Neural Net for Determining DEM-Based Model Drainage Pattern
Publication: Journal of Irrigation and Drainage Engineering
Volume 122, Issue 2
Abstract
Manually determining drainage patterns from topographical maps for a grid-based model is time consuming and occasionally subjective. Eight methods including neural network are developed in this study to automatically determine the pattern from Digital Elevation Model (DEM) data. These methods are tested for a subwatershed located on Chin-Mei Creek, Taipei County, Taiwan, R.O.C. Results obtained using the neural network method are superior to those obtained using the drainage network method, which has performed the best among the other seven methods excluding the neural network method. The neural network method has a self-learning capability that could likely replace human assessment involved in the conventional approach. The implementation of the drainage network and neural network methods is described. Performances of the two methods are compared on the basis of their differences from the manually determined result.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Andrews, J. F. (1992). “Dynamics and control of the activated sludge process.”Water quality management library, Vol. 6, Technomic Publishing Co., Inc., Lancaster, Pa., 226–227.
2.
Band, L. E.(1986). “Topographic partition of watersheds with digital elevation models.”Water Resour. Res., 22(1), 15–24.
3.
Burrough, P. A. (1986). Principles of geographical information systems for land resources assessment . Clarendon Press, Oxford, U.K.
4.
Camp, D., Plate, T., and Hinton, G. (1993). The XERION neural network simulator version 3.1 . Dept. of Comp. Sci., Univ. of Toronto, Ontario, Canada.
5.
Eli, R. N. (1990). “Cellular automation processing of digital elevation data for overland flow continuity.”Proc., 7th Conf. on Comp. in Civ. Engrg., ASCE, New York, N.Y., 113–122.
6.
Gaudill, M., ed. (1990). Theory track, neural & cognitive sciences track of the proceedings of the international joint conference on neural networks . Lawrence Erlbaum Associates, Publishers, Washington, D.C.
7.
Kao, J.-J. (1992a). “Determining drainage pattern using DEM data for nonpoint source water quality modeling.”Water Sci. and Technol., 26(5–6), 1431–1438.
8.
Kao, J.-J. (1992b). Determining drainage pattern using DEM data for nonpoint source water quality modeling. NSC 80-0410-E-009-18, National Science Council, Taiwan, R.O.C.
9.
Lee, M. T., Kao, J.-J., and Ke, Y. (1990). “Integration of GIS, remote sensing and digital elevation data for an hydrologic model.”Proc., 1990 ASCE Nat. Conf. on Hydr. Engrg., ASCE, New York, N.Y.
10.
Mirchandani, G., and Cao, W.(1989). “On the hidden nodes for neural nets.”IEEE Trans. on Circuits and Sys., 36(5), 661–664.
11.
O'Callaghan, J. F., and Mark, D. M.(1984). “The extraction of drainage networks from digital elevation data.”Comp. Vision, Graphics, and Image Processing, 28, 324–344.
12.
Press, W., Flannery, B., Teukolsky, S., and Vetterling, W. (1992). Numerical recipes in C . Cambridge University Press, Cambridge, U.K.
13.
Puecker, T. K., and Douglas, D. H.(1975). “Detection of surface specific points by local parallel processing of discrete terrain elevation data.”Comp. Vision, Graphics, and Image Processing, 28, 375–387.
14.
Rumelhart, D. E., McClelland, J. L., and the PDP Research Group. (1989). Parallel distributed processing . The MIT Press, Cambridge, Mass.
15.
Wolfram, S. (1991). Mathematica . 2nd Ed., Addison-Wesley Publishing Co., Reading, Mass.
16.
Young, R. A., Onstad, C. A., Bosch, D. D., and Anderson, W. P. (1994). Agricultural non-point source pollution model, Version 4.03, AGNPS user's guide . USDA-ARS North Central Soil Conservation Research Laboratory, Morris, Minn.
17.
Yuan, L. P., and Vanderpool, N. L.(1986). “Drainage network simulation.”Comp. Geosci., 12(5), 653–665.
Information & Authors
Information
Published In
Journal of Irrigation and Drainage Engineering
Volume 122 • Issue 2 • March 1996
Pages: 112 - 121
Copyright
Copyright © 1996 American Society of Civil Engineers.
History
Published online: Mar 1, 1996
Published in print: Mar 1996
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.