133 citations as recorded by crossref.

1. Calibration of hydraulic parameters for large-scale vertical flow constructed wetlands U. Maier et al. 10.1016/j.jhydrol.2009.02.032
2. Classification of hydro-meteorological conditions and multiple artificial neural networks for streamflow forecasting E. Toth 10.5194/hess-13-1555-2009
3. Diagnostic evaluation of conceptual rainfall–runoff models using temporal clustering N. de Vos et al. 10.1002/hyp.7698
4. On the use of multi‐algorithm, genetically adaptive multi‐objective method for multi‐site calibration of the SWAT model X. Zhang et al. 10.1002/hyp.7528
5. Parameter estimation of a physically based land surface hydrologic model using the ensemble Kalman filter: A synthetic experiment Y. Shi et al. 10.1002/2013WR014070
6. When are multiobjective calibration trade‐offs in hydrologic models meaningful? J. Kollat et al. 10.1029/2011WR011534
7. Comparison of efficiency between differential evolution and evolution strategy: application of the LST model to the Be River catchment in Vietnam N. Hang & H. Chikamori 10.1007/s10333-017-0593-z
8. Parallelization strategies for rapid and robust evolutionary multiobjective optimization in water resources applications Y. Tang et al. 10.1016/j.advwatres.2006.06.006
9. Integration of evolutionary based assimilation into Kalman-type methods for streamflow simulations in ungauged watersheds G. Dumedah & P. Coulibaly 10.1016/j.jhydrol.2012.10.033
10. Searching for an Optimized Single-objective Function Matching Multiple Objectives with Automatic Calibration of Hydrological Models F. Tian et al. 10.1007/s11769-019-1068-5
11. Sensitivity-guided reduction of parametric dimensionality for multi-objective calibration of watershed models K. van Werkhoven et al. 10.1016/j.advwatres.2009.03.002
12. Multiresponse multilayer vadose zone model calibration using Markov chain Monte Carlo simulation and field water retention data T. Wöhling & J. Vrugt 10.1029/2010WR009265
13. Comparison of Performance between Genetic Algorithm and SCE-UA for Calibration of SCS-CN Surface Runoff Simulation J. Jeon et al. 10.3390/w6113433
14. Multi-Site Calibration of Linear Reservoir Based Geomorphologic Rainfall-Runoff Models B. Saeidifarzad et al. 10.3390/w6092690
15. Characterization of watershed model behavior across a hydroclimatic gradient K. van Werkhoven et al. 10.1029/2007WR006271
16. Attribution of streamflow trends in snow and glacier melt‐dominated catchments of the Tarim River, Central Asia D. Duethmann et al. 10.1002/2014WR016716
17. Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction J. Chu et al. 10.5194/hess-19-3557-2015
18. Responses of hydrological model equifinality, uncertainty, and performance to multi-objective parameter calibration Y. Her & C. Seong 10.2166/hydro.2018.108
19. Multi-objective automatic calibration of hydrodynamic models utilizing inundation maps and gauge data N. Dung et al. 10.5194/hess-15-1339-2011
20. A framework for Visually Interactive Decision-making and Design using Evolutionary Multi-objective Optimization (VIDEO) J. Kollat & P. Reed 10.1016/j.envsoft.2007.02.001
21. Calibration analysis for water storage variability of the global hydrological model WGHM S. Werth & A. Güntner 10.5194/hess-14-59-2010
22. Modeling and Combined Application of Orthogonal Chaotic NSGA-II and Improved TOPSIS to Optimize a Conceptual Hydrological Model T. Peng et al. 10.1007/s11269-018-2019-0
23. Comparative Study of Evolutionary Algorithms for the Automatic Calibration of the Medbasin-D Conceptual Hydrological Model D. Tigkas et al. 10.1007/s40710-016-0147-1
24. Parameter identification and calibration of the Xin’anjiang model using the surrogate modeling approach Y. Ye et al. 10.1007/s11707-014-0424-0
25. Physical Mechanisms Related to Climate-Induced Drying of Two Semiarid Watersheds in the Southwestern United States S. Rajagopal et al. 10.1175/JHM-D-13-0106.1
26. Incorporating multiple observations for distributed hydrologic model calibration: An approach using a multi-objective evolutionary algorithm and clustering S. Khu et al. 10.1016/j.advwatres.2008.07.011
27. Calibração do Storm Water Management Model (SWMM) utilizando algoritmos evolucionários multiobjetivo K. Formiga et al. 10.1590/s1413-41522016131862
28. Application research of multi-objective Artificial Bee Colony optimization algorithm for parameters calibration of hydrological model J. Huo & L. Liu 10.1007/s00521-018-3483-4
29. Efficient prediction uncertainty approximation in the calibration of environmental simulation models B. Tolson & C. Shoemaker 10.1029/2007WR005869
30. Resolving structural errors in a spatially distributed hydrologic model using ensemble Kalman filter state updates J. Spaaks & W. Bouten 10.5194/hess-17-3455-2013
31. Development of an Automatic Calibration Tool Using Genetic Algorithm for the ARNO Conceptual Rainfall-Runoff Model M. Khazaei et al. 10.1007/s13369-013-0903-8
32. Pareto-Optimal Multi-objective Inversion of Geophysical Data S. Schnaidt et al. 10.1007/s00024-018-1784-2
33. Comparing calibration strategies of a conceptual snow hydrology model and their impact on model performance and parameter identifiability S. Nemri & C. Kinnard 10.1016/j.jhydrol.2019.124474
34. Multiobjective sensitivity analysis and optimization of distributed hydrologic model MOBIDIC J. Yang et al. 10.5194/hess-18-4101-2014
35. Evaluation of the Parameter Sensitivities of a Coupled Land Surface Hydrologic Model at a Critical Zone Observatory Y. Shi et al. 10.1175/JHM-D-12-0177.1
36. Comparison of Three Multiobjective Optimization Algorithms for Inverse Modeling of Vadose Zone Hydraulic Properties T. Wöhling et al. 10.2136/sssaj2007.0176
37. Multi-objective performance comparison of an artificial neural network and a conceptual rainfall—runoff model N. DE VOS & T. RIENTJES 10.1623/hysj.52.3.397
38. Current awareness 10.1002/hyp.6560
39. One decade of multi-objective calibration approaches in hydrological modelling: a review A. Efstratiadis & D. Koutsoyiannis 10.1080/02626660903526292
40. Evolutionary multiobjective optimization in water resources: The past, present, and future P. Reed et al. 10.1016/j.advwatres.2012.01.005
41. Comparative analysis of multiobjective evolutionary algorithms for random and correlated instances of multiobjective d-dimensional knapsack problems R. Shah & P. Reed 10.1016/j.ejor.2011.01.030
42. Evolutionary assimilation of streamflow in distributed hydrologic modeling using in-situ soil moisture data G. Dumedah & P. Coulibaly 10.1016/j.advwatres.2012.07.012
43. Advancing SWAT Model Calibration: A U-NSGA-III-Based Framework for Multi-Objective Optimization H. Mao et al. 10.3390/w16213030
44. Streamflow prediction in ungauged catchments using copula‐based dissimilarity measures L. Samaniego et al. 10.1029/2008WR007695
45. Many-objective optimization and visual analytics reveal key trade-offs for London’s water supply E. Matrosov et al. 10.1016/j.jhydrol.2015.11.003
46. Selecting Model Parameter Sets from a Trade-off Surface Generated from the Non-Dominated Sorting Genetic Algorithm-II G. Dumedah et al. 10.1007/s11269-010-9668-y
47. State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management J. Nicklow et al. 10.1061/(ASCE)WR.1943-5452.0000053
48. Research on Combination Forecast Mode of Conceptual Hydrological Model M. Dai et al. 10.1007/s11269-016-1401-z
49. Parallel multi-objective calibration of a component-based river temperature model C. Buahin et al. 10.1016/j.envsoft.2019.02.012
50. Screening reservoir systems by considering the efficient trade-offs—informing infrastructure investment decisions on the Blue Nile R. Geressu & J. Harou 10.1088/1748-9326/10/12/125008
51. Advancing the identification and evaluation of distributed rainfall‐runoff models using global sensitivity analysis Y. Tang et al. 10.1029/2006WR005813
52. A new selection metric for multiobjective hydrologic model calibration M. Asadzadeh et al. 10.1002/2013WR014970
53. Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework D. Hadka & P. Reed 10.1162/EVCO_a_00075
54. DEMCMC-GPU: An Efficient Multi-Objective Optimization Method with GPU Acceleration on the Fermi Architecture W. Zhu et al. 10.1007/s00354-010-0103-y
55. Assessment of a seasonal calibration technique using multiple objectives in rainfall–runoff analysis H. Kim & S. Lee 10.1002/hyp.9785
56. A new approach to solve a general system of linear inequalities based on NSGA-II R. Goyal et al. 10.1007/s13198-012-0087-8
57. Multi-objective autocalibration of SWAT model for improved low flow performance for a small snowfed catchment V. Chilkoti et al. 10.1080/02626667.2018.1505047
58. Comment on "How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration?" by Y. Tang et al., Hydrol. Earth Syst. Sci., 10, 289–307, 2006 J. Vrugt 10.5194/hess-11-1435-2007
59. A comparison of the discrete cosine and wavelet transforms for hydrologic model input data reduction A. Wright et al. 10.5194/hess-21-3827-2017
60. Navigating financial and supply reliability tradeoffs in regional drought management portfolios H. Zeff et al. 10.1002/2013WR015126
61. Are modern metaheuristics successful in calibrating simple conceptual rainfall–runoff models? A. Piotrowski et al. 10.1080/02626667.2016.1234712
62. Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation Y. Tang et al. 10.5194/hess-11-793-2007
63. An efficient framework for hydrologic model calibration on long data periods S. Razavi & B. Tolson 10.1002/2012WR013442
64. Evaluating Autoselection Methods Used for Choosing Solutions from Pareto-Optimal Set: Does Nondominance Persist from Calibration to Validation Phase? G. Dumedah et al. 10.1061/(ASCE)HE.1943-5584.0000389
65. Evaluating multiple performance criteria to calibrate the distributed hydrological model of the upper Neckar catchment T. Wöhling et al. 10.1007/s12665-013-2306-2
66. Ensemble Streamflow Forecasting across the U.S. Mid-Atlantic Region with a Distributed Hydrological Model Forced by GEFS Reforecasts R. Siddique & A. Mejia 10.1175/JHM-D-16-0243.1
67. Toward essential union between evolutionary strategy and data assimilation for model diagnostics: An application for reducing the search space of optimization problems using hydrologic genome map G. Dumedah 10.1016/j.envsoft.2014.09.025
68. Catchment Variability and Parameter Estimation in Multi-Objective Regionalisation of a Rainfall–Runoff Model D. Deckers et al. 10.1007/s11269-010-9642-8
69. A calibration framework for distributed hydrological models considering spatiotemporal parameter variations Y. Liu et al. 10.1016/j.jhydrol.2024.132273
70. Integration of GRACE mass variations into a global hydrological model S. Werth et al. 10.1016/j.epsl.2008.10.021
71. Multi-objective calibration of a distributed hydrological model (WetSpa) using a genetic algorithm M. Shafii & F. De Smedt 10.5194/hess-13-2137-2009
72. Two-Objective Design of Benchmark Problems of a Water Distribution System via MOEAs: Towards the Best-Known Approximation of the True Pareto Front Q. Wang et al. 10.1061/(ASCE)WR.1943-5452.0000460
73. Solution of a set of linear inequalities by NSGA-II R. Goyal 10.1007/s12597-011-0060-3
74. A new epsilon-dominance hierarchical Bayesian optimization algorithm for large multiobjective monitoring network design problems J. Kollat et al. 10.1016/j.advwatres.2008.01.017
75. The value of satellite‐derived snow cover images for calibrating a hydrological model in snow‐dominated catchments in Central Asia D. Duethmann et al. 10.1002/2013WR014382
76. MOMCMC: An efficient Monte Carlo method for multi-objective sampling over real parameter space Y. Li 10.1016/j.camwa.2012.09.003
77. Assimilating multi-site measurements for semi-distributed hydrological model updating J. Chen et al. 10.1016/j.quaint.2012.01.030
78. Design and implementation of a general software library for using NSGA-II with SWAT for multi-objective model calibration M. Ercan & J. Goodall 10.1016/j.envsoft.2016.06.017
79. How Hydrologic Processes Differ Spatially in a Large Basin: Multisite and Multiobjective Modeling in the Tarim River Basin G. Fang et al. 10.1029/2018JD028423
80. Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization Y. Chen et al. 10.5194/hess-20-375-2016
81. A fast hypervolume driven selection mechanism for many-objective optimisation problems S. Rostami & F. Neri 10.1016/j.swevo.2016.12.002
82. Applying multiobjective RBFNNs optimization and feature selection to a mineral reduction problem A. Guillén et al. 10.1016/j.eswa.2009.11.056
83. Parameter extrapolation to ungauged basins with a hydrological distributed model in a regional framework J. Vélez et al. 10.5194/hess-13-229-2009
84. Application of a Sampling Based on the Combined Objectives of Parameter Identification and Uncertainty Analysis of an Urban Rainfall-Runoff Model D. Zhao et al. 10.1061/(ASCE)IR.1943-4774.0000522
85. Pareto archived dynamically dimensioned search with hypervolume-based selection for multi-objective optimization M. Asadzadeh & B. Tolson 10.1080/0305215X.2012.748046
86. Reply to comment by Chu et al. on “High‐dimensional posterior exploration of hydrologic models using multiple‐try DREAM (ZS) and high‐performance computing” J. Vrugt & E. Laloy 10.1002/2013WR014425
87. A Framework for Algorithmic Improvement to Mitigate the Effects of Equifinality in the Calibration of High-dimensional Parameters for Hydrological Models X. Tang et al. 10.1007/s11269-023-03667-x
88. Evaluation of Model Parameter Convergence when Using Data Assimilation for Soil Moisture Estimation G. Dumedah & J. Walker 10.1175/JHM-D-12-0175.1
89. Confronting tipping points: Can multi-objective evolutionary algorithms discover pollution control tradeoffs given environmental thresholds? V. Ward et al. 10.1016/j.envsoft.2015.07.020
90. Enhanced watershed model evaluation incorporating hydrologic signatures and consistency within efficient surrogate multi-objective optimization W. Xia et al. 10.1016/j.envsoft.2024.105983
91. Visual analytics clarify the scalability and effectiveness of massively parallel many-objective optimization: A groundwater monitoring design example P. Reed & J. Kollat 10.1016/j.advwatres.2013.01.011
92. Many-objective de Novo water supply portfolio planning under deep uncertainty J. Kasprzyk et al. 10.1016/j.envsoft.2011.04.003
93. A WEAP-MODFLOW surface water-groundwater model for the irrigated Miyandoab plain, Urmia lake basin, Iran: Multi-objective calibration and quantification of historical drought impacts A. Dehghanipour et al. 10.1016/j.agwat.2019.105704
94. Calibration of the Global Flood Awareness System (GloFAS) using daily streamflow data F. Hirpa et al. 10.1016/j.jhydrol.2018.09.052
95. Issues of experimental design for comparing the performance of hydrologic models R. Clarke 10.1029/2007WR005927
96. A balanced calibration of water quantity and quality by multi-objective optimization for integrated water system model Y. Zhang et al. 10.1016/j.jhydrol.2016.05.001
97. Cyber-enabled autocalibration of hydrologic models to support Open Science A. Rajib et al. 10.1016/j.envsoft.2022.105561
98. HydroTest: A web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts C. Dawson et al. 10.1016/j.envsoft.2006.06.008
99. Evaluating forecasting performance for data assimilation methods: The ensemble Kalman filter, the particle filter, and the evolutionary-based assimilation G. Dumedah & P. Coulibaly 10.1016/j.advwatres.2013.07.007
100. Toward Improved Calibration of SWAT Using Season-Based Multi-Objective Optimization: a Case Study in the Jinjiang Basin in Southeastern China Y. Chen et al. 10.1007/s11269-017-1862-8
101. Propagation of CMORPH rainfall errors to REW streamflow simulation mismatch in the upper Zambezi Basin W. Gumindoga et al. 10.1016/j.ejrh.2021.100966
102. A multi-objective hierarchical calibration procedure for land surface/ecosystem models C. Varejão et al. 10.1080/17415977.2011.639453
103. Reply to J. Vrugt's comment on "How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration?" P. Reed et al. 10.5194/hess-11-1437-2007
104. Parameter sensitivity analysis for a biochemically-based photosynthesis model T. Han et al. 10.1016/j.rcar.2023.04.005
105. Parallel Evolutionary Multi-Objective Optimization on Large, Heterogeneous Clusters: An Applications Perspective P. Reed et al. 10.2514/1.36467
106. A benchmarking framework for simulation-based optimization of environmental models L. Matott et al. 10.1016/j.envsoft.2012.02.002
107. Personalized tourism product design focused on tourist expectations and online reviews: An integrated MCDM method X. Liu et al. 10.1016/j.cie.2023.109860
108. Reservoir system expansion scheduling under conflicting interests R. Geressu & J. Harou 10.1016/j.envsoft.2019.04.002
109. Toward effective many-objective optimization: Rounded-archiving S. Sahraei et al. 10.1016/j.envsoft.2019.104535
110. Optimal Design of Water Distribution Systems Using Many-Objective Visual Analytics G. Fu et al. 10.1061/(ASCE)WR.1943-5452.0000311
111. Comparing single and multi-objective hydrologic model calibration considering reservoir inflow and streamflow observations J. Bomhof et al. 10.1080/07011784.2019.1623077
112. Reducing uncertainty in predictions in ungauged basins by combining hydrologic indices regionalization and multiobjective optimization Z. Zhang et al. 10.1029/2008WR006833
113. Optimisation of water treatment works performance using genetic algorithms R. Swan et al. 10.2166/hydro.2017.083
114. Assessing River Basin Development Given Water‐Energy‐Food‐Environment Interdependencies R. Geressu et al. 10.1029/2019EF001464
115. Value recovery options portfolio optimization for remanufacturing end of life product Z. Jiang et al. 10.1016/j.jclepro.2018.10.316
116. Diagnostic Framework for Evaluating How Parametric Uncertainty Influences Agro‐Hydrologic Model Projections of Crop Yields Under Climate Change T. Karimi et al. 10.1029/2021WR031249
117. Formulation of the Evolutionary-Based Data Assimilation, and its Implementation in Hydrological Forecasting G. Dumedah 10.1007/s11269-012-0107-0
118. Multi-Objective Optimization of Low Impact Development Designs in an Urbanizing Watershed G. Zhang et al. 10.4236/ojop.2013.24013
119. Quantifying dynamic sensitivity of optimization algorithm parameters to improve hydrological model calibration W. Qi et al. 10.1016/j.jhydrol.2015.11.052
120. Extraction and Preference Ordering of Multireservoir Water Supply Rules in Dry Years L. Kang et al. 10.3390/w8010028
121. Deep learning for water quality W. Zhi et al. 10.1038/s44221-024-00202-z
122. Comparison of different multi-objective calibration criteria using a conceptual rainfall-runoff model of flood events R. Moussa & N. Chahinian 10.5194/hess-13-519-2009
123. Multiobjective training of artificial neural networks for rainfall‐runoff modeling N. de Vos & T. Rientjes 10.1029/2007WR006734
124. Estimating the Risk of River Flow under Climate Change in the Tsengwen River Basin H. Wei et al. 10.3390/w8030081
125. Uncertainty assessment and optimization of hydrological model with the Shuffled Complex Evolution Metropolis algorithm: an application to artificial neural network rainfall-runoff model J. Guo et al. 10.1007/s00477-012-0639-0
126. Enhancing the Performance of a Multiobjective Evolutionary Algorithm for Sanitary Sewer Overflow Reduction O. Ogidan & M. Giacomoni 10.1061/(ASCE)WR.1943-5452.0000774
127. Assessment of Rainfall-Sediment Yield-Runoff Prediction Uncertainty Using a Multi-objective Optimization Method G. Lee et al. 10.3741/JKWRA.2010.43.12.1011
128. Information visualization for selection in Design by Shopping A. Abi Akle et al. 10.1007/s00163-016-0235-2
129. A Novel Multi-Objective Shuffled Complex Differential Evolution Algorithm with Application to Hydrological Model Parameter Optimization J. Guo et al. 10.1007/s11269-013-0324-1
130. Watershed calibration using multistart local optimization and evolutionary optimization with radial basis function approximation C. SHOEMAKER et al. 10.1623/hysj.52.3.450
131. Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins M. Yadav et al. 10.1016/j.advwatres.2007.01.005
132. Multiobjective Optimization of Operational Responses for Contaminant Flushing in Water Distribution Networks L. Alfonso et al. 10.1061/(ASCE)0733-9496(2010)136:1(48)
133. Why do karst catchments exhibit higher sensitivity to climate change? Evidence from a modified Budyko model M. Liu et al. 10.1016/j.advwatres.2018.10.013