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January - Volume 12, Issue 1, Pages 1 - 117
March - Volume 12, Issue 2, Pages 119 - 239
July - Volume 12, Issue 3, Pages 241 - 364
October - Volume 12, Issue 4, Pages 365 - 520
Volume 12, Issue 2
March 2010
ISSN 1464-7141
EISSN 1465-1734
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In this Issue
Research Articles
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Research Articles
Towards a hydroinformatics framework to aid decision-making for catchment management
C. J. M. Hewett
;
A. Doyle
;
P. F. Quinn
Abstract
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Simulation of urban wastewater systems using artificial neural networks: embedding urban areas in integrated catchment modelling
Guangtao Fu
;
Christos Makropoulos
;
David Butler
Abstract
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Cost and reliability comparison between branched and looped water supply networks
J. B. Martínez
Abstract
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Application of hydroinformatics tools for water quality modeling and management: case study of Vientiane, Lao P.D.R
O. Mark
;
J. O. Lacoursière
;
L. B.-M. Vought
;
Z. Amena
;
M. S. Babel
Abstract
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Urban water demand forecasting based on HP filter and fuzzy neural network
Wu Li
;
Zhou Huicheng
Abstract
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Development of multi-objective reservoir operation rules for integrated water resources management
T. S. Cheong
;
I. Ko
;
J. W. Labadie
Abstract
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Application of neuro-fuzzy model to estimate the characteristics of local scour downstream of stilling basins
J. Farhoudi
;
S. M. Hosseini
;
M. Sedghi-Asl
Abstract
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Ant-colony-based simulation–optimization modeling for the design of a forced water pipeline system considering the effects of dynamic pressures
H. Abbasi
;
A. Afshar
;
M. R. Jalali
Abstract
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Realising social justice in the water sector: 2
M. B. Abbott
;
Z. Vojinovic
Abstract
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Macro-scale grid-based and subbasin-based hydrologic modeling: joint simulation and cross-calibration
Prediction of the optimal dose of coagulant for various potable water treatment processes through artificial neural network
Pipeline failure prediction in water distribution networks using weather conditions as explanatory factors
Groundwater productivity potential mapping using frequency ratio and evidential belief function and artificial neural network models: focus on topographic factors
Trained meta-models and evolutionary algorithm based multi-objective management of coastal aquifers under parameter uncertainty
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