By Topic

Prediction of the hydrologic behavior of a watershed using artificial neural networks and geographic information systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Chiari, F. ; Univ. of Corsica, Corti, France ; Delhom, M. ; Santucci, J.-F. ; Filippi, J.B.

The authors have been working on the modeling and simulation of environmental systems. We have developed an object oriented approach mainly based on discrete events and object oriented simulation. In order to validate our approach, we applied it to the simulation of watershed behavior; the results were quite satisfactory. However, a more accurate rainfall/runoff model is necessary in order to take into account hourly flow variations, particularly for flood prediction. As our first approach was not efficient enough to do this, we chose to define a new one based on artificial neural networks (ANNs) and geographic information systems (GIS) paradigms

Published in:

Systems, Man, and Cybernetics, 2000 IEEE International Conference on  (Volume:1 )

Date of Conference: