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Nutrient loads were estimated for the 34 watersheds draining into Cayuga Lake, New York, through use of a watershed model. Financial and human resources were very limited for the project, but significant cost savings were achieved through project decisions. Chief among these were selection of a watershed model that did not require calibration and use of historic water quality monitoring data for model testing. Savings were also obtained by extrapolating soil properties from related information (nutrient contents from organic matter), substituting literature concentrations for missing point source data, extrapolating septic system performance from one area to another, and use of synthetic weather data generated from a model. None of the decisions was remarkable in itself, but together, they permitted a watershed study and its associated modeling to be accomplished with modest resources.

Pesticide runoff loads from grass surfaces were estimated through simulation experiments for 37 chemicals registered for use on U.S. lawns and golf courses. Simulation runs were made for each chemical and surface (lawns, greens, fairways) using 100-year weather records generated for nine U.S. cities. Results were summarized as mean annual and 1-in-10 year annual maximum daily pesticide loads. These loads varied greatly with pesticide, grass surface, and city, ranging from less than one to over 400 g/ha for mean annual loads and from less than one to over 500 g/ha for 1-in-10 year maximum daily loads. Mean annual loads averaged over the 37 chemicals and three grass surfaces were found to be closely related to growing season precipitation. Variations among the nine cities were well-captured by three general climate categories: humid, represented by Atlanta and Houston; mesic, as with Albany, Columbus, Madison, and Olympia; and dry, represented by Bismarck, Fresno, and Roswell. Mean annual pesticide runoff...

An ecological risk assessment was performed for runoff of 37 pesticides registered for use on grass surfaces (lawns and golf courses) in the U.S. The assessment was based on 100-yr simulations using TPQPond, a newly developed model of pesticide runoff and subsequent accumulation in a receiving pond. One-in-10 yr pond concentrations were compared with acute toxicity end points for fish, invertebrates, and algae. Simulations were performed for pesticides applied at label rates on lawns, fairways, and greens using weather data for nine U.S. locations. Runoff of 4 of the 37 pesticides produced potential acute risk to invertebrates or fish. Two chemicals posed a comparable danger to plants. Risk was highest with fairways and lowest for greens. Locations with long growing seasons and large amounts of precipitation produced the highest risks. The risk assessment followed the general protocols recommended by USEPA, but with different models, weather data, and scenarios. In spite of the differences, the results confirmed that most but not all of the pesticides which had survived the USEPA registration process were also demonstrated safe, with respect to acute risks, by this independent assessment. The five exceptions were explained by differences in models, simulation scenarios, and input data. These results do not mean that the studied pesticides are free of any ecological dangers. In particular, no attempt was made to evaluate chronic risk.

Pesticide runoff loads from grass surfaces were estimated for 29 chemicals commonly applied to U.S. lawns and golf courses. Data on pesticide properties and typical application rates and schedules were developed and summarized as input parameters for the TurfPQ runoff model. Weather data for each of 9 U.S. cities were generated by the USCLIMATE model and modified by the addition of growing season irrigation. Simulation runs were made for each chemical, grass surface (lawns, greens, fairways), and city, and the results were summarized as mean annual and 1-in-10 year annual maximum daily pesticide loads. These loads varied greatly with pesticide, grass surface, and city, ranging from 0 to 875 g/ha for mean loads and 0 to 818 g/ha for 1-in-10 year daily loads. Mean annual loads averaged over the 29 chemicals and 3 grass surfaces were found to be closely related to growing season precipitation. Variations among the nine cities were well-captured by three general climate categories: Humid, characterized by abundant precipitation and warm temperatures, represented by Atlanta and Houston; temperate, with moderate precipitation and temperature, as with Albany, Columbus, Madison, and Olympia; and dry, with sparse precipitation, represented by Bismarck, Fresno, and Roswell. Mean annual pesticide runoff was 37, 9, and 2 g/ha in the humid, temperate, and dry regions, respectively.

Golfers may be subject to chronic health risks from inhalation of vapors from pesticides applied to turf surfaces. The objective of this study was to provide a comprehensive evaluation of the volatilization potential of pesticides used on golf courses in the United States and to assess the resulting inhalation health risks. Long-term exposures were simulated using a fate and transport model for inhaled concentrations. The model was tested using data from field experiments for eight pesticides. Mean concentrations were overestimated by a factor of two, and the model explained 82% of observed variations. The model was subsequently used to estimate volatilization mass fluxes and air concentrations for 37 chemicals using weather information from nine climatic zones in the United States. Simulation results indicated substantial regional variations in volatilization fluxes, concentrations, and health risks, largely due to weather and pesticide application variations. Hazard quotients associated with chronic noncarcinogenic health risks were found to be less than 10 for all chemicals and locations. Similarly, carcinogenic health risks for the 10 pesticides considered likely or possible carcinogens were determined to be less than 10. Based on currently available levels of chronic toxicity endpoints for human health (chronic reference doses and cancer potency factors), we could find no evidence of health risk to golfers from inhalation of these 37 pesticides.

Hydrologic (i.e., flow volumes) and sediment loading calibration and validation were completed for a New York City water supply watershed, the Cannonsville Reservoir basin, located in upstate New York. An unusually large amount of data exist for this watershed, with more than 20,000 data points consisting of climate, flow, and sediment measurements for calibration and validation. Hydrology results using the Soil and Water Assessment Tool (SWAT) displayed a Nash–Sutcliffe measure (NS) of 0.74 at the main monitoring station that drains 80% of the 1,200 km2 basin. Sediment results at this station came within 1% of average loading estimated from data for calibration (with one large storm and snowmelt event removed). Two of the three smaller drainage areas displayed calibrated hydrology NS values above 0.7. Adjustments in parameter values for calibration reflected northeastern conditions related to snowmelt events and fragipan soils. Validation of the hydrology and sediment results was based on an independent ...

Systems analysis or the ‘‘systems approach’’ has been with us in one form or another since the 1940s. It has never been welldefined, but its main features were best described by Churchman ~1968!. He defined a system as a ‘‘set of parts coordinated to accomplish a set of goals’’ and further identified the following factors that must be considered when the systems approach is applied to a problem: 1. Objectives, or performance measures; 2. System environment or fixed constraints, 3. System resources, 4. Components, and 5. Management.

The TurfPQ model was used to simulate the runoff of 15 pesticides commonly applied to creeping bentgrass (Agrostis stolonifera L.) fairways and greens on golf courses in the northeastern USA. Simulations produced 100-yr daily records of water runoff, pesticide runoff, and pesticide concentration in runoff for three locations: Boston, MA, Philadelphia, PA, and Rochester, NY. Results were summarized as annual and monthly means and annual maximum daily loads (AMDLs) corresponding to 10- and 20-yr return periods. Mean annual pesticide runoff loads did not exceed 3% of annual applications for any pesticide or site, and most losses were substantially less than 1% of application. However, annual or monthly mean concentrations of chlorothalonil, iprodione, and PCNB in fairway runoff often exceeded concentrations that result in 50% mortality of the affected species (LC 50 ) for aquatic organisms. Concentrations of azoxystrobin, bensulide, cyfluthrin, and trichlorfon in extreme (1 in 10 yr or 1 in 20 yr) events often approached or exceeded LC 50 levels. Concentrations of halofenozide, mancozeb, MCPP, oxadiazon, propiconazole, thiophanate-methyl, triadimefon, and trinexapac-ethyl were well below LC 50 levels, and turf runoff of these chemicals does not appear to be hazardous to aquatic life in surface waters.

Zero runoff subirrigation (ZRS) technology can effectively manage fertilizer input while improving greenhouse production efficiency. However, high capital investment costs and inadequate technical information to growers are impediments for adoption. A Monte Carlo simulation was used to compare the profitability and risks of alternative ZRS system investments for greenhouse operations in the northeastern and north central United States. Results showed that the Dutch movable tray system and the flood floor system were most profitable and least risky for small potted plant and bedding crop flat production, respectively. The trough bench system was least favorable because its profitability was low and highly volatile.

The curve number equation is one of the simplest and most commonly used models for estimating surface runoff. However, its applicability to turfgrasses has not been previously demonstrated. This study evaluated the approach by comparing model estimates with measured runoff data from turf field plots in six different states, including three different soil hydrologic groups, four turfgrasses, and a range of antecedent moisture and turf conditions. A set of curve numbers were developed for short and long grasses with and without thatch, and curve number selection was based on linear functions of 5-d antecedent precipitation. With the standard growing season antecedent moisture limits of 36 mm and 53 mm, the curve number model explained 78% of the observed variation in runoff and underpredicted the mean event runoff by 15%. With a downward adjustment of these limits to 22 mm and 53 mm in split-sample calibration, the underprediction of means was reduced to less than 3%. More significantly, the model mean for the largest observed events was within 6% of the observed mean. Provided model results are interpreted in a statistical sense rather than as individual events, the curve number model, as modified in this study, is a relatively accurate means of estimating turf runoff.

A set of simulation models consisting of a weather generator, and irrigation supply, soil moisture and crop growth components was used to evaluate the impacts of climate change on irrigated corn in locations near Albany, New York, Indianapolis, Indiana, and Oklahoma City, Oklahoma. The models evaluated the combined effects of modified water demand, supply and crop management (planting date, cultivar selection, irrigation). Simulations were duplicated for 100-year weather sequences based on current (1961–1988) weather statistics, and statistics modified by outputs from the GFDL GCM runs showing the effects from doubling of atmospheric CO2. Climate impacts differed greatly with location and management. Effects were most adverse in New York and least damaging in Indiana. At all sites, the beneficial effects of longer growing season and increased water supply were generally overcome by the detrimental impacts of increased evapotranspiration and reduced solar radiation during plant maturing stages. Adverse impacts of climate change can be substantially reduced by irrigation and appropriate selection of planting dates and cultivars.

A spreadsheet model MSWFLOW was developed as an accounting procedure for determining impacts of management decisions on the physical scale and productive outputs of a municipal solid-waste system. The model tracks the disposition of 50 different waste products and includes source reduction, recovery (recycling and composting), waste-to-energy (WTE) combustion, and landfilling. Outputs from the calculations include mass and volume of waste generated, collected, and diverted by source reduction or recovery; physical scale (daily mass and/or volume) of the recovery and combustion facilities; landfilled mass and associated volume requirement; potential (maximum) annual landfill gas production; and net electrical power production from the combustion facility. The spreadsheet was demonstrated by evaluations of several alternative management strategies for municipal solid waste from a typical U.S. city with a population of 100,000.

Impacts of global warming on streamflows were estimated for four large watersheds in New York State using a daily streamflow model. Three different 100-yr daily weather sequences were input to the model. The first was produced using statistics of current (1961–90) weather records. The second and third sequences were based on modifications of these historic statistics according to the monthly mean temperature and precipitation changes associated with a doubling of atmospheric CO 2 as predicted by two different general circulation models. For 2 × CO 2 conditions, mean annual water balances for all four watersheds indicated modest (1–9%) decreases in precipitation, but much larger (16–42%) decreases in streamflow due to increases in evapotranspiration. Winter flows generally increased, but flows in the remaining seasons often decreased. Monthly streamflow changes varied considerably among watersheds, and we could not attribute these changes to specific differences in land uses or soils.

A Monte Carlo simulation experiment was conducted to explore the relationships between land use, climate, and water supply yields. A watershed streamflow and sediment yield model was coupled with a reservoir model and used to estimate storage-yield relationships for otherwise identical 5,000-ha forested, agricultural, and urban watersheds using weather data from four different sections of the eastern U.S. (Georgia, Indiana, New York, and Texas). Simulation results indicated that although land use very significantly affects water supply yields, the magnitudes of the effects are quite dependent on climate. Thus the differences in yields among the three watershed types are much greater in areas such as Georgia and Texas that have high evapotranspiration than they are in Indiana and New York. For example, at the Texas and Georgia sites, urban watersheds produced more than twice the water supply yield of forests at high levels of flow regulation (large reservoir capacities) while in Indiana and New York, increases of 25–50% were obtained. Agricultural watersheds also generally provided greater yields than forests, although at smaller reservoir capacities, the loss of reservoir capacity due to sedimentation in agricultural watersheds sharply reduced yields.

The research described in this paper extended a deterministic screening model for ground‐water contamination to include specification of variability in water flux and soil and chemical properties. Uncertainty in these parameters was characterized by independent log‐normal probability distributions and a Monte Carlo simulation process was used to estimate the expected percentages of chemical mass reaching the water table. These Monte Carlo results were compared with a deterministic analysis that ignored hydrologic and soil spatial variability. For many of the 49 chemicals analyzed in this study, the Monte Carlo results produced substantially higher estimates of groundwater contamination than the deterministic analyses, indicating that neglecting hydrologic and soil spatial uncertainty may underestimate the potential for pollution. However, for those chemicals and site conditions most likely to produce major contamination, the Monte Carlo and deterministic analyses produced comparable results.

A mathematical model is developed to evaluate applying municipal wastewater sludges to forest land. The model is used to estimate sludge loading rates that produce steady state nitrate concentrations in percolation that meet water quality standards. Annual loading rates for aerobically and anaerobically digested sludges consistent with a 10‐mg/l standard are computed for conifer and hardwood forests in the eight forest regions of New York. These rates vary from 1.7 to 2.7 Mg/ha of dry mass for conifers and from 1.4 to 2.3 Mg/ha for hardwoods among the various forest areas, or in terms of sludge nitrogen, 85 to 135 kg/ha for conifers and 70 to 115 kg/ha for hardwoods. Sludge application rates are sensitive to annual nitrogen uptakes by vegetation, and estimates of these quantities are very uncertain. A geographic information system is used to identify the amount of forest land within each region that meets state regulatory restrictions for sludge disposal. It is determined that sufficient forest land is av...

Decay rates are central parameters in modeling pesticide fate and transport in the environment. Pesticide decay is usually modeled as a first-order process, and variations in half-life can have significant impacts on model predictions. Decay rates for the foliage and thatch components of turf are scarce, and most simulation efforts must resort to values based on pesticide behavior in soil. This paper describes the main dissipation processes affecting pesticides applied to turf and compares aerobic soil decay rates from the USDA-Agricultural Research Service Pesticide Properties Database (ARS PPD; USDA-ARS, 2006) and from The Pesticide Manual (Tomlin, 2003) to dissipation values in turf found in the literature for 18 pesticides currently registered for turf. Median half-lives were 39.5 d for the ARS values, 35.8 d for Tomlin's values, and 5.7 d for the turf-specific values. The turf dissipation half-lives are considered to be representative of the microbial decay processes occurring in the foliage and thatch layers of well established turf, where the majority of the pesticide is intercepted and retained.

Chronic health risks from inhalation of vapors from 15 pesticides were estimated for golfers in Boston, MA, Philadelphia, PA, and Rochester, NY. Two previously tested fate and transport models were used to determine exposures from pesticide inhalation for an adult golfer, and the exposures were in turn used to evaluate health risks from chronic non-carcinogenic effects through calculation of hazard quotients. Hazard quotients for all 15 chemicals were found to be much less one, indicating little risk of non-carcinogenic effects. Carcinogenic health risks for the five pesticides considered to be likely or possible carcinogens were determined to be much less than 10(-6). Based on these results, long-term health risks to golfers from inhalation of these 15 pesticides appear to be minimal in the Northeastern U.S. Estimated hazard quotients were found to be similar to those calculated from field measurements.

A previously developed model by Haith et al. (2002) related pesticide volatilization from turf to evapotranspiration (ET) by scaling factors determined from vapor pressures and heats of vaporization. Although the model provided volatilization estimates that compared well with field measurements, it relied on the Penman ET equation, requiring hourly temperature, wind speed, and solar radiation data, none of which are routinely available at field sites. The current study determined that the volatilization model works equally well with a simpler ET equation requiring only daily temperatures. Three daily temperature-based ET models were evaluated as vehicles for estimating pesticide volatilization from turf: Hamon, Hargreaves-Samani, and a modified Priestley-Taylor. When compared with field volatilization measurements for eight pesticides, volatilization estimates produced from the Hargreaves-Samani model most closely approximated both the field observations and the previous estimates based on the more data-intensive Penman model. Mean estimated volatilization exceeded mean observations by 15% and the coefficient of variation (R 2 ) between estimates and observations was 0.65. The comparable values based on Penman ET were 17% and 0.63, respectively.

Environmental assessments of golf courses and other turf systems must often rely on mathematical modeling. However, in the case of pesticide runoff, successful modeling applications are rare. Available models were developed for agricultural applications and have seen very limited testing for turf. TurfPQ is a pesticide runoff model developed exclusively for turf. The model is based on a curve number calculation for runoff volume and linear partitioning of pesticide into adsorbed and dissolved components during a precipitation or irrigation event. Calibration is optional, so the model can be applied, using default parameter values, to situations where runoff and chemical loss data are unavailable. TurfPQ was tested with default parameter values for 52 pesticide runoff events involving six pesticides measured in plot studies in four states. The model typically produced conservative overpredictions of pesticide runoff, particularly with strongly adsorbed pesticides. Mean predicted pesticide runoff was 2.9% [corrected] of application, compared with an observed mean of 2.1%. TurfPQ captured the dynamics of the pesticide runoff events well with R2 = 0.65 [corrected]. Sensitivity analyses indicated that prediction errors could be reduced by better estimates of adsorption parameters and runoff curve numbers. However, even with default parameters, TurfPQ predictions are at least as accurate as those produced by more complex models.

The Cannonsville Reservoir, which serves as a source of drinking water to New York City, has been under a `phosphorous-loading restriction' due to the high phosphorus concentrations within the water body. These high concentrations are attributed to the non-point source loads from the agricultural land in the basin. Currently, the county is attempting the implementation of Best Management Practices (BMPs) in certain areas to abate this pollution problem. However, the county and regulatory agencies need a way to evaluate the effectiveness of the BMPs. In addition, it would be useful to have tool to project future conditions of the reservoir resulting from changing land use practices and BMPs. The approach of the evaluation of the BMPs and land use practices is to adapt a basin-wide watershed model for the Cannonsville Basin. The model simulates hydrology, sediment, and phosphorous transport throughout the watershed, which ultimately becomes an input to the reservoir. The model being applied is the Soil and Water Assessment Tool (SWAT), which was developed in Texas for use on agricultural lands. This model, which will be combined with Geographical Information Systems (GIS), is spatially distributed, requiring that the entire basin be divided into smaller sub-basins of similar land use, soil properties, and topography. The model uses this information, along with meteorological data, river geometry information, and constituent parameters to develop the fate and transport of phosphorus and sediment over the land surface. This paper will describe the calibration of the model for hydrology, suspended sediments, and phosphorus. In addition, it will discuss the use of the model in evaluating `future scenarios' regarding basin-wide BMP implementation.

Pesticide volatilization models are typically based on equilibrium partitioning of the chemical into solid, liquid, and gaseous phases in the soil environment. In turf systems direct vaporization from vegetation surfaces is a more likely source, and it is difficult to apply equilibrium methods to plant material due to the uncertainties of solid-liquid-gas partitioning. An alternative approach is to assume that pesticide volatilization is governed by the same processes that affect water evaporation. A model was developed in which evapotranspiration values, as determined by the Penman equation, were adjusted to chemical vaporization using ratios of water and chemical saturated vapor pressures and latent heats of vaporization. The model also assumes first-order degradation of pesticide on turf vegetation over time. The model was tested by comparisons of predictions with measurements of volatilization for eight pesticides measured during 3 to 7 d in 11 field experiments. Measured volatilization fluxes ranged from 0.1 to 22% of applied chemical. Pesticides were divided into two groups based on saturated vapor pressures and organic C partition coefficients. One pesticide was selected from each group to calibrate the model's volatilization constant for the group, and the remaining pesticides were used for model testing. Testing results indicated that the model provides relatively conservative estimates of pesticide volatilization. Predicted mean losses exceeded observations by 20%, and the model explained 67% of the observed variation in volatilization fluxes. The model was most accurate for those chemicals that exhibited the largest volatilization losses.

Although zero runoff subirrigation (ZRS) technology has great promise to manage fertilizer inputs while improving production efficiency in greenhouse operations, high initial investment costs and inadequate technical background are major impediments for initiating the change. In a world of uncertainty, greenhouse operators face the challenge of making an optimal investment decision to satisfy environmental compliance expectations and meet the companies' financial goals. Using Monte Carlo simulation, cost risk was analyzed to compare the relative risks of investing in alternative ZRS systems for greenhouse crop production. An investment model was defined for greenhouse production with alternative ZRS systems. Each cost variable was allowed to vary based on a probability distribution. Random numbers were generated to determine parameters for the probability distributions for the uncertain variables. The simulation process was repeated 300 times for each production model. Simulation results showed that among the four ZRS systems studied (ebb-and-flow benches, Dutch movable trays, flood floors, and trough benches), the Dutch movable tray system returned the highest average profit for small potted plant production and the flood floor system returned the highest average profit for large potted plant and bedding crop flat production. Risk of the production models were compared by the variability of simulation results. The Dutch movable tray system is the least risky for small potted plant production, and the flood floor system is the least risky for large potted plant and bedding crop flat production. Despite its low initial costs of adoption, the trough bench system was least competitive as a ZRS technology for a greenhouse operation because of the relative low profitability and high risk of production due to volatile profitability.

Three stochastic weather models are developed for use with nonpoint‐source pollution simulation models that require sequences of daily precipitation and mean daily temperature. Two simple models have parameters that can be estimated from available secondary data. Both generate temperature and precipitation independently. A third model represents a more sophisticated approach and requires primary data for parameter estimation. A model validation analysis was attempted using three U.S. weather stations. The first two models did not reproduce the higher‐order moments or the tail of the wet‐dry precipitation distribution. All models used normal temperature distributions which did not reproduce the higher‐order moments of the observed temperature distributions. Using historical and generated weather data as input to the Cornell Nutrient Simulation model, annual runoff and percolation, and dissolved nitrogen and phosphorus losses were compared. The third model gave output that was not statistically different fr...

Loading functions are proposed as a general model for estimating monthly nitrogen and phosphorus fluxes in stream flow. The functions have a simple mathematical structure, describe a wide range of rural and urban nonpoint sources, and couple surface runoff and ground water discharge. Rural runoff loads are computed from daily runoff and erosion and monthly sediment yield calculations. Urban runoff loads are based on daily nutrient accumulation rates and exponential wash off functions. Ground water discharge is determined by lumped parameter unsaturated and saturated zone soil moisture balances. Default values for model chemical parameters were estimated from literature values. Validation studies over a three-year period for an 850 km2 watershed showed that the loading functions explained at least 90 percent of the observed monthly variation in dissolved and total nitrogen and phosphorus fluxes in stream flow. Errors in model predictions of mean monthly fluxes were: dissolved phosphorus - 4 percent; total phosphorus - 2 percent; dissolved nitrogen - 18 percent; and total nitrogen - 28 percent. These results were obtained without model calibration.

An operational procedure has been developed which is suitable for estimating nonpoint source water pollution due to runoff from agricultural land and is sensitive to regional variations in weather, soils, and crop management. Although not presently applicable to snowmelt runoff, the procedure could be extended to winter runoff by use of suitable snowmelt estimating methods. Nitrogen and phosphorus in agricultural runoff were estimated for a five-watershed area totaling 578 sq km in Broome and Tioga Counties, N.Y., for the years 1971 and 1972. Comparison was made with two other estimates which were obtained using areal loading factors (losses of nutrients per unit area). Although the three different estimates were of comparable orders of magnitude, the loading factor estimates were not sensitive to the soils, weather, and crop distributions of the study region, and may overestimate losses of nitrogen in agricultural runoff.

A simple mathematical model is presented for estimating nitrate‐nitrogen concentrations in percolation from sludge land application sites. The model is based on annual mass balances of sludge and soil inorganic nitrogen and includes the processes of mineralization, ammonia volatilization, crop uptake, and leaching. Most input parameters are readily obtained from published sources and standard sludge analyses. Default values are given for remaining parameters. Model predictions compared favorably with field measurements taken over three years in a previous study in Ocean County, New Jersey.

Modelisation mathematique des phenomenes de ruissellement. Influence de variables telles que le climat et le sol

THERE has been a tendency to equate best manage-ment practices, as defined in water quality legisla-tion, with soil and water conservation practices. The effectiveness of SWCP's at controlling potential pollut-ants other than sediment depends on the characteristics of pollutants. Pollutants have been categorized in groups having distinctly different soil adsorption properties which have been related to the effect of SWCP's on water and soil movement.

A loading function methodology is presented for predicting runoff, sediment, and nutrient losses from complex watersheds. Separate models are defined for cropland, forest, urban and barnyard sources, and procedures for estimating baseflow nutrients are provided. The loading functions are designed for use as a preliminary screening tool to isolate the major contributors in a watershed. Input data sources are readily available and the functions do not require costly calibrations. Data requirements include watershed land use and soil information, daily precipitation and temperature records and rainfall erosivities. Comparison of predicted and measured water, sediment, and nutrient runoff fluxes for the West Branch Deleware River in New York, indicated that runoff was underpredicted by about 14 percent while dissolved nutrients were within 30 percent of observed values. Sediment and solid-phase nutrients were overpredicted by about 50 percent. An annual nutrient budget for the West Branch Delaware River showed that cornland was the major source of sediment, solid phase nutrients, and total phosphorus. Waste water treatment plants and ground water discharge contributed the most dissolved phosphorus and dissolved nitrogen, respectively.

The Federal Water Pollution Control Act Amendments of 1972 require that land-use management and control of nonpoint pollution sources be included in areawide water quality planning. At the present time, few tested procedures are available to implement this policy. Statistical techniques, including correlation and regression analyses, offer a promising methodology for the study of land use and nonpoint source impacts on water quality. The methodology has been applied to water quality and land-use data from 20 river basins in New York State. The results indicated that river basin land uses could account for up to 89% of the observed variation in mean river nitrogen concentrations and 63% of the observed variation in mean total suspended solids concentrations. No relationships between phosphorus concentrations and land uses were found in the basins.

A mathematical model has been developed for the preliminary screening of wastewater management alternatives involving treatment and discharge to receiving waters and land application. The model consists of a dissolved oxygen model of receiving waters, mass balances of nitrogen and water at the land application site and cost estimating equations. The model is used to estimate costs and water quality impacts on surface and ground waters of wastewater management options. The objective of the model is the identification of alternatives that demonstrate cost-effective potential as specified in regulations for best practicable waste treatment technology (BPWTT). The screening model was used to evaluate wastewater management alternatives for a hypothetical city with a wastewater flow of 10 mgd.

Asimple model is proposed for estimating the short-term sediment yields often needed in studies of nonpoint source water pollution and sediment control. The model consists of a two-stage computation which separately considers the generation of sediment supply and its subsequent transport by runoff. Inputs include daily temperature and precipitation records and parameters for the Universal Soil Loss and curve number equations. Testing over a 25-month period for an 850 km2 New York watershed indicated that the model explained 95% of the observed monthly variation of sediment yields

A Monte Carlo simulation approach is proposed for estimating the groundwater pollution risk from nitrate in percolation from sludge land application sites. The approach is used to estimate the probability that annual nitrate‐nitrogen concentrations will fail to meet a water quality standard. Failure probabilities and mean annual nitrate‐nitrogen concentrations were computed as functions of sludge application rates for 12 example systems in New York. The results for aerobic, anaerobic, and composted sludges indicated that application rates that are designed to limit mean nitrate‐nitrogen concentrations to no more than 10 mg/L during a system's operating life result in failure probabilities of 30–40%. Thus, although the average groundwater nitrate concentration will meet a water quality standard, the standard will be violated in three or four years out of ten.

A modeling procedure has been developed to estimate nonpoint source pollution from agricultural runoff in large watersheds. The procedure is based on simple equations for runoff and soil loss prediction. It is designed for use in situations where resources are not available for extensive water quality sampling or more sophisticated modeling efforts. The simple models or loading functions were tested by comparing predicted and observed nitrogen and phosphorus mass fluxes in streamflow from a 391-km² Pennsylvania watershed for a 16-month period. The comparisons indicated that loading functions provided reasonable estimates of dissolved nitrogen, solid-phase nitrogen and total phosphorus mass fluxes in runoff from the watershed. Rather, these simple methods are most suitable as screening devices to: (1)Identify the approximate magnitudes of nonpoint source loading of pollutants in agricultural runoff; and (2)evaluate the likely changes in loadings associated with alternative agricultural management practices.

A simple model is proposed for predicting corn yields as a function of hybrid, planting timeliness, growing season temperatures, moisture stress and frost occur-rence. The model is used in conjunction with a daily soil moisture balance model. Required meterologic data are daily temperatures, precipitation, and pan evaporation rates. Additional yield data such as hybrid factor and timeliness penalty are obtained from state field trial in-formation. Moisture stress parameters for each of three stress periods are estimated by model calibration. The model was tested in a two-stage calibration and valida-tion application in New York. Comparison of model predictions with measured crop yields showed errors of 3 to 8 percent in predicted yields.

Analytical procedures are proposed for estimating probability distributions of travel times for chemical waste loads to groundwater. Travel distance of the chemical is treated as a renewal process, and travel time is given by the number of annual chemical displacements or renewals required for passage through the soil unsaturated zone. The methods were evaluated for two organic chemicals for a range of site conditions near Lexington, Kentucky, and Des Moines, Iowa. It was found that groundwater contamination risk is very dependent on site-specific soil and hydrologic conditions. Probability distributions based on both hydrologic and soil spatial variability differed markedly from those that considered only hydrologic variability. The effect of soil spatial variability is to increase travel-time variability and risk of groundwater contamination. Travel-time probability distributions were combined with biochemical degradation rates to estimate the expected fraction of chemical mass reaching the water table. This fraction serves as a screening criterion to identify and rank combinations of chemicals and sites that are likely to produce groundwater pollution.

The land disposal alternative is not free from water pollution potential. Nitrogen losses from percolation and runoff may contaminate water supplies and contribute to the eutrophication of aquatic systems. A general model of the soil nitrogen budget has been developed for the purpose of comparing alternative strategies for controlling nitrogen leaching losses from a cropped land disposal area. The model is based on monthly inventory equations for both inorganic and organic soil nitrogen and includes the processes of plant nitrogen uptake, mineralization of organic nitrogen, and leaching. The model was tested using nitrogen budget data from several New York corn production field studies. The model was linearized and linear programming was used to find monthly disposal schedules that maximize annual returns from a sewage sludge disposal system subject to constraints on nitrogen leaching losses.

Mathematical models are useful means of analyzing agricultural nonpoint-source pollution. This review summarizes and classifies many of the available chemical transport and planning and management models. Chemical transport models provide estimates of chemical losses from cropland to water bodies; they include continuous simulation, discrete simulation, and functional models. A limited number of transport models have been validated in field studies, but none has been tested extensively. Planning and management models, including regional impact, watershed planning and farm management models, are used to evaluate tradeoffs between environmental and agricultural production objectives. Although these models are in principle the most useful for policy making, their economic components are much better developed than components for predicting water pollution.