PET/P) as well as the increase in runoff ratio (Q/P). This study concluded that future changes in climate, precipitation in particular, will significantly impact water resources in the Loess Plateau region an area that is already experiencing a decreasing trend in water yield.     

Long‐Term Trends in Streamflow and Precipitation in Northwest California and Southwest Oregon, 1953‐2012

Using nonparametric Mann‐Kendall tests, we assessed long‐term (1953‐2012) trends in streamflow and precipitation in Northern California and Southern Oregon at 26 sites regulated by dams and 41 “unregulated” sites. Few (9%) sites had significant decreasing trends in annual precipitation, but September precipitation declined at 70% of sites. Site characteristics such as runoff type (groundwater, snow, or rain) and dam regulation influenced streamflow trends. Decreasing streamflow trends outnumbered increasing trends for most months except at regulated sites for May‐September. Summer (July‐September) streamflow declined at many sites, including 73% of unregulated sites in September. Applying a LOESS regression model of antecedent precipitation vs. average monthly streamflow, we evaluated the underlying streamflow trend caused by factors other than precipitation. Decreasing trends in precipitation‐adjusted streamflow substantially outnumbered increasing trends for most months. As with streamflow, groundwater‐dominated sites had a greater percent of declining trends in precipitation‐adjusted streamflow than other runoff types. The most pristine surface‐runoff‐dominated watersheds within the study area showed no decreases in precipitation‐adjusted streamflow during the summer months. These results suggest that streamflow decreases at other sites were likely due to more increased human withdrawals and vegetation changes than to climate factors other than precipitation quantity.     

GENERATION OF SYNTHETIC AND MISSING CLIMATIC DATA FOR PUERTO RICO1

ABSTRACT: Climatic data such as temperature, solar radiation, relative humidity, and wind speed have been widely used to estimate evapotranspiration. Moat of the solar radiation data and portions of the relative humidity data are either not available or missing from the records in Puerto Rico. Depending upon the availability and data characteristics of records, three methods (including a regression technique, an averaging of historical data, and a regional average) were used to generate missing data, and a time series analysis was used to synthesize a series of climatic data. The limitations and applicability of each method are discussed. The results showed that the time series analysis method can be successfully used to synthesize a series of monthly solar radiations for several stations. The regression technique and the regional average can be successfully applied to generate missing monthly solar radiation data. The regression technique and the averaging of historical data have been satisfactorily used to interpolate missing monthly relative humidity. The explained variance (R²) varied from 0.68 to 0.88, which are both significant at the 0.05 level of significance.     

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.     

EFFECTIVENESS OF DROUGHT POLICIES FOR MUNICIPAL WATER MANAGEMENT1

During the 1976–77 drought, three principal mechanisms were used to reduce water use in Utah communities: price increases, maximum monthly use restrictions, and restrictions on outdoor watering times. A regression model was developed to explain observed changes in water use, with price, type of restriction, household size, and summer rainfall as independent variables. For an average system, a 1 percent increase in price would reduce water use by 0.07 to 0.09 percent. A 1 percent increase in outdoor watering time restriction reduces use by 0.064 to 0.075 percent. A 1 percent increase in quantity restrictions leads to a reduction in water use of 0.014 to 0.054 percent. The effectiveness of rationing policies is influenced by system characteristics. For example, outdoor watering time restrictions were less effective in systems with above average household size and below average monthly use.     

DETERMINISTIC MODELS FOR PREDICTING RESIDENTIAL WATER CONSUMPTION1

ABSTRACT: Forecasts of future urban water demand traditionally have been made by the projection of historic trends in per capita consumption and population. This paper outlines the use of two deterministic models to forecast the residential component of urban water demand. The models incorporate specific representation of the activities which result in water consumption at each residence. Predictions of water use can then be made by modeling the changes expected in the number of these activities and the consumption for each such activity.     

Water quality trends and changing agricultural practices in a midwest U.S. watershed, 1994-2006

Sediment and nutrient concentrations in surface water in agricultural regions are strongly influenced by agricultural activities. In the Corn Belt, recent changes in farm management practices are likely to affect water quality, yet there are few data on these linkages at the landscape scale. We report on trends in concentrations of N as ammonium (NH(4)) and nitrate (NO(3)), soluble reactive phosphorus (SRP), and suspended sediment (SS) in three Corn Belt streams with drainage areas of 12 to 129 km(2) for 1994 through 2006. During this period, there has been an increase in conservation tillage, a decline in fertilizer use, and consolidation of animal feeding operations in our study watersheds and throughout the Corn Belt. We use an autoregressive moving average model to include the effects of discharge and season on concentrations, LOWESS plots, and analyses of changes in the relation between discharge and concentration. We found significant declines in mean monthly concentrations of NH(4) at all three streams over the 13-yr period, declines in SRP and SS in two of the three streams, and a decline in NO(3) in one stream. When trend coefficients are converted to percent per year and weighted by drainage, area changes in concentration are -8.5% for NH(4), -5.9% for SRP, -6.8% for SS, and -0.8% for NO(3). Trends in total N and P are strongly tied to trends in NO(3), SRP, and SS and indicate that total P is declining, whereas total N is not.     

STATISTICAL ANALYSIS OF WATER CONSUMPTION1

The purpose of this study was to determine the degree of influence of various factors on municipal water consumption in Illinois. For the collection of basic data, questionnaires were sent to all public water works of incorporated towns. The questionnaire was designed to obtain information on factors which may have any effect on water use. The effects of the different parameters on water consumption were based on several correlation and regression combinations of predictands and predictors. It was found that in the Chicago region the percent of services and water used for commercial and industrial purposes and the age of the water works were the most important parameters influencing water consumption (gallons per capita per day) when pumpage is metered at the water works as well as at the customers. For the State, excluding the Chicago region, percent of public water use, persons per service, population and commercial and industrial water use were the most important parameters. It has been recommended that similar statistical analysis be conducted periodically to establish a trend or law of change from the influencing parameters.     

MULTIVARIATE TREND TESTING OF LAKE WATER QUALITY1

ABSTRACT: Multivariate methods of trend analysis offer the potential for higher power in detecting gradual water quality changes as compared to multiple applications of univariate tests. Simulation experiments were used to investigate the power advantages of multivariate methods for both linear model and Mann-Kendall based approaches. The experiments focused on quarterly observations of three water quality variables with no serial correlation and with several different intervariable correlation structures. The multivariate methods were generally more powerful than the univariate methods, offering the greatest advantage in situations where water quality variables were positively correlated with trends in opposing directions. For illustration, both the univariate and multivariate versions of the Mann-Kendall based tests were applied to case study data from several lakes in Maine and New York which have been sampled as part of EPA's long term monitoring study of acid precipitation effects.     

WATER DEMAND AT WESTERN U.S. RECREATION DEVELOPMENTS1

Although the volume of potable water used at recreation developments is minor relative to total regional water use, very high quality is required and the source is often of limited capacity, such as a mountain spring or small local aquifer. Frequent confrontations between developers and regulatory agencies result from claims by developers that water demand will be very small while regulators tend to treat such developments the same as municipal residence. Almost no published data base exists for resolving such conflicts. Included here are: 1) Water use measurements of various peak period durations (seasonal, monthly, daily, and instantaneous) at several types of recreational developments in Utah and Wyoming (mountain cabins, both ski- and water-based condominiums, and recreation vehicle campgrounds), 2) statistical (frequency) analysis of the data and a comparison with municipal demands in the same region, and 3) analysis of occupancy rates at the various categories of developments.     

TECHNIQUES FOR DETECTING TRENDS IN LAKE WATER QUALITY1

ABSTRACT: With the advent of standards and criteria for water quality variables, there has been an increasing concern about the changes of these variables over time. Thus, sound statistical methods for determining the presence or absence of trends are needed. A Trend Detection Method is presented that provides: 1) Hypothesis Formulation - statement of the problem to be tested, 2) Data Preparation - selection of water quality variable and data, 3) Data Analysis - exploratory data analysis techniques, and 4) Statistical Tests - tests for detecting trends. The method is utilized in a stepwise fashion and is presented in a nonstatistical manner to allow use by those not well versed in statistical theory. While the emphasis herein is on lakes, the method may be adopted easily to other water bodies.     

PERMEABILITY OF AIR AND IMMISCIBLE ORGANIC LIQUIDS IN POROUS MEDIA1

ABSTRACT: The conductivity of air, mineral oil (relative viscosity 77), and a light nontoxic oil (relative viscosity 4.7) was measured in three porous media: a sand, loamy sand, and a silt loam. The measurements were made over a range of water contents for each porous medium. Small volumes of air were present as well as significant amounts of water during most of the oil conductivity measurements. The results were compared to two methods for calculating conductivities of immiscible fluids in water-wet porous media. A new equation that accounts for swelling and for the gas slippage effect in very small pores was formulated for use with these methods The observed conductivities, spanning seven orders of magnitude, agree reasonably well with calculated values. Only three soil parameters are required to calculate the conductivities: (1) the saturated conductivity of water, (2) the saturated conductivity of the immiscible fluid of interest, and (3) a pore size index value that is obtained from an estimate from the water release curve of the porous material. Remediation of organic liquid spills is briefly discussed to illustrate the practical applications of gas phase conductivities, as well as those for immiscible organic liquid phases. It is concluded that, in light of spatial variation under field conditions, the method presented for calculating values of three-phase conductivities will be useful in the management of immiscible organic liquid spills and leaks.     

RELATING TRENDS OF PRINCIPAL COMPONENTS TO TRENDS OF WATER-QUALITY CONSTITUENTS1

ABSTRACT: The seasonal Kendall test is used for detecting water-quality trend or lack of trend for monthly data of 15 water-quality constituents at 15 sampling stations in the Arkansas River, the Neosho River, and the Verdigris River basins. Trends of individual constituents and the trends of the first four principal components for the correlation matrix of water-quality data at each station are determined, and the relationships between the trends of constituents and the trends of principal components are established. Using the principal components not only reduces the high dimensionality of the original data to a few principal components, but also presents an overall picture of water-quality trend of these river basins.