Open-File Report 95 156 

COLLECTION OF SHORT PAPERS ON THE 

BEAVER CREEK WATERSHED STUDY 

IN WEST TENNESSEE, 1989-94 

Prepared by the 

U.S. GEOLOGICAL SURVEY 
Organizations involved in assessment studies in the Beaver Creek area: 

U.S. Department of Agriculture, Natural Resources Conservation Service 

(formerly known as Soil Conservation Service) 

U.S. Department of the Interior, U.S. Geological Survey 

Tennessee Department of Agriculture 

Tennessee Department of Environment and Conservation 

Shelby County Conservation District 

University of Tennessee, Agricultural Extension Service 

Clemson University 

The University of Memphis 

Cover photograph. Loosahatchie River looking 

upstream at Highway 205 in the Beaver Creek 

watershed. 
COLLECTION OF SHORT PAPERS ON THE 

BEAVER CREEK WATERSHED STUDY 

IN WEST TENNESSEE, 1989-94 

Compiled by W. Harry Doyle, Jr., and Eva G. Baker 

U.S. GEOLOGICAL SURVEY 

Open-File Report 95-156 

Memphis, Tennessee 

1995 
U.S. DEPARTMENT OF THE INTERIOR 

BRUCE BABBITT, Secretary 

U.S. GEOLOGICAL SURVEY 

Gordon P. Eaton, Director 

Any use of trade, product, or firm name in this report is for identification 

purposes only and does not constitute endorsement by the U.S. 

Geological Survey. 

For additional information write to: Copies of this report may be purchased from: 

District Chief 

U.S. Geological Survey 

810 Broadway, Suite 500 

Nashville, Tennessee 37203 

U.S. Geological Survey 

Earth Science Information Center 

Open-File Reports Section 

Box 25286, MS 517 

Denver Federal Center 

Denver, Colorado 80225 
In 1989, the U.S. Geological Survey began a scientific investigation to evaluate the effect of 

agricultural activities on water quality and the effectiveness of agricultural best management practices in 

the Beaver Creek watershed, West Tennessee. The project is being conducted jointly with other Federal, 

State, County agencies, the farming community, and academic institutions, in support of the U.S. 

Department of Agriculture’s Hydrologic Unit Area program. 

The Beaver Creek project has evolved into a long-term watershed assessment and monitoring 

program. In 1991, a grant was received to develop and evaluate sampling strategies for higher order 

streams. During the summer of 1992, a reconnaissance of water-quality conditions for the shallow 

aquifers in Shelby, Tipton, Fayette, and Haywood Counties was conducted and included 89 domestic 

wells in the Beaver Creek watershed. Results from this effort lead to the development of a l-year 

program to evaluate cause-and-effect relations that can explain the observed water-quality conditions for 

the shallow aquifers in the watershed. In 1992 the USGS, in cooperation with the Soil Conservation 

Service and the Shelby County Soil Conservation District, began an evaluation of in-stream processes 

and in-stream resource-management systems. In 1993, a biomonitoring program was established in the 

watershed. 

This collection of articles and abstracts was originally published in the American Water Resources 

Association National Symposium on Water Quality Proceedings for the National conference held in 

Chicago in 1994. These articles address the optimimum sampling strategy for obtaining water-quality 

data in nonpoint-source pollution studies; provide an understanding of the fate and transport of 

agrichemicals in the surface runoff and the soil profile; demonstrate that the most significant waterquality problem in the watershed is the transport of sediment; support qualitative and quantitative 

statements of the effects agriculture has on water quality in the Beaver Creek watershed. The purpose of 

this report is to present the current (1994) results of these investigations in one document related to the 

Beaver Creek watershed. 

Preface ill 
CONTENTS 

Assessment of agricultural nonpoint-source pollution and best management practices 

for the Beaver Creek watershed, West Tennessee: an overview 

Roman-Mas, Angel, Stogner, Robert W., Sr., Doyle, W. Harry, Jr., and Klaine, Stephen J. . . . . . . 1 

Evaluation of biomonitoting techniques used in assessing agricultural nonpoint source 

pollution 

Byl,ThomasD.,andRoman-Mas,Angel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 

Transport and degradation of aldicarb in the soil profile: a comparison of conventional 

tillage and non-tillage 

Olsen, Lisa D., Roman-Mas, Angel, Weisskopf, Carol P., and Klaine, Stephen J. . . . . . . . . . . . .21 

Relation between nitrate concentrations and potential nitrate sources for water-table aquifers 

in the Beaver Creek watershed, West Tennessee: a statistical analysis 

Williams, Shannon, and Roman-Mas, Angel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33 

Fate and transport of nitrogen in an agricultural watershed 

Roman-Mas, A., Cochrane, H.H., Smink, J.A., and Klaine, S.J. . . . . . . . . . . . . . . . . . . . . . . . . .41 

Suspended-sediment yield and channel evolution in a small agriculturaJ catchment 

Stogner,RobertW.,Sr.,andDiehl,TimothyH. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 

Mechanistic evaluation of pesticide temporal patterns for a first-order stream 

Roman-Mas, Angel, Weisskopf, Cam1 I?, and Klaine, Stephen J. . . . . . . . . . . . -. . . . . . . . . . . .45 

Research and monitoring needs for the implementation of the USDA water quality HUA 

program: the Beaver Creek watershed project 

Hankin,HowardC.,andSmith,GeorgeF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .47 

Contents v 
ASSESSMENT OF AGRICULTURAL NONPOINT-SOURCE POLLUTION AND BEST 

MANAGEMENT PRACTICES FOR THE BEAVER CREEK WATERSHED, 

WEST TENNESSEE: AN OVERVIEW 

Angel Roman-Mas’, Robert W. Stogner, Sr.‘, 

W. Harry Doyle Jr.‘, and Stephen J. Klaine* 

ABSTRACT: In 1989, the U.S. Geological Survey began a long-term research project to evaluate the effect of 

agricultural activities on water quality and the effectiveness of agricultural best management practices in the 

Beaver Creek watershed, West Tennessee. The project is being conducted jointly with other Federal, State, and 

county agencies, the farming community, and academic institutions, in support of the U.S. Department of 

Agriculture Hydrologic Unit Area program. This paper presents a historical account of the project, a general 

description of the study area and the methods used for data collection and analyses, and a synopsis of the most 

significant project findings. 

KEY TERMS: Agriculture, nonpoint-source pollution; best management practices; water quality; ground water; 

surface water; soils. 

INTRODUCTION 

In 1989, efforts by the farming community in Tennessee facilitated a cooperative agreement between the 

U.S. Geological Survey (USGS) and the Tennessee Department of Agriculture (TDA) to evaluate agricultural 

nonpoint-source pollution and best management practices (BMP’s) in the Beaver Creek watershed, West 

Tennessee. An assessment conducted by the Tennessee Department of Environment and Conservation (TDEC) 

(formerly the Tennessee Department of Health and Environment, 1988) indicated that agricultural activities were 

the principal cause for water-quality degradation in this watershed. This paper presents a historical account of 

the project, a general description of the study area and the methods used for data collection and analyses, and 

a synopsis of the most significant project findings. 

For this study, a multidisciplinary, multiagency team of scientists from the USGS, Clemson University, 

University of Memphis, and the University of Tennessee Agricultural Extension Service (UTAES) was assembled. 

The team selected four small basins (less than 50 hectares each) to conduct deterministic (cause-and-effect 

relation) and mechanistic (processes and factors) evaluations of agricultural nonpoint-source pollution and BMP’s. 

A major component of this study was the evaluation of existing sampling methods for runoff and soils and the 

development of new methods as needed. 

In 1990, the Beaver Creek watershed was selected for the U.S. Department of Agriculture (USDA) 

Hydrologic Unit Area (I-IUA) program. The HUA program provides technical, financial, and educational 

assistance to farmers for the implementation of BMP’s. The following BMP’s were identified: (1) conservation 

tillage systems, (2) terrace systems, (3) conservation reserve program, (4) contour stripcropping, (5) diversions, 

(6) critical area treatment, (7) grass waterways, and (8) water and sediment control basins. 

‘Hydrologist, U.S. Geological Survey, 7777 Walnut Grove Rd., Suite LLB2, Memphis, Tennessee 38120. 

*Associate Professor, Department of Environmental Toxicology and The Institute of Wildlife and 

Environmental Toxicology, Clemson University, Pendleton, South Carolina, 29670-0709. 

1 
The Beaver Creek project has evolved into a long-term watershed research and monitoring program. In 

1991, a grant was received from the Water Environment Federation to develop and evaluate sampling strategies 

for higher order streams. During the summer of 1992, a reconnaissance of water-quality conditions for the 

shallow aquifers in Shelby, Tipton, Fayette, and Haywood Counties was conducted (Fielder and others, 1994). 

The reconnaissance, which was undertaken in cooperation with the TDA and the UTAES, included 89 domestic 

wells in the Beaver Creek watershed. Results from this effort lead to the development of a l-year program to 

evaluate cause-and-effect relations that can explain the observed water-quality conditions for the shallow aquifers 

in the watershed. The evaluation is being funded by the TDA, the TDEC, and the Shelby County Conservation 

District (SCCD). In 1992 the USGS, in cooperation with the Soil Conservation Service and the SCCD, began 

an evaluation of in-stream processes and in-stream resource-management systems. In 1993, a biomonitoring 

program was established in the watershed. 

Current project objectives include the: (1) evaluation of the extent that agricultural activities affect water 

quality and threaten environmental integrity in the Beaver Creek watershed, (2) evaluation of in-field and instream BMP’s, (3) development and evaluation of chemical and biological sampling strategies, (4) identification 

and quantification of processes and factors that control the degradation and transport of agricultural pollutants, 

and (5) evaluation of mathematical-mechanistic models. Results from the Beaver Creek watershed project can 

assist resource management agencies in developing strategies for use in their conservation programs. 

DESCRIPTION OF STUDY AREA 

The Beaver Creek watershed, located in Shelby, Tipton, Haywood, and Fayette Counties in southwest 

Tennessee (see Figure l), encompasses about 40,000 hectares (ha). The watershed lies within the Southern 

Mississippi Valley Silty Uplands major land resource area (U.S. Department of Agriculture, Soil Conservation 

Service, 1988). Two major physiographic regions, upland and bottomland, can be distinguished in the watershed. 

Agriculture is vital to the local economy. Cropland covers about 70 percent of the watershed; cotton, soybeans, 

and corn are the principal crops. Forests and range land occupy 10 and 20 percent of the watershed, respectively. 

Forest stands are primarily pole and small saw timber, reflecting extensive harvesting 40 to 60 years ago. All 

major tributaries in the Beaver Creek watershed were channel&d in the early to mid-1900’s to facilitate drainage. 

The mean annual rainfall is about 130 centimeters (cm); about 25 cm fall during the 180day growing 

season of April through September. The wettest month is April, with a mean rainfall of 14 cm, and the driest 

month is October, with a mean of 6 cm. Mean monthly temperatures range from 1 “C (January) to 27 “C (July) 

and the mean annual temperature is 16 “C. 

Geologically, the watershed is in the Mississippi embayment of the Gulf Coastal Plain physiographic 

province. Alluvium and fluvial deposits of Quaternary and Tertiary(?) age make up the shallow aquifer in the 

watershed (Parks, 1990; Parks and Carmichael, 1990a, 1990b). Alluvium, consisting of sand, gravel, silt, and 

clay, is present beneath the bottomland areas; fluvial deposits of sand , gravel, minor clay, and ferruginous 

sandstone are present beneath the loess in the uplands and valley slope areas (Parks, 1990; Parks and Carmichael, 

1990a, 1990b). Locally, the alluvium and fluvial deposits are underlain by the Cockfield Formation, Cook 

Mountain Formation, or the Memphis Sand of Tertiary age. The Cockfield Formation and the Memphis Sand 

consist of sand, silt, clay, and lignite and make up the Cockfield and Memphis aquifers (Parks, 1990; Parks and 

Carmichael, 1990a, 1990b). The Cook Mountain Formation, which consists primarily of clays, makes up the 

confining unit overlaying the Memphis aquifer. 

Soils in the watershed consist of well to poorly drained silt loam (U.S. Department of Agriculture, Soil 

Conservation Service, 1988). Three principal soil associations are present: Memphis-Loring, Granada-LoringMemphis, and Falaya-Waverly-Collins. The Falaya-Waverly-Collins soil association occurs in the bottomland 

areas whereas the other two soil associations are typically in upland areas. The soils are acidic with pH ranging 

from 5.1 to 5.5 units. 

2 
39 31 TENNESSEE 

35O 18 

89” 46’ 89 27’ 

I I 

EXFUNATION 

5V MONITORINGSITEi AND 

MAPNUMBER 

-.-WATERSHED BOUNDARY 

I 

igital data from the l;lOO,OOO National 

apping Diviian Universal Transverse 

ercator projection. Projected In 

tats Plane 1927 North American datum 

I 

Figure 1. Location of the Beaver Creek watershed study area and surface-water monitoring sites. 

RESEARCH AND MONITORING ACTIVITIES 

For the Beaver Creek watershed project, a watershed-based risk assessment approach was adopted to 

design the research and monitoring activities. The following steps were taken as part of this approach: 

(1) Identification of the natural resources and their specificfunctions: For the Beaver Creek project, this task 

was conducted by the SCS in support of the HUA program. Soils and water quality were the identified 

resources. Specific functions of these resources are production agriculture, fish and wildlife, aquatic 

recreation activities, irrigation, and livestock. 

(2) Identification of stressors: This step refers to anthropogenic activities that can degrade the resources or 

impair specific functions identified in step 1. Row-crop production (cotton, soybean, corn), cattle (range 

land), and channelization were identified as potential stressors. 

(3) Assessment of physiographic variations: The watershed-based risk assessment approach requires 

identification of the range of physiographic settings that can produce different resource-stressor or 

function-stressor responses. For instance, in the Beaver Creek watershed, cotton and soybeans are 

cultivated iqupland and bottomland areas. Therefore, the evaluation of cotton and soybean crops as a 

potential stressor must include experimental fields located in both these areas. 

3 
(4) Evaluation of BMP’s: The evaluation of BMP’s adds another dimension to the monitoring program. Pairedbasins analysis, which is the preferred technique to evaluate BMP’s, required two monitoring sites for 

every resource-stressor response identified in a given physiographic setting. The upstream-downstream 

approach also requires two monitoring sites for every resource-stressor response to be studied. In this 

approach, data from a site downstream from the area where the BMP’s have been implemented are 

compared to data collected at a site upstream from the BMP area. Trend analysis is the third and most 

common approach for evaluating BMP’s. In this approach, pre- and post-BMP’s implementation data are 

collected and compared. This approach typically includes one monitoring site at the downstream end of 

the area where the BMP’s are implemented. In some instances, monitoring sites upstream and 

downstream of the BMP implementation area are needed to isolate the area’s contribution to water-quality 

conditions. 

(5) Selection of monitoring sites: The number of sites to be monitored is based on the number of resourcestressors identified in the watershed and the BMP’s to be evaluated. In the Beaver Creek watershed, 

row-crop agriculture and channelization were determined to be the most important stressors to soils and 

water resources in the watershed, and non-tillage and riparian zone restoration were the most important 

BMP’s. The scale of the monitoring sites is dictated by the type of investigation being conducted. 

Whereas occurrence and distribution studies can be conducted in relatively large-scale systems, 

mechanistic and deterministic evaluations typically require small-scale systems. Both types of evaluation 

are required to fulfill the Beaver Creek project objectives. 

(6) Data collection: Any biases imposed by the data-collection methods must be recognized and quantified. 

Sensitivity analyses, in which the magnitude of response of a parameter is evaluated relative to changes 

in other parameters, are necessary to develop, evaluate, and modify data-collection methods. 

(7) Modeling: Modeling efforts should provide resource managers with tools (1) to simulate field- and 

watershed-level processes related to specific stressor-resource response and (2) to extend information 

gained in bench-mark studies to other areas. Models can range in approach from synoptic, which provide 

a broad overview of the resource-stressor response with minimum data, to mathematical-mechanistic, 

which attempt a full differentiation of the processes and factors controlling the resource-stressor response. 

Surface Water 

Twelve surface-water monitoring sites have been established in the watershed (see Figure 1). Climatic, 

hydrologic, chemical, biological, and geomorphological (channel evolution) data collected at these sites are being 

used in paired-basin analyses, upstream-downstream comparisons, and trend analyses (see Table 1). 

Streamflow Stations and Measurements 

Each surface-water monitoring site includes a stream-gaging station to measure discharge. The stations 

were constructed and are being operated according to standard USGS procedures. Drainage boundaries for each 

station were determined and the drainage areas computed. Topographic maps for each basin were developed from 

7.5minute quadrangle topographic maps or from field surveys. A detailed inventory of farm activities is being 

maintained. 

Each station was outfitted with a pressure sensor or a stilling well and an automated recorder programmed 

to record stream elevation (stage) at variable time intervals according to the rate of change in stage. Continuous 

discharge records were developed from the stage data following standard USGS methods (Kennedy, 1983). At 

selected monitoring sites (see Figure 1, sites 1, 8, 9, and 10) automated rain gages were installed. 

Unit hydrograph analysis and water budgets are being used to evaluate the hydrologic response of the 

basins. It is reasonable to expect that changes in the hydrologic response of the basins would be observed if the 

implementation of BMP’s are effective. Increases in infiltration rates and evapotranspiration and associated 

decreases in runoff to rainfall ratio, basin response time, and peak discharge are expected to result from the 

implementation of BMP’s. 

4 
Table 1. Location, data collection, physiographic and agricultural information for surface-water monitoring stations in the 

Beaver Creek watershed, Tennessee 

[hyd, hydrological; cli, climatic; chm, chemical; bio, biological; geo, gemorphological; ‘, estimated from topographic maps] 

Map Data Being Type of Evaluation 

Number Collected Being Conducted 

Drainage Area Under 

Areas Cultivation 

(hectares) (percent) Crop(s) Physiography 

l-2 

3-4 

54 

7 

8 

9 

10 

11-12 

hyd, cli. 

chm. bio. 

and gw 

1. Upstream/down-stream, 

in-stream processes, and 

resources management 

2. Sampling protocols 

hyd. cli, 1. Pa&d-basins, 

chm, and conventionally tilled 

@= versus non-tilled cotton 

hyd. cli, 

chm, and 

bio 

1. Upstream/downstream, constructed 

wetland 

hyd. cli, 

chm. and 

PJ 

1. Trend analyses 

2. Sampling protocols 

hyd. cli. 

chm, and gw 

hyd, cli, 

chm. and gw 

hyd, cli, 

chm. and gw 

hyd, cli, 

chm. bio, 

and gw 

1. Trend analyses 

2. Sampling protocols 

1. Trend analyses 

2. Sampling protocols 

1. Trend analyses 

2. Sampling protocols 

1. Paired basin, 

channelized versus 

non-channel&d 

2. Sampling protocols 

171-258 95-95 Bottomland 

soybean 

6.88-6.93 loo-loo Bottomland 

0.4 (wetland)- o- Soybean 

28 (cropland) 100 corn 

Bottomland 

12.W 65 Upland and 

bottomland 

44 loo Soybeans Upland 

26 80 Soybeans Upland 

11 

1,2151,135’ 

100 

70-70 

Cotton Upland 

Cotton 

soybeans 

Upland 

Water Quality 

Surface-water samples for the determination of nitrogen and phosphorous species, organic carbon, 

suspended sediment, and selected pesticides and their metabolites are being collected during stormflow and baseflow conditions. Two automated samplers were installed at each station to aid in the sample collection. 

Approximately 20 rainfall-runoff events are monitored annually. During stormflow, water samples are collected 

at an interval equal to 5 percent of the total stormflow duration. During base-flow, water samples are collected 

every 15 minutes for the first 3 hours after stormflow and every hour thereafter until the end of the event or the 

beginning of a new event. 

Annual and seasonal concentration-frequency curves (percent of the time that a particular concentration 

is exceeded during a given period of time) are being developed for each basin. Loads for annual, seasonal, and 

individual rainfall-runoff events are being computed. Statistical analyses will be used to determine if the variance 

in concentration-frequency curves and loads could be attributed to the implementation of BMP’s. In addition, 

changes in chemical speciation and the phase (suspended or dissolved) in which the constituents occur are being 

evaluated. 

5 
Coarse particulate organic matter (CPOM) in surface water is being sampled by diverting approximately 

8 percent of the total flow into a collection net. Trapped CPOM is collected, placed in a labeled plastic bag, and 

transported to the laboratory after each storm event. CPOM samples are being analyzed for particle size and for 

nitrogen, phosphorous, and pesticide content. Differences in the physical, chemical, and biological characteristics 

of the CPOM that determine its suitability as a food source for organisms downstream are also being evaluated. 

Mathematical models that can simulate runoff and constituent transport at the field and watershed levels 

[for example, AGNPS (Young and others, 1991) and HSPF (Donigian, 1991)] will be calibrated and applied to 

the basin being monitored. A detailed evaluation of the mathematical algorithms used in these models will be 

conducted and modified as needed. Only those models that attempt a full differentiation of the processes and 

factors controlling the degradation and transport of agricultural chemicals are being considered. 

Benthic macroinvertebrate data are being collected at selected sites in the Beaver Creek watershed (see 

Figure 1 and Table 1). The primary goal of the biomonitoring program is to evaluate and develop, as needed, 

biological sampling methods for streams in the watershed. Various methods are currently being studied. In 

addition, structural and functional indices are being used to evaluate water-quality conditions and environmental 

integrity. 

In-Stream Processes 

Modifications to the drainage network to improve drainage and control floods have altered the hydrologic 

regime of streams and marginal ecosystems (such as wetlands) in the Beaver Creek watershed. The preservation 

of biological and non-biological functions (for example, habitat and water quality, respectively) performed by 

streams and marginal ecosystems is central to the development of environmentally sound agriculture in the 

watershed. Quantitative understanding of these functions and the extent to which they have been impaired by 

drainage modifications is needed before in-stream resource-management systems can be developed and 

implemented. 

Although little information is available on the natural drainage system in the bottomlands of the Beaver 

Creek watershed, the system was likely dominated by forested riverine wetlands. Flooding conditions of the 

bottomlands hampered their exploitation for timber and agriculture and lead local landowners to seek engineering 

solutions to drainage problems (Ashley, 1910). Channelization has been the most common engineering practice 

used in the watershed. 

The Upper Middle Beaver Creek Canal subwatershed (see Figure 1, monitoring site 12) represented a 

typical example of a channelized condition. In contrast, the Baxter Bottom subwatershed at monitoring site 11 

(see Figure 1) has not been channelized. A 250-ha forested riverine wetland is part of the Baxter Bottom 

subwatershed drainage network. This condition likely resembles natural drainage conditions for bottomlands in 

the Beaver Creek watershed. The two subwatersheds are of comparable size, slope, and land use. In 1993, a 

paired-basin study was started to document differences in water quality between the two subwatersheds and to 

identify and quantify biological, geochemical, and geomorphological processes responsible for the observed 

differences in water quality. 

Constructed Wetlands 

Wetlands can immobilize and metabolize chemical constituents through a complex network of physical, 

chemical, and biological processes and thereby improve water quality at their downstream ends. Constructed 

wetlands have been proposed as an off-site BMP for the treatment of cropland runoff because in many instances 

the transport of agricultural chemicals in runoff cannot be controlled in the field. Constructed wetlands have been 

successfully used to treat domestic and animal wastewater (Watson and others, 1989). 

6 
The design parameters used in constructed wetlands for the treatment of wastewater are typically 

determined by reaction kinetics (Kadlec, 1989; Watson and others, 1989). These parameters. are unsuitable for 

designing wetlands to be used for treating cropland runoff because of the extreme temporal variations in flow and 

constituent concentrations, the chemical speciation of the constituents, and the unknown reaction mechanisms and 

rates for these chemical species in wetland environments. 

In 1993, a 0.4-ha single-cell herbaceous wetland was constructed in the Beaver Creek watershed. Its 

purposes are to (1) evaluate the effectiveness of the wetland in assimilating or modifying the nutrient and pesticide 

content in cropland runoff; (2) identify and quantify the relevant processes responsible for the immobilization and 

metabolization of selected constituents within the wetland; and (3) develop design criteria for constructed wetlands 

to be used for treating cropland runoff. 

Stream-gaging and water-quality monitoring stations were established upstream and downstream of the 

wetland (see Figure 1, monitoring sites 5 and 6). Water samples are being collected and analyzed for the 

determination of total and dissolved nitrogen and phosphorous species, organic carbon, selected pesticides and 

their metabolites, and suspended-sediment concentration. Changes with time in the concentration of these 

constituents, chemical speciation, and loads at the upstream and downstream sampling stations are being 

compared. Biological samples are being collected within the wetland for the determination of succession patterns 

in the benthic macroinvertebrate and the plant communities. 

Soils 

Non-tillage has been effectively used to reduce soil erosion. However, researchers have suggested that 

non-tillage can enhance chemical transport through the soil zone and increase the potential for ground-water 

contamination (Dick and others, 1989; Hall and others, 1989). Resource management agencies in the Beaver 

Creek watershed, which has soils that are highly susceptible to erosion, have recommended non-tillage as a BMP. 

The potential for ground-water contamination associated with the implementation of non-tillage in the watershed 

needs to be addressed before non-tillage is widely adopted. 

Since 1990, a series of experiments have been conducted to (1) develop a sampling strategy that accurately 

characterizes the spatial and temporal distribution of agricultural chemicals in the soil profile, (2) evaluate the 

transport and degradation of agricultural chemicals in the soil profile, (3) compare the behavior of agricultural 

chemicals in conventionally tilled and non-tilled cotton fields, and (4) evaluate solute transport models such as 

CMLS (Nofiiger and Homsby, 1987), MOUSE (Steenhuis and others, 1987), PRZM (Carsel and others, 1985), 

GLEAMS (Leonard and others, 1987), and LEACHMP (Wagenet and Hutson, 1987). 

Ground-Water Quality 

As in many rural areas in the United States, residents in the Beaver Creek watershed rely on domestic 

wells for their primary source of water. Residents share a growing concern that agricultural activities could be 

affecting the quality of ground water in the watershed. 

Water-quality, well-construction, and land-use data for 89 domestic wells (See Figure 2) completed within 

the shallow aquifers in the Beaver Creek watershed were used to statistically relate water-quality conditions to 

land-use activities. The data are part of a ground-water-quality reconnaissance conducted during the summer of 

1992 for the shallow aquifers in Shelby, Tipton, Fayette, and Haywood Counties (Fielder and others, 1994). 

Non-parametric statistical methods were used to determine the extent to which land use affects the occurrence and 

distribution of nitrate within the water-table aquifer in the Beaver Creek watershed. 

7 
35Ol9 I, 

Digital data from thq l;lOO.OOO National 

Mapping DiWon Universal Transverse 

Mercator projection. Projected in 

State Plane 1927 North American datum 

EXPLANATION 

l SAMPLED WELL 

-.- WATERSHED BOUNDARY 

D 

Figure 2. Location of sampled wells in the Beaver Creek watershed, 1992. 

In 1993, a ground-water-quality network was established in the watershed. The network includes about 

100 shallow wells that are sampled 5 times a year. Water samples are being analyzed for major constituents, 

nutrients, fecal bacteria, and selected pesticides. The water-quality data being collected will allow further 

investigation of cause-and-effect relations controlling the occurrence of pollutants in the shallow aquifers. 

SIGNIFICANT FINDINGS 

The following is a synopsis of the project’s most significant findings. 

(1) An optimal sampling strategy for the temporal characterization of chemicals and suspended sediment in 

agricultural runoff includes frequent sampling during stormflow and less frequent sampling during 

recession or base flow. Sensitivity analyses showed that a sampling interval equal to 5 percent of the 

stormflow duration is required during stormflow. For recession or base flow, a calibrated regression can 

supplement a limited number of concentration measurements. 

(2) Soil-sampling transects perpendicular to the orientation of the rows provided adequate spatial representation 

to conduct statistical analyses and compute reliable field averages for the concentration of agricultural 

chemicals in soils. 

8 
(3) Surface-catalyzed reactions appear to be an important mechanism for the degradation of aldicarb metabolites 

in the soil profile. The calculated half-lives of aldicarb metabolites were an order of magnitude shorter 

than those computed from laboratory experiments in which surface-catalyzed reactions were absent. 

(4) Horizontal transport within the soil profile was negligible for the conventionally tilled and the non-tilled 

fields. 

(5) Observed patterns in the concentration of aldicarb and its metabolites in runoff are consistent with the 

convective-diffusion limited transfer concept and inconsistent with the instantaneous-equilibrium concept 

used in lumped-parameter models. 

(6) Sediment transport resulting from soil erosion was identified as the major water-quality problem in the 

watershed. Computed suspended-sediment loads for these basins exceeded 30 metric tons per ha. 

(7) Crop residue at different stages of decomposition accounted for about 80 percent of the total nitrogen 

exported from crop fields. The chemical speciation and the temporal distribution of nitrogen exported 

from these basins could not be directly related to fertilizer application. 

(8) Background nitrate concentrations in water from the shallow aquifers have increased as a result of fertilizer 

application in the watershed. Significantly higher nitrate concentrations were measured in water from 

wells near septic tanks and confined animal facilities. 

(9) Community structure indices for benthic macroinvertebrates varied greatly depending on the sampling 

techniques used. Potential biases resulting from the sampling technique can be reduced by using multiple 

sampling techniques. 

REFERENCES 

Ashley, G. H., 1910. Drainage problems in Tennessee. Tennessee. State Geological Survey Bulletin 3-A, pp. l-15. 

Carsel, R. F., L. A. Mulkey, M. N. Lorber and L. B. Baskin, 1985. The Pesticide Root Zone Model (PRZM): Procedure 

for Evaluating Pesticide Leaching Threats to Groundwater. Ecological Modelling 30:49-69. 

Dick, W. A., R. J. Roseberg, E. L. McCoy and W. M. Edwards, 1989. Surface Hydrological Response of Soils to Notillage. Soil Science Society of America Journal 53: 1520-1526. 

Donigian, A. S., Jr., 1984. Application Guide for Hydrological Simulation Program--Fortran (HSPF). U.S. Environmental 

Protection Agency, Environmental Research Laboratory, Athens, GA, EPA/600/63/83/065. 

Fielder, A. M., A. Roman-Mas and M. W. Bennett, 1994. Reconnaissance of Ground-Water Quality at Selected Wells in 

the Beaver Creek Watershed, Shelby, Fayette, Tipton, and Haywood Counties, West Tennessee, July and August 

1992. U.S. Geological Survey Open-File Report 93-366, 28 pp. 

Hall, J. K., M. R. Murray and N. L. Hartwig, 1989. Herbicide Leaching and Distribution in Tilled and Untilled Soil. 

Journal of Environmental Quality 218:439-445. 

Kadlec, R. H., 1989. Hydrologic Factors in Wetland Water Treatment, in Hammer, D. A., ed., Constructed Wetlands for 

Wastewater Treatment: Municipal, Industrial, and Agricultural. Lewis Publishers, Chelsea, MI, pp. 21-40. 

Kennedy, E. G., 1983. Computation of Continuous Records of Streamflow. U.S. Geological Survey Techniques of WaterResources Investigations, Book 3, chapter A13, 53 pp. 

Leonard, R. A., W. G. Knisel and D. A. Still, 1987. GLEAMS: Ground-Water Loading Effects of Agricultural Management Systems. Transactions of the American Society of Agricultural Engineers 30:1403-1418. 

Nofxiger, D. L. and A. G. Homsby, 1987. Chemical Movement in Layered Soils: User’s Manual. Florida Cooperative 

Extension Services, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, Circular 

780, 44 pp. 

Parks, W. S., 1990. Hydrogeology and Preliminary Assessment of the Potential for Contamination of the Memphis Aquifer 

in the Memphis Area, Tennessee. U.S. Geological Survey Water-Resources Investigations Report 904092, 39 pp. 

Parks, W. S. and J. K. Carmichael, 1990a. Geology and Ground-Water Resources of the Cockfield Formation in Western 

Tennessee. U.S. Geological Survey Water-Resources Investigations Report 884181, 17 pp. 

Parks, W. S. and J. K. Carmichael, 1990b. Geology and Ground-Water Resources of the Memphis Sand in Western Tennessee. U.S. Geological Survey Water-Resources Investigations Report 88-4182, 30 pp. 

Steenhuis, T. S., S. Pacenka and K. S. Porter, 1987. MOUSE: A Management Model for Evaluating Groundwater Contamination from Diffuse Surface Sources Aided by Computer Graphics. Applied Agricultural Research 2277-289. 

Tennessee Department of Health and Environment, 1988. Status of Water Quality in Tennessee. Tennessee Department of 

Health and Environment, Division of Water Management, Nashville, TN., 156 pp. 

9 
U.S. Department of Agriculture, Soil Conservation Service, 1988. Drainage Basin Plan-Environmental Assessment, Beaver 

Creek Drainage Basin, Tennessee. lU.S.1 Department of Agriculture, Soil Conservation Service, Nashville, TN, 

74 PP. 

Wagenet, R. J. and J. L. Hutson, 1987. LEACHMP, Leaching Estimation and Chemistry Model. Center for Environmental 

Research, Cornell University, Ithaca, NY, 50 pp. 

Watson, J. T., S. C. Reed, R. H. Kadlec, R. L. Knight and A. E. Whitehouse, 1989. Performance Expectations and Loading Rates for Constructed Wetlands, in Hammer, D. A., ed., Constructed Wetlands for Wastewater Treatment: 

Municipal, Industrial, and Agricultural. Lewis publishers, Chelsea, MI, pp. 319-350. 

Young, R. A., C. A. G&ad, D. D. Bosch and W.P. Anderson, 1991. Agricultural Non-Point Source Pollution Model, 

User’s Guide, version 3.65. U.S. Department of Agriculhm, Agriculhm Research Services, Morris, Minn~h 

57 PP. 

10 
EVALUATION OF BIOMONITORING TECHNIQUES USED IN ASSESSING 

AGRICULTURAL NONPOINT SOURCE POLLUTION 

Thomas D. Byll and Angel Roman-Mas2 

ABSTRACT: A biomonitoring program was established in the Beaver Creek 

Hydrologic Unit Area, West Tennessee in 1993, as part of an ongoing 

comprehensive water quality assessment program. A primary goal of the 

biomonitoring project was to evaluate and develop biomonitoring 

protocols appropriate for first- and second-order streams in the Beaver 

Creek watershed. The biomonitoring techniques examined included 

benthic community structure, colonization of multiplate samplers and 

plant debris packs, and decomposition of the plant material. Results 

varied greatly between biomonitoring techniques at the same sites. The 

multiplate samplers generally had the lowest number of organisms and 

the smallest values for diversity. The plant debris packs and the 

benthic community structure techniques both provided high numbers for 

abundance and diversity, but under different conditions. The plant 

debris packs had a greater total number for abundance in the open 

streams than the shaded streams, whereas the benthic community 

structure-technique had higher numbers for abundance in the shaded 

streams than the open streams. These trends demonstrate a bias in the 

sampling techniques that should be considered when designing a 

biomonitoring project. Biases could be minimized by applying more than 

one biological collection technique to the same site. 

KEY TERMS: Biomonitoring; channelized streams; macroinvertebrate; 

agriculture. 

INTRODUCTION 

Increased concern for water quality has resulted in the escalated 

use of biomonitoring to determine the impact of non-point pollution 

derived from agricultural activities, a major contributor of pollution 

in the USA (USEPA, 1989; USEPA, 1992). Biomonitoring is a technique 

that utilizes the natural biological community in the ecosystem to 

assess the impact of environmental stress. If a pollution problem 

exists, one expects to find a corresponding adverse effect on the 

aquatic biological community. The ecosystem can also be modified by 

human-induced channelization of streams, as has been done in many of 

the riverine systems in the southeast and southwest. The hydrologic 

and geomorphic modifications resulting from channelization can affect 

the biological community as much as pollution can (Cooper, 1993). 

Thus, aquatic biomonitoring techniques that were developed for study of 

natural settings must be validated and adapted before they are applied 

to these modified aquatic systems. Several biomonitoring techniques 

were evaluated to determine their effectiveness for assessing water 

quality in a modified stream of West Tennessee. 

1Research Biologist, U.S. Geological Survey, Water Resources Division, 

810 Broadway, Suite 500, Nashville, TN 37203 

2ResearchHydrologist, U.S. Geological Survey, Water Resources Division, 

7777 Walnut Grove, Suite LLBZ, Memphis, TN 38120 

11 
The site selected for study was the Beaver Creek Watershed (BCW), 

located in the West Tennessee section of the Mississippi embayment. It 

is an area intensively farmed with row crops of cotton, soybean, winter 

wheat and corn. Soils in the BCW are predominately alluvial silt 

deposits in the bottomlands and loess deposits in the uplands. 

Recently, (1989-present) conservation practices have been initiated by 

the farming community, in connection with the US Department of 

Agriculture, to reduce the impact of agricultural activities on water 

quality. 

The main Beaver Creek channel and most of the tributaries were 

channelized in the early to mid-1900's to facilitate the drainage of 

land. Channelization has resulted in increased hydrologic responses 

such as rapidly rising water levels and increased stream velocity 

during rain events. In 1990, the U.S. Geological Survey initiated a 

water-quality monitoring research program. The program included 

collection and evaluation of water chemistry, stream hydrology and 

geomorphology data. Biomonitoring was added as a fourth parameter in 

early 1993 as part of this comprehensive project. 

The modified hydrology and geomorphology of the BCW brought the 

applicability of established toxicity bioassessment protocols under 

question. It was unclear how the modified geomorphology and hydrology 

would affect the collection and interpretation of biomonitoring data 

with regard to chemical disturbance. Other ecological factors had to 

be considered as well, such as species distribution patterns in the 

different stream orders, geographic location of the watershed, 

seasonality and natural habitat. Thus, study were: (1) to evaluate and 

develop biomonitoring protocols appropriate for modified streams such 

as those in the BCW, (2) determine if the effects of chemical 

perturbation could be distinguished from hydrologic and geomorphic 

disturbances, and (3) characterize the general structure and function 

of a first-second order channelized stream in the BCW. This paper 

presents the results to the first objective and preliminary results of 

objective number 3. 

METHODS AND MATERIALS 

Macroinvertebrates ("organisms that are retained by a Standard #30 

sieve [600 urn meshIV') were selected as the indicator organisms because 

considerable research has demonstrated that they are excellent 

biological indicators of water quality (Klemm, et. al., 1990; Plafkin, 

et. al., 1989; Rosenberg and Resh, 1993). Benthic macroinvertebrates 

were collected with scoops and sieves during two reconnaissance trips 

through the basin. This was done to obtain a general census of the 

species distribution pattern in the basin. The difference in biological 

community structure between upstream and downstream sites indicated 

that if any correlation was to be made between macroinvertebrate 

response and chemical exposure, initial efforts should focus on a first 

and second order tributary. Therefore, the main monitoring sites were 

selected in a well characterized, channelized, first-second order 

tributary, draining a 300 hectare cotton and soybean field. The stream 

had intermittent riffles with perennial pools. 

Sampling sites were chosen in this tributary to reflect unique 

riparian conditions. The riparian features represented were herbaceous 

bank vegetation and woody bank vegetation. The herbaceous and woody 

reaches of stream were each approximately 1 kilometer long and straight 

due to channelization. All the data reported herein were collected in 

12 
the pools of the tributary because flow in the riffle sections reduced 

to a trickle during the dry season. General site characteristics of 

the herbaceous and woody riparian stream segments are shown in Table 1. 

TABLE 1. Site characteristics observed during June through September. 

[HRV, herbaceous riparian vegetation; WRV, woody riparian vegetation; 

FFB, forest flood basin; WR, wetland reference site. 

Site 

Characteristics HRV WRV FFB WR 

Lentic (ponded) water perennial perennial perennial perennial 

Lotic (flowing) water seasonal seasonal 

2732 

perennial 

Temperature ("C) range 27-34 24-30 25-30 

pH range 7.5-9.2 7.0-8.1 7.0-9-o 7.5-8.2 

Width (meters) range 0.8-2.0 1.2-2.0 0.5-4.0 1.3-2.5 

Depth (meters) range 0.1-0.5 0.1-0.7 . 05-0.3 O-2-0.7 

Periphyton (% coverage) 95 35 45 70 

Woody debris in water no intermittent yes yes 

Emersent acuatic plants ves no no yes 

We were unsusccessful at locating a nonchannelized reference site 

with a similar hydrologic regime (flowing water during the wet season, 

and ponded water during the dry season) in the same watershed, so two 

reference sites were selected to represent these hydrologic conditions. 

The first reference site was in a flooded forest basin adjacent to the 

cotton field. This non-channelized site was annually inundated with 5 

to 30 cm of ponded (lentic) water. The second reference site was 

located in another branch of Beaver Creek just downstream from a 

natural, hardwood, bottomland wetland and series of beaver ponds. This 

site was in a small third order stream with perennial flowing (lotic) 

water. The characteristics of the two non-channelized reference sites 

also are listed in Table 1. 

Standard U.S. Environmental Protection Agency (EPA) biomonitoring 

protocols were reviewed and procedures were selected based on 

adaptability to the BCW system. Two conventional biomonitoring 

techniques, colonization of multiplate samplers and composition of the 

benthic macroinvertebrate community, were chosen from the EPA standard 

protocols (Klemm, et. al., 1990; Plafkin, et. al., 1989). The first 

procedure surveys the macroinvertebrates that colonize a Masonite, 

multiplate sampler placed in the water column and harvested after a set 

incubation time. This method has been standardized and comparisons are 

often made between studies in the literature (Rosenberg and Resh, 

1993). The second method quantifies the macroinvertebrates that 

inhabit the top few inches of the stream bottom (LaPoint and Fairchild, 

1992). Both methods are considered semi-quantitative because the 

number of organisms within a sampling area are counted. Three 

replicate samples per location (e.g., three multiplate samplers) were 

collected on each sampling date. 

A less conventional biomonitoring method was also examined. The 

technique used natural material, such as leaf and cotton plant debris, 

as a substrate for colonization. The application of leaf packs as an 

indicator of biological integrity has been explored by other 

investigators (Elder and Cairns, 1982; Paul et al., 1978). The data 

gathered in those studies provided information on the function (i.e., 

biogeochemical processes) of the waterway. The present study modified 

and adapted the leaf-pack methods to include structure (e.g., quantify 

macroinvertebrate colonization) and function (e.g., rate of plant 

13 
debris decomoosition). It was assumed leaf or cotton packs provided a 

better replication of substrates occurring in these streams for 

macroinvertebrate colonization than the artificial substratemultiplate samplers. The leaf materials were collected in early winter 

from an adjacent bottomland forest, dried and sorted by genus. The 

composition of the leaves, dry weight (in grams), and percent of sample 

per bag were: oak 7.5 (50%), willow 2 (13%), hickory I.5 (lo%), sweet 

gum 1 (6.6%), silver maple 1 (6.6%), cottonwood 1 (6.6%) and dogwood 1 

(6.6%). Cotton stems and bolls ("cotton debris") were also collected, 

dried, weighed, and placed in similar mesh bags. Cotton was selected 

because it is a primary crop in the Beaver Creek basin and large 

quantities of debris have been reported to wash into receiving streams 

after harvest during intense rain events. 

The plant material was dried in an oven at 70°C until the decrease 

in dry weight stopped (about 1 week). Predetermined dry weights of 

plant material (15.0 g leaves, 35 g cotton) were placed in labelled l-.6 

mm mesh bags of 10 by 10 cm size. The bags were closed and tied off to 

2-ft stakes with nylon string. They were installed in late April 1993 

at the same time as the multiplate samplers. Replicate samples were 

retrieved in early June, early July and early September. The contents 

of the bags were emptied into plastic tubs and the macroinvertebrates 

were sorted out, identified, quantified and preserved for identity 

confirmation. The plant material was gently cleaned with deionized 

water and dried in an oven at 70°C until dry. The resulting weight was 

recorded and the change in weight was calculated for each bag of plant 

material. 

Biological samples were collected 6, 12 and 18 weeks after the 

substrates were placed in the field. The substrate samplers were 

enclosed with zip-lock plastic bags and placed on ice until the 

organisms could be harvested, taken to the laboratory, and preserved in 

70% alcohol. The benthic sediment samples were collected using a long 

handled shovel with a special steel scoop, 8 inches across, 10 inches 

long and having 2 inch sides. The collected sediment was sifted in the 

field and the macroinvertebrates were preserved in 70% alcohol, brought 

to the laboratory and identified to Family. Surface-water samples were 

collected every 5 minutes during storm flow at the water-chemistry 

sampling station separating the herbaceous and woody riparian zones. 

These samples were analyzed for pesticides, nitrogen and sediment load. 

Preliminary results of the chemical analyses indicate that pesticides 

were not a problem during this study period. Additional field 

measurements were made every 2 to 3 weeks during the study period to 

monitor low-flow conditions of water depth, pH, temperature, and 

dissolved oxygen. Aquatic plant and animal species observations were 

also recorded at this time. Many of these organisms represent sentinel 

indicator species analogous to macroinvertebrates (Table 1). 

Data observed or calculated for this study included abundance 

(total number of organisms), taxonomic richness (number of Families), 

mean diversity of taxon (Shannon-Weaver mean diversity, Klemm, et al., 

1990) and Beck's biotic index (Beck, 1955; Terre11 and Perfetti, 1989; 

Resh and Jackson, 1993). The data are reported on a temporal and 

spatial comparison, and the average change in dry weight of replicate 

leaf and cotton debris packs are reported as a function of time. 

Standard deviations for the Beck biotic index are reported. 

14 
RESULTS 

Community structure estimated by the abundance of macroinvertebrates at each location and sampling date is depicted by the height of 

the bars in Figure la-lc. Abundance is the total number of organisms 

counted per 3 replicate samples at each site. The overall abundance of 

organisms collected increased over the duration of the study (from 1259 

in June, to 1498 in July and 1651 in September). The multiplate 

samplers generally had the lowest abundance of the four sampling 

methods tested. The cotton packs located in the herbaceous riparian 

vegetation streams always provided the greatest abundance on each 

sampling date. However, cotton packs located at the other sampling 

locations did not have the same trend. Benthic community sampling 

appeared to be the most consistent sampling technique with regard to 

abundance at each location or time. 

TABLE 2. Richness, abundance, and mean diversity of sampling method. 

[HRV, herbaceous riparian vegetation; WRV, woody-riparian vegetation; 

FFB, forest flood basin; WR, wetland reference site; MPS, multiplate 

sampler; BCC, benthic community composition; LP, leaf pack; CP, 

cotton pack; R, richness, number of Families; Ab, abundance, sum 

total; MD, mean diversity; ---, no data collected] 

MPS BCC LP CP 

Site R Ab MD R Ab MD RAbMD R Ab MD 

June 

HRV 3 8 1.36 7 144 2.49 8 151 1.36 7 329 0.87 

WRV 4 39 1.52 6 192 1.95 6 35 2.10 5 39 2.55 

FFB ------ ------ 7 56 2.09 9 161 1.77 WR ------ 5 105 1.73 ------ ------ 

July 

HRV 5 195 1.75 10 145 3.73 9 194 2.50 9 258 2.57 

WRV 5 45 1.92 8 216 2.46 5 116 1.58 6 100 2.34 

FFB ------ ---w-e 8 50 2.35 8 57 2.41 

WR ------ 7 126 2.18 ------ ---meSept 

HRV 5 108 1.85 10 144 2.11 9 265 2.20 9 475 1.26 

WRV 4 25 1.38 9 98 2.09 7 132 1.93 8 209 2.01 

FFB ______ ------ 9 77 2.73 5 46 1.99 WR ------ 8 108 2.69 ------ --m-eAvg* 4.5 70 1.63 8.3 151 2.47 7.3 149 1.95 7.3 235 1.93 

*Averases calculated usins HRV and WRV values only from all three sanmlinq dates 

. 

Richness is a measure of the number of different taxa (Families) 

found at each location and sampling date. The richness of each 

sampling technique during each sampling date is depicted in Figure 1 

and tabulated in Table 2. The patterns shown in the bars of Figure 1 

represent different taxa (Families) collected from each site. The 

height of each pattern represents the number of organisms within that 

taxon. In general, the benthic community sampling provided the 

greatest measure of richness compared to the three substrate-sampling 

techniques (multiplate samplers, leaf packs and cotton packs). 

Multiplate samplers consistentlygatheredthe poorest taxon-richness of 

the 4 techniques at any particular site. 

15 
350 9 

(A) June 

I 

300 ---.---..--- . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..~..____~~~........... 

MPS BCC LP CP ‘YPS BCC CP ’ LP CP’BCC 

500 L 

An 

. . . . . . . . . . . ..___._ . . . . . . . . . . . . . . . . . . . . . .._._...-_............ 

. (C) Sept 

ia \ 

$ 

400 

g300 

z 

3 200 

: 

. . . . . . . . . . 

. . . . . . . . 

. . xl. 

2 ,5 

100 7. . 

d 

: :::_ : 

/ 

0 us 

. . . . . . . 

..g 

B : ,. Al 9 

m 

: :: 

R / ,/ 

MPS BCC LP CP ‘MPS BCC LP CP ’ LP CP- BCC 

HRV FFP WR 

(# on top of bar = # of Families) 

Figure.1. Richness and diversity as measured by sampling technique 

collected in (a) June (b) July and (c) September 1993. Patterns in the 

bars indicate- abundance of different taxa. [E3V, herbaceous riparian 

vegetation; WRV, woody riparian vegetation; F3, forest flood basin; 

W, wetland reference site; MPS, multiplate sampler; BCC, benthic 

community ccmposition; LP, leaf pack; CP, cotton pack] 

Mean diversity is a measure of taxonomic diversity and 

distribution. The scale increases with increasing diversity and 

distribution of organisms between the taxa. The rationale behind this 

measure is that species diversity decreases with decreasing water 

quality. Quite frequently a particular Family dcminatedthe percentage 

of organisms collected using a particular sampling technique or date. 

16 
For example, a high density of organisms was observed in the cotton 

packs collected from the herbaceous riparian stream in June (Fig. 1). 

Yet, only one species of snail represented almost 90% of the total 

number of organisms. This resulted in a low mean diversity (Table 2). 

Of the four sampling techniques tested, the benthic community grab 

samples provided the highest value for average mean diversity. Smaller 

values were associated with leaf packs and cotton packs, and the 

smallest values were provided by multiplate samplers (Table 2). 

Beck's biotic index is a score that weighs the taxonomic richness 

of the sample and the tolerance of the taxa to pollution. Organisms 

are classified by three categories: sensitive, moderately sensitive and 

tolerant of pollution. The categories for Beck's biotic index were 

established from ecological surveys in Florida (Resh and Jackson, 

1993). Points are given for sensitive and moderately sensitive taxa. 

A score of 10 or less is considered polluted water and warrants further 

attention to determine and remediate the problem (Terre11 and Perfetti, 

1989). With one exception, the multiplate samplers always had a very 

low biotic index score that indicated a polluted stream (Table 3). The 

benthic community grab samples consistently resulted in healthy 

scores. Thus, one could reach completely opposite conclusions from the 

same location in the BCW depending on the sampling technique used. The 

leaf pack and cotton packs each averaged moderately healthy biotic 

index scores over time and location. These data suggest that streams 

where physical habitat is lacking or constantly changing, or where 

predation is highly selective, biotic indices scores are tremendously 

influenced by the sampling technique used. 

Table 3. Beck's biotic index for the four sampling techniques. [HRV, 

herbaceous riparian vegetation; WRV, woody riparian vegetation; FFB, 

forest flood basin; WR, wetland reference site; MPS, multiplate 

sampler; BCC, benthic community composition; LP, leaf pack; CP, cotton 

pack; ---, no data;] The bottom line [C'V] is the coefficient of 

variation of Beck's biotic index for the four sampling techniques at 

the HRV and WRV sites. 

Site MPS BCC LP CP 

June 

HRV 

WRV 

FFB 

WR 

July 

HRV 

WRV 

FFB 

WR 

Sept 

HRV 

WRV 

FFB 

0 71 25 

2 122 14 

--- --- 40 

m-e 54 --- 

89 59 

10 75 

--- --- 

--- 59 

10 45 

8 64 

--- --- 

78 44 

35 57 

32 24 

--- --- 

104 94 

67 123 

47 18 

18 

11 

37 

--- 

WR --- 50 --- --- 

cv 1.6 0.31 0.54 0.76 

A basic stream function was evaltuated by measuring the change in 

leaf weight over time at three of the sites. This was done to 

determine how rapidly plant material would decompose under stream 

17 
conditions in the BCW. The results are shown in Figure 2. Both the 

leaf material and the cotton debris lost approximately 35% of their 

initial dry weight over the course of the study. The material in the 

forest flood basin location was slowest to lose weight. In fact, the 

leaves gained weight due to sediment embedding in the material. 

Sediment embedded in leaf material at the other sites as well, but the 

amount on the leaves in the forest flood basin was greatest. Forest 

flood plains have been noted for their ability to retain sediment 

(Mattraw and Elder, 1984). It has also been demonstrated that plant 

material will usually decompose faster under permanently inundated 

conditions (Elder and Cairns, 1982). The cotton debris was less 

vulnerable to embedding sediment material and lost much of its weight 

in the first 6 weeks. This quick weight loss could be explained by a 

quick loss in easily consumable food, followed by a slow decay in the 

less energy efficient fibers and waxes. Microscopic examination of the 

plant material revealed that fungal hyphae were more prominent on the 

cotton stalks than leaf material. The leaf material sustained 

macroinvertebrates classified as shredders (Cummins, 1973) more 

frequently than the cotton material. However, leaf material that was 

heavily embedded with sediment particles had noticeably fewer shredders 

than particle-free material. 

ri .’ -* 

. 

(A) leaf packs # -. _ _ _. . _. _ -;A. _ ______ _. _ _. .‘2&;. .-. -. . . . . _ - __. _. _. _. _ __. 

.* -*. 

d’ 

I 

. 

. 

~ . . .,-* ., “ -“..- +. ;;. -. -. . . . . 

l . l * 

1 

l . 

Location ___.___..........._... 15 

10 

5 

Location 

- HRV 

-+ WRV 

-m- FFP 

.............................................. 

.............................................. 

.............................................. 

April June July Sept April June July sept 

Sampling Date Sampling Date 

Figure 2. Average weight of the (A) forest leaves and (B) cotton 

debris as a function of time at three sites. 

DISCUSSION AND CONCLUSION 

There were distinct differences between the sampling methods used 

and the results of the biological assesment. The benthic community 

grab sampling technique p?ovLded the best scores for mean diversity and 

Beck's biotic index compared to the use of plant-material packs or 

artificial substrdtes. In fact,' the results for multiplate samplers 

and benthic community grab samples were completely opposite. The 

multiplate samplers failed to attract many species even after an 18 

weeks incubation period. Multiplate samplers did not provide a true 

picture of the taxonomic richness or abundance in this particular 

18 
tributary. 

The results support the assertion by LaPoint and Fairchild (1992) 

that benthic grab sampling provides the best representation of the 

benthic community composition and ecolological health of the system. 

The consistent scores and low coefficient of variation (Table 3) 

resulting from the use of this method supports this hypothesis. Proper 

sampling of the benthos precludes many of the sampling biases 

associated with substrate colonization studies. Benthic grab sampling 

requires more time than artificial substrates, but the data appear to 

be more accurate. 

The assumption behind substrate sampling is that it removes 

habitat as a variable and provides standardized surface between sites. 

The plant material packs, which served as more natural substrates, had 

greater macroinvertebrate taxonomic richness and biotic index scores 

than the multiplate substrates. Some of this could be explained by the 

fact that the leaf and cotton material served as a primary or secondary 

food source as well as a shelter for the organisms. The low mean 

diversity in several of the cotton- and leaf-pack samplers could be 

explained by the removal of predation pressure. For example, 329 

macroinvertebrates were counted in the cotton packs collected in June 

from the herbaceous riparian location. Eighty-eight percent of these 

organisms were snails that could move about freely without fear of 

predation. Snail-eating beetles, common in that reach of the 

tributary, were excluded from the sample because they were unable to 

get through the mesh. Therefore, the leaf and cotton debris packs 

biased the outcome of the stream survey. 

Channelizing a stream results in increased water velocity and a 

reduction in the debris retention-time, producing a flushing effect 

(Petersen and Petersen, 1991). Inspection of the tributary revealed 

that most of the plant debris moved a significant distance with each 

rain event. Thus, very little information about the rate of 

decomposition or the ability of the system to recycle this material has 

been determined. Retaining plant debris in packs provided some 

information on the function of the stream. Results confirm that many 

of the leaves in the forest leaf packs would decompose at a steady rate 

after an initial weight gain (Figure 2). The cotton debris however, 

appeared to be resistent to decomposition after the initial weight 

loss. This indicates that the stream could process and transform 

forest leaf-material faster than cotton crop debris. 

In summary, based on the results of the different sampling 

strategies tested, multiplate samplers were found inadequate for 

biomonitoring a channelized stream with conditions similar to the BCW. 

The data derived from multiplate samplers were misleading. The plant 

material packs were valuable in determining the functions of the 

stream. Hcwever, they had some drawbacks when used to characterize 

stream community structure. Benthic grab sampling was the most 

effect,ive sampling method tested in this study. Plant material packs 

and benthic grab sampling each have their advantage. They should be 

considered jointly when designing a biomonitoring project for 

channelized streams such as in the Beaver Creek Watershed. 

REFERENCES 

Beck, W.M., Jr. 1955. Suggested Method for Reporting Biotic Data. 

Sewage and Industrial Wastes 27:1193-1197. 

19 
Cooper, C.M., 1993. Biological Effects of Agriculturally Derived 

Surface Water Pollutants on Aquatic Systems - a review. J. Environ. 

Qual. 22:402-408. 

Cummin, K.W., 1973. Trophic Relations of Aquatic Insects. Ann. Review 

of Entomology 18:183-206. 

Elder, J.F. and D.J. Cairns, 1982. Production and Decomposition of 

Forest Litter Fall on the Apalachicola River Flood Plain, Florida. 

U.S. Geological Survey Water-Supply Paper 2196-B, pp B12 - B32. 

Klemm, D.J., P.A. Lewis, F. Fulk and J.M. Lazorchak, 1990. 

Macroinvertebrate Field and Laboratory Methods for Evaluating the 

Biological Integrity of Surface Waters. EPA/600/4-90/030, pplO9-lS8. 

LaPoint, T.W. and J.F. Fairchild, 1992. Evaluation of Sediment 

Contaminant Toxicity: The Use of Freshwater Community Structure. in 

Sediment Toxicity Assessment, ed. G.A.Burton. Lewis Publishing, 

Ann Arbor, MI, pp. 87-110. 

Mattraw, H.C., Jr. and J.F. Elder, 1984. Nutrient and Detritus 

Transport in the Apalachicola River, Florida. U.S. Geological Survey 

Water-Supply Paper 2196-C, pp. C31-CSS. 

Paul, R.K., Jr., E.F. Benfield and J.D. Cairns, Jr., 1978. Effects 

of Thermal Discharge on Leaf Decomposition in a River Ecosystem. 

Verh. Internat. Verein. Limnol. 20:1759-1766. 

Petersen, L.B.M. and R.C. Petersen, Jr., 1991. Short term retention 

properties of channelized and natural streams. Verh. Internat. 

Verein. Liinnol. 24:1756-1759. 

Plafkin, J.L., M.T. Barbour, K.D. Porter, S.K. Gross and R.M. Hughes, 

1989. Rapid Bioassessment Protocols for use in Streams and 

Rivers: Benthic Macroinvertebrates and Fish. EPA/440/4-89/001. 

Resh, V.H. and J.K. Jackson, 1993. Rapid Assessment Approaches to 

Biomonitoring Using Benthic Macroinvertebrates, in Freshwater 

Biomonitoring and Benthic Macroinvertebrates, eds. D.M. Rosenberg & 

V.H. Resh. Chapman and Hall, New York, N.Y., pp. 195-233. 

Rosenberg, D.M. and V.H. Resh, 1993. Introduction to Freshwater 

Biomonitoring and Benthic Macroinvertebrates. in Freshwater 

Biomonitoring and Benthic Macroinvertebrates, eds. D.M. Rosenberg & 

V.H. Resh, Chapman and Hall, New York, N.Y., pp l-9. 

Terrell, C.R. and P.B. Perfetti, 1989. Water Quality Indicators Guide: 

Surface Waters. U.S. Department of Agriculture, Soil Conservation 

Service, Washington, D.C., pp. 43-68. 

U.S. Environmental Protection Agency, 1989. Report to Congress; Water 

Quality of the Nation's Lakes. EPA Rep. 440/S-89-003. Office of 

Non-point Source Control Branch, Washington, DC. 

U.S. Environmental Protection Agency, 1992. Framework for Ecological 

Risk Assessment. EPA630/R-92/001. Risk Assess. Forum, Washington, DC. 

20 
TRANSPORT AND DEGRADATION OF ALDICARB IN THE SOIL PROFILE: 

A COMPARISON OF CONVENTIONAL TILLAGE AND NON-TILLAGE 

Lisa D. Olsen’, Angel Roman-Ma?, 

Carol P. Weisskopf, and Stephen J. Klaine) 

ABSTRACT: Paired cotton fields (conventionally tilled and non-tilled) in the Beaver Creek watershed, West 

Tennessee, were selected to (1) develop a sampling strategy that accurately characterizes the spatial and temporal 

distribution of aldicarb and its metabolites in the soil profile, (2) evaluate the transport and degradation of aldicarb 

and its metabolites in the soil profile, and (3) compare the behavior of aldicarb and its metabolites in conventionally tilled and non-tilled cotton fields. The observed concentration distributions support sampling in multiple 

positions within transects perpendicular to the orientation of the rows. Multiple transects were proven necessary 

to achieve field representation for a given transect position. This sampling strategy provided suitable data sets 

for calculating representative and statistically defensible field values. Base-catalyzed and surface-catalyzed 

hydrolysis appeared to be the most important mechanisms for the disappearance of aldicarb sulfoxide in the soil 

profile in both tillage systems. Degradation rate constants were 0.046 day-’ for the conventionally tilled field and 

0.040 day-’ for the non-tilled field. The half-lives of aldicarb sulfoxide were 15 days and 16 days for the conventionally tilled and the non-tilled fields, respectively. Horizontal transport was negligible, and vertical transport 

was minimal for both tillage systems. 

KEY TERMS: transport; degradation; soils; aldicarb; aldicarb sulfoxide; aldicarb sulfone. 

INTRODUCTION 

Non-tillage has been effectively used to reduce soil erosion. However, researchers have suggested that 

non-tillage can enhance chemical transport and increase the potential for ground-water contamination (Dick and 

others, 1989; Hall and others, 1989; Isensee and others, 1990). Resource-management agencies in the Mississippi 

embayment, where the soils are highly susceptible to erosion, have recommended non-tillage as a best management practice (BMP). The risk of ground-water contamination associated with the implementation of non-tillage 

in this region needs to be addressed before this BMP is widely adopted. 

Field studies comparing pesticide transport and degradation in conventionally tilled and non-tilled soils 

in this region are needed. An important precursor for such studies is the development of sampling strategies that 

systematically address the spatial and temporal distribution of pesticides within the soil profile. An insufficient 

characterization of the pesticide distribution can bias the evaluation of pesticide transport and degradation, and 

subsequently can bias the comparison of conventional tillage and non-tillage results. 

‘Graduate Student, Department of Geography, University of Memphis, Memphis, TN 38152. 

‘Hydrologist, U.S. Geological Survey, 7777 Walnut Grove Rd., Suite LLB-2, Memphis, TN 38120. 

‘Assistant Professor and Associate Professor, respectively, The Institute of Wildlife and Environmental 

Toxicology, Clemson University, Pendleton, SC 29670. 

21 
In 1993 the U.S. Geological Survey, in cooperation with the Tennessee Department of Agriculture, 

initiated a study was initiated to (1) develop a sampling strategy that accurately characterizes the spatial and 

temporal distribution of aldicarb and its metabolites in the soil profile, (2) evaluate the transport and degradation 

of aldicarb and its metabolites in the soil profile, and (3) compare the behavior of aldicarb and its metabolites 

in conventionally tilled and non-tilled cotton fields. This study is part of a comprehensive research and 

monitoring program to evaluate agricultural non-point source pollution and BMP’s in the Beaver Creek watershed, 

West Tennessee. This report discusses results for the 1993 growing season. 

ALDICARB DEGRADATION 

Aldicarb is a widely used insecticide and nematicide for cotton crops in the Beaver Creek watershed. 

Granular aldicarb is typically integrated into the soil during planting. The 0.3 meter (m) wide application band 

is centered along the row tops. Application rates range from 0.6 to 0.9 kilogram per hectare (kg/ha) of the active 

ingredient. Upon contact with soil moisture, aldicarb is released. Plant uptake is generally less than 5 percent 

of that applied (Smith and Parrish, 1993). Transport in surface runoff is less than 10 percent of that applied. 

Because of its high water solubility (5,730 milligrams per liter), aldicarb is considered highly mobile 

(Seiber, 1987). However, aldicarb mobilization can be retarded by adsorption into organic phases in the soil 

profile. Rao and others (1986) reported that in sandy soils, aldicarb sorption is controlled by the organic carbon 

content. The molecular structure of aldicarb implies that the pesticide has potential for binding ionically to clays. 

However, the sorption mechanism and sorption coefficient are unknown. 

Laboratory experiments conducted by Lightfoot and others (1987) show that microbial oxidation is the 

most important degradation mechanism for aldicarb in soils. Half-lives of 1 to 2 days were reported in these 

experiments. The first product of aldicarb oxidation is aldicarb sulfoxide, which can further oxidize to form 

aldicarb sulfone. Aldicarb, aldicarb sulfoxide, and aldicarb sulfone concurrently hydrolyze to form non-carbamate 

oximes and nitriles. 

Hydrolysis is the most important degradation mechanism for aldicarb sulfoxide and aldicarb sulfone in 

soils (Lightfoot and others, 1987; Hansen and Speigel, 1983; Lemeley and Zhong, 1984). Data presented by 

Lightfoot and others (1987) show that the hydrolysis rates for aldicarb sulfoxide and aldicarb sulfone follow firstorder kinetics and are pH and temperature dependent. Lightfoot and others (1987) also reported half-lives for 

these metabolites in experimental soil microcosms ranging from 10 days to greater than 2,000 days, depending 

upon the pH and temperature. 

Aldicarb and its metabolites are relatively toxic (Fukuto, 1987). Their primary mechanism of action is 

to inactivate the acetylcholinesterase enzyme (Fukuto, 1987; Metcalf, 1971). Rat oral LD, values are 1 milligram 

per kilogram (mg/kg) for aldicarb and aldicarb sulfoxide, and 24 mg/kg for aldicarb sulfone (Lightfoot and 

others, 1987). Non-carbamate metabolites of aldicarb are of little environmental concern because their toxicities 

are relatively low and they continue to degrade to form aldehydes, acids, and alcohols. 

PROTOCOLS AND METHODS 

Two adjacent cotton fields in the Beaver Creek watershed were selected for this study (See Figure 1). 

The fields are located in Shelby County, near the Collierville-Arlington Road. These fields are of similar size, 

slope, and soil type. The south field was cultivated by conventional tillage (the top 0.3 meter was disked before 

planting). The north field was cultivated by non-tillage (crop residues from the previous growing season were 

not disturbed during planting). The nominal rate of application was 0.84 kg of aldicarb (active ingredient) per 

hectare. Agricultural limestone was added to these fields as recommended by the University of Tennessee, 

Agricultural Extension Service (John C. Wilson, farmer, oral commun., 1993). 

22 
\ 0 0.5 1 KILOM!Cl-ER 

Study area I I I 

Figure 1. Location of study area and sampling plots. 

Soils in these fields were classified in 1966 by the U.S. Department of Agriculture, Soil Conservation 

Service, as Falaya silt loam. Soil pH ranges from 5.1 to 5.5. However, these soils are usually limed to bring 

the pH to about 6.5. The water table is often within a foot of the land surface in winter and spring, and declines 

several feet below the surface in the summer and fall (U.S. Department of Agriculture, Soil Conservation Service, 

1989). 

Sampling Protocols 

A 30- by 30-m sampling plot was delineated in each field. All sampling in this study was conducted 

within the plot boundaries. Prior to pesticide application, soil samples were taken from these plots to verify the 

absence of aldicarb and its metabolites. Aldicarb was applied to both fields on May 18, 1993. Soil samples were 

collected from the conventionally tilled field at 9, 22, 52, 84, 115, and 149 days after the application of aldicarb 

and from the non-tilled field at 3, 21, 43, 70, 113, and 148 days after the application date. For each sampling 

23 
date, three transects were randomly established from row top to adjacent row top (see Figure 2). Five equidistant 

coring positions were sampled in each transect. Soil cores were taken at each position in 0.15-m intervals from 

the land surface to a maximum depth of 0.90 m. Soil cores were collected using a 0.054-m diameter stainlesssteel auger. The auger was cleaned with deionized water between sampling depths to avoid contamination from 

one depth interval to the next. For the same reason, the top 3 centimeters of each soil core (except for the uppermost interval) were discarded. 

30 METERS 

1 MnER 

4% 4. 

i 

TRANSECT POSITION - 

Figure 2. Schematic diagram of soil-sampling strategy. 

Each soil core (0.15 m long) was transferred to a large sealable plastic bag and homogenized. Half of 

each soil sample was transferred to a second plastic bag, packed with ice, and sent by overnight carrier to The 

Institute of Wildlife and Environmental Toxicology (TIWET), Clemson University, for analysis of aldicarb, 

aldicarb sulfoxide, and aldicarb sulfone. 

Analytical Methods 

The samples were analyzed using TIWET standard operational procedure #401-53-01. To summarize 

the procedure, aldicarb residues for each sample were isolated by shaking together 0.050 kg of homogenized soil 

24 
and 0.100 kg deionized water in a sealed polyethylene bottle for 1 hour, centrifuging the slurry, and extracting 

the supematant with methylene chloride. The methylene chloride fractions were then rotary evaporated to 

dryness. Aldicarb- residues for each sample were resuspended in 2.0 mL of acetonitrile and analyzed with a 

Hewlett-Packard 1090 Liquid Chromatograph (any use of trade, product, or firm names in this publication is for 

descriptive purposes only and does not imply endorsement by the U.S. Government) with a fluorescence detector. 

Ten percent of the samples were run in triplicate. Analyses were accepted only if the coefficients of 

variation were less than 5 percent. Laboratory blanks representing 5 percent of the total number of samples were 

also analyzed. 

RESULTS AND DISCUSSION 

Most of the results -and discussion presented in this paper are centered on the transport and degradation 

of Bldicarb sulfoxide. Aldicarb was not detected after the first sampling date in each field, and the occurrence 

and distribution of aldicarb sulfone was similar to that of aldicarb sulfoxide. 

Evaluation of Sampling Protocols 

In general, the occurrence of aldicarb sulfoxide was limited to the row tops (transect positions 1 and 5) 

where the pesticide was applied (see Figure 2). Aldicarb sulfoxide concentrations in the slopes (positions 2 and 

4) and furrows (position 3) were low or below the detection limit of 1.5 micrograms per kilogram. This 

distribution was observed in all transects, at all depth intervals, for all sampling dates, and in both fields (see 

Figure 3). 

For a given sampling date, the variances in the aldicarb sulfoxide concentrations at the row-top position 

were relatively high among and within transects (see Table 1). Therefore, a larger number of samplesare needed 

to obtain representative concentrations at this position than at the slope and furrow positions where concentration 

variances were smaller. 

The aldicarb sulfoxide concentration distribution supports sampling in multiple positions within transects 

perpendicular to the orientation of the rows. Because the concentrations for a given transect position varied 

widely among transects, multiple transects proved necessary to achieve field representation for that particular 

position. Considerable spatial variability in the pesticide residue concentrations in soil samples has been reported 

in many field studies (Smith and others, 1987; Jones and others, 1988; Hornsby and others, 1990). Concentration 

medians were assumed to provide representative and statistically defensible field values for a given transect 

position. Medians were selected over other measurements of, central tendency because they are less biased by 

extreme values and, therefore, better suited to describe data sets with large variances. Concentration medians 

were used to characterize the spatial and temporal distribution of aldicarb sulfoxide in the two fields. 

Transport 

Aldicarb sulfoxide concentration distributions were used to determine the vertical and horizontal transport 

in the soil profile. Because aldicarb was applied at the row top position at about 0.07 m below land surface, 

occurrence of aldicarb or its metabolites in other transect positions or depths would constitute horizontal or 

vertical transport. The nonoccurrence of aldicarb sulfoxide in the slope and furrow positions of both fields 

indicates that horizontal transport is negligible. The absence of horizontal mobilization for aldicarb and its 

metabolites was also observed by Smith and Parrish (1993) in peanut fields in sandy loam soils. 

Aldicarb sulfoxide concentrations peaked in the uppermost interval, 0 to 0.15 m, throughout the sampling 

period (See Figure 4 and Table 1). Concentrations in the uppermost interval of the row-top position accounted 

for about 85 percent of the total aldicarb sulfoxide in the soil profile. No occurrence of aldicarb sulfoxide was 

25 
CONVENTIONALLY TILLED FIELD NON-TILLED FIELD 

1,000 

vl 

5 

EXPLANATION g 

s 

TRANSECT POSITION “E f 100 

w Position-l 

K 

5: 

q Position-2 -I 

i E 

q Position-3 

0 

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au 

Q Position-4 Ka 10 

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Z 

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K~RIBUT~CN BY TRANSECT AT THE 0- TO 0.11 

Mm DEPTH INTERVAL ON DAY 52 

jb DETECTION LMT 8 

1.5 MICROGRAMS PER 

KILOGRAM 

TRANSECT-1 TRANSECT-Z TRANSECT-3 TRANSECT-1 TRANSECT-2 TRANSECT-3 

OISTRIEUTION BY DEPTH FOR A SELECTED 

TRANSECT ON DAY 52 

DISTRIW?ON BY DEPTH FOR A SELECTED 

TRANSECT ON DAY 52 

o-o.15 0.1:-0.30 0.30-0.45 0.45-0.60 0.60-0.X o-o.15 0.15-0.30 0.30-0.45 0.45-0.60 0.60-0.75 

DEPTH INTERVALS. IN METERS DEPTH INTERVALS. IN METERS 

10,000 

DISTRIWllCY BY TIME FOR A SELECTED WSEC 

In AT THE 3- TO 0.15~METER DEPTH INTERVAL 

I I DISTRIBUTlON BY TIME FOR A SELECTED 

TRANSECT AT THE D- TO 0.15~MEfER 

DEPTH INTERVAL 

0 P 1,000 

22 

=d 

‘3 

i E 100 

0 

FK 

au KL 

t E 10 

8 

,: 

DAY 9 W 22 MY 52 MY 64 MY 115 DAY 149 

SAMPLING DATE, IN DAYS AFTER APPLICATION 

CAY 3 DAY 21 DAY 43 MY 70 MY 113 DAY 146 

SAMPLING DATE, IN DAYS AFTER APPLICATION 

Figure 3. Typical aldicarb sulfoxide distribution for the conventionally tilled and non-tilled fields. 

26 
0 

HdO 

8 8 

2 ; 

‘: v! v! old.4 

vv 

I I I I I I I I I 

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27 
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28 
CONVENTIONALLY TILLED 0.1 so.30 

0.30-0.45 

0.45-0.60 

0.60-0.75 

DATA FOR DAYS 9. 22. AND 52 

m DAY 115 

9. 22. AND 52 

A bfINIMU?d DETECTION 

I.JwEL (1.5 MICROGRAMS PER KILO0.75-0.90 DATA FOR DAYS 9, 22. 52. AND a4 GM) 

E 

E 

I 

1 A 10 100 1,000 10,000 

r ALOICARB SULFOXIOE CONCENTRATION, IN MICROGRAMS PER KILOGRAM 

F 

% o-o.15 

NON-TILLED 0.15-0.30 

m DAY 3 

0.30-0.4s 

mm DAY 43 

DATA FOR DAYS 3 AND 21 gjgj DAY 70 

0.45-0.60 

?a DAY 113 

DATA FOR DAYS 3 AND 21 m DAY 148 

O-60-0.75 A MINIbWdDETEXTION 

LEVEL (1.5 MICROGRAMS PER KILONO DATA FOR DAYS 0.75-0.90 3, 21, AND 43 GRAM) 

1 A 10 100 1,000 10,000 

ALDICARB SULFOXIDE CONCENTRATION. IN MICROGRAMS PER KILOGRAM 

Figure 4. Median aldicarb sulfoxide for row-top position. 

29 
observed below the 0.60- to 0.75-m depth interval in either field. This indicates that the vertical transport in the 

row-top position was minimal. However, it was not determined if aldicarb sulfoxide had migrated below the 

0.30- to 0.45-m depth interval early in the growing season. Soil samples below this depth interval were not 

collected until day 53 and day 43 in the conventionally tilled and the non-tilled fields, respectively. 

Degradation 

The median aldicarb sulfoxide concentrations for the 0 to 0.15-m depth interval were observed to decrease 

exponentially with time (see Figure 5). Correlation coefficients for the natural logs of the median aldicarb 

sulfoxide concentrations and time since application were -0.80 and -0.61 for the conventionally tilled and the nontilled fields, respectively (See Figure 5). An analysis of the residuals showed that the data points for day 22 in 

the conventionally tilled field and for day 148 in the non-tilled field are outliers, therefore, respective adjusted 

correlation coefficients were -0.99 and -0.92. These correlation coefficients demonstrate that the disappearance 

of aldicarb sulfoxide at the 0 to 0.15-m depth interval follows a first-order kinetics reaction. 

I I I I I I I I I I I I I I 

n NON-TILLED 

. CONVENTIONALLY TILLED 

r CORRELATlON COEFFICIENT 

0 

0 30 60 90 120 150 

TIME SINCE APPLICATION, IN DAYS 

Figure 5. Natural log of the median aldicarb sulfoxide concentration for soil samples at the 0- to 0.15-meter depth 

interval within the band of application as a function of time since application. 

The degradation rate constant, k, is the negative of the slope of the line generated by the correlation of 

the natural log of aldicarb sulfoxide concentration and the time since application (see Figure 5) (Castellan, 1983). 

Degradation rate constants were 0.046 day-’ for the conventionally tilled field and 0.040 day’ for the non-tilled 

30 
field. The half-lives of aldicarb sulfoxide calculated from these rate constants were 15 and 16 days for the 

conventionally tilled and the non-tilled fields, respectively. 

These half-lives are about seven times shorter than the half-lives computed from the base-catalyzed 

distilled water hydrolysis equation presented by Lightfoot and others (1987) for a pH of 6.5 and a temperature 

of 303 kelvin. Surface-catalyzed hydrolysis can explain the shorter half-lives computed from our field data. Bank 

and Tyrrell (1984), Bromilow and others (1986), and Lightfoot and others (1987) have shown that distilled water 

hydrolysis rates are considerably lower than those measured where a solid phase is present. 

Smith and Parrish (1993) reported half-lives of 13 to 20 days for total aldicarb residues in a sandy loam 

soil. In a study conducted in sandy loam soils in the Western United States, half-lives of 15 to 65 days for total 

aldicarb residues were reported (Jones, 1987). Hornsby and others (1990) showed that the half-life of aldicarb 

metabolites taken collectively averaged about 69 days for a sandy soil in Florida. In general, the half-lives 

reported in these studies were somewhat higher than those computed in this study. However, the effects of 

surface-catalyzed hydrolysis on aldicarb sulfoxide degradation are somewhat greater in the clay-rich Falaya silt 

loam soils of the sampling plots in this study. 

CONCLUSIONS 

The aldicarb sulfoxide concentration distributions support sampling in multiple positions within transects 

perpendicular to the orientation of the rows. Multiple transects were proven necessary to achieve field representation for a given transect position. This sampling strategy provided suitable data sets for calculating representative 

and statistically defensible field values. 

Base-catalyzed and surface-catalyzed hydrolysis appeared to be the most important mechanisms for the 

disappearance of aldicarb sulfoxide in the soil profile in both tillage systems. Degradation rate constants were 

0.046 day” for the conventionally tilled field and 0.040 day“ for the non-tilled field. The half-lives of aldicarb 

sulfoxide were 15 and 16 days for the conventionally tilled and the non-tilled field, respectively. Horizontal 

transport was negligible, and vertical transport was minimal for both tillage systems. 

REFERENCES 

Bank, S. and R. J. Tyrrell, 1984. Kinetics and Mechanism of Alkaline and Acidic Hydrolysis of Aldicarb. 

Journal of Agricultural and Food Chemistry 32:1223-1232. 

Bromilow, R. H., G. G. Briggs, M. R. Williams, J. H. Smelt, L. G. M. Th. Tuinstra and W. A. Traag, 1986. 

The Role of Ferrous Ions in the Rapid Degradation of Oxamyl, Methomyl, and Aldicarb in Anaerobic 

Soils. Pesticide Science 17:535-547. 

Castellan, G. W., 1983. Physical Chemistry, Third Edition. The Benjamin/Cummings Publishing Company, 

Menlo Park, CA, 943 pp. 

Dick, W. A., R. J. Roseberg, E. L. McCoy and W. M. Edwards, 1989. Surface Hydrological Response of Soils 

to No-tillage. Soil Science Society of America Journal 53: 1520-1526. 

Fukuto, T. R., 1987. Organophosphorus and Carbamate Ester: The Anticholinesterase Insecticides, Fate of 

Pesticides in the Environment: Proceedings of a Technical Seminar, pp. 5-18. Division of Agriculture 

and Natural Resources, University of CA, Oakland, CA, 158 pp. 

Hall, J. K., M. R. Murray and N. L. Hat-twig, 1989. Herbicide Leaching and Distribution in Tilled and Untilled 

Soil. Journal of Environmental Quality 18:439-445. 

Hansen, J. I. and W. H. Spiegel, 1983. Hydrolysis Studies of Aldicarb, Aldicarb Sulfoxide, and Aldicarb 

Sulfone. Environmental Toxicology and Chemistry 2: 147-153. 

Hornsby, A. G., P. S. C. Rao and R. L. Jones, 1990. Fate of Aldicarb in the Unsaturated Zone Beneath a Citrus 

Grove. Water Resources Research 26(10): 2287-2302. 

31 
Isensee, A. R., R. G. Nash and C. S. Helling, 1990. Effect of Conventional Vs. No-tillage on Pesticide Leaching 

to Shallow Groundwater. Journal of Environmental Quality 19:434-440. 

Jones, R. L., 1987. Aldicarb Environmental Fate Studies Conducted in the Western United States. Fate Of 

Pesticides in the Environment: Proceedings of a Technical Seminar, pp. 105-108. Division of Agriculture 

and Natural Resources, University of CA, Oakland, CA, 158 pp. 

Jones, R. L., A. G. Homsby and P. S. C. Rao, 1988. Degradation and Movement of Aldicarb Residues in 

Florida Citrus Soils. Pesticide Science 23:307-325. 

Lemely, A. T. and W. 2. Zhong, 1984. Hydrolysis of Aldicarb, Aldicarb Sulfoxide, and Aldicarb Sulfone at 

Parts Per Billion Levels in Aqueous Medium. Journal of Agricultural and Food Chemistry X:714-719. 

Lightfoot, E. N., P. S. Thome, R. L. Jones, 1. L. Hansen and R. R. Romine, 1987. Laboratory Studies on 

Mechanisms for the Degradation of Aldicarb Sulfoxide and Aldicarb Sulfone. Environmental Toxicology 

and Chemistry 6:377-394. 

Metcalf, R. L. 1971. Structure-Activity Relationship for Insecticidal Carbamate. Bulletin of the World Health 

Organization 44:43 ff. 

Rao, P. S. C., K. S. V. Edvardsson, L. T. Qu, R. E. Jessup, P. Nkedi-Kizza and A. G. Homsby, 1986. Spatial 

variability of pesticide sorption and degradation parameters, in Garner, W. Y., R. C. Honeycutt, and 

H. N. Nigg, Evaluation of Pesticides in Ground Water, ACS Symposium Ser. 315, American Chemical 

Society, Washington D.C. 

Seiber, J. N., 1987, Solubility, Partition Coefficient, and Bioconcentration Factors. Fate of Pesticides in the 

Environment: Proceedings of a Technical Seminar, pp.53-59. Division of Agriculture and Natural 

Resources, University of CA, Oakland, CA, 158 pp. 

Smith, C. N. and R. S. Parrish, 1993. A Field Study to Evaluate Leaching of Aldicarb, Metolachlor, and 

Bromide in a Sandy Loam Soil. Journal of Environmental Quality 22:562-577. 

Smith, C. N., R. S. Parrish and R. F. Carsel, 1987. Estimating Sample Requirements for Field Evaluation of 

Pesticide Leaching. Environmental Toxicology and Chemistry 6:343-357. 

U.S. Department of Agriculture, Soil Conservation Service, 1989. Soil Survey of Shelby County, Tennessee. 

U.S. Government Printing Qffice, Washington, D.C., 56 pp. and 90 maps. 

32 
RELATION BETWEEN NITRATE CONCENTRATIONS AND POTENTIAL NITRATE 

SOURCES FOR WATER-TABLE AQUIFERS IN THE BEAVER CREEK WATERSHED, 

WEST TENNESSEE: A STATISTICAL ANALYSIS 

Shannon Williams’ and Angel Roman-Ma? 

ABSTRACT: Non-parametric statistical methods were used to examine the relation between nitrate 

concentrations and potential sources of nitrate for the water-table aquifers in the Beaver Creek 

watershed. Water-quality data collected in 1992 from 81 domestic wells were used for these analyses. 

The data showed that nitrate concentrations (measured as nitrate) exceeded 13 milligrams per liter in 

16 percent of the water samples analyzed. The Spearman Rank correlation analysis indicated that nitrate 

concentrations are well-depth dependent. The Kruskal-Wallis test indicated that the variance in nitrate 

concentration can be explained in terms of selected potential nitrate-source categories. The StudentNewman-Keuls multiple comparison of the means test showed that: (1) the mean nitrate concentration 

for wells in the deeper than 45-meter category was lower and statistically different than the mean 

concentrations for the other categories, (2) the mean nitrate concentrations for categories that include 

septic tanks were higher and statistically different than the mean concentration for the crop category, 

and (3) the mean nitrate concentration for the confined animals category was higher and statistically 

different than the mean concentration for the crop category. 

KEY TERMS: Water,table aquifers; nitrate; rural areas; statistical analyses. 

INTRODUCTION ._ - . 

The increasing incidence of ground-water contamination has resulted in a need for: (1) ground-water 

quality and land-use data and (2) analytical tools to establish relations between anthropogenic activities 

and ground-water quality. Row-crop agriculture has been recognized as a potential non-point source of 

ground-water contamination. Water draining cropland can contributeslarge amounts of nitrate and other 

contaminants to receiving aquifers, thus impairing their suitability for designated uses. However, row 

crops are not grown isolated from other nitrate sources, such as septic tanks and facilities with confined 

animals. Accordingly, analytical tools must be able to differentiate the various nutrient sources. 

Parametric and non-parametric statistical analyses are commonly used to relate anthropogenic 

activities to ground-water quality conditions. Although statistical analyses can provide significant 

insight, investigators should exercise caution in the selection of the proper statistical methods. Objectives of the evaluation and the statistical characteristics of the water-quality data and other relevant 

‘Graduate Student, Department of Geography, University of Memphis, Memphis, TN 

38152 

%Iydrologist, U.Si Geological Survey, 7777 Walnut Grove Rd.. Suite LLB-2, Memphis, 

TN 38120 

33 
variables, such as well depth and distance-to-source, also should be considered when selecting appropriate statistical methods. In performing the statistical analyses, it is assumed that each well or spring 

sampled and the associated water-quality data can be categorized according to potential sources of a 

contaminant. The categorization process should be consistent with the physiographic and hydrogeologic 

setting of the area. 

Agriculture is vital to the economy of the Beaver Creek watershed in West Tennessee. About 

70 percent of the watershed is under crop production that consists mainly of soybean, cotton, and corn. 

As in many rural areas in the United States, residents in the Beaver Creek watershed rely on domestic 

wells as their primary source of water. The residents also share a growing concern that agricultural 

activities could be affecting the quality of the ground water in the watershed. 

In the summer of 1992, a water-quality reconnaissance of the water-table aquifers in Shelby, Tipton, 

Fayette, and Haywood Counties, Tennessee, was conducted by the U.S. Geological Survey, in 

cooperation with the Tennessee Department of Agriculture, and the University of Tennessee Agricultural 

Extension Service. The reconnaissance included the collection of water samples from 81 domestic wells 

completed in the water-table aquifers in the Beaver Creek watershed (Figure 1) (Fielder and others, 

1994). 

890 48’ 890271 

I I 

OOD 

Figure 1. Location of Beaver Creek study area and sampled wells. 

Nitrate concentrations (measured as nitrate) exceeding 13 mg/L (milligrams per liter) were observed 

in 16 percent of the water samples for wells in the Beaver Creek watershed. Concentrations above 

13 mg/L can indicate influence of anthropogenic activities (Madison and Brunett, 1985). Water samples 

from two of the wells exceeded the primary drinking water standard for nitrate (measured as nitrate) 

of 45 mg/L adopted by the Tennessee Department of Environment and Conservation (1993). Ingestion 

34 
of water with high nitrate content has been found to cause methemoglobinemia in infants (Klaassen and 

Rozman, 1991). Statistical analyses are used in this paper to relate nitrate concentrations to potential 

nitrate sources in the Beaver Creek watershed. 

HYDROGEOLOGY 

Alluvium and fluvial deposits of Quatemary and Tertiary(?) ages make up the shallow aquifers in 

the Beaver Creek watershed (Parks and Carmichael, 1990a, 1990b; Parks, 1990). Alluvium, consisting 

of sand, gravel, silt, and clay, is present beneath the bottomland areas. Fluvial deposits, consisting of 

sand, gravel, minor clay, and ferruginous sandstone, are present beneath the loess in upland and valley 

slope areas. Locally, the alluvium and fluvial deposits are underlain by the Cockfield Formation, Cook 

Mountain Formation, or the Memphis Sand (Parks and Carmichael, ,1990a, 1990b). The Cockfield 

Formation and Memphis Sand consist of sand, silt, clay, and lignite and make up the Cockfield and 

Memphis aquifers. The Cook Mountain Formation consists primarily of clay and is the confining unit 

overlying the Memphis aquifer. Hydrogeologic information for the deeper wells sampled during this 

investigation was insufficient to determine whether or not some of these wells are screened in the 

Cockfield or Memphis aquifers. 

METHODS 

Protocols for well selection and for sample collection and analysis have been described by Fielder 

and others (1994). A detailed land-use inventory was conducted for each well included in the sampling. 

Land use near each well site was described and distances and topographic gradients between wells and 

potential nitrate sources were recorded. Well construction data were provided by well owners. Well 

records from the Tennessee Department of Environment and Conservation (TDEC) were used to verify 

information obtained from well owners. 

The selection of statistical methods used in this paper follows the discussion by Harris and others 

(1987) and Montgomery and others (1987). All statistical analyses were performed using CoStat 

statistical software (CoHort, 1990) (Any use of trade, product, or firm names in this article is for 

descriptive purposes only and does not imply endorsement by the U.S. Government). 

RESULTS AND DISCUSSION 

Well Depth and Distance-to-Source 

Researchers have shown that the nitrate concentration in ground water is a function of well depth 

and distance-to-source (Madison and Brunett, 1985; Murphy, 1992). Correlation analyses can be conducted to assess the concentration/well depth and the concentration/distance-to-source dependencies. 

The well depth and distance-to-source at which the water quality of the well is no longer affected by 

a particular source can be determined from these analyses. These outer limits should be integrated into 

the classification process. If nitrate concentrations are dependent on well depth and distance-to-source, 

then depths and distances among potential nitrate-source categories cannot be statistically different for 

a comparison among categories to be valid. 

35 
Well depth and nitrate concentration data were not normally dis- ~ 

tributed; they were skewed to the 2 2o 

right (positive skewness). Accord- # 

ingly, a non-parametric correlation g e 40 

test (Spearman Rank) was used. E 2 a0 

Nitrate concentrations were ob- L z 

served to decrease with depth and z c3 80 

the Spearman Rank coefficient was g 3 

-0.55 (Figure 2). This analysis g 100 - 

l - 

l 

SPEARMAN RANK COEFFICIENT = -0.55 

indicates that nitrate concentra- j 

tions are well-depth dependent; g 1201- 

therefore, well depth must be con140 I I I I I I I I I 

sidered when evaluating the rela- 0 5 10 15 20 25 30 35 40 45 50 

tion between potential nitrate NITRATE CONCENTRATION. IN MILLIGRAMS PER UTER 

sources and nitrate concentrations. 

The y-intercept resulting from Figure 2. Relation between nitrate-as-nitrate concentration and depth 

the correlation between well depth of Samnled welts. 

and nitrate concentration (45 m) 

was used to segregate the data into two categories (less than 45 m and greater than 45 m in depth). The 

segregated data were subjected to a series of statistical analyses to prove or disprove the null hypothesis: 

the variance in nitrate concentration between the two well-depth categories is random. Nitrate 

concentrations for both well-depth categories also showed positive skewness. Therefore, the MannWhitney test (non-parametric) was utilized to test the null hypothesis. The test indicated that the 

variation in the nitrate concentration has a low probability (106) of being due to random variation 

(Figure 3). Therefore, the variance in the nitrate concentration can be explained in terms of the selected 

well-depth categories. These analyses indicate that nitrate concentration for wells deeper than 45 m are 

not affected by anthropogenic activities. 

Distance-to-source (nearest source) and nitrate-concentration data were also positively skewed. 

Because these data were not normally distributed, the Spearman Rank non-parametric correlation test 

was used. A significant relation 

between the two variables was not 

observed; the Spearman Rank 

coefficient was -0.21 (Figure 4). 

tn _. 60 I 

s 

0 i 50 

z I 

1 

16 “Mw+iI”MEuRklOF SAMPLE: i 

I 

MEAN 

MINIMUM 

Nitrate-Source Categories 

In order to apply statistical 

analyses to relate the nitrate concentrations to potential nitrate 

sources, each well sampled was 

classified into one potential 

nitrate-source category. Each category included one or more nitrate 

sources. Only those sources that 

were relevant to the individual 

well were considered. The 

16 

T 1 

!Z 

Z 01 Ic 

WELL-DEPTH CATEGORY WELL-DEPTH CATEGORY 

LESS THAN 45 METERS GREATER THAN 45 METERS 

Figure 3. Summary of nitrate-as-nitrate concentration data by welldepth category. 

36 
hydrogeologic characteristics 

of the aquifer and well hydraulics were used for determining which were the potential contributing sources. 

However, the available hydrogeologic and hydraulic data 

were somewhat limited. 

Distances and topographic 

gradients were used to classify 

the sampled wells into potential nitrate-source categories. 

The direction of ground-water 

flow in the shallow aquifers 

was assumed to generally correspond to topographic gradients. Accordingly, all potential 

. 

P 

2 Y! P 

300. I I I I I I I I I 

l 

250 - SPEARMAN RANK COEFFICIENT = -0.21 

150 

1 

n 

I 

100 mm ' 

n n T 

I l 

‘:mmi n l 

mm 

:;-rmm mm m 

50 

t 

n f I 

n 

l m 

l 

n 

I T ml mm I I I I I I 

-0 5 10 15 20 25 30 35 40 45 50 

NiTRATE CONCENTRATION, IN MILLIGRAMS PER LITER 

Figure 4. Relation between nitrate-as-nitrate concentration and distance to 

nearest potential nitrate source for sampled wells. 

nitrate sources upgradien t were 

considered in the classification. The sampled wells are low-yield domestic wells that are pumped 

intermittently to holding tanks. Pumping periods are usually less than 5 minutes and pumping rates are 

less than 38 liters per minute. The well radius of influence is assumed to be relatively small. 

Therefore, potential nitrate sources more than 15 m downgradient were not considered in the 

classification. 

Potential nitrate sources considered in the classification were: 

(1) cropland (fertilizer application), (2) septic tank systems, and 

(3) confined animal facilities. 

These sources resulted in six combinations of categories (Table 1). 

The wells deeper than 45 m were 

considered as an individual category. Nine of the wells sampled 

did not fall into any of the selected 

categories and were not used for 

further analyses. 

Statistical Analyses 

TABLE 1. Classification of wells by potential nitrate sources 

Potential Nitrate Sources No. of Wells 

Septic tanks only (ST) 

Septic tanks and crops (ST/CR) 

Septic tanks and confined animals (ST/CA) 

Crops only (CR) 

Confined animals only (CA) 

Crops and confined animals (CR/CA) 

Wells more than 45 meters deep (TD) 

Wells that did not fit into any of the 

12 

26 

9 

3 

3 

3 

16 

above categories 9 

TOTAL 81 

In order to evaluate the relative contribution of potential 

nitrate sources to nitrate concentrations, the variance in the nitrate concentrations should be explained 

in terms of the selected potential nitrate-source categories. The Kruskal-Wallis test (non-parametric) 

was used for this evaluation. Skewness tests indicated that nitrate concentration data for several of the 

categories were not normally distributed; therefore, parametric tests could not be used. The KruskalWaIlis test determines only the probability at which the variance for a particular variable (nitrate 

concentration) is due to random variation (null hypothesis). If the null hypothesis is rejected, the 

37 
selected data treatments (potential nitrate-source categories) can be a plausible explanation for the 

observed variance. Results of the Kruskal-Wallis test indicated that the variance in the nitrate 

concentration has a low probability (10-9 of being due to random variation. Therefore, the variance in 

nitrate concentration is explained in terms of the selected potential nitrate-source categories. 

Because more than two 

categories were considered, 

the analysis of the variances 

was followed by a multiple 

comparison of the means. 

The S tudent-Newman-Keuls 

multiple comparison test (nonparametric) was used to rank 

the nitrate-concentration 

means and to determine which 

means were statistically different at a 0.05 level of significance (Figure 5). The 

tests showed that: (1) the 

mean concentration for wells 

classified as deeper than 45 m 

was lower and statistically different than the means for the 

other six categories, (2) the 

means for categories that ins 

; 

60 

i 

5 so- l2 26 ;tJJEE&OF SAMPLES - 

z 10.1 b 1 

MEAN 

-K 40 - MINIMUM 

gif 

pi 

SK 

30 - 

Sk! 

9 .26 

0” 

3 

20 - 

8 

1 1 

12.8ab 14.6a 

I I 

3 

11.4b 

E 

10 - lO.lb 

is I 

3 16 _ 

6.2~ 

t 0 

z ST ST/CA CA ST/CR CR CR/CA TD 

Figure 5. Summary of nitrate-as-nitrate concentration data for selected 

potential nitrate-source categories (letter following mean value represents 

populations that are not statistically different at the 0.05 probability as 

determined by the Student-Newman-Keuls multiple corn-parison test. ST, 

septic tank; CA, confined animals; CR, crops; TD, wells deeper than 45 

meters). 

elude septic tanks were higher and statistically different than the mean for the crop category, and (3) the 

mean for the confined animals category was higher and statistically different than the mean for the crop 

category. 

The test of the variance and the multiple comparison of the means test assumed that the nitrate data 

were stationary in time and space. These assumptions were supported by: (1) the relatively short time 

period (July-August) in which the samples were collected, (2) the uniformity in the climatic conditions 

during the sampling period (dry season), (3) the absence of on-going agricultural activities that could 

affect nitrate concentrations (planting season ends in early June), and (4) the relatively low hydraulic 

conductivity of these aquifers. For these reasons, the data were assumed to be independent and serial 

correlations were not conducted. 

Because nitrate concentrations were determined to be dependent on well depth, the Kruskal-Wallis 

test was used to compare well-depth distribution among the various potential nitrate-source categories. 

The results showed that the variation in well depth among the various categories can be explained by 

random variation (p = 0.35) (Figure 6). Therefore, well depths do not bias the comparison among the 

nitrate-source categories. 

CONCLUSIONS 

Results from the Spearman Rank correlation test indicated that nitrate concentrations are well-depth 

dependent. Therefore, well depth had to be considered when evaluating nitrate source-concentration 

relations. The results of the Mann-Whitney test supported the assumption that nitrate concentrations 

for wells deeper than 45 m are not affected by anthropogenic activities. 

38 
The Kruskal-Wallis test 0 

indicated that the variance in 3 9 

9 ;Lii;E&OF SAMPLES 

nitrate concentration can be g 10 - 28.6 I 

MEAN 

explained in terms of the selected 

MINIMUM 26 

12 

potential nitrate-source 

E w 

cate- E z 2. _ 

9 

gories. The Student-Newman- x 5 

31 -. 

23.8 & 

Keuls multiple comparison of the z 1 

means test showed that: (1) the g: 

3. 28*6 26.6 27.3 28.9f - 

mean nitrate concentration for g 

3 

37.4 I 

wells in the deeper than 45 m i 

category was lower and statisti- g 

tally different than the means for 

the other six categories, (2) the 

4o 

50 - 

ST ST/CA CA ST/CR CR CR/CA 

mean nitrate concentrations for Figure 6. Relation between well depth and selected potential nitratecategories that include septic source categories (ST, septic tank; CA, confined animals; CR, crops). 

tanks were higher and statistically different than the mean for the crop category, and (3) the mean nitrate concentration for the 

confined animals category was higher and statistically different than the mean for the crop category. 

The results of these analyses are limited by the relatively small sample sizes for some of the 

potential nitrate-source categories. However, the number of wells per unit area for a given category 

is relatively large when compared to similar investigations reported in the literature. Furthermore, the 

distribution of sampled wells among the various categories reflects the occurrence of potential nitrate 

sources with respect to well location throughout the watershed. 

REFERENCES 

CoHort Software, 1990. CoStat statistical software manual revision 4.20. CoHort Software, Berkeley, 

California, 278 p. 

Fielder, A.M., A. Roman-Mas and M.W. Bennett, 1994. Reconnaissance of Ground-Water Quality at 

Selected Wells in the Beaver Creek Watershed, Shelby, Fayette, Tipton, and Haywood Counties, 

West Tennessee, July and August 1992. U.S. Geological Survey Open-File Report 93-366, 28 p. 

Harris, J., J.C. Loftis and R.H. Montgomery, 1987. Statistical Methods for Characterizing GroundWater Quality. Ground Water 25(2): 185-193. 

Klaassen, C.D. and K. Rozman, 1991. Absorption, Distribution, and Excretion of Toxicants in 

Amdoor, M.O., J. Doull and C.D. Klaassen, eds. Toxicology: The Basic Science of Poisons. 

Pergamon Press, Elmsford, NY, chapter 3, pp. 50-85. 

Madison, R.J. and J.O. Brunett, 1985. Overview of the Occurrence of Nitrate in Ground Water of the 

United States. U.S. Geological Survey Water-Supply Paper 2275, pp. 93-105. 

Montgomery, R.H., J.C. Loftis and J. Harris, 1987. Statistical Characteristics of Ground-Water 

Quality Variables. Ground Water 25(2): 176-184. 

Murphy, E.A., 1992. Nitrate in Drinking Water Wells in Burlington and Mercer Counties, New 

Jersey. Journal of Soil and Water Conservation 47(2): 183-187. 

Parks, W.S., 1990. Hydrogeology and Preliminary Assessment of the Potential for Contamination of 

the Memphis Aquifer in the Memphis Area, Tennessee. U.S. Geological Survey Water-Resources 

Investigations Report 90-4092, 39 p. 

39 
Parks, W.S. and J.K. Carmichael, 1990a. Geology and Ground-ivater Resources of the Cockfield 

Formation in Western Tennessee. U.S. Geological Survey Water-Resources Investigations Report 

88-4181, 17 p. 

Parks, W.S. and J.K. Carmichael, 1990b. Geology and Ground-Water Resources of the Memphis Sand 

in Western Tennessee. U.S. Geological Survey Water-Resources Investigations Report 88-4182, 

30 p. 

Shapiro, S.S., M.B. Wilk and H.J. Chen, 1968. A Comparative Study of Various Tests for Normality. 

American Statistical Association Journal, pp. 1343-1372. 

Tennessee Department of Environment and Conservation, 1993. Regulations for Public Water Systems 

and Drinking Water Quality. Tennessee Department of Environment and Conservation, Division 

of Water Supply, chapter 1200-5-1, 174 p. 

40 
FATE AND TRANSI’ORT OF NITROGEN IN AN AGRICULTURAL WATERSHED 

A. Roman-Mas’, H.H. Cochrane’, J.A. Smink!, and S.J. Klaine) 

The fate and transport of nitrogen in an agricultural watershed in West Tennessee was studied 

at the field and watershed levels. Runoff and water-quality data for four ditches draining row crop 

fields in the Beaver Creek watershed were used to quantify the amount of nitrogen exported from 

cropland. Drainage areas for these fields ranged from 7 to 200 hectares, with about 75 to 95 percent 

of the drainage areas under row crop cultivation. Runoff and water-quality data for a 3rd-order and a 

Sth-order stream site downstream of the ditches in the Middle Beaver Creek Canal were used to evaluate 

potential changes in nitrogen speciation and load in the watershed streams. Drainage areas for these 

sites were 1,200 and 12,000 hectares, respectively, with about 70 percent of the areas under row crop 

cultivation. 

Data from about 100 rainfall-runoff events were used for this study. Discharge records were 

developed from modified U.S. Geological Survey operational procedures. Discrete water samples were 

collected at intervals ranging from 5 to 30 minutes and analyzed for total and dissolved nitrogen species. 

Data for the four ditches show that nitrogen in runoff from row crop fields was dominated by 

the suspended-organic fraction. Crop residue in different stages of decomposition accounted for about 

80 percent of the total nitrogen export. Nitrite plus nitrate accounted for about 20 percent of the total 

nitrogen export from these fields. Ammonia was detected in trace concentrations only. Some seasonal 

patterns were evident. Late winter and early spring rainfall-runoff events accounted for 75 percent of 

the suspended-organic nitrogen exported annually. Late spring rainfall-runoff events accounted for 

80 percent of the nitrite plus nitrate exported annually. Growing-season rainfall-runoff events accounted 

for less than 10 percent of the annual nitrite plus nitrate export. 

Data for the 3rd- and 5th- order stream sites show that no significant changes in the nitrogen 

chemical speciation or the load per unit area occurred downstream from the row crop fields. Data for 

these sites show that channelized streams in this watershed are efficient at conveying runoff as well as 

dissolved and particulate nitrogen in runoff. However, these streams do not change the nitrogen content 

of cropland runoff. 

‘Hydrologist, U.S. Geological Survey, 7777 Walnut Grove Rd., Suite LLB2, Memphis, Tennessee 

38120. 

*Graduate Student, University of Memphis, Department of Geography, Memphis, Tennessee 38152. 

‘Graduate Student and Associate Professor, respectively, Department of Environmental Toxicology and 

The Institute for Wildlife and Environmental Toxicology, Clemson University, Pendleton, South 

Carolina 29670. 

41 
SUSPENDED-SEDIMENT YIELD AND CHANNEL EVOLUTION 

IN A SMALL AGRICULTURAL CATCHMENT 

Robert W. Stogner, Sr.l and Timothy H. Diehl' 

Research on suspended-sediment yield from agricultural land and 

channel evolution in permanent field ditches is being conducted in a 

small catchment in the Beaver Creek watershed of West Tennessee. This 

catchment has an area of about 11 hectares, 90 percent of which has been 

planted in cotton annually since 1989. The soils are Grenada, Loring, 

Memphis, and Adler silt loams. 

Surface-water discharge was measured from July 9, 1991 to October 

15, 1993, except for short periods of equipment failure. Rainfall during 

this period was typical of average conditions. Total runoff volume 

during 95 measured storms was 61,000 cubic meters. The median elapsed 

time from initial hydrograph rise to hydrograph peak for 20 selected 

storms was 15 minutes. 

Suspended-sediment concentration was measured during 43 storms, 

typically at a sampling interval of 5 minutes. The total runoff volume 

for these storms was 30,000 cubic meters, about 49 percent of the total 

runoff volume during the study period. The measured total 

suspended-sediment yield from these storms was 170 metric tons (mt). 

Suspended-sediment yield from storms during which sediment concentration 

was not measured was estimated to be about 200 mt using the regression 

of storm load on storm volume. The go-percent confidence interval for 

this estimate, based on the standard error of the regression, is from 

100 to 460 mt. The estimated total suspended-sediment yield from all 95 

storms was 370 mt, with a go-percent confidence interval from 250 to 

640 mt. 

Evolution of the permanent ditch draining the cotton field was 

studied. The ditch is about 22 m long, about 1 m wide at the bank tops, 

and from 0.6 to 0.9 m deep. Its bed slope is about 1 percent. During 

the study period, the thalweg of the ditch degraded an average of 0.11 

m and a net volume of 5 cubic meters of bed and bank material was 

eroded, contributing an estimated 7 mt of suspended sediment. Erosion 

in the ditch contributed between 1 and 3 percent of the total 

suspended-sediment yield from the catchment. 

lHydrologist, U.S. Geological Survey, 7777 Walnut Grove Blvd., 

Suite LLB2, Memphis, Tennessee 38120. 

2Hydrologist, U.S. Geological Survey, 810 Broadway, Suite 500, 

Nashville, Tennessee 37203. 

43 
MECHANISTIC EVALUATION OF PESTICIDE TEMPORAL PATTERNS 

FOR A FIRST-ORDER STREAM 

Angel Roman-Mas’, Carol P. Weisskopf, and Stephen J. Klaine’ 

Processes and factors affecting the temporal patterns in the concentration of aldicarb and its 

metabolites were evaluated for a first-order stream in the Beaver Creek watershed, West Tennessee. 

Mathematical algorithms proposed to explain solute transport mechanics for soil-applied chemicals and, 

in particular, the mass transfer of a chemical from the soil solution into runoff were examined. 

Two general patterns in the concentration distribution of aldicarb and its metabolites were 

observed during rainfall-runoff events. In the early stages of the event, the natural log of the 

concentration increased linearly with time-and inversely in proportion to the rainfall-runoff ratio. The 

duration of this initial pattern was similar to the basin response (lag) time. The pattern ended when the 

concentration peaked. After peak concentration, a second pattern was observed. The natural log of the 

concentration decreased exponentially with time and was proportional to the rainfall-runoff ratio. These 

patterns in the concentration of aldicarb and its metabolites are consistent with the rate-limited transfer 

algorithm used in physically based models and are inconsistent with the instantaneous-equilibrium 

algorithm used in lumped-parameter models. 

Peak concentrations for aldicarb and its first metabolite, aldicarb sulfoxide, for rainfall-runoff 

events decreased exponentially with elapsed time between application and an event. The rate at which 

the peak concentrations of aldicarb and aldicarb sulfoxide in runoff decreased with time was similar to 

the degradation rates in the soil profile. The peak concentrations of aldicarb sulfone, the last metabolite 

in the oxidation of aldicarb, increased exponentially with time until day 18 and decreased exponentially 

with time after that. These patterns were consistent with those observed in soils. Multiple regression 

analyses indicated that peak concentration in runoff for a given rainfall-runoff event is controlled 

primarily by the concentrations in the soil solution. 

‘Hydrologist, U.S. Geological Survey, 7777 Walnut Grove Rd., Memphis, Tennessee 38120. 

*Assistant Professor and Associate Professor, respectively, The Institute for Wildlife and Environmental 

Toxicology and Department of Environmental Toxicology, Clemson University, Pendleton, South Carolina 29670. 
RESEARCH AND MONITORING NEEDS FOR THE IMPLEMENTATION 

OF THE USDA WATER QUALITY HUA PROGRAM: 

THE BEAVER CREEK WATERSHED PROJECT 

Howard C. Hankin' and George F. Smith2 

Abstract: The hydrologic unit area (HUA) program was initiated 

because of increasing concern for water resources in rural United 

States. The HJJA program is a major element of the President's 

Water Quality Initiative within the U.S. Department of Agriculture. 

Previous experiences with rural water-quality programs have 

demonstrated the need for intensive monitoring programs to identify 

the sources and magnitudes of agricultural non-point source 

pollutants and to document water-quality improvements. 

Additionally, many questions remain about the effects of best 

management practices on the transport and fate of potential 

contaminants, including sediment, nutrients and pesticides. HUA 

projects should be designed to address these issues and concerns. 

They should also serve as demonstration projects to increase 

awareness in water-quality issues within the agricultural 

community. 

KEY TERMS: agriculture; nonpoint source pollution; water quality. 

INTRODUCTION 

Concern for water-quality issues in rural United States has 

increased in the past decade. Nonpoint source pollution and 

watershed protection have become areas of special attention 

(Knopman and Smith, 1993). As a result of this concern, the 

President's Water Quality Initiative has initiated the hydrologic 

unit area (HUA) program within the U.S. Department of Agriculture 

(USDA) . The HUA program targeted watersheds at locations 

throughout the United States where water quality was considered 

impaired as a result of agricultural non-point source pollution. 

The primary objective of the HUA program was to improve water 

quality in these watersheds through the implementation of best 

management practices (BMPs). 

The Soil Conservation Service (SCS), Agricultural Extension 

Service (AES) and Agricultural Stabilization and Conservation 

Service (ASCS) are USDA agencies that each play a major role in the 

HUA program. The SCS, AES and ASCS have the responsibility to 

provide technical, educational and financial assistance, 

respectively, to farmers. Landowners can choose among many 

'Resource Conservationist, USDA Soil Conservation Service, 675 U.S. 

Courthouse and Federal Building, 801 Broadway, Nashville, TN 37203. 

2Professor, Resource Development, TN Agricultural Extension 

Service, University of Tennessee, PO Box 1071, Knoxville, TN 37901. 

47 
alternative resource management options with different production, 

economic and environmental consequences. The USDA representatives 

must be able to offer landowners the most accurate information 

available to assist them in making the best possible decisions for 

each unique situation. This can only be accomplished with a 

reliable understanding of the targeted watershed. 

Experiences from the Rural Clean Water Program and agriculture 

nonpoint source studies have demonstrated the need for intensive 

monitoring programs to achieve reliable information about the 

watershed (Richards and Baker, 1993). Successful monitoring will 

help identify the sources and magnitudes of agricultural non-point 

source pollution (NPS) . Continued water-quality monitoring was 

also deemed important to document improvements in water quality 

resulting from changes in land-management practices. Additionally, 

many questions remain about the effects of BMPs on the transport 

and fate of potential contaminants, including sediment, nutrients 

and pesticides (Cooper, 1993). 

Another objective of the HUA program is to demonstrate the 

effectiveness of voluntary programs at mitigating water quality in 

the targeted watersheds. 

makers 

This feedback is vital to farmers, policy 

and the general public. Demonstrating improved water 

quality as a result of BMPs encourages other farmers to participate 

and become involved. The HUA projects should demonstrate economic 

feasibility, and improve environmental sensitivity and public 

acceptability. These are key determinants in the decision-making 

process of contemporary agriculture. 

Successful implementation of many HUA projects has been 

hindered by the absence of data and modeling capabilities that (1) 

accurately define the nature and extent of the impacts of 

agricultural activities on water quality, and (2) support the 

selection and implementation of BMPs that best fit conditions at 

the field and at the watershed level. The intent of this paper is 

to focus on several major needs USDA agencies have in order to 

better assist landowners in managing their natural resources. 

Examples will be drawn from the Beaver Creek HUA in Southwestern 

Tennessee to highlight successes and future needs. 

Beaver Creek HUA Project 

The Beaver Creek HUA project in Southwestern Tennessee was 

initiated in 1990 as a result of farmers' concern about NPS 

pollution. Reasons for the concern ranged from statements in the 

national media attributing significant water-quality impairments to 

modern agriculture, to an assessment level evaluation conducted by 

state agencies in Tennessee. The water-quality degradation in the 

Beaver Creek Watershed (BCW) was attributed to agricultural 

activities (Thompson, 1993). A comprehensive water-quality 

monitoring program was initiated in addition to implementing BMPs 

in the Beaver Creek HUA to achieve the objectives of the HUA 

program. 
Research activity that would improve the ability to manage the 

natural resource base is needed. The goals of this research effort 

should include: (1) improving our ability to determine the nature 

and extent to which agricultural activities impact water quality 

and threaten environmental integrity, (2) improving our ability to 

differentiate agricultural NPS pollution from other sources of 

pollution and from natural conditions, (3) developing and 

evaluating monitoring and sampling strategies that accurately 

represent water quality, (4) understanding the processes and 

factors that control the transport and fate of agricultural 

pollutants, (5) assessing the validity of present criteria used to 

set standards for water quality, (6) calibrating and validating 

water-quality models. 

The effects of agricultural BMPs such as conservation tillage, 

nutrient management and pesticide management have been studied 

throughout the country (Sharpley and others, 1988; Jayachandron and 

others, 1993). Inconsistent results have been obtained by virtue 

of a number of site specific factors influencing the processes of 

soil erosion and nutrient pesticide movement (Betson and Marius, 

1969; Griffin, 1992)). More research is needed to quantify site 

specific variables which determine the effectiveness of BMPs used 

alone and in various combinations. 

The use of the simulation model, CREAMS, in Pennsylvania, 

resulted in substantial variance among sites and practices with 

regards to effectiveness of BMPs and nutrient management programs 

(NMPs) in reducing off-site sediment and nutrient loads (Hamlett 

and Epp, 1994). It was concluded that "typically there is not a 

single BMP or NMP that is adequate for controlling pollutant losses 

from agricultural lands. Therefore, to control sediment and 

nutrient losses from agricultural areas, control programs should 

emphasize the use of improved NMPs with the more traditional BMPs", 

(Hamlett and Epp, 1994). It was also concluded that field 

conditions such as slope, crop rotation, and the predominant 

transport pathways should be considered when selecting BMPs and 

NMPS. 

A study using the paired watershed approach in the limestone 

soils of northern Alabama was conducted by Soileau and others 

(1994). Analyses of the data collected over a 6-year period 

suggested a strong effect of tillage on runoff water. 

Specifically, a greater volume of runoff water occurred with the 

use of conservation tillage than conventional tillage. However, 

soil losses for both tillage systems were below soil tolerance (T), 

but significantly lower for conservation tillage when soil loss 

calculations were determined using the erosion index. also, the 

presence of a grass filter strip together with crop residue cover 

in the winter and spring also helped minimize sediment loss from 

the watershed, especially with conventional tillage. 

Soileau and others (1994) found that tillage operations 

appeared to have no significant effect on nitrogen (N) losses, 

either as Kjeldahl nitrogen or as NO,-N. Phosphorus (P) runoff 

tended to be greater with conservation tillage than with 

conventional tillage. This contradicts studies done by Sharpley 
and others (1991) who found a reduction in nutrient (N and P) 

transport from a sorghum field located in the southern plains with 

conservation tillage. The dissimilar results could be explained in 

part by the unique site variables. Most of the annual P runoff 

from the Alabama site occurred with the filtered water component 

instead of the sediment-bound fraction because this site had a 

relatively large volume of runoff water and small sediment loss. 

Another explanation could be the use of different sampling and 

analytical techniques. 

Again, these different research projects demonstrate the 

variability in results, 

strategies, 

possibly due to sampling or research 

geographical location, soil types, climate or even the 

duration of the project. They also demonstrate the need for 

additional research utilizing consistent sampling methodology so 

that legitimate comparisons between data sets become possible. 

An important factor that must be considered is the financial 

feasibility of the BMP to the farmer. 

Epps (19941, 

As concluded by Hamlett and 

various approaches may prove effective in the field, 

but they may negatively influence the farm enterprise or may not be 

financially feasible in a real-world situation. Therefore, 

economic analyses of all practices and programs are needed. 

USDA agency personnel need to understand how the 

implementation of no-till and combinations of other BMPs behave 

with respect to the fate of nutrients and pesticides. This 

includes the migration of agri-chemicals through different types of 

soils. The agent must be able to integrate that knowledge with the 

myriad combinations of crops, vegetative cover, soil types, field 

slopes, climate and economic feasibility. Ultimately a system of 

conservation and nutrient practices which will provide beneficial 

effects to the environment must be achieved. 

Additional information is needed on the types of vegetation 

best suited for erosion control and nutrient and/or pesticide 

uptake and deposition under the varying climatic and geographic 

conditions. An enormous amount of research has been conducted on 

these topics, but the results need to be integrated to provide the 

best recommendations for land-users. 

The success of BMPs is dependant upon the types of vegetation 

associated with these practices. 

vegetation as winter cover crops, 

Promoting certain types of 

conservation cropping systems or 

in filter strips and vegetated waterways has proven to be extremely 

successful at reducing the transport of soil, nutrients and 

pesticides that have an affinity to clay. For example, it has been 

shown that grasses and legumes were effective for erosion control 

purposes in row crops. It has also been demonstrated that 

vegetative barriers (known as stiff grass hedges) can reduce 

sediment yield and decrease runoff velocity (Dabney and others, 

1993). 

The introduction of legumes into a conservation cropping 

system has proven to be useful both as erosion control and adding 

nitrogen to the soil for the following seasons crop. It has been 

demonstrated that some winter cover crops, such as rye, can 

scavenge nitrogen from previous applications and prevent its 

movement through the soil profile into ground water. However, some 

of these same cover crops may actually promote NPS pollution into 

50 
adjacent water systems. An example of this condition has been 

shown with P leaching from cotton foliage, wheat straw (Soileau and 

others, 19941, and the canopy of sorghum and soybeans (Sharpley, 

1981). The P leached from the crops was a major portion of the 

total P runoff in these studies. This P leached from plant tissue, 

may partly explain why cotton plus rye in the conservation tillage 

cropping system had more total P runoff loss than cotton only in 

the conventionally tilled system in the northern Alabama project 

(Soileau and others, 1994). 

Recognizing the sources of nutrient loading is a critical 

factor in developing natural resource plans. All of the pollution 

sources potentially affecting soil, water, air, plants, animals, 

and humans must be identified as plans are developed to alleviate 

problems affecting designated use impairments. If potential 

nonpoint pollution sources are not accounted for, the restoration 

plan may never achieve its intended goals. Thus, we must continue 

to develop our understanding of both the natural and human 

influences on the environment. 

Monitoring Needs 

Optimized sampling strategies to assess agricultural NPS 

pollution and BMPs must be considered as the foundation for 

determining baseline conditions, sources of contaminants, and the 

effectiveness of decisions made and actions taken. Meeting these 

needs requires an intensive monitoring program at both the field, 

sub-watershed, and large watershed level (Richards and Baker, 

1993). Analyses and subsequent conclusions are only as reliable as 

the methodology that is utilized. Therefore, it is imperative that 

quality assurance and quality controls are employed as part of the 

monitoring strategy. 

There are additional concerns when monitoring nonpoint 

pollution parameters in large watersheds. These concerns include 

site selection and multiple nonpoint pollution sources. Proper 

selection of sampling sites is imperative when sampling at the 

watershed level. One should be aware of hydrologic factors, such 

as backwater at the mouth of a watershed, that could influence the 

chemical and biological parameters being assessed. Caution must be 

taken, as these conditions generally yield higher concentrations of 

the contaminants being evaluated owing to the retardation of water 

flow. 

Another concern that a successful monitoring program must 

address is that of multiple nonpoint pollution sources. It is 

extremely difficult, if not impossible, to differentiate sources of 

NPS pollution at the watershed level. A thorough reconnaissance of 

the watershed must be done to catalog the possible sources of 

pollutants. Specific sites should be monitored to determine the 

NPS contribution of an area to the watershed. Additional sampling 

should be done downstream to determine if the NPS pollution has 

been removed from the system (by assimilation and breakdown) or has 

migrated downstream. Without characterizing this process, it is 

possible to incorrectly identify and target a source as the primary 

contributor. 

51 
Many of the desired water-quality goals were developed for 

low-flow conditions. However, 

primarily during rain events. 

NPS pollutant loading occurs 

These elevated levels of NPS 

pollutants last for relatively short periods of time. This implies 

that chemical monitoring must be intensive during the rain event to 

accurately characterize the NPS pollutant load, especially in 

small basins (Richardson and Baker, 1993). Temporal and spatial 

considerations are critical to a successful chemical monitoring 

program. 

required 

A great deal of financial and personnel resources are 

to accurately characterize 

watershed. 

the NPS pollution in a 

Many agencies are turning to biological monitoring to avoid 

the problems associated with a chemical 

However, 

monitoring program. 

there are concerns with the use of biological monitoring 

to draw conclusions regarding NPS pollutants. 

biological database is 

For example, the 

presently too small to establish 

scientifically defensible limits for specific geophysical regions 

(Griffin and others, 1992). Preliminary research must be done to 

develop an acceptable baseline data set. This is essential to 

factor out the inherent diversity of the watershed system, as well 

as seasonal and annual fluctuations. Acceptable ranges must be 

established to account for natural variability. 

Many sampling protocols are available for 

monitoring (By1 and Roman-Mas, 

biological 

1994). However, these protocols 

were developed for specific hydrologic and geographic conditions 

that may or may not apply to the watershed under investigation. 

For example, the use of the sensitive 

Trichoptera, 

taxa (Ephemeroptera, 

and Plecoptera) to evaluate water quality may not be 

applicable to watersheds that do not supply the correct habitat for 

these organisms. It is entirely possible that these organisms 

never inhabited the watershed in question, and therefore, accurate 

comparisons cannot be made. 

Despite the many needs of monitoring programs, accurate 

biological and chemical assessments are necessary in order to 

properly characterize the contaminants and their sources. 

Otherwise, application of conservation management systems, or BMPs, 

to restore or enhance the impaired water 

ineffective. 

quality will be 

The Beaver Creek HUA Program 

The Beaver Creek HUA project has provided a vehicle to conduct 

intensive monitoring and research in real farm situations. It has 

presented the opportunity to improve methodologies for surface and 

ground-water monitoring. Experience gained from several years of 

pre-BMP monitoring has allowed the Beaver Creek program to develop 

a considerable data base to use in water-quality models. The 

intensive studies conducted in the Beaver Creek HUA have also 

improved our understanding of in-stream assimilation processes. 

This has led to the development and testing of innovative new BMPs, 

such as a constructed wetland to mitigate runoff from a field of 

row crops. 

52 
The U.S. Geological Survey, in cooperation with USDA, local 

and state agencies, is conducting a comprehensive assessment of the 

effect of agricultural activities on water quality and the 

effectiveness of BMPs in the Beaver Creek Watershed. The main goal 

of this project is to develop tools that can be used by federal and 

state agencies in their resource management programs. A holistic 

watershed approach has been adopted for this program. Intensive 

water sampling has been done during rain-events to get chemical 

data and characterize the transport of XPS pollution in the 

watershed. The chemical monitoring has examined both surface and 

ground water. Biological samples have also been gathered in 

connection with the chemical and geomorphology studies. Some of 

the results of these monitoring activities can be found in these 

proceedings. 

SUMMARY 

Effectively addressing NPS water-quality problems from 

agricultural sources depends upon (1) careful identification of the 

NPS problems and their source, (2) implementation of effective and 

cost efficient practices to address the prcblems identified, and 

(3) the capability to demonstrate the benefits of resource 

management decisions on water quality. Research is needed to aid 

identifying NPS sources, 

itllutants identified, 

to sort out the sources of the 

and to demonstrate the effectiveness of BMPs 

in management systems. These results are crucial to provide 

resource management agencies with the best possible information. 

Monitoring is needed to (1) document baseline conditions, (2) 

track progress and identify possible modifications or refocusing of 

efforts, and (3) document water-quality improvements. 

Demonstrating improvement is essential to justify the resources 

invested both to the landowners and, perhaps more importantly, to 

the tax-paying public demanding improved water quality and 

effective agency programs. 

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