Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-28T06:18:17.205Z Has data issue: false hasContentIssue false

Using a Geographic Information System (GIS) for Herbicide Management

Published online by Cambridge University Press:  12 June 2017

Keith M. Mitchell
Affiliation:
N. 305 Turner Hall, 1102 S. Goodwin, Univ. Illinois, Urbana, IL 61801
David R. Pike
Affiliation:
N. 305 Turner Hall, 1102 S. Goodwin, Univ. Illinois, Urbana, IL 61801
Helena Mitasova
Affiliation:
USA-CERL, Champaign, IL 61821

Abstract

An algorithm was developed for use in a geographic information system (GIS) to model the surface movement of herbicide in response to a rainfall event as modulated by slope, soil, management practices, and time of herbicide application. This algorithm was implemented in the GIS software Geographic Resource Analysis Support System (GRASS) and uses as submodels the Natural Resources Conservation Service (NRCS) curve number procedure, the Universal Soil Loss Equation (USLE), and the pesticide submodel from the model Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS). The algorithm estimates the loss of pesticide from field areas, runoff flow patterns, and the accumulation of pesticide downslope in response to a rainfall event. The simulated movement of atrazine, cyanazine, and alachlor was studied under hypothetical management scenarios in the Lake Pittsfield watershed in Pike Co., IL. Tillage for the simulation was by moldboard plow. An alternate no-till scenario was simulated to test tillage effect on atrazine movement. Herbicides were applied either PPI, PRE, POST, or early preplant for no-till (treated as same application time as PPI but without incorporation). The experiment was designed to incorporate timing of application as a management factor from the standpoint of a single rain event on May 16. The results used for comparison were data from 1 d after POST application, 15 d after PRE application and 30 d after PPI application. The algorithm showed that areas of greater herbicide risk can be located within a watershed and that the effect of alternative management practices can be evaluated using a GIS.

Type
Research
Copyright
Copyright © 1996 by the Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

1. Agricultural Stabilization and Conservation Service. 1992. Land use and erodability status classification maps. Pike County, IL.Google Scholar
2. Alter, L., Bennet, T., Lehr, J., and Petty, R. J. 1985. DRASTIC: a standardized system for evaluating ground water pollution potential using hydrogeologic settings. National Well Water Assn. USEPA Agreement No. EPA/600/2-85/018. Ada, OK. p. 15.Google Scholar
3. Beasley, D. B., Huggins, L. F., and Monke, B. J. 1980. ANSWERS: a model for watershed planning. Trans. Am. Soc. Agric. Eng. 23:938944.Google Scholar
4. Cooperative Extension Service. 1983. Estimating your soils erosion loss with the universal soil loss equation (USLE). Coop. Ext. Ser. Circ. 1220. Univ. Illinois. Champaign-Urbana, IL, 19 p.Google Scholar
5. Fehrenbacher, J. B., Alexander, J. D., Janson, I. J., Darmody, R. G., Pope, R. A., Flock, M. A., Voss, E. E., Scott, J. W., Andrews, W. F., and Bushue, L. J. 1984. Soils of Illinois. Univ. Illinois and USDA Soil Cons. Serv. Bull. 778. Champaign-Urbana, IL. 85 p.Google Scholar
6. Goss, D. and Wauchope, R. D. 1990. The SCS/ARS/CES Pesticide Properties Database: II Using It with Soils Data in a Screening Procedure. p. 471–193 in Weigmann, D. L., ed. Pesticides in the Next Decade: the Challenges Ahead; Proc. Third Nat. Res. Conf. on Pesticides.Google Scholar
7. Hornsby, A. G. 1992. Site-specific pesticide recommendations: the final step in environmental impact prevention. Weed Technol. 6:736742.Google Scholar
8. Illinois State Water Survey. 1992. Illinois climate database. Champaign IL 61821.Google Scholar
9. Kellog, R. L., Maizel, M. S., and Goss, D. 1994. The potential for leaching of agrichemicals used in crop production: a national perspective. J. Soil Water Conserv. 49:294298.Google Scholar
10. Knisel, W. G., ed. 1980. CREAMS: A field scale model for chemicals. runoff, and erosion from agricultural management systems. USDA, Conserv. Res. Rep. No. 26. 643 p.Google Scholar
11. McDonald, R. E., Hickman, J. S., Seyler, H. L., and Ransom, M. D. 1992. A geographic information system procedure for pesticide impact assessment. Agron. Abstr.—1992. Am. Soc. Agron. Ann. Mtg., Minneapolis, MN. p. 48.Google Scholar
12. Mitasova, H., Hofierka, J., Zlocha, M., and Iverson, L. R. 1994. Modeling topographic potential for erosion and deposition using GIS. Int. J. of Geog. Inf. Syst. (in press).Google Scholar
13. Moore, I. D. and Burch, G. J. 1985. Physical basis of the length-slope factor in the universal soil loss equation. Soil Sci. Soc. Am. J. 50:12941298.Google Scholar
14. Pantone, J. D., Young, R. A., Buhler, D. D., Eberlein, C. V., Koskinen, W. C., and Forcella, F. 1992. Water quality impacts associated with pre- and post-emergence applications of atrazine in maize. J. Environ. Qual. 21:567573.Google Scholar
15. Taylor, A. G. 1992. Illinois Water Quality Sampling Update—Pesticides. Illinois EPA, 2200 Churchill Rd., Springfield, IL. 5 p.Google Scholar
16. USACERL. 1992. GRASS reference manual. US ARMY. Champaign, IL. 537 p.Google Scholar
17. USDA Soil Conservation Service. 1984. National Engineering Field Manual. Chap. 2, Estimating runoff and peak discharges. p. 2–1 to 2–16.Google Scholar
18. US Geological Survey. 1980. 7.5 minute series topographic maps— Griggsville quadrangle, Pike County, IL. Reston, VA.Google Scholar
19. US Geological Survey. 1981. 7.5 minute series topographic maps—New Salem quadrangle, Pike County, IL. Reston, VA.Google Scholar
20. Wauchope, R. D., Butler, T. M., Hornsby, A. G., Augustijn-Beckers, P.W.M., and Bun, J. P. 1992. The SCS/ARS/CES pesticide properties database for environmental decision making. Rev. Environ. Contam. Toxicol. 123:133.Google Scholar
21. Williams, J. R., Dyke, P. T., and Jones, C. A. 1982. EPIC—A model for assessing the effects of erosion on soil productivity. Lauenroth, W. K., Skogerboe, G., and Flug, M., ed. Proc. Third Int. Conf. on State-of-the-Art in Ecological Modeling. p. 553572.Google Scholar
22. Young, R. A., Bosch, D. D., and Anderson, W. P. 1989. AGNPS: a nonpoint-source pollution model for evaluating agricultural watersheds. J. Soil Water Conserv. 44:168173.Google Scholar