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Issue
1 January - Volume 13, Issue 1, Pages 1 - 139
1 March - Volume 13, Issue 2, Pages 143 - 293
1 July - Volume 13, Issue 3, Pages 295 - 573
1 October - Volume 13, Issue 4, Pages 575 - 876
Volume 13, Issue 4
1 October 2011
ISSN 1464-7141
EISSN 1465-1734
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In this Issue
Research Articles
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Research Articles
A practical protocol for calibration of nutrient removal wastewater treatment models
Giorgio Mannina
;
Alida Cosenza
;
Peter A. Vanrolleghem
;
Gaspare Viviani
Abstract
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Pipe burst diagnostics using evidence theory
Josef Bicik
;
Zoran Kapelan
;
Christos Makropoulos
;
Dragan A. Savić
Abstract
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PDF
Prediction of pile group scour in waves using support vector machines and ANN
Samaneh Ghazanfari-Hashemi
;
Amir Etemad-Shahidi
;
Mohammad H. Kazeminezhad
;
Amir Reza Mansoori
Abstract
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PDF
Water distribution network calibration using enhanced GGA and topological analysis
O. Giustolisi
;
L. Berardi
Abstract
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Impact of an incomplete solute mixing model on sensor network design
Pedro Romero-Gomez
;
Kevin E. Lansey
;
Christopher Y. Choi
Abstract
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PDF
Extracting physical homogeneous regions out of irrigation networks using fuzzy clustering method: a case study for the Ghazvin canal irrigation network
M. J. Monem
;
S. M. Hashemy
Abstract
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Use of Landsat ETM+ data for delineation of water bodies in hilly zones
Vijay S. Bhagat
;
Kishor R. Sonawane
Abstract
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Novelty detection for time series data analysis in water distribution systems using support vector machines
Stephen R. Mounce
;
Richard B. Mounce
;
Joby B. Boxall
Abstract
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Quantifying the economy of flow distribution in water supply looped networks
Jose Bienvenido Martínez
Abstract
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ANFIS-based approach to scour depth prediction at abutments in armored beds
Mohammad Muzzammil
;
Javed Alam
Abstract
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A bottom-up approach of stochastic demand allocation in a hydraulic network model: a sensitivity study of model parameters
E. J. M. Blokker
;
H. Beverloo
;
A. J. Vogelaar
;
J. H. G. Vreeburg
;
J. C. van Dijk
Abstract
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PDF
Laminar pipe flow with time-dependent viscosity
Alan E. Vardy
;
James M. B. Brown
Abstract
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Validation of the STRIVE model for coupling ecological processes and surface water flow
L. De Doncker
;
P. Troch
;
R. Verhoeven
;
K. Buis
;
P. Meire
Abstract
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Probabilistic streamflow forecasts based on hydrologic persistence and large-scale climate signals in central Texas
Wenge Wei
;
David W. Watkins, Jr
Abstract
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Subsurface characterization using a D-optimality based pilot point method
Yong Jung
;
Ranji S. Ranjithan
;
G. Mahinthakumar
Abstract
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MOPSO algorithm and its application in multipurpose multireservoir operations
E. Fallah-Mehdipour
;
O. Bozorg Haddad
;
M. A. Mariño
Abstract
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Prediction of local scour depth at bridge piers under clear-water and live-bed conditions: comparison of literature formulae and artificial neural networks
E. Toth
;
L. Brandimarte
Abstract
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Evolutionary product unit based neural networks for hydrological time series analysis
Dulakshi S. K. Karunasingha
;
A. W. Jayawardena
;
W. K. Li
Abstract
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Modeling flood discharge at ungauged sites across Turkey using neuro-fuzzy and neural networks
Neslihan Seckin
Abstract
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Studying of flow model and bed load transport in a coarse bed river: case study – Aland River, Iran
Kiyoumars Roushangar
;
Yousef Hassanzadeh
;
Mohammad Ali Keynejad
;
Mohammad Tagi Alami
;
Vahid Nourani
...
Abstract
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Monthly groundwater level prediction using ANN and neuro-fuzzy models: a case study on Kerman plain, Iran
Amir Jalalkamali
;
Hossein Sedghi
;
Mohammad Manshouri
Abstract
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Attribution of growing season vegetation activity to climate change and human activities in the Three-River Headwaters Region, China
Edge betweenness for water distribution networks domain analysis
A 2D vertical model for simulating surface and subsurface flows using finite element–finite volume methods
A new framework for the optimal management of urban runoff with low-impact development stormwater control measures considering service-performance reduction
Experimental studies on scour of supercritical flow jets in upstream of screens and modelling scouring dimensions using artificial intelligence to combine multiple models (AIMM)
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