IAHR, founded in 1935, is a worldwide independent member-based organisation of engineers and water specialists working in fields related to the hydro-environmental sciences and their practical application. Activities range from river and maritime hydraulics to water resources development and eco-hydraulics, through to ice engineering, hydroinformatics, and hydraulic machinery.
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You are here : eLibrary : IAHR World Congress Proceedings : 32nd Congress - Venice (2007) : THEME B: Data Acquisition and Processing For Scientific Knowledge and Public Awareness. : Ihacres versus anns in water resources design
Ihacres versus anns in water resources design
Author : Carcano Elena Carla, Bartolini Paolo, Muselli Marco, Croke Barry
An analysis of potential scenarios of daily streamflows starting from rainfall, runoff and temperature series comparing Artificial Neural Networks (ANNs) to a conceptual model approach (Ihacres) is herein conducted. Particular attention is reserved to the reconstruction of hydrograph drought periods where water sources design and control are mostly needed. Concerning ANNs two connectionist models are introduced: a feedforward Multilayer Perceptron (MLP) is put aside to an hybrid version of Jordan Recurrent Neural Network in order to reproduce real world data coming from two small catchments (192 and 69 km2 of size) with torrential regime. Different networks configurations are explored in order to
determine a good combination of input features (mostly runoff and rainfall data) able to catch the variability of Rainfall-Runoff process. Temporal dependence is introduce with traditional Tapped Delayed Line (TDL) technique and with memory effects. Results suggest that when poor measures are available total empirical models are able to stand the comparison to conceptual ones and, in general, to perform slightly better.
File Size : 211,997 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 32nd Congress - Venice (2007)
Article : THEME B: Data Acquisition and Processing For Scientific Knowledge and Public Awareness.
Date Published : 01/07/2007
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