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  List of Accepted Contributions - HS38 Hydroinformatics: computational intelligence and technological developments in water science applications (co-listed in NH)

Please, click Abstract Number to find the corresponding abstract as PDF file; if necessary, download Adobe Acrobat Reader 4.0 first to open the file. Any abstract may be freely reproduced for non-commercial, scientific purposes; however, the moral right of the author(s) to be identified as the author(s) of such abstracts is asserted.

Huard, D.; Mailhot, A.
Dealing with input, output and structural uncertainties using Bayesian analysis

Loucks, D
Environmental Sensors Linked to Cyber-Networks a New Dimension for Hydroinformatics (withdrawn)

Dawson, C; Abrahart, R; See, L
HydroTest: collaborative development of hydrological assessment and evaluation procedures

Kumar, J; Jain, A; Srivastava, R
Estimating groundwater pollution source location using neural networks presented with partial and noisy data

Kumar, A.; Jain, A.
Assessment of neural network technique for estimating fecal coliform based on hydrologic and climatic data

Narain, S.; Tiwari, P. C.; Jain, A.
Modeling rainfall occurrence using neural networks

Singh, S.P.; Jain, A.
Optimal design of composite channels using classical methods and genetic algorithm

Parasuraman, K.; Elshorbagy, A.; Si, B. C.
Estimating saturated hydraulic conductivity in spatially-variable fields using neural network ensembles

Elshorbagy, A.; Jutla, A.
Hydrological modelling of reconstructed watersheds using system dynamics

Efstratiadis, A.; Koutsoyiannis, D.; Karavokiros, G.
Linking hydroinformatics tools towards integrated water resource systems analysis

Purdel, A.; Pasoi, I.
C.A.M.D.A.R. - Excel application for the automatic calculation of discharge and sediment transport measuremets

Baltas, E.; Mimikou, M.
A Database System For Hydrogeological Analysis in Thessaly

Pancescu, M.
Groundwater vulnerability assesment for Mostistea Plain hydrogeological GIS database for DRASTIC index method

Vlad, M.
Connecting a hydrological database with a GIS database

de Vos, N.J.; Rientjes, T.H.M
Multi-objective training of artificial neural networks for rainfall-runoff modelling

Kamp, R.G.; Savenije, H.H.G
Model integration through Artificial Neural Networks

See, L.M.; Shamseldin, A.Y.; Abrahart, R.J.; Dawson, C.W.; Heppenstall, A.J.
Rainfall-runoff modelling of the Shiquan River using a committee approach

Amisigo, B. A.; van de Giesen, N.; Rogers, C.
Filling gaps in daily riverflow series with a spatio-temporal state-space model and the EM algorithm

Mediero, L.; Garrote, L.; Molina, M.
Probabilistic modelling of reservoir operation during floods

Johst, M.; Casper, M.; Gemmar, P.; Gronz, O.; Stueber, M.
Using fuzzy systems to integrate soil moisture information into rainfall runoff models

Janisch, S.; Barthel, R.; Schulz, C.; Trifkovic, A.; Schwarz, N.; Nickel, D.
A Framework for the Simulation of Human Response to Global Change

Heppenstall, AJ; See, LM; Abrahart, RJ
Timing optimisation applied to neural network rainfall-runoff modelling of a large catchment in northern England

Heppenstall, AJ; Abrahart, RJ; See, LM
Neuroevolution methodologies applied to sediment forecasting

See, L.M.; Heppenstall, A.J.; Abrahart, R.J.
Hidden unit specialisation in two neuroevolution rainfall-runoff models

Fenicia, F.; Solomatine , D.P.; Savenije, H.H.G; Hoffmann, L.
An approach to multi-criteria calibration of hydrologic models and their mixtures

Stravs, L.; Brilly, M.
Analysis of the rising limbs of the high flow events

Matreata, M.
Artificial neural networks and fuzzy logic models in operational hydrological forecasting systems (withdrawn)

Coppola, E.; Tomassetti, B.; Verdecchia, M.; Visconti, G.
Rainfall nowcasting using a Neural Network based algorithm and small-catchment flood forecast in complex orography with a distributed hydrological model, implementing a Cellular Automata technique for drainage network extraction

Abrahart, R.J.; Heppenstall, A.J.; See, L.M.
Neural network rainfall-runoff modelling: structural explorations based on neuroevolution and topological complexification

Donchyts, G.; Shlyahtun, N.; Treebushny, D.; Primachenko, A.; Zheleznyak, M.
The architecture and prototype implementation of the Model Environment system.

Corzo, G.; Solomatine, D.
Multi-objective Optimization of ANN Hybrid Committees Based on Hydrologic Knowledge

Shoemaker, C.; Mugunthan, P.; Regis, R.
Function approximation global optimization algorithms for calibration of expensive simulations with applications to water resources

Shrestha, D.; Solomatine, D.
Fuzzy clustering and neural networks in localized estimation of the total model uncertainty

Goswami, M.; O'Connor, K. M.
Application of data-driven ANN and K-NN techniques for lead-time flow forecasting for two Irish catchments

Goswami, M.; O'Connor, K. M.
Comparative assessment of six automatic optimization techniques for calibration of a conceptual rainfall-runoff model

Markus, M.
Weekly nitrate-nitrogen forecasting using artificial neural networks

Singh, A.K.; Deo, M.C.; Kumar, S.
A two-stage ANN to predict littoral drift

Abrahart, R.J.; See, L.M.
Neural network emulation of a rainfall-runoff model

Abrahart, R.J.; See, L.M.; Solomatine, D.P.
Neural network hydrological modelling: all that glisters is not gold?

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