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GIS-Based W atershed Modeling Systems 191
Certain modeling steps that are becoming necessary for compre-
hensive application of watershed models include sensitivity analysis,
calibration and validation, uncertainty analysis, and BMP optimiza-
tion. Currently available GIS-based modeling systems include some
of these steps but are currently not very sophisticated and user
friendly. In the future, incorporating these modeling steps in a GIS-
based interface will be critical.
With the invention of Internet GIS, more and more GIS function-
alities are currently being deployed through a Web browser. In the
watershed modeling area as well, researchers have started to use Web
browsers for screening-level watershed modeling studies. In future,
it would be possible to deploy a comprehensive watershed model
through a Web browser.
Using GIS has greatly simplified the task of watershed modeling,
which has resulted in efficient use of models, even by nonmodelers.
In future, GIS will make watershed modeling even simpler. However,
this has resulted in misuse of models. With new developments in
GIS-based modeling systems, it would be even more critical to train
future modelers in such a way that they have a thorough grounding
in underlying physical, chemical, and biological processes. This
would result in not only efficient but also accurate and effective mod-
eling efforts.
References
Aller, L., Bennett, T., Lehr, J.H., Petty, R.J. and Hackett, G. 1987. DRASTIC: a
standardized system for evaluating ground water pollution potential using
hydrogeologic settings. U.S. Environmental Protection Agency, Robert S.
Kerr Environmental Research Laboratory, Ada, OK. Office of Research and
Development, EPA/600/2–87/035. p. 641.
Arnold, J. G. and Fohrer, N. 2005. SWAT2000: Current capabilities and research oppor-
tunities in applied watershed modeling. Hydrological Processes. 19:563–572.
Arnold, J. G., Williams, J. R., Nicks, A. D., and Sammons, N. B. 1990. SWRRB, a Basin
Scale Simulation Model for Soil and Water Resources Management. College Station,
TX: Texas A & M University Press.
Bhasker, N. R., James, W. P., and Devulapalli, R. S. 1992. Hydrologic parameter
estimation using geographic information system. Journal of Water Resources
Planning and Management. 118(5):492–512.
Bicknell, B. R., Imhoff, J. C., Kittle, Jr., J. L., Jobes, T. H., and Donigian, Jr., A. S. 2001.
Hydrological Simulation Program—FORTRAN Version 12. User’s Manual. Aqua
Terra Consultants, Mountain View, CA.
Bingner, R. L. and Theurer, F. D. 2003. AnnAGNPS Technical Processes Documentation.
Version 3.2.
Bromberg, J. G., McKeown, R., Knapp, L., Kittel, T. G. F., Ojima, D. S., and Schimel,
D. S. 1995. Integrating GIS and CENTURY model to manage and analyze data.
In GIS and Environmental Modeling: Progress and Research Issues, eds. Goodchild,
M. F. et al. eds. Fort Collins, CO: GIS World Books:429–431.
Burrough, P. A. 1997. Environmental modeling with geographical information sys-
tems. In Innovations in GIS, ed. Kemp, Z. London:Taylor and Francis. 43–153.
Croft, F. and Kessler,B. 1996. Remote sensing, image processing, and GIS: Trends
and forecasts. Journal of Forestry. 4(6):31–35.