GROUND WATER QUALITY IMPLICATIONS OF SOIL CONSERVATION MEASURES: AN ECONOMIC PERSPECTWE1

ABSTRACT: An evaluation of the intermedia movement of pesticides applied under various land management systems already in place, or to be implemented, under the Conservation Reserve and Conservation Compliance programs is presented. The simulation modeling approach followed in this analysis consists of a mathematical programming model and leaching/surface runoff, Pesticide Root Zone Model (PRZM) models. Special care was taken to ensure that the physical model was sensitive to the chemical characteristics of individual pesticides and the important physical changes brought about by different agricultural practices. Results show that, although these programs as now planned, increase farm income and achieve soil conservation goals, they may adversely affect ground water quality. Also, depending on soil and location characteristics, there are tradeoffs between surface and ground water quality implications. Hence, if these programs are to address water quality problems, the recommended practices must be evaluated for their impact on water quality, particularly in potentially vulnerable areas.     

HYDROLOGIC LANDSCAPES ON THE DELMARVA PENINSULA PART 2: ESTIMATES OF BASE-FLOW NITROGEN LOAD TO CHESAPEAKE BAY1

ABSTRACT: Base-flow samples were collected from 47 sampling sites for four seasons from 1990–91 on the Delmarva Peninsula in Delaware and Maryland to relate stream chemistry to a “hydrologic landscape” and season. Two hydrologic landscapes were determined: (1) a well-drained landscape, characterized by a combination of a low percentage of forest cover, a low percentage of poorly drained soil, and elevated channel slope; and (2) poorly drained landscape, characterized by a combination of an elevated percentage of forest cover, an elevated percentage of poorly drained soil, and low channel slope. Concentrations of nitrogen were significantly related to the hydrologic landscape. Nitrogen concentrations tended to be higher in well-drained landscapes than in poorly drained ones. The highest instantaneous nitrogen yields occurred in well-drained landscapes during the winter. These yields were extrapolated over the part of the study area draining to Chesapeake Bay in order to provide a rough estimate of nitrogen load from base flow to the Bay and its estuarine tributaries. This estimate was compared to an estimate made by extrapolating from an existing long-term monitoring station. The load estimate from the stream survey data was 5 ± 10⁶ kg of N per year, which was about four times the estimate, made from the existing long-term monitoring station. The stream-survey estimate of base flow represents about 40 percent of the total nitrogen load that enters the Bay and estuarine tributaries from all sources in the study area.     

HYDROLOGIC LANDSCAPES ON THE DELMARVA PENINSULA PART 1: DRAINAGE BASIN TYPE AND BASE-FLOW CHEMISTRY1

ABSTRACT: The relation between landscape characteristics and water chemistry on the Delmarva Peninsula can be determined through a principal-component analysis of basin characteristics. Two basin types were defined by factor scores: (1) well-drained basins, characterized by combinations of a low percentage of forest cover, a low percentage of poorly drained soil, and elevated channel slope; and (2) poorly drained basins, characterized by a combinations of an elevated percentage of forest cover, an elevated percentage of poorly drained soil, and low channel slopes. Results from base-flow sampling of 29 basins during spring 1991 indicate that water chemistry of the two basin types differ significantly. Concentrations of calcium, magnesium, potassium, alkalinity, chloride, and nitrate are elevated in well-drained basins, and specific conductance is elevated. Concentrations of aluminum, dissolved organic carbon, sodium, and silica are elevated in poorly drained basins whereas specific conductance is low. The chemical patterns found in well-drained basins can be attributed to the application of agricultural chemicals, and those in poorly drained basins can be attributed to ground-water flowpaths. These results indicate that basin types determined by a quantitative analysis of basin characteristics can be related statistically to differences in base-flow chemistry, and that the observed statistical differences can be related to major processes that affect water chemistry.     

MULTIVARIATE ANALYSIS OF WATER QUALITY IN THE RICHIBUCTO DRAINAGE BASIN (NEW BRUNSWICK,CANADA)1

ABSTRACT: Specific conductivity, pH, dissolved oxygen, carbon, phosphorous, and nitrogen species were measured at 36 stations in the Richibucto River drainage basin, including the estuary, in New Brunswick, Canada, over the six‐year period 1996 through 2001. Each station was sampled between 1 and 26 times (mean = 7.5, standard deviation = 6.0) during the ice free seasons without regard to tide. There was significant variance among stations in most parameters. Principal component analysis (PCA) was used to identify the processes explaining the observed variance in water quality. Because of the high variability in specific conductance, stations were first grouped in a freshwater subset and an estuarine (brackish water) subset. For freshwater stations, most of the variance in water quality was explained by pH and total organic carbon, as well as high nutrient concentrations. These high nutrient concentrations, along with water salinity, which varies with flow and tides, are also important in determining water quality variability in brackish water. It is recommended that water quality parameters that were found to explain most of the variance by PCA be monitored more closely, as they are key elements in understanding the variability in water quality in the Richibucto drainage basin. Cluster analyses showed that high phosphorous and nitrate concentrations were mostly found in areas of peat runoff, tributaries receiving treated municipal effluent, and lentic zones upstream of culverts. Peat runoff was also shown to be acidic, whether it is runoff from a harvested area or a natural bog.     

ORGANOCHLORINE PESTICIDE RESIDUES IN BED SEDIMENTS OF THE SAN JOAQUIN RIVER,CALIFORNIA1

ABSTRACT: Bed sediments of the San Joaquin River and its tributaries were sampled during October 7–11, 1985, and analyzed for organochiorine pesticide residues in order to determine their areal distribution and to evaluate and prioritize needs for further study. Residues of DDD, DDE, DDT, and dieldrin are widespread in the fine-grained bed sediments of the San Joaquin River and its tributaries despite little or no use of these pesticides for more than 15 years. The San Joaquin River has among the highest bed-sediment concentrations of DDD, DDE, DDT, and dieldrin residues of major rivers in the United States. Concentrations of all four pesticides were correlated with each other and with the amount of organic carbon and fine-grained particles in the bed sediments. The highest concentrations occurred in bed sediments of westside tributary streams. Potential tributary loads of DDD, DDE, DDT, and dieldrin to the San Joaquin River were computed from bed-sediment concentrations and data on streamfiow and suspended-sediment concentration in order to identify the general magnitude of differences between streams and to determine study priorities. The estimated loads indicate that the most important sources of residues during the study period were Salt Slough because of a high load of fine sediment, and Newman Wasteway, Orestimba Creek, and Hospital Creek because of high bed-sediment concentrations. Generally, the highest estimated loads of DDD, DDE, DDT, and dieldrin were in Orestimba and Hospital Creeks.     

MULTIVARIATE NONPARAMETRIC TESTS FOR TREND IN WATER QUALITY1

ABSTRACT: National and state fixed station stream quality monitoring networks have now been in existence for over ten years. The resulting data bases provide opportunities and challenges for statistical trend assessment. Although nonparametric tests have been developed that are well suited to such problems, the interpretation of variations in trend significance between seasons and variables remains a problem. One recently developed test is based on the sum of Mann-Kendall statistics over seasons or variables, with the test statistic variance computed as the sum of the covariances of the individual Mann-Kendall statistics. In this method, up- and downtrends can cancel, giving an overall indication of no trend. A related test which is sensitive to trend regardless of direction has been shown to behave poorly for typical stream quality record lengths. An alternative formulation which is sensitive to up- and downtrends and has power approaching that of the covariance sum method, is described. In addition, a variation of a contrast test for discriminating trend directions and magnitudes among variables or seasons where correlation between seasons or variables is present is described, and tests of its performance reported.     

Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

大同市地表水“十五”与“九五”期间污染状况比较及原因分析

“十五”期间大同市地表水氨氮、总汞、六价铬、砷等项目比“九五”期间有所恶化,而生化需氧量、化学需氧量、镉等项目有所好转,其它项目变化不大。主要原因是随着经济的发展,排污企业日益增多,因此需要各排污单位增强环保意识,严格管理污水处理设施,杜绝偷排和超标排放现象,加快城市污水处理厂建设步伐。     

GOALS AND DATA COLLECTION DESIGNS FOR WATER QUALITY MONITORING1

ABSTRACT: Water quality monitoring cannot address every information need through one data collection procedure. This paper discusses the goals and related procedures for designing water quality monitoring programs. The discussion focuses on the broad information needs of those agencies operating water quality networks. These information needs include the ability to assess trends and environmental impacts, determine compliance with objectives or standards, estimate mass transport, and perform general surveillance. Each of these information needs has different data requirements. This paper outlines these goals and discusses factors to consider in developing a monitoring plan on a site by site basis.