Artificial Neural Network estimation of soil erosion and nutrient concentrations in runoff from land application areas

Computers and Electronics in Agriculture

Volumn 64, Issue 2, 2008, Pages 268-275

  Kim, Minyoung ^a   Gilley, John E ^b  

^a National Institute of Animal Science   (South Korea)

^b UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Artificial Neural Network (ANN); Land application; Manure runoff; Nitrogen; Nutrient losses; Phosphorus; Soil erosion; Water quality

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; DISSOLUTION; ELECTRIC FAULT LOCATION; EROSION; MANURES; NETWORK PROTOCOLS; NUTRIENTS; RUNOFF; SEDIMENTATION; SENSOR NETWORKS; SOIL MECHANICS; SOILS; VEGETATION;

ARTIFICIAL NEURAL NETWORK (ANN); LAND APPLICATION; MANURE RUNOFF; NITROGEN; NUTRIENT LOSSES; PHOSPHORUS; SOIL EROSION; WATER QUALITY;

NEURAL NETWORKS;

AGRICULTURAL LAND; ARTIFICIAL NEURAL NETWORK; CONCENTRATION (COMPOSITION); ESTIMATION METHOD; NUTRIENT AVAILABILITY; RUNOFF; SEDIMENT TRANSPORT; SOIL EROSION; WATER QUALITY;

LINCOLN [NEBRASKA]; NEBRASKA; NORTH AMERICA; UNITED STATES;

EID: 53549097342     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2008.05.021     Document Type: Article

References (36)

1. Bhattacharya B., and Solomatine D.P. Application of artificial neural network in stage-discharge relationship. Proceedings of the 4th International Conference on Hydro-informatics. Iowa City, IA (2000) 1-7
2. Bishop C.M. Neural Networks for Pattern Recognition. 1st Edition (1995), Oxford, Clarendon
3. Czapar G.F., Laflen J.M., McIsaac G.F., and McKenna D.P. Proceedings of the Effect of Erosion Control Practices on Nutrient Loss The Gulf Hypoxia and Local Water Quality Concerns Workshop. Ames, IA, 26-28 September (2005)
4. DiLuzio M., and Arnold J.G. Formulation of a hybrid calibration approach for a physically based distributed model with NEXRAD data input. J. Hydrol. 298 (2004) 136-154
5. Edwards D.R., and Daniel T.C. Quality of runoff from fescuegrass plots treated with poultry litter and inorganic fertilize. J. Environ. Qual. 23 (1994) 579-584
6. Eghball B., and Power J.F. Phosphorus and nitrogen-based manure and compost applications: corn production and soil phosphorus. Soil Sci. Soc. Am. J. 63 4 (1999) 895-901
7. Foster G.R. Keynote: soil erosion prediction technology for conservation planning. In: Stott D.E., Mohtar R.H., and Steinhartdt G.C. (Eds). Proceedings of the Sustaining the Global Farm. Selected papers from the 10th International Soil Conservation Organization Meeting. Purdue University and the USDA-ARS National Soil Erosion Research Laboratory, 24-29 May 1999 (2001)
8. Gérard-Marchant P., Walter M.T., and Steenhuis T.S. Simple models for phosphorus loss from manure in runoff. J. Environ. Qual. 34 3 (2005) 872-876
9. German S., Bienenstock E., and Doursat R. Neural networks and the bias/variance dilemma. Neural Comput. 4 (1992) 1-58
10. Gilley J.E., and Eghball B. Residual effects of compost and fertilizer applications on nutrients in runoff. Trans. ASAE 45 6 (2002) 1905-1910
11. Gilley, J.E., Eghball, B., Marx, D.B., submitted for publication. Nutrient concentrations of runoff during the year following manure application. Trans. ASAE, 50.
12. Govindaraju R.S., and Rao A.R. Artificial Neural Networks in Hydrology (2000), Kluwer Academic Publishers, Amsterdam
13. Heathman G.C., Sharpley A.N., Smith S.J., and Robinson J.S. Poultry litter application and water quality in Oklahoma. Fertil. Res. 40 (1995) 165-173
14. Johnson C.M., and Ulrich A. Analytical methods for use in plant analysis. Agric. Exp. Stn. Bull. 766 (1959) 26-78
15. Kolehmainen M., Martikainen H., and Ruuskanen J. Neural networks and periodic components used in air quality forecasting. Atmos. Environ. 35 (2001) 815-825
16. Kuo J.-T., Hsieh M.-H., Lung W.-S., and She N. Using artificial neural network for reservoir entrophication prediction. Ecol. Model. 200 (2007) 171-177
17. Lane, L.J., Nearing, M.A., 1989. USDA-Water Erosion Prediction Project-Hillslope Profile Version. NSERL Report No. 2. US Department of Agriculture, Agriculture Research Service, W. Lafayette, IN.
18. Li J., Yoder R.E., Odhiambo L.O., and Zhang J. Simulation of nitrate distribution under drip irrigation using artificial neural networks. Irrig. Sci. 23 1 (2004) 29-37
19. Lugo-Ospina A., Dao T.H., Van Kessel J.A., and Reeves-III J.B. Evaluation of quick tests for phosphorus determination in dairy manures. Environ. Pollut. 135 1 (2005) 155-162
20. Moral R., Perez-Murcia M.D., Perez-Espinosa A., Moreno-Caselles J., and Paredes C. Estimation of nutrient values of pig slurries in Southeast Spain using easily determined properties. Waste Manage. 25 7 (2005) 719-725
21. Murphy J., and Riley J.P. A modified single solution method for the determination of phosphate in natural waters. Anal. Chem. Acta 27 (1962) 31-36
22. National Research Council Committee on Animal Nutrition, 1993. Building a North American Feed Information System. Online book. Available at http://www.nap.edu/catalog/9296.html. Accessed April 2007.
23. NeuralWare Inc., 1996. Software manual of NeuralWorks Plus/II.
24. Renard K.G., and Freimund J.R. Using monthly precipitation data to estimate the R-factor in the revised USLE. J. Hydrol. 157 (1994) 287-306
25. Renard, K.G., Foster, G.R., Weesies, G.A., McCool, D.K., Yoder, D.C., 1997. Predicting soil erosion by water: A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). Agric. Handbook No. 703. U.S. Gov. Print. Office, Washington, DC.
26. Schalkoff R.J. Artificial Neural Networks (1997), McGraw-Hill, New York pp. 146-188
27. Schneiderman E.M., Pierson D.C., Lounsbury D.G., and Zion M.S. Modeling the hydrochemistry of the Cannonsville watershed with Generalized Watershed Loading Functions (GWLF). J. Am. Water Resour. Assoc. 38 5 (2002) 1323-1347
28. Sharpley A.N., and Kleinman P. Effect of rainfall simulator and plot scale on overland flow and phosphorus transport. J. Environ. Qual. 32 (2003) 2172-2179
29. Sharpley A.N., Chapra S., Wedepohl R., Sims J.T., Daniel T.C., and Reddy K. Managing agricultural phosphorus for protection of surface waters: issues and options. J. Environ. Qual. 23 3 (1994) 437-451
30. Soil Conservation Service, 1994. Waste utilization standard and specifications. SCS Tech. Practice Code 633. SCS, Stillwater, OK.
31. Steinheimer T.R., Scoggin K.D., and Kramer L.A. Agricultural chemical movement through a field-size watershed in Iowa: surface hydrology and nitrate losses in discharge. Environ. Sci. Technol. 32 (1998) 1048-1052
32. Suen J.P., and Eheart J.W. Evaluation of neural networks for modeling nitrate concentration in rivers. J. Water Resour. Plan. Manage. 129 6 (2003) 505-510
33. Tate D.F. Determination of nitrogen in fertilizer by combustion: collaborative study. J. AOAC Int. 77 (1994) 829-839
34. United States Environmental Protection Agency (USEPA), 1986. Quality criteria for water. Office of Water Regulation and Standards. EPA-440/586-001.
35. United States Environmental Protection Agency (USEPA), 2000. Ecoregional nutrient criteria. Office of Water, USEPA. Available at http://www.epa.gov/waterscience/criteria/nutrient/ecoregions/. Accessed May 2007.
36. Wischmeier, W.H., Smith, D.D., 1978. Predicting rainfall erosion losses: a guide to conservation planning. Agric. Handbook No. 282. US Department of Agriculture, Washington, DC.