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Steven J. Larson

Publications and source records attributed to Steven J. Larson.

10 recordsLinked to original sources

Development and Application of Watershed Regressions for Pesticides (WARP) for Estimating Atrazine Concentration Distributions in Streams

Regression models were developed for predicting atrazine concentration distributions in rivers and streams, using the Watershed Regressions for Pesticides (WARP) methodology. Separate regression equations were derived for each of nine percentiles of the annual distribution of atrazine concentrations and for the annual time-weighted mean atrazine concentration. In addition, seasonal models were developed for two specific periods of the year--the high season, when the highest atrazine concentrations are expected in streams, and the low season, when concentrations are expected to be low or undetectable. Various nationally available watershed parameters were used as explanatory variables, including atrazine use intensity, soil characteristics, hydrologic parameters, climate and weather variables, land use, and agricultural management practices. Concentration data from 112 river and stream stations sampled as part of the U.S. Geological Survey's National Water-Quality Assessment and National Stream Quality Accounting Network Programs were used for computing the concentration percentiles and mean concentrations used as the response variables in regression models. Tobit regression methods, using maximum likelihood estimation, were used for developing the models because some of the concentration values used for the response variables were censored (reported as less than a detection threshold). Data from 26 stations not used for model development were used for model validation. The annual models accounted for 62 to 77 percent of the variability in concentrations among the 112 model development stations. Atrazine use intensity (the amount of atrazine used in the watershed divided by watershed area) was the most important explanatory variable in all models, but additional watershed parameters significantly increased the amount of variability explained by the models. Predicted concentrations from all 10 models were within a factor of 10 of the observed concentrations at most model development and model validation stations. Results for the two sets of seasonal models were similar. Concentration distributions derived from the seasonal-model predictions provided additional information compared to distributions derived from the annual models.

Water-Resources Investigations Report↗

Selected data from field studies of pesticide runoff to surface waters

Citations from the scientific literature for studies that quantified selected pesticides in field runoff or streams were obtained from two computerized bibliographic databases: Chemical Abstracts and AGRICOLA. Selected data were extracted from studies in field environments that lasted longer than a day and are summarized here. The data extracted from each article, if available, include pesticide information, environmental setting, year of study, and the mass of the pesticide in runoff as a percent of the mass applied. Data from two national studies of pesticides in surface waters done by the U.S. Geological Survey (National Water-Quality Assessment Program, 1992?1995, and National Stream-Quality Accounting Network, 1996-1998) also are summarized.

Water-Resources Investigations Report↗

Pesticides in streams of the United States : initial results from the National Water-Quality Assessment Program

Water samples from 58 rivers and streams across the United States were analyzed for pesticides as part of the National Water-Quality Assessment Program of the U.S. Geological Survey. The sampling sites represent 37 diverse agricultural basins, 11 urban basins, and 10 basins with mixed land use. Forty-six pesticides and pesticide degradation products were analyzed in approximately 2,200 samples collected from 1992 to 1995. The target compounds account for approximately 70 percent of national agricultural use in terms of the mass of pesticides applied annually. All the target compounds were detected in one or more samples. Herbicides generally were detected more frequently and at higher concentrations than insecticides. Nationally, 11 herbicides, 1 herbicide degradation product, and 3 insecticides were detected in more than 10 percent of samples. The number of target compounds detected at each site ranged from 7 to 37. The herbicides atrazine, metolachlor, prometon, and simazine were detected most frequently; among the insecticides, carbaryl, chlorpyrifos, and diazinon were detected the most frequently. Distinct differences in pesticide occurrence were observed in streams draining the various agricultural settings. Relatively high levels of several herbicides occurred as seasonal pulses in corn-growing areas. Several insecticides were frequently detected in areas where the dominant crops consist of orchards and vegetables. The number of pesticides detected and their concentrations were lower in wheat-growing areas than in most other agricultural areas. In most urban areas, the herbicides prometon and simazine and the insecticides carbaryl, chlorpyrifos, diazinon, and malathion were commonly detected. Concentrations of pesticides rarely exceeded standards and criteria established for drinking water, but some pesticides commonly exceeded criteria established for the protection of aquatic life.

Water-Resources Investigations Report↗

Pesticides in surface waters: Current understanding of distribution and major influences

This report summarizes a comprehensive analysis of existing information on national and regional patterns of pesticide occurrence in surface waters of the United States and the major influences on the sources and transport of pesticides. It is one of a four-part series that synthesizes current knowledge and understanding of pesticides in the nation's water resources as part of the National Water Quality Assessment Program.

Fact Sheet↗

Pesticides in surface waters: distribution, trends, and governing factors

Pesticde use in agriculture and non-agriculture settings has increased dramatically over the last several decades. Concern about adverse effects on the environment and human health has spurred an enormous amount of research into their environmental behavior and fate. Pesticides in Surface Waters presents a comprehensive summary of this research. This book evaluates published studies that focus on measuring pesticide concentration. The studies chosen include peer reviewed scientific literature, government reports, laboratory studies, and those using microcosms and artificial streams and ponds. The authors used this information to develop their overview of pesticide contamination of surface waters. The exhaustive compilation of data along with the fundamental science make this book essential for those involved in pesticide use, environmental protection, water quality, and human or ecological risk assessment. Pesticides in Surface Waters covers the results of actual studies, sources of pesticides to surface water, fate and transport, and environmental significance. Hundreds of data-packed tables, maps, charts, and drawings illustrate the key points, making research and application easy and cost effective.

Book↗

Relations between pesticide use and riverine flux in the Mississippi River Basin

In an intensive subcontimental study of pesticides in surface waters of the United States, concentrations of 26 high-use pesticides were measured at nine sites in the Mississippi River basin from May 1991 through March 1992. Calculated total fluxes were combined with agricultural-use data to estimate the percentage of applied pesticide reaching the mouths of the Mississippi River and six major tributaries. For most pesticides, the riverine flux was less than 2% of the mass applied agriculturally. The insecticide diazinon was detected frequently in rivers draining the three basins with the highest population densities, apparently as a result of urban use.

Mississippi River basin↗

Precision of a splitting device for water samples

Two identical cone splitters, devices designed to split water and its suspended solids into equal aliquots for semi-volatile organic chemical and trace element analyses, were evaluated for their precision. The water-splitting evaluations consisted of experiments to test the effect of water volume, the effect of combining outlet ports, and the effect of different techniques of water introduction. The solids-splitting evaluations consisted of experi- ments to test the effect of particle size (nine different particle diameters ranging from very coarse sand to clay) and suspended-solids concentration. In general, water was equally split with a precision of less than 5 percent relative standard deviation. The accuracy of splitting the solids was a function of particle size. Clay, silt, and fine and medium sand were split with a precision relative standard deviation of less than 7 percent, and coarse sand was split with a relative standard deviation between 12 and 45 percent.

Open-File Report↗

An appraisal of groundwater for irrigation in the Appleton area, west-central Minnesota

Supplemental irrigation of well-drained sandy soils has prompted an evaluation of ground water in the Appleton area. Glacial drift aquifers are the largest source of ground water. The surficial outwash sand and gravel is the most readily available and a really extensive drift aquifer and underlies much of the sandy soil area. Saturated thickness of the outwash is more than 80 feet (24 metres) in places and potential well yields may exceed 1,200 gallons per minute (76 litres per second) in some areas. In about 17 percent of the area, yields of more than 300 gallons per minute (19 litres per second) are obtainable. Recharge to the outwash aquifer occurs primarily during the spring thaw and averages about 5 inches (12.7 centimetres) annually. Most discharge from the aquifer appears as base flow in the Pomme de Terre River. Despite dissolved-solids concentrations ranging from 280 to 1,350 milligrams per litre the water is chemically suitable for irrigation.

Minnesota↗