Number  53                                                    May 1992

This article is the fifth in a series designed to share the experience and lessons learned by Rural Clean Water Program (RCWP) project personnel by highlighting the projects' Ten- Year Reports.

John Sanders and Douglas Valentine, USDA - Soil Conservation Service
Elizabeth Schaeffer, USDA - Agricultural Stabilization and Conservation Service
David Greene, University of Maryland Cooperative Extension Service
John McCoy, Maryland Department of the Environment

Project Synopsis

The Double Pipe Creek drainage basin, located in Carroll County, is part of the multi-county Monocacy River Basin which runs from within Pennsylvania southeast to the Potomac River above Washington, D.C. Carroll County, located in the north central part of the state, is known as one of the leading dairy counties in Maryland. Geographically, the area is characterized by rolling hills and lush valleys. Land use in the watershed/RCWP project area (112,200 acres) consists of 65% cropland, 15% woodland, 12% pasture, and 8% urban/roads. Approximately 45,000 animal units are present in the watershed. The management of farm nutrients from livestock wastes and commercial fertilizers is thus vitally important for good water quality. High fecal coliform counts, indicators of pathogenic bacteria, in streams within the project area (Little Pipe and Big Pipe Creeks), threaten domestic water supplies, aquatic life, and contact recreation. Sediment, nutrients, pesticides, and herbicides are also concerns.

The RCWP project critical area included 18,180 acres. The first priority critical area included farms where livestock and the waste management situation presented a water quality problem and where severe gully erosion existed. Farms with primarily erosion control problems due to sheet and rill erosion became the second priority critical area. Water quality monitoring was conducted by the Maryland Department of the Environment.

Project Objectives and Goals

The objective of the project was to reduce the agriculturally generated pollutant load in the watershed. Specific water quality goals were 1) to meet state standards for turbidity and fecal coliform and 2) to reduce the sediment delivery to the streams by approximately 36,000 tons per year.

The primary implementation goal was to have an acreage equal to 50% of the critical area under contract by the end of the third year of the project.

Water quality monitoring program objectives were to 1) establish a baseline water quality data base for evaluating BMP effectiveness at the watershed and field levels by comparing storm event water quality data from a pre-treatment period with data from a post-treatment period and 2) provide sufficient data to design a long-term monitoring program in the area.

Project Administration and Coordination

The Local Coordinating Committee (LCC) coordinated the activities of the participating agencies. The Agricultural Stabilization and Conservation Service (ASCS) administered cost sharing for the project. The Soil Conservation Service (SCS) provided technical assistance. Information and Education (I&E) activities were primarily the responsibility of the University of Maryland Cooperative Extension Service; several other agencies also participated in the I&E program.

Best Management Practices Implemented

The Double Pipe Creek Project included the following BMPs: permanent vegetative cover, animal waste control facilities, stripcropping systems, diversions, grazing land protection, waterway systems, cropland protective cover, conservation tillage systems, stream protection systems, permanent vegetative cover of critical areas, sediment retention, erosion or water control structures, fertilizer management, and pesticide management.

To make the project more cost-effective, major emphasis was placed on preventative measures and management of the soil resource which directly affected water quality. For example, the concept of diverting fresh water around a livestock area as well as the proper handling of animal wastes inside the facility was considered in all applicable plans. Preventing the displacement of soil particles in a water course was emphasized over collecting it downstream.

Selected Findings and Recommendations

• Water Quality Plans covering 20,273 acres had been written and approved for 149 contracts by the end of the contracting period (1986).

• Results through 1990 suggest that BMPs implemented under the RCWP in the project area improved water quality in Big Pipe Creek. Concentrations of ammonia and total organic carbon decreased in Big Pipe Creek. Total nitrogen and nitrate-nitrite nitrogen concentrations increased during the project period.
  

• More time should have been provided during the application period for needs assessment and establishment of goals.

• For projects of this type, where special results are desired, management staff at the national, state, and local levels need to insure that adequate staffing is available to carry out the "special project" without negatively impacting the ongoing local program.

• Having ASCS administer the project was a tremendous advantage, since ASCS already had experience administering cost sharing programs.

• Excellent cooperation existed among all the agencies involved in the Double Pipe Creek Project. The LCC and I&E subcommittee had good participation from local farm organizations and public officials.
  

• Although agency roles and personnel changed throughout the project, these changes seemed to have minimal impact on the successful reaching of project goals and objectives.
  

• A separate budget line should have been added to provide for the printing of the annual and 10-year reports.
  

• The original guidelines for the project should have clearly outlined the expected contents of the yearly, 10-year, and closeout reports.
  

• A wide variety of I&E activities were conducted to promote the Double Pipe Creek Project. A sharing of ideas with some of the other RCWP projects may have provided additional input during the first four years, when it was most needed.
  

• Having I&E funding handled separately through the Cooperative Extension Service (CES) worked extremely well and enabled I&E projects to be funded quickly.
  

• At the end of the sign-up period, much effort revolved around one-to-one contact with producers. More personnel efforts during this time might have resulted in a higher number of contracts.
  

• Results through 1990 suggest that BMPs implemented under the RCWP in the project area improved water quality in Big Pipe Creek, where concentrations of ammonia and total organic carbon decreased by 44% and 51%, respectively. Total nitrogen increased by 25% and nitrate-nitrogen increased by 34% in Big Pipe Creek during the project period.
  

• The results of the monitoring program indicate that the state's turbidity and fecal coliform standards are exceeded regularly in Big Pipe Creek.
  

• Water quality goals were not set at attainable levels and should have been goals that could have been achieved.
  

• An adequate pre-implementation water quality characterization was difficult to obtain.
  

• Control of monitoring sites and contract performance needs to be guaranteed for monitoring sites.
  

• Implementation is correlated to farm income and farm income is difficult to project over a 10-15 year program period. Weather cycles affect farm income. During the project, the area experienced three serious droughts.
  

• Through the experimental nature of the project, a wide range of innovative options were planned and installed, particularly through BMP 2 (animal waste systems).
  

• The tracking and record system could have been better developed at the beginning of the project to facilitate more pertinent data collection in the form later requested.
  

• Availability of contractors with the required experience, equipment, and ability was not a problem.
  

• More personnel were needed to work with land owners and operators concerning the management and maintenance of installed BMPs.
  

• The flexibility to try new ideas during practice application and the $50,000 payment limitation were great assets.
  

For Further Information

Elizabeth Schaeffer, County Executive Director
Carroll County ASCS
1004 Littlestown Pike, Suite C, Westminster, MD 21157
Tel: (410) 848-2780

Douglas Valentine, Acting District Conservationist
USDA-SCS
1004 Littlestown Pike, Suite B-1, Westminster, MD 21157
Tel: (410) 848-6696

This is the second part of a three-part article on models being used to evaluate the effectiveness of best management practices (BMPs) in controlling nonpoint source (NPS) pollution (see NWQEP NOTES No. 52, March 1992) and NWQEP NOTES No. 54, July 1992) for the first and third parts of the article). Such evaluations are one of a wide range of applications for which models are being used in NPS pollution control and research. Other NPS model applications include estimating pollutant loadings for current and projected land use scenarios within a watershed; defining and mapping critical areas for NPS control projects; identifying high priority areas for implementation of stormwater management techniques; and many others. A range of models and applications will be discussed in this series, with the goal of introducing NOTES readers to some of the ways in which models and geographic information systems (GIS) are being used in NPS pollution research and control. Readers interested in contributing to the series are encouraged to contact Judith Gale, NWQEP NOTES editor.

Theo A. Dillaha, Department of Agricultural Engineering, Virginia Polytechnic Institute and Scientific University
Judith A. Gale, NCSU Water Quality Group

Part one of this article provided a discussion of modeling as an approach to evaluation of best management practice (BMP) effectiveness and identified the general types of models being used in NPS work: screening models and hydrologic assessment models, including field-scale hydrologic models and watershed-scale hydrologic assessment models. The second and third parts of the article, beginning with this issue, briefly describe specific NPS models.

Brief Descriptions of Selected Nonpoint Source (NPS) Models

CORNELL NUTRIENT SIMULATION (CNS) AND CORNELL PESTICIDE SIMULATION (CPS) MODELS (Haith and Loehr, 1982) are field-scale models developed to predict nutrient and pesticide losses from agricultural fields. Both models use the SCS curve number equations to predict surface runoff (CPS also uses the Green-Ampt infiltration equation (Green and Ampt, 1911)) and a modification of the Universal Soil Loss Equation (USLE) to predict soil erosion (Onstad and Foster, 1975). Some problems were encountered in comparing the CNS model simulations and observed data in New York and Georgia (Novotny, 1986). The CPS pesticides model considers pesticide degradation, volatilization, percolation through the root zone, and loss in surface runoff.

GROUNDWATER LOADING EFFECTS OF AGRICULTURAL MANAGEMENT SYSTEMS (GLEAMS) MODEL (Leonard et al., 1987) uses the basic foundation of CREAMS and adds components to simulate the movement of water and chemicals within the crop root zone. At present, GLEAMS only simulates subsurface movement of pesticides, but a nitrogen model is being developed. GLEAMS does not consider movement between the root zone and the water table. GLEAMS divides the root zone into 3 to 12 layers and pesticide transport within the root zone is by advection. Diffusion and volatilization are not considered.

Pesticide application can be partitioned between the soil and foliage and can be incorporated to any depth. Pesticide degradation rates can vary by soil zone. GLEAMS can simultaneously model the transport of 10 chemicals and their degradation products, and multiple applications of pesticides are allowed each year. In an independent evaluation, GLEAMS was found to predict peak pesticide concentrations within an order of magnitude and often within a factor of 2 or 3 of observed values (Smith et al., 1989).

NITROGEN-TILLAGE-RESIDUE MANAGEMENT (NTRM) MODEL (Shaffer and Larsen, 1982; Shaffer and Pierce, 1985; Shaffer, 1985) is a field-scale, continuous simulation model developed to evaluate existing and proposed soil management practices with respect to erosion, soil fertility, tillage, crop yield, crop residues, and irrigation. The model simulates carbon and nitrogen transformations including nitrification, denitrification, mineralization, immobilization, urea hydrolysis, and non- symbiotic nitrogen fixation as a function of soil moisture and temperature, using zero- and first-order process equations. The model is more sophisticated than other field-scale models in describing the physical processes affecting transport and transformations, but computing requirements are high.

PESTICIDE ROOT ZONE MODEL (PRZM) (Carsel et al., 1984) is a field-scale, continuous simulation model developed by U.S. EPA to simulate the effects of agricultural management practices on pesticide fate and transport. Runoff is predicted using the SCS curve number equation; soil loss, with a modification of the USLE. The model simulates the vadose zone from the soil surface to ground water. The vadose zone is divided into several layers with varying properties and degradation rates. Pesticide processes considered include advective and dispersive flux, sorption, degradation in the soil, and plant uptake. Volatilization is not considered. Applications can be partitioned between foliage and the soil surface. Surface applications can be incorporated by tillage. The model permits only one application of pesticides per year. In a study in south Georgia, PRZM was used as a screening model (no calibration) and predictions were similar to those of GLEAMS. Most predictions of peak pesticide concentrations were within a factor of 2 or 3 of observed values and almost all were within an order of magnitude (Smith et al., 1989).

AGRICULTURAL NONPOINT SOURCE POLLUTION (AGNPS) MODEL (Young et al., 1989) is an event-based, watershed-scale model developed to simulate runoff, sediment, chemical oxygen demand (COD), and nutrient transport in surface runoff from ungaged agricultural watersheds. Subsurface transport processes are not considered at present, but a ground water loading version of the model is planned. Nutrients considered include nitrogen and phosphorus. The model operates on a square cell basis, which facilitates data base creation. All model inputs are defined on the cell level. Pollutants are routed from the source cell through intervening cells to the watershed outlet. Model output may be viewed at any cell, a capability that allows identification of critical source areas and evaluation of targeting alternatives. Runoff volume is simulated using the SCS curve number method and the peak runoff rate equation used in CREAMS. Erosion and sediment transport are calculated with modified forms of the USLE and Bagnold's stream power equation (Bagnold, 1966). Nutrient yield in the sediment-bound phase is calculated as a function of the nutrient content of the field soil, the sediment yield, and an enrichment ratio which is a function of soil texture and sediment yield. Soluble nutrient loss is a simple function of the soil nutrient level and an extraction coefficient. The model considers only losses of total nitrogen and phosphorus and does not consider nutrient transformations. The model also allows for inputs from feedlots, sewage treatment plants, and other point sources. Data file creation is time consuming, since 22 parameters must be specified for each cell; however, a model user's guide is available (Young et al., 1987) and the CREAMS handbook (Knisel, 1980) is a useful source of parameter values. The model has been tested for runoff estimations on 20 watersheds in the north central United States. Peak runoff rates were approximately 1.6% less than observed values with a coefficient of determination of 0.81. Sediment yield predictions compared well with observed sediment yields from two watersheds in Iowa and Nebraska (Young et al., 1989). The nutrient model has not been adequately tested, but limited testing on Minnesota watersheds indicated that the model provides realistic estimations of nutrient concentrations in runoff (Young et al., 1989). The model's effectiveness in predicting total runoff volume was not reported, so it is difficult to assess the ability of the model to predict total yields.

AREAL NONPOINT SOURCE WATERSHED ENVIRONMENT RESPONSE SIMULATION (ANSWERS) MODEL (Beasley and Huggins, 1982) is an event-oriented, watershed-scale model developed to describe the impact of existing and proposed agricultural management practices on water quality in ungaged watersheds. Recent versions of ANSWERS include an extended sediment detachment/transport model allowing prediction of sediment yield and concentrations for mixed particle size distributions (Dillaha and Beasley, 1983), a phosphorus transport model (Storm et al., 1988), and a nitrogen transport model (Dillaha et al., 1988). ANSWERS subdivides the watershed into a uniform grid of square cells. Land use, slopes, soils and management practices are assumed uniform within each cell. Typical cell sizes range from 0.4 to 4 ha, with smaller cells providing more accurate simulations. Eight to 10 parameter values must be provided for each cell. The extended sediment model uses a modification of Yalin's equation similar to that in CREAMS (Foster et al., 1980).

A non-equilibrium desorption equation is used to account for the desorption of soluble phosphorus from the soil surface to surface runoff. Sediment-bound phosphorus is modeled as a function of the specific surface area of the eroded sediment. The equilibrium between soluble and sediment-bound phosphorus is modeled using a Langmuir isotherm (Storm et al., 1988). The nitrogen transport version of the model simulates nitrogen transformations of applied fertilizer and soil nitrogen between the time of fertilizer applications and runoff events. Soluble nitrogen transport in surface runoff is modeled with the assumption of complete mixing of the soil surface and surface runoff. Sediment-bound nitrogen is modeled as a function of the clay content of transported sediment. The nutrient transport versions of ANSWERS received preliminary verification using water quality data collected from rainfall simulator plot studies. Model predictions of dissolved orthophosphorus, nitrate, ammonia, and sediment-bound total nitrogen and phosphorus were generally within a factor of 3 of observed values. The phosphorus transport version has been used to demonstrate how targeting of BMPs can be used to increase the cost- effectiveness of cost-share monies (Storm et al., 1988). Targeting of cost-share funds to critical areas in the Nomini Creek, Virginia, watershed (10% of the cropland area) was shown to cut the cost of reducing phosphorus losses by approximately 80%.

In an independent evaluation of ANSWERS, the Wisconsin Department of Planning found that ANSWERS was inaccurate and impractical for their land use planning purposes (Baun et al., 1986). A review of the Department's report, however, shows that ANSWERS was not designed for the Department's intended application. This mismatch demonstrates a common modeling problem: attempts to make the model fit the situation rather than finding a model suitable for the situation are seldom successful.

AGRICULTURAL RUNOFF MANAGEMENT (ARM) MODEL (Donigian and Davis, 1978) is a continuous simulation model developed to estimate runoff, sediment, nutrient, and pesticide loadings to surface waters from surface and subsurface flow. The model is an overland flow version of the Stanford Watershed Model (Crawford and Linsley, 1966). Small watersheds of 200 to 500 ha in size can be simulated. Land use, cropping, and management practices are assumed to be uniform throughout the watershed, so it is not possible to identify critical source areas or evaluate targeting strategies. ARM is poorly suited for NPS planning on ungaged watersheds because it requires long-term historical runoff and water quality records for calibration. Data requirements are extensive and data are difficult to obtain in most cases because many parameters have little physical significance. Calibration, testing, and verification are suggested for each application of the model (Crowder, 1987).

Additional NPS models will be described in part three of this article, to be published in the next issue of NWQEP NOTES, No. 54, July 1992.

References

Baun, K., M. Bohn, R. Bannerman, and J. Konrad. 1986. Application of the ANSWERS Model in a Nonpoint Source Program. Madison, WI: Wisc. Dept. Natural Resources, Nonpoint Source and Land Management Section.

Beasley, D.B. and L.F. Huggins. 1982. ANSWERS - Users Manual. Chicago, IL: U.S. Environmental Protection Agency, Great Lakes Program Office; 53 p.; EPA-905/9-82-001.

Carsel, R.F., C.N. Smith, L.A. Mulkey, J.D. Dean and P.P Jowise. 1984. Users Manual for the Pesticide Root Zone Model (PRZM): Release 1. Athens, GA: U.S. Environmental Protection Agency; EPA-600/3- 84-109.

Clausen, J. C. 1985. The St. Albans Bay watershed RCWP: A case study of monitoring and assessment: In: Perspectives on Nonpoint Source Pollution: Proceedings of a National Conference; May 19-22, 1985; Kansas City, MI. Washington, DC: U.S. Environmental Protection Agency; pp. 21-24; EPA-440/5-85- 001.

Crawford, N.H. and R.K. Linsley. 1966. Digital Simulation in Hydrology: The Stanford Watershed Model IV. Palo Alto, CA: Dept. of Civil Engineering, Stanford University; Tech. Rep. No. 39.

Crowder, B.M. 1987. Issues in water quality modeling of agricultural management practices: an economic perspective. In: Proceedings of the Symposium on Monitoring, Modeling, and Mediating Water Quality; May 1987; Minneapolis, MN. American Water Resources Association; pp. 313-327.

Dillaha, T.A. and D.B. Beasley. 1983. Sediment transport from disturbed upland watersheds, Trans. of the ASAE 26(6):1766-1772,1777.

Dillaha, T.A., C.D. Heatwole, M.R. Bennett, S. Mostaghimi, V.O. Shanholtz, and B.B. Ross. 1988. Water Quality Modeling for Nonpoint Source Pollution Control Planning: Nutrient Transport. Blacksburg, VA: prepared for the Virginia Division of Soil and Water Conservation; Virginia Polytechnic Institute and State University, Dept. of Agricultural Engineering; 117 p.; Rep. No. SW-88-02.

Donigian, A.S. and H.H. Davis. 1978. User's Manual for Agricultural Runoff Management (ARM) Model. Athens, GA: U.S. Environmental Protection Agency; EPA-600/3-78-080.

Foster, G.R., L.J. Lane, J.D. Nowlin, J.M. Laflen, and R.A. Young. 1980. A model to estimate sediment from field sized areas. In: Knisel, W.G., ed. CREAMS: A Field-Scale Model for Chemical, Runoff, and Erosion from Agricultural Management Systems. Washington, DC: U.S. Dept. Agric., Science and Education Administration; pp. 36-64; Conservation Research Report No. 26.

Green, W.H. and G.A. Ampt. 1911. Studies in Soil Physics: I. The Flow of Air and Water Through Soils. J. Agric. Sci. 4:1-24.

Haith, D.A. and R.C. Loehr. 1982. Effectiveness of Soil and Water Conservation Practices for Pollution control. Athens, GA: U.S. Environmental Protection Agency; EPA-600/3-82-024.

Knisel, W.G., ed. 1980. CREAMS: A Field-Scale Model for Chemical, Runoff, and Erosion from Agricultural Management Systems. Washington, DC: U.S. Dept. Agric., Science and Education Administration; 640 p.; Conservation Research Report No. 26.

Leonard, R.A. and W.G. Knisel. 1988. Selection and application of models for nonpoint source pollution and resource conservation. In: Modeling Agricultural, Forest, and Rangeland Hydrology. Proceedings of the 1988 International Symposium; 1988 Dec. 12-13; Chicago, IL. St. Joseph, MI: American Society of Agricultural Engineers; pp. 213-229.

Leonard, R.A., W.G. Knisel, and D.A. Still. 1987. GLEAMS: groundwater loading effects of agricultural management systems, Trans. of the ASAE 30(5):1403-1418.

Novotny, V. 1986. A review of hydrologic and water quality models used for simulation of agricultural pollution. In: Giorgini, A. and F. Zingales (eds). Agricultural Nonpoint Source Pollution: Model Selection and Application. New York: Elsevier Publishers; pp. 9-35.

Onstad, C.A. and G.R. Foster. 1975. Erosion modeling on a watershed, Trans. of the ASAE 18:288- 292.

Shaffer, M.J. and W.E. Larson. 1982. Nitrogen-Tillage-Residue Management (NTRM) Model: Technical Documentation. St. Paul, MN: U.S. Dept. of Agriculture, Agricultural Research Service.

Shaffer, M.J. and F.J. Pierce. 1985. Nitrogen-Tillage-Residue Management (NTRM) Model: User's Manual. St. Paul, MN: U.S. Dept. of Agriculture, Agricultural Research Service.

Shaffer, M.J. 1985. Simulation model for soil erosion- productivity relationships, J. Environ. Qual. 14(1):144-150.

Smith, M.C. and J.R. Williams, 1980. Simulation of surface water hydrology. In: Knisel, W.G., ed. CREAMS: A Field-Scale Model for Chemical, Runoff, and Erosion from Agricultural Management Systems. Washington, DC: U.S. Dept. Agric., Science and Education Administration; pp. 13-35; Conservation Research Report No. 26.

Smith, M.C., K.L. Campbel, A.B. Bottcher, and D.L. Thomas. 1989. Field Testing and Comparison of the PRZM and CREAMS Models. ASAE Paper No. 89- 2072. Available from: Am. Soc. of Agric. Engrs., St. Joseph, Mich.

Storm, D.E., T.A. Dillaha, S. Mostaghimi, and V.O. Shanholtz. 1988. Modeling phosphorus transport in surface runoff, Trans. of the ASAE 31(1):117-127.

Young, R. A., C.A. Onstad, D.D. Bosch, and W.P. Anderson. 1987. AGNPS, Agricultural Non-Point- Source Pollution Model: A Watershed Analysis Tool. Washington, DC: U.S. Dept. of Agriculture, Agricultural Research Service; 80 p.; Conservation Research Report 35.

Young, R.A., C.A. Onstad, D.D. Bosch, and W.P. Anderson. 1989. AGNPS: a nonpoint source pollution model for evaluating agricultural watersheds. J. Soil and Water Conserv. 44(2):168-173.

U.S. EPA. 1991. Seminar Publication - Nonpoint Source Watershed Workshop>. EPA/625/4-91/1027. 209p.

The proceedings from the Nonpoint Source Watershed Workshop held in New Orleans, LA, January 29- 31, 1991, have been going like hotcakes and the NCSU Water Quality Group's supply of the publication is now exhausted. Copies may still be requested by writing or calling U.S. EPA's Center for Environmental Research Information, Document Distribution Section, Mail Stop G-72, 26 W. Martin L. King Dr., Cincinnati, OH 45268 (Tel: 513-569-7562).

NWQEP NOTES is issued bimonthly. Subscriptions are free (contact: Publications Coordinator at the address below or via email at wq_puborder@ncsu.edu). A list of publications on nonpoint source pollution distributed by the NCSU Water Quality Group is included in each hardcopy issue of the newsletter.

I welcome your views, findings, information, and suggestions for articles. Please feel free to contact me.

Judith A. Gale, Editor
Water Quality Extension Specialist
North Carolina State University Water Quality Group
Campus Box 7637
North Carolina State University
Raleigh, NC 27695
Tel: 919-515-3723
Fax: 919-515-7448
email: notes_editor@ncsu.edu