ANTIDEGRADATION WATER QUALITY CRITERIA FOR THE DELAWARE RIVER: A DISTRIBUTION-FREE STATISTICAL APPROACH1

ABSTRACT: Existing water quality for the Middle Delaware Scenic and Recreational River is significantly better than is required by current standards, leaving a potential for degradation. A method is presented for deriving candidate antidegradation water quality criteria for this segment of the Delaware River using statistical analysis of historic (ambient) water quality data. Data for 34 water quality parameters are first evaluated for data density, serial correlation, trend, seasonality, and other factors. These preliminary analyses are based on observation of data plots and application of distribution-free statistical techniques that are insensitive to outliers and are robust to relatively mild violations of basic assumptions. Data for 12 of the parameters have sufficient density for further analysis and can reasonably be modeled as independent and identically distributed over time (either seasonally or for the entire data sets). For these 12 parameters, distribution-free statistical methods are developed and used to derive intervals within which there is high confidence (usually greater than 95 percent) that the quantiles with potential use as anti-degradation criteria (the 0.85^th, 0.90^th, and 0.95^th quantiles in this study) for a particular parameter lie.     

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

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

Application of Multivariate Statistical Methods and Water-Quality Index to Evaluation of Water Quality in the Kashkan River

The Kashkan River (KR), located in the west of Iran, is a major source of water supply for residential and agricultural areas as well as livestock. The objective of this study was to assess the spatial and long temporal variations of surface water quality of the KR based on measured chemical ions. The Canadian Council of Ministers of Environment Water Quality Index (CCME WQI) technique was utilized using measurements from 10 sampling stations during a period of 36 years (1974–2009). The measured data included cations (Na⁺, K⁺, Ca²⁺, Mg²⁺), anions (HCO₃ ^?, Cl^?, SO₄ ^2?), pH, and electrical conductivity. Principal component analysis was performed to identify which of the parameters to be included in the CCME WQI calculations were actually correlated and which ones were responsible for most of the variance observed in the water-quality data. In addition, KR water quality was evaluated for its suitability for drinking and irrigation purposes using conventional methods. Last, trend detection in the WQI time series of the KR showed water-quality degradation at all sampling stations, whereas the Jelhool sub-basin more adversely affects the quality of KR water in the watershed. Nonetheless, on average, the water quality of the KR was rated as fair.     

Water quality assessment and meta model development in Melen watershed – Turkey

Istanbul, being one of the highly populated metropolitan areas of the world, has been facing water scarcity since the past decade. Water transfer from Melen Watershed was considered as the most feasible option to supply water to Istanbul due to its high water potential and relatively less degraded water quality. This study consists of two parts. In the first part, water quality data covering 26 parameters from 5 monitoring stations were analyzed and assessed due to the requirements of the “Quality Required of Surface Water Intended for the Abstraction of Drinking Water” regulation. In the second part, a one-dimensional stream water quality model with simple water quality kinetics was developed. It formed a basic design for more advanced water quality models for the watershed. The reason for assessing the water quality data and developing a model was to provide information for decision making on preliminary actions to prevent any further deterioration of existing water quality. According to the water quality assessment at the water abstraction point, Melen River has relatively poor water quality with regard to NH₄⁺, BOD₅, faecal streptococcus, manganese and phenol parameters, and is unsuitable for drinking water abstraction in terms of COD, PO₄^3?, total coliform, total suspended solids, mercury and total chromium parameters. The results derived from the model were found to be consistent with the water quality assessment. It also showed that relatively high inorganic nitrogen and phosphorus concentrations along the streams are related to diffuse nutrient loads that should be managed together with municipal and industrial wastewaters.     

WEST AFRICA: VOLTA DISCHARGE DATA QUALITY ASSESSMENT AND USE1

ABSTRACT: Water resource management in West Africa is often a complicated process due to inadequate resources, climatic extremes, and insufficient hydrological information. Insufficient data hinder sustainable watershed management practices, one of the top priorities in the Volta River Basin. This research properly fills in missing data by modeling the hydrological distribution in the Volta River Basin. On average, discharge gages across the basin are missing 20 percent of their monthly data over 20 years. Two methods were used to supplement missing data: a statistically linear model and a conceptual hydrological model. A linear equation, developed from the regression of precipitation and runoff, was used to evaluate the quality of existing data. The hydrological model separates the system into root and groundwater zones. Measured values were used to calibrate the hydrological model and to validate the statistical model. The quality of existing data was analyzed and organized for usability. Accuracy of the hydrological model was also evaluated for its effectiveness using R² and standard error. It was found that the hydrological model was an improvement from the linear model on a monthly basis; R² values improved by as much as 0.5 and monthly error decreased. Monthly predictions of the hydrological model were used to fill gaps of measured data sets.     

RISK OF EXTREME EVENTS IN A MULTIOBJECTIVE FRAMEWORK1

ABSTRACT: This paper summarizes advances made in risk-based decisionmaking in water resources through use of the partitioned multiobjective risk method (PMRM). (Risk is a measure of the probability and severity of adverse effects.) In the PMRM, the risk of extreme events is differentiated from risk involving less extreme damage severity and is evaluated within a multiobjective framework. Study of the extreme-event risk function f₄(*) has addressed the following issues: methods for calculating f₄(*); the sensitivity of f₄(*) to various parameters, particularly to the partitioning point of the extreme-event range and the selection of probability density functions; insight provided by the statistics of extremes; and the impact of f₄(*) on risk management, for example, in the application of the PMRM to water resources problems. In particular, this paper shares with the reader recent research results on the PMRM, the relationship between the statistics of extremes and the conditional expected value, derived formulas for f₄(*), distribution-free estimates of f₄(*), documented case studies in dam safety, and future research directions.     

Water quality standards: Everglades National Park

Water quality criteria were developed for delivery waters to Everglades National Park. The park receives a minimum of 12.34 m³/sec (315,000 acre-ft/yr) of water from controlled sources external to its boundary. These waters often originate from areas that are or potentially are impacted from urban and agricultural developments. When, in 1970, the U.S. Congress guaranteed minimum water deliveries to Everglades National Park, it also required that these waters be of good quality.The Everglades National Park water quality data base was analyzed from 1970 to 1978 at both in-park and water delivery sites to determine the current level of delivery water quality and to select representative delivery sites. It was found that current delivery water quality was sufficiently high to be adopted as criteria against which future water quality could be compared. From the delivery sites S-12C and L-67A all data were combined from 1970–1978 for 36 parameters including macronutrients, heavy metals, and field parameters such as DO, pH, and specific conductance. Mean concentrations and upper limits were computed and tabulated for comparison during future monitoring programs. These criteria were subsequently adopted through a joint memorandum of agreement between the U.S. Army Corps of Engineers, South Florida Water Management District and the U.S. National Park Service.     

Using Regression Tree Analysis to Improve Predictions of Low-Flow Nitrate and Chloride in Willamette River Basin Watersheds

The use of regression tree analysis is examined as a tool to evaluate hydrologic and land use factors that affect nitrate and chloride stream concentrations during low-flow conditions. Although this data mining technique has been used to assess a range of ecological parameters, it has not previously been used for stream water quality analysis. Regression tree analysis was conducted on nitrate and chloride data from 71 watersheds in the Willamette River Basin to determine whether this method provides a greater predictive ability compared to standard multiple linear regression, and to elucidate the potential roles of controlling mechanisms. Metrics used in the models included a variety of watershed-scale landscape indices and land use classifications. Regression tree analysis significantly enhanced model accuracy over multiple linear regression, increasing nitrate R ² values from 0.38 to 0.75 and chloride R ² values from 0.64 to 0.85 and as indicated by the ΔAIC value. These improvements are primarily attributed to the ability for regression trees to more effectively handle interactions and manage non-linear functions associated with watershed heterogeneity within the basin. Whereas hydrologic factors governed the conservative chloride tracer in the model, land use dominated control of nitrate concentrations. Watersheds containing higher agricultural activity did not necessarily yield high nitrate concentrations, but agricultural areas combined with either small proportions of forested land or greater urbanization generated nitrate levels far exceeding water quality standards. Although further refinements are recommended, we conclude that regression tree analysis presents water resource managers a promising tool that improves on the predictive ability of standard statistical methods, provides insight into controlling mechanisms, and helps identify catchment characteristics associated with water quality impairment.     

DEVELOPMENT OF A NONDEGRAIATION POLICY FOR HIGH QUALITY WATERS1

ABSTRACT: The development of a nondegradation policy for high quality waters is a complex and often controversial process. This paper discusses the development of a nondegradation policy for two components of the National Wild and Scenic Rivers System. Water quality in these reaches of the Delaware River is threatened by rapid growth and development and the cumulative impacts from numerous wastewater discharges and nonpoint sources of pollution. The Delaware River Basin Commission, with assistance from its member states and the National Park Service, conducted a highly public, six-year planning process to develop a nondegradation policy that protected existing water quality without impinging upon local and state economic development objectives. The resulting non-degradation policy includes such features as numeric definitions of existing water quality and measurable change; stringent point source requirements; nonpoint source requirements including watershed planning requirements; and other water quality management policies.     

Improving watershed decisions using run-off and yield models at different simulation scales

Water managers face the daunting task of balancing limited water resources with over-subscribed water users among competing demands. They face the additional challenge of taking water planning decisions in an uncertain environment with limited and sometimes inaccurate observed and simulated hydrological data. Within South African watersheds, spatial parameterization data for hydrological models are now available at two different basin management resolutions (termed quaternary and quinary). Currently, water management decisions in the Crocodile River watershed are often made at a more coarse resolution, which may exclude crucial insights into the data. This research has the following aims (1) to explore whether model performance is improved by parameterization using a more detailed quinary-scale watershed data and (2) to explore whether quinary-scale models reduce uncertainty in allocation or restriction decisions to provide better informed water resources management and decision outcomes. This study used the Agricultural Catchments Research Unit (ACRU) agro-hydrological watershed model, to evaluate the effects of spatial discretization at the quaternary and quinary scales on watershed hydrological response and runoff within the Crocodile River basin. Model performance was evaluated using statistical comparisons of results using traditional goodness-of-fit measures such as the coefficient of efficiency (C _eff), root mean square of the error and the coefficient of determination (R ²) to compare simulated monthly flows and observed flows in six subcatchments. Traditional interpretation of these goodness-of-fit measures may be inadequate as they can be subjectively interpreted and easily influenced by the number of data points, outliers and model bias. This research utilizes a recently released model evaluation program (FITEVAL) which presents probability distributions of R ²and C _eff derived by bootstrapping, graphical representation of observed and simulated stream flows, incorporates statistical significance to detect the sufficiency of the R ²and C _eff and determines the presence of outliers and bias. While analyses indicate that the ACRU model performs marginally better when parameterized and calibrated at the quinary scale, the measurements at both scales show significant variability in predictions for both high and low flows that are endemic to southern African hydrology. The improved evaluation methods also allow for the analysis of data collection errors at monitoring sites and help determine the effect of data quality on adaptive water planning management decisions. Given that many water resource challenges are complex adaptive systems, these expanded performance analysis tools help provide deeper insights into matching watershed decision metrics and model-derived predictions.     

Comparison of Measured and MM5 Modeled Meteorology Data for Simulating Flow in a Mountain Watershed1

Herr, Joel W., Krish Vijayaraghavan, and Eladio Knipping, 2010. Comparison of Measured and MM5 Modeled Meteorology Data for Simulating Flow in a Mountain Watershed. Journal of the American Water Resources Association (JAWRA) 46(6):1255–1263. DOI: 10.1111/j.1752-1688.2010.00489.x Abstract: Accurate simulation of time-varying flow in a river system depends on the quality of meteorology inputs. The density of meteorology measurement stations can be insufficient to capture spatial heterogeneity of precipitation, especially in mountainous areas. The Watershed Analysis Risk Management Framework (WARMF) model was applied to the Catawba River watershed of North and South Carolina to simulate flow and water quality in rivers and a series of 11 reservoirs. WARMF was linked with the AMSTERDAM air model to analyze the water quality benefit from reduced atmospheric emissions. The linkage requires accurate simulation of meteorology for all seasons and for all types of precipitation events. WARMF was driven by the mesoscale meteorology model MM5 processed by the Meteorology Chemistry Interface Processor, which provides greater spatial density but less accuracy than meteorology stations. WARMF was also run with measured data from the National Climatic Data Center (NCDC) to compare the performance of the watershed model using measured data vs. modeled meteorology as input. A one year simulation using MM5 modeled meteorology performed better overall than the simulation using NCDC data for the volumetric water balance measure used for calibration, but MM5 represented precipitation from a dissipated hurricane poorly, which propagated into errors of simulated flow.     

SAMPLING STRATEGIES FOR ESTIMATING ACUTE AND CHRONIC EXPOSURES OF PESTICIDES IN STREAMS1

ABSTRACT: The Food Quality Protection Act of 1996 requires that human exposure to pesticides through drinking water be considered when establishing pesticide tolerances in food. Several systematic and seasonally weighted systematic sampling strategies for estimating pesticide concentrations in surface water were evaluated through Monte Carlo simulation, using intensive datasets from four sites in northwestern Ohio. The number of samples for the strategies ranged from 4 to 120 per year. Sampling strategies with a minimal sampling frequency outside the growing season can be used for estimating time weighted mean and percentile concentrations of pesticides with little loss of accuracy and precision, compared to strategies with the same sampling frequency year round. Less frequent sampling strategies can be used at large sites. A sampling frequency of 10 times monthly during the pesticide runoff period at a 90 km² basin and four times monthly at a 16,400 km² basin provided estimates of the time weighted mean, 90^th, 95^th, and 99^th percentile concentrations that fell within 50 percent of the true value virtually all of the time. By taking into account basin size and the periodic nature of pesticide runoff, costs of obtaining estimates of time weighted mean and percentile pesticide concentrations can be minimized.     

WATER QUALITY FROM TWO SMALL FORESTED WATERSHEDS IN SOUTHERN ILLINOIS1

Two intermittent streams on oak-hickory watersheds in southern Illinois were gaged with a V-notched weir and sampled with an automatic water sampler. For three years data were collected on flow volume and water quality. Flow volumes show large variations between years and watersheds. Samples were analyzed for Na⁺, K⁺, Ca⁺⁺, Mg⁺⁺, P, and NO^-₃. Water quality was consistently high, although there were significant differences between watersheds. A baseline for water quality has been established for comparison after one of the watersheds is clearcut at a later date.     

CUMULATIVE IMPACTS OF LANDUSE ON WATER QUALITY IN A SOUTHERN APPALACHIAN WATERSHED1

ABSTRACT: Water quality variables were sampled over 109 weeks along Coweeta Creek, a fifth-order stream located in the Appalachian mountains of western North Carolina. The purpose of this study was to observe any changes in water quality, over a range of flow conditions, with concomitant downstream changes in the mix of landuses. Variables sampled include pH, HCO₃^2?, conductivity, NO₃^?_?-N, NH₄⁺-N, PO₄^3?-P, C1^?-, Na, K, Ca²⁺, Mg²⁺, SO₄^2?, 5iO₂, turbidity, temperature, dissolved oxygen, total and fecal coliform, and focal streptococcus. Landcover/landuse was interpreted from 1:20,000 aerial photographs and entered in a GIS, along with information on total and paved road length, building location and density, catchment boundaries, hydrography, and slope. Linear regressions were performed to relate basin and near-stream landscape variables to water quality. Consistent, cumulative, downstream changes in water quality variables were observed along Coweeta Creek, concomitant with downstream, human-caused changes in landuse. Furthermore, larger downstream changes in water quality variables were observed during stormflow when compared to baseflow, suggesting cumulative impacts due to landscape alteration under study conditions were much greater during storm events. Although most water quality regulations, legislation, and sampling are promulgated for baseflow conditions, this work indicates they should also consider the cumulative impacts of physical, chemical, and biological water quality during stormflow.     

Assessment of the Hydrogeochemistry and Groundwater Quality of the Tarim River Basin in an Extreme Arid Region, NW China

The concentrations of the major and trace elements in the groundwater of the Tarim River Basin (TRB), the largest inland river basin of China, were analyzed before and during rainy seasons to determine the hydrogeochemistry and to assess the groundwater quality for irrigation and drinking purposes. The groundwater within the TRB was slightly alkaline and characterized by high ionic concentrations. The groundwater in the northern sub-basin was fresh water with a Ca²⁺–HCO₃ ^? water type, whereas the groundwater in the southern and central sub-basins was brackish with a Na⁺–Cl^? water type. Evaporite dissolution and carbonate weathering were the primary and secondary sources of solutes in the groundwater within the basin, whereas silicate weathering played a minor role. The sodium adsorption ratio (SAR), water quality index (WQI), and sodium percentage (%Na) indicated that the groundwater in the northern sub-basin was suitable for irrigation and drinking, but that in the southern and central sub-basins was not suitable. The groundwater quality was slightly better in the wet season than in the dry season. The groundwater could be used for drinking after treatment for B³⁺, F^?, and SO₄ ^2? and for irrigation after control of the sodium and salinity hazards. Considering the high corrosivity ratio of the groundwater in this area, noncorrosive pipes should be used for the groundwater supply. For sustainable development, integrated management of the surface water and the groundwater is needed in the future.     

WASTE LOADINGS FROM A FRESHWATER ATLANTIC SALMON FARM IN SCOTLAND1

ABSTRACT: Recent studies suggest that waste generation from the freshwater phase of Atlantic salmon (Salmo salar L.) production varies considerably on an annual basis. A fish farm on the West Coast of Scotland was visited regularly during a two-year period to determine inflow and outflow water quality. Waste output budgets of suspended solids (SS), biochemical oxygen demand (BOD), total nitrogen (TN), total phosphorus (TP), total ammonia nitrogen (TAN = NH₃+NH₄⁺), dissolved reactive phosphorus (DRP) and total phosphorus (TP) were produced. The annual waste loadings obtained were 71 kg TN t fish^?1 yr^?1 (one year of data only), 10.9–11.1 kg TP t fish^?1 yr^?1, 1.2–2.1 kg DRP t fish^?1 yr^?1, 422–485 kg BOD₅ t fish^?1 yr^?1, 327–337 kg SS t fish^?1 yr^?1, and 30–35 kg TAN-N t fish^?1 yr^?1. Simple linear regression models relating waste parameter production to water temperature and feeding regime were developed. When compared to existing data for other salmonid production systems, greater ranges of daily waste loadings were observed. Wide variations in concentrations of these parameters during a daily cycle were also observed, suggesting that mass balance estimates of waste production will provide more robust estimates of waste output than frequent monitoring of outflow water quality.     

Fertilizer Management in Watersheds of Two Ramsar Wetlands and Effects on Quality of Inflowing Water

Two field experiments were carried out in the watersheds of two Ramsar wetland areas, Lakes Koronia and Volvi (area A) and Lakes Mikri and Megali Prespa (area B), to study the effect of application of N fertilizer on wheat yields, the quality of runoff water, and the quality of stream water. The treatments were a combination of two methods of fertilizer application (total amount in fall, and 2/3 in fall + 1/3 in spring) at three rates (0, 100, and 200 kg N/ha) with four replications. Concentrations of NH₄ ⁺, NO₃ ⁻, NO₂ ⁻, P, and Cl⁻ and pH were determined in all water samples. Runoff water quality was not influenced by fertilizer application in either area. Chemical parameters for water did not differ along the selected watercourses in area B, while in area A they were higher in the samples taken near Lake Koronia than in the samples taken upstream, indicating that the watercourses are polluted downstream by nonagricultural sources. The differences in wheat yields between the 100 and 200 kg N/ha application rates were not high. These results call for better fertilizer management in order to achieve better yields and to diminish the possibility to have negative effects to the environment.     

Assessment of biomass and lipid productivity and biodiesel quality of an indigenous microalga Chlorella sorokiniana MIC-G5

Generation of biodiesel from microalgae has been extensively investigated; however, its quality is often not suitable for use as fuel. Our investigation involved the evaluation of biodiesel quality using a native isolate Chlorella sorokiniana MIC-G5, as specified by American Society for Testing and Materials (ASTM), after transesterification of lipids with methanol, in the presence of sodium methoxide. Total quantity of lipids extracted from dry biomass, of approximately 410–450 mg g^?1 was characterized using FTIR and ¹H NMR. After transesterification, the total saturated and unsaturated fatty acid methyl esters (FAMEs) were 43% and 57%, respectively. The major FAMEs present in the biodiesel were methyl palmitate (C16:0), methyl oleate (C18:1), and methyl linoleate (C18:2), and the ¹H NMR spectra matched with criteria prescribed for high-quality biodiesel. The biodiesel exhibited a density of 0.873 g cm^–3, viscosity of 3.418 mm² s^?1, cetane number (CN) of 57.85, high heating value (HHV) of 40.25, iodine value of 71.823 g I₂ 100 g^?1, degree of unsaturation (DU) of 58%, and a cold filter plugging point (CFPP) of –5.22°C. Critical fuel parameters, including oxidation stability, CN, HHV, iodine value, flash point, cloud point, pour point, density, and viscosity were in accordance with the methyl ester composition and structural configuration. Hence, C. sorokiniana can be a promising feedstock for biodiesel generation.     

A Water Quality Index Applied to an International Shared River Basin: The Case of the Douro River

A Water Quality Index (WQI) is a numeric expression used to evaluate the quality of a given water body and to be easily understood by managers. In this study, a modified nine-parameter Scottish WQI was used to assess the monthly water quality of the Douro River during a 10-year period (1992–2001), scaled from zero (lowest) to 100% (highest). The 98,000 km² of the Douro River international watershed is the largest in the Iberian Peninsula, split between upstream Spain (80%) and downstream Portugal (20%). Three locations were surveyed: at the Portuguese–Spanish border, 350 km from the river mouth; 180 km from the mouth, where the river becomes exclusively Portuguese; and 21 km from the mouth. The water received by Portugal from Spain showed the poorest quality (WQI 47.3 ± 0.7%); quality increased steadily downstream, up to 61.7 ± 0.7%. In general, the water quality at all three sites was medium to poor. Seasonally, water quality decreased from winter to summer, but no statistical relationship between quality and discharge rate could be established. Depending on the location, different parameters were responsible for the episodic decline of quality: high conductivity and low oxygen content in the uppermost reservoir, and fecal coliform contamination downstream. This study shows the need to enforce the existing international bilateral agreements and to implement the European Water Quality Directive in order to improve the water quantity and quality received by the downstream country of a shared watershed, especially because two million inhabitants use the water from the last river location as their only source of drinking water.