Groundwater Loading Effects Of Agricultural Management Systems Research Articles

Assessing Annual Actual Evapotranspiration Based on Climate, Topography and Soil in Natural and Agricultural Ecosystems

Simple formulas for estimating annual actual evapotranspiration (AET) based on annual climate data are widely used in large scale applications. Such formulas do not have distinct compartments related to topography, soil and irrigation, and for this reason may be limited in basins with high slopes, where runoff is the dominant water balance component, and in basins where irrigated agriculture is dominant. Thus, a simplistic method for assessing AET in both natural ecosystems and agricultural systems considering the aforementioned elements is proposed in this study. The method solves AET through water balance based on a set of formulas that estimate runoff and percolation. These formulas are calibrated by the results of the deterministic hydrological model GLEAMS (Groundwater Loading Effects of Agricultural Management Systems) for a reference surface. The proposed methodology is applied to the country of Greece and compared with the widely used climate-based methods of Oldekop, Coutagne and Turk. The results show that the proposed methodology agrees very well with the method of Turk for the lowland regions but presents significant differences in places where runoff is expected to be very high (sloppy areas and areas of high rainfall, especially during December–February), suggesting that the proposed method performs better due to its runoff compartment. The method can also be applied in a single application considering irrigation only for the irrigated lands to more accurately estimate AET in basins with a high percentage of irrigated agriculture.

Modification of GLEAMS for modeling movement of organic contaminants from land-applied biosolids

Municipal biosolids are commonly applied to agricultural lands as fertilizer, but this also poses potential risks to groundwater and surface water quality from constituents that may be mobilized during storm events. In the present study, an existing model, Groundwater Loading Effects of Agricultural Management Systems (GLEAMS), is modified to predict the fate and transport of organic contaminants from land-applied biosolids, primarily via addition of a labile biosolids organic carbon phase distinct from soil organic carbon. While capable of simulating contaminant transport in runoff and via percolation, only the runoff portion of the model was able to be calibrated using existing experimental data, and showed good agreement with field runoff data for acetaminophen, ibuprofen, triclosan, triclocarban, and estrone, but substantially under-predicted concentrations for carbamazepine, androstenedione, and progesterone. The model is applied to various scenarios using varied chemical properties, application date in the arid west, and application method (i.e., surface spreading vs. incorporation). Chemicals with longer half-lives and lower KOCs exhibited higher losses in runoff than chemicals with shorter half-lives and higher KOCs. For short half-life chemicals (i.e., ≤100 days), application at the beginning of the dry season resulted in the lowest losses. However, for long half-life chemicals (∼1000 days) with high KOC (10,000–100,000), application during the rainy season resulted in the lowest losses, because this caused organic carbon to be high during the period of highest runoff. While further work is necessary to calibrate the percolation and subsurface transport portion, the model can help predict environmental risk from land-application of biosolids, highlight gaps in our knowledge about how chemicals are mobilized and transported from biosolids, and help identify management practices that result in minimal impacts to water quality.

Integrating GLEAMS sedimentation into RZWQM for pesticide sorbed sediment runoff modeling

Sediment transport from agricultural fields to native waterways is a significant pollution vector, not just for the bulk sediment, but also for additional mass of pesticides traveling offsite that are sorbed to soil particles. Existing field scale models that track plant growth as well as the fate and transport of applied pesticides lack an integrated sediment transport component. This study sought to address this lack of available modeling tools for researchers and regulators by integrating the sediment and surface flow components of Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model into the mature Root Zone Water Quality Model (RZWQM) to create a derivative model named RZWQM-Sed. Previous research identified RZWQM as a quick running, agricultural field scale model that accurately estimated offsite transport of solutes. Unlike other well performing field scale agricultural models, the full source code of RZWQM was available for modification and extension. However, RZWQM lacked a sediment component and thus could not measure all pollutants moving offsite. GLEAMS sedimentation was chosen for integration due to its well documented history, compatibility with the RZWQM codebase, and source code availability. Sensitivity analysis of the RZWQM runoff variables showed that the residual water content, saturated water content, and bubbling pressure from the Brooks-Corey equation had the highest influence for RZWQM followed by the saturated hydraulic conductivity and the non-Brooks-Corey bubbling pressure. Analysis of GLEAMS variables showed the most significant variables are the USLE parameters (cfact, pfact, ksoil) and Manning's N. The latter variable only showed sensitivity at very high surface roughness while the USLE parameters had a linear relationship over the entire domain. The integrated model was calibrated and validated using multiple real-world datasets spanning ranges of space and time. The final model performed well in the primary task of predicting the mass of sorbed chemicals in the tailwater (Nash-Sutcliffe coefficient > 0.3).

Evaluating Effects of Poultry Waste Application on Phosphorus Loads to Lake Tenkiller

Lake Tenkiller located in Oklahoma, USA is a large midcontinent reservoir in a eutrophic state due to excess phosphorus (P) loads. Poultry waste application within the Illinois River Watershed in northeast Oklahoma and northwest Arkansas has been identified as a major contributor to overall P loads within Lake Tenkiller. In this study, Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) was applied to evaluate the effect of poultry waste application on P loads to Lake Tenkiller. Historical P loads to Lake Tenkiller during 1951–2000 have increased from approximately 166,000 kg/year to more than 295,000 kg/year with the Illinois River at Tahlequah subwatershed increasing from 68% to 78% of total P loads over that period. Increased poultry waste application based on poultry growth rates could increase P load to Lake Tenkiller from 311,000 kg/year to more than 528,000 kg/year. Cessation of poultry waste application and addition of buffers along streams could reduce P loads to approximately 92,000 kg/year for cessation of poultry waste application alone and about 89,000 kg/year for cessation of poultry waste application with buffers. One possible strategy to reduce P load to Lake Tenkiller is to cease applying poultry waste application, especially in the portion of the Illinois River above the Tahlequah USGS gage station.

CREAMS/GLEAMS: Model Use, Calibration, and Validation

The Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) model was developed by a multidisciplinary team of research scientists from the USDA Agricultural Research Service. The primary purpose of the model was to aid the USDA Natural Resources Conservation Service (NRCS) specialists in assessing nonpoint-source pollution from agricultural areas and to compare impacts of alternative management practices. Existing readily modifiable and new components were assembled into a field-scale model. Modelers also were charged with publication of model documentation, validation, and a user manual. Model validation with available data and sensitivity analyses of parameters in the hydrology, erosion, plant nutrient, and pesticide components were essential to demonstrate the model capabilities and effectiveness. Technology transfer to NRCS personnel was necessary to gain acceptance and proper use as well as to identify weaknesses and areas for needed improvement. Following publication and NRCS acceptance, improvements to CREAMS were made to better represent soil layering, crop rotations, irrigation, soil water routing, and chemical movement, which resulted in the Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model. Climatic records were increased from a maximum of 20 years to 50 years. The modifications were validated with available data and included in subsequent publications. The user manual gives more comprehensive description of the model parameters and their relative sensitivity. This article describes the historical development of the CREAMS and GLEAMS models with an emphasis on providing model users with an understanding of the degree of model verification and validation that was undertaken during development of these multidisciplinary models. Model calibration is discussed, including sensitive parameters and recommended procedures. Finally, two specific case studies are presented along with brief synopses of numerous case studies that have been used to validate model components. Future users are encouraged to use the model source code to further expand its utility for analyzing the nonpoint-source pollution impacts of agricultural management practices.

Assessment of the Intrinsic Vulnerability of Agricultural Land to Water and Nitrogen Losses via Deterministic Approach and Regression Analysis

A set of indices was developed in order to classify the vulnerability of agricultural land to water and nitrogen losses (LOS), setting a basis for the integrated water resources management in agricultural systems. To calibrate the indices using multiple regression analysis, the simulation results of Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model for combinations of different soil properties, topography, and climatic conditions of a reference field crop were used as “observed values.” GLEAMS quantified (1) the annual losses of the percolated water beneath the root zone, (2) the annual losses of the surface runoff, (3) the annual losses of the nitrogen leaching beneath the root zone, and (4) the annual losses of nitrogen through the surface runoff, which were used to calibrate the following indices LOSW-P, LOSW-R, LOSN-PN, and LOSN-RN, respectively. All the simulations to gain the LOS indices were carried out for the same reference field crop, the same nitrogen fertilization, and the same irrigation practice, in order to obtain the intrinsic vulnerability of agricultural land to water and nitrogen losses. The LOS indices were also combined to derive nitrogen concentrations in the percolated and in the runoff water. Finally, the connection of LOS indices with the groundwater was performed using an additional equation, which determines the minimum transit time of the percolated water to reach the groundwater table.

GLEAMS COMPUTER MODEL PESTICIDE PREDICTION IN TWO SOILS

Recent concerns about the presence of pesticide residues in surface and groundwater have resulted in a need for computer model simulation to assess the impacts of agrichemicals on potential surface and groundwater contamination. GLEAMS (Groundwater Loading Effects of Agricultural Management Systems), is a mathematical model developed for fieldsize areas to evaluate the effects of agricultural management systems on the movement of agrichemicals. It can be used as a tool to evaluate the effects of different tillage systems on pesticide, and nutrient losses. Agriculture is being increasingly criticized for the deterioration of surface and subsurface water resources all over the world. In the Balochistan province of Pakistan, almost all the urban and rural population depend on groundwater resources for drinking water, irrigation, and the water for livestock use. The objective of this study was to simulate pesticide (Metolachlor) losses from conventional tillage and no-till systems using the GLEAMS pesticide submodel. The pesticide submodel simulated results showed that the runoff losses of Metolachlor from convectional tillage were 94%, and by sediment, the losses were 92% higher than that for the no-till system. However, the percolation losses of Metolachlor were 61%, and the total Metolachlor losses were 39% higher from no-till system as compared to conventional tillage system. The total Metolachlor losses were higher for no-till system because 91 to 99% of the annual total no-till losses were by percolation as compared to 41 to 90% for conventional tillage.

Agricultural Land Use and Best Management Practices to Control Nonpoint Water Pollution

In recent years, improvements in point-source depuration technologies have highlighted the problems regarding agricultural nonpoint (diffuse) sources, and this issue has become highly relevant from the environmental point of view. The considerable extension of the areas responsible for this kind of pollution, together with the scarcity of funds available to local managers, make minimizing the impacts of nonpoint sources on a whole basin a virtually impossible task. This article presents the results of a study intended to pinpoint those agricultural areas, within a basin, that contribute most to water pollution, so that operations aimed at preventing and/or reducing this kind of pollution can be focused on them. With this aim, an innovative approach is presented that integrates a field-scale management model, a simple regression model, and a geographic information system (GIS). The Lake Vico basin, where recent studies highlighted a considerable increase in the trophic state, mainly caused by phosphorus (P) compounds deriving principally from the intensive cultivation of hazelnut trees in the lake basin, was chosen as the study site. Using the management model Groundwater Loading Effects of Agricultural Management Systems (GLEAMS), the consequences, in terms of sediment yield and phosphorus export, of hazelnut tree cultivation were estimated on different areas of the basin with and without the application of a best management practice (BMP) that consists of growing meadow under the trees. The GLEAMS results were successively extended to basin scale thanks to the application of a purposely designed regression model and of a GIS. The main conclusions can be summarized as follows: The effectiveness of the above-mentioned BMP is always greater for erosion reduction than for particulate P reduction, whatever the slope value considered; moreover, the effectiveness with reference to both particulate P and sediment yield production decreases as the slope increases. The proposed approach, being completely distributed, represents a considerable step ahead compared to the semidistributed or lumped approaches, which are traditionally employed in research into tools to support the decision-making process for land-use planning aimed at water pollution control.

Prediction of NO3-N Losses in Surface Runoff from a Field with Seepage Zones Using GLEAMS and RZWQM

Seepage zones have been shown to be of critical importance in controlling contaminant export from agricultural watersheds. However, their impacts on water quality have not been effectively modeled. The Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model and the Root Zone Water Quality Model (RZWQM) were used to predict daily and monthly nitrate-nitrogen (NO3-N) concentration and loss in surface runoff from an agricultural field with seepage zones. The results of the study show that calibrated GLEAMS and RZWQM predicted daily NO3-N concentration [index of agreement (D) > 0.57] in surface runoff from the field with seepage zones. Based on the different model evaluation techniques used in this study, both GLEAMS and RZWQM performed fairly well in assessing the effects of seepage zones on daily NO3-N losses in surface runoff. However, GLEAMS (D = 0.93) performed relatively better than RZWQM (D = 0.45) in predicting NO3-N loss in surface runoff on a monthly basis, while both GLEAMS and RZWQM performed equally well in predicting NO3-N loss in surface runoff on a daily basis. Both models performed poorly in predicting NO3-N concentration in surface runoff on a monthly basis (D < 0.44). Additionally, since neither model adequately simulated monthly NO3-N concentration in surface runoff from the field with seepage zones, their ability in water quality modeling for such fields will be compromised, and further model evaluation and development is justified.

Modification and Validation of GLEAMS for Prediction of Phosphorus Leaching in Waste-Amended Soils

Excess phosphorus applied to soils with low P adsorption capacities can enter surface water via leaching and subsurface transport, thereby negatively impacting water quality. Computer simulation models can be used to describe the effects of management practices on P leaching losses, provided the models are appropriately validated. The objectives of this research were to modify and validate P subroutines in the GLEAMS (Groundwater Loading Effects of Agricultural Management Systems) model to more accurately reflect P sorption and desorption, and then use the modified model to determine crop and waste management effects on long-term P leaching losses below the root zone of a grazed pasture with >20-year history of swine lagoon liquid application and considerable P buildup in the soil profile. GLEAMS was modified with the Langmuir equation to partition labile P between adsorbed and solution phases. The modification improved predictions of percolate P concentrations and soil P accumulation in acid sandy soils receiving waste-based P additions. The modification also increased model sensitivity to changes in crop and P management. The modified model predicted that P-based swine lagoon liquid applications would decrease P leaching by >20 kg ha-1 year-1 compared to N-based applications. Eliminating all P applications decreased the predicted P leaching losses by less than 1 kg ha-1 year-1 compared to P-based swine lagoon liquid application. Results show that P can continue leaching from P-saturated soils even in the absence of P additions.

Prediction of Soil and Nutrient Losses in A Highland Catchment

Highland catchments in tropical regions are frequently subjected to soil erosion and the transport of chemicals downstream. Any drastic changes in land use will increase the severity of these processes of land degradation. A simulation study using GLEAMS (Groundwater Loading Effects of Agricultural Management Systems) was conducted at a catchment presently under tea farming in Cameron Highlands, Malaysia. Soil, water and nutrient transport associated with several alternative land uses was studied. In addition, the effect of a disruptive form of land clearing on soil, water and nutrient losses was also investigated. Modelling with GLEAMS required information from field measurements and observations, laboratory analyses, guide tables, industry records, maps and reports published by soil survey and meteorological departments.

PREDICTION OF PESTICIDE LOSSES IN SURFACE RUNOFF FROM AGRICULTURAL FIELDS USING GLEAMS AND RZWQM

Seepage zones have been shown to be of critical importance in controlling contaminant export from agricultural watersheds. To date, no multipurpose agricultural water quality model has seepage zones incorporated into its process-level representations. We chose to test two widely used models of agricultural water quality, the Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) and the Root Zone Water Quality Model (RZWQM), by seeing how well each predicted solution pesticide concentration and loss in surface runoff from two agricultural fields: one with and one without seepage zones. Daily simulated atrazine and metolachlor concentration and loss in surface runoff from both calibrated and default (or non-calibrated) GLEAMS and RZWQM were compared with three years of measured data from the two fields. The results of the study show that GLEAMS and RZWQM using default input parameters were not capable of predicting atrazine and metolachlor concentration and loss in surface runoff from the fields with and without seepage zones (modeling efficiency <0.16). Site-calibrated GLEAMS and RZWQM predicted atrazine and metolachlor concentration and loss in surface runoff from both fields (coefficient of determination >0.52, index of agreement >0.83, and modeling efficiency >0.53) and can be used for assessing the effects of seepage zones on pesticide loss in surface runoff from agricultural fields.

Simulation of nitrate leaching for different nitrogen fertilization rates in a region of Valencia (Spain) using a GIS–GLEAMS system

Abstract The groundwater loading effects of agricultural management systems (GLEAMS) model coupled to a GIS was used to evaluate the effect of different fertilization treatments on the total N leaching in a selected area of eastern Spain with intensive agriculture. Four nitrogen fertilization rates (traditional or base, base rate reduced by 20%, reduced by 50%, and the rate calculated by the Nmin recommendation system for vegetables, and reduced by 70% for citrus) were evaluated at a regional scale to find the rate that minimized N leaching without reducing crop N uptake. Nitrate leaching maps were obtained for the different nitrogen rates studied. A great reduction of N leaching (up to 68% for vegetables, and 75% for citrus) was observed under the most reduced fertilization rates and this reduction was greater in areas irrigated with surface water in comparison to those irrigated with groundwater. The GIS–GLEAMS system was a useful tool to assess the N leaching at a regional scale for the different N management considered. For example, it was shown that the Nmin recommendation system was the most efficient for vegetables, and for citrus the most efficient fertilization rate was the reduced 50%, that is similar to that recommended by the Code of Good Agricultural Practices. The areas irrigated with groundwater with high nitrate content had a high leaching rate, and the nitrate applied in irrigation water should be considered when planning the crop fertilization. A temporal analysis of the NO3-N in soil, N leaching, crop evapotranspiration and rainfall allowed to identify the influence of the soil NO3-N and the rainfall on nitrate leaching.

THE IMPORTANCE OF SEEPAGE ZONES IN PREDICTING SOIL MOISTURE CONTENT AND SURFACE RUNOFF USING GLEAMS AND RZWQM

Seepage zones have been shown to be of critical importance in controlling contaminant export from agriculturalcatchments. To date, no multi-purpose agricultural water quality model has incorporated seepage zones into its process-levelrepresentations. We chose to test two commonly used models of agricultural water quality, Groundwater Loading Effects of AgriculturalManagement Systems (GLEAMS) and the Root Zone Water Quality Model (RZWQM), by seeing how well each predictedsurface runoff and soil moisture content in two agricultural fields: one with and one without seepage zones. Dailysimulated surface runoff and soil moisture content from both calibrated and default (or non-calibrated) GLEAMS and RZWQMwere compared with three years of measured surface runoff and soil moisture content in the two fields. The results of the studyshow that GLEAMS and RZWQM, using default model parameters, were not capable of predicting surface runoff and soil moisturecontent in either field. Site-calibrated GLEAMS and RZWQM performed well in simulating surface runoff trends from thefield with and without seepage zones, but they predicted soil moisture content poorly. Several statistical tests were used thatshowed that although both site-calibrated GLEAMS and RZWQM performed well, RZWQM performed better than GLEAMSand is better suited in assessing the effects of seepage zones on soil moisture content and surface runoff from agricultural fields.

Application timing impact on runoff losses of atrazine

Field experiments were conducted from 1996 to 2000 near Manhattan, KS, to determine the effects of application timing on atrazine loss in surface water runoff. In addition, Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) was run to compare simulated loss with actual loss in the field. Atrazine treatments were fall plus preemergence (FALL + PRE), early preplant plus PRE (EPP + PRE), PRE at a low rate (PRE-LOW), and PRE at a full (recommended) rate (PRE-FULL). Ridge-till furrows served as mini watersheds for the collection of surface water runoff. Water runoff volumes and herbicide concentrations were determined for each runoff event. Across four sampling years, mean atrazine runoff loss was 1.7, 4.3, and 1.7% of applied for FALL + PRE, EPP + PRE, and the mean of the PRE treatments, respectively. Thus, actual average losses from FALL + PRE and EPP + PRE treatments were somewhat higher than that predicted by GLEAMS. For PRE treatments, actual average losses were significantly lower than that predicted by GLEAMS, with measured losses falling below the bottom of the graph in 3 of 4 yr. These findings suggest that in certain parts of the Great Plains, FALL + PRE split applications of atrazine offer acceptably low atrazine runoff loss potential; EPP + PRE is more vulnerable to loss than FALL + PRE; and the GLEAMS model may overestimate atrazine runoff potential for PRE applications.

Extension and enhancement of national agricultural pesticide risk analysis (NAPRA) WWW decision support system to include nutrients

The nutrient component of the groundwater loading effects of agricultural management systems (GLEAMS) model was incorporated into the original national agricultural pesticide risk analysis (NAPRA) WWW system to create a nutrient loss decision support system to evaluate the effects of agricultural management systems on surface and subsurface nutrient water quality. The NAPRA WWW system ( http://pasture.ecn.purdue.edu/∼napra) was extended to the entire US by adding soil data and weather generator models with supporting input data for the continental US. Thus, the NAPRA WWW system can be run for any location in the US. The nutrient enabled NAPRA WWW system can be accessed from any location with a web browser, and it provides an easy to use interface for model users by simplifying model input preparations. The NAPRA WWW system can be used to identify appropriate nutrient application rates to meet water quality specifications such as total maximum daily loads, and to identify critical watersheds or areas from nutrient management perspectives.

Review of the validation of models used in Federal Insecticide, Fungicide, and Rodenticide Act Environmental exposure assessments

The first activity of the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) Environmental Model Validation Task Force, established to increase confidence in the use of environmental models used in regulatory assessments, was to review the literature information on validation of the pesticide root zone model (PRZM) and the groundwater loading effects of agricultural management systems (GLEAMS). This literature information indicates that these models generally predict the same or greater leaching than observed in actual field measurements, suggesting that these models are suitable for use in regulatory assessments. However, additional validation research conducted using the newest versions of the models would help improve confidence in runoff and leaching predictions because significant revisions have been made in models over the years, few of the literature studies focused on runoff losses, the number of studies having quantitative validation results is minimal, and modelers were aware of the field results in most of the literature studies. Areas for special consideration in conducting model validation research include improving the process for selecting input parameters, developing recommendations for performing calibration simulations, devising appropriate procedures for keeping results of field studies from modelers performing simulations to validate model predictions while providing access for calibration simulations, and developing quantitative statistical procedures for comparing model predictions with experimental results.

A decision support system for phosphorus management at a watershed scale.

Phosphorus (P) is one of the main nutrients controlling algal production in aquatic systems. Proper management of P in agricultural production systems can greatly enhance our ability to combat pollution of aquatic environments. To address this issue, a decision support system (DSS) consisting of the Maryland Phosphorus Index (PI), diagnosis expert system (ES), prescription ES, and a nonpoint-source pollution model, Ground Water Loading Effects of Agricultural Management Systems (GLEAMS), was developed and applied to an agricultural watershed in southern Sweden. This system can identify critical source areas (CSAs) regarding phosphorus losses within the watershed, make a diagnosis of probable causes, prescribe the most appropriate best management practices (BMPs), and test the environmental effects of the applied BMPs. The PI calculations identified small parts of the watershed as CSAs. Only 10.4% of the total watershed area in 1995 and 5.2% of the total watershed area in 1996 were classed as "high potential P movement." Four probable causes (high P level in soil, excessive P fertilization, stream proximity, and subsurface drainage) and three BMPs (riparian buffer strips, reduced P fertilizer application, and P fertilizer incorporation) were identified by a diagnosis and prescription expert system. The GLEAMS simulations conducted for one selected CSA field for a 24-yr period showed that the recommended BMP reduced runoff P losses by 55% and sediment P losses by 71%, if applied from the first year. Results showed that using DSS may enable us to select a proper BMP implementation strategy and to realize the beneficial effect of BMPs on a long-term basis.

Effect of soil variability, within and between soil taxonomic units, on simulated nitrate leaching under arable farming, New Zealand

A Monte Carlo approach was used to predict the effect of soil variability on nitrate leaching from 8 soil series, encompassing a wide range of drainage, texture, and age of soil development characteristics. A database of soil physical properties consisting of a minimum of 9 profiles per soil series was used to derive correlated probability distribution functions of key soil properties. The distribution functions were then used for random sampling to derive input soil-data for the GLEAMS (Groundwater Loading Effects of Agricultural Management Systems) simulation model. Variability in soil properties found within single soil taxonomic units (depth/stoniness phases of soil series) resulted in an appreciable range of predicted leaching of nitrate. Leaching from soils with greatest variability (generally shallow and stony phases) had an inter-quartile range of predicted leaching of up to 19 kg N/ha in 1992. Sensitivity analysis indicated that organic matter content, depth to the base of the upper 2 horizons, and available water storage were important drivers of variability within soil taxonomic units. Despite wide variation within soil taxonomic units, there were still clear differences between them. Effective soil depth accounted for most of this variance, which was attributed to differences in total profile available water storage. Soil drainage had some effect on risk of leaching. This effect would probably have been greater if water table effects had been accounted for. Soil series distinctions related to soil age had no significant effect of leaching risk. These results indicate that nitrogen leaching risk assessment using GLEAMS is dependent upon soil maps with accurate identification of soil depth/stoniness phases and organic matter content.

Review of the validation of models used in Federal Insecticide, Fungicide, and Rodenticide Act environmental exposure assessments.

The first activity of the Federal Insecticide. Fungicide, and Rodenticide Act (FIFRA) Environmental Model Validation Task Force, established to increase confidence in the use of environmental models used in regulatory assessments, was to review the literature information on validation of the pesticide root zone model (PRZM) and the groundwater loading effects of agricultural management systems (GLEAMS). This literature information indicates that these models generally predict the same or greater leaching than observed in actual field measurements, suggesting that these models are suitable for use in regulatory assessments. However, additional validation research conducted using the newest versions of the models would help improve confidence in runoff and leaching predictions because significant revisions have been made in models over the years, few of the literature studies focused on runoff losses, the number of studies having quantitative validation results is minimal, and modelers were aware of the field results in most of the literature studies. Areas for special consideration in conducting model validation research include improving the process for selecting input parameters, developing recommendations for performing calibration simulations, devising appropriate procedures for keeping results of field studies from modelers performing simulations to validate model predictions while providing access for calibration simulations, and developing quantitative statistical procedures for comparing model predictions with experimental results.