58 citations as recorded by crossref.

1. A Combined Optimization‐Assimilation Framework to Enhance the Predictive Skill of Community Land Model C. Zhang et al. 10.1029/2021WR029879
2. Efficient surrogate modeling methods for large-scale Earth system models based on machine-learning techniques D. Lu & D. Ricciuto 10.5194/gmd-12-1791-2019
3. Multiobjective adaptive surrogate modeling‐based optimization for parameter estimation of large, complex geophysical models W. Gong et al. 10.1002/2015WR018230
4. A Dynamic Baseline Calibration Procedure for CGE models J. Ziesmer et al. 10.1007/s10614-022-10248-4
5. A multi-objective adaptive surrogate modelling-based optimization algorithm for constrained hybrid problems R. Sun et al. 10.1016/j.envsoft.2021.105272
6. Reprint of: Active subspaces for sensitivity analysis and dimension reduction of an integrated hydrologic model J. Jefferson et al. 10.1016/j.cageo.2015.11.002
7. Assessing the weighted multi-objective adaptive surrogate model optimization to derive large-scale reservoir operating rules with sensitivity analysis J. Zhang et al. 10.1016/j.jhydrol.2016.12.008
8. Assessing MODIS carbon and water fluxes in grasslands and shrublands in semiarid regions using eddy covariance tower data Y. Li et al. 10.1080/01431161.2020.1811915
9. Potential application of hydrological ensemble prediction in forecasting floods and its components over the Yarlung Zangbo River basin, China L. Liu et al. 10.5194/hess-23-3335-2019
10. A review of parallel computing applications in calibrating watershed hydrologic models M. Asgari et al. 10.1016/j.envsoft.2022.105370
11. Improving WRF model turbine-height wind-speed forecasting using a surrogate- based automatic optimization method Z. Di et al. 10.1016/j.atmosres.2019.04.011
12. Adaptive learning of effective dynamics for online modeling of complex systems I. Kičić et al. 10.1016/j.cma.2023.116204
13. Diet composition uncertainty determines impacts on fisheries following an oil spill H. Morzaria-Luna et al. 10.1016/j.ecoser.2018.05.002
14. Optimization of high resolution COSMO model performance over Switzerland and Northern Italy A. Voudouri et al. 10.1016/j.atmosres.2018.05.026
15. Inverse Modeling of Hydrologic Parameters in CLM4 via Generalized Polynomial Chaos in the Bayesian Framework G. Karagiannis et al. 10.3390/computation10050072
16. Automatic Model Calibration: A New Way to Improve Numerical Weather Forecasting Y. Gan et al. 10.1175/BAMS-D-15-00104.1
17. Finding plausible and diverse variants of a climate model. Part II: development and validation of methodology A. Karmalkar et al. 10.1007/s00382-019-04617-3
18. Improving runoff simulation in the Western United States with Noah-MP and variable infiltration capacity L. Su et al. 10.5194/hess-28-3079-2024
19. Machine learning in agricultural and applied economics H. Storm et al. 10.1093/erae/jbz033
20. On the applicability of surrogate‐based Markov chain Monte Carlo‐Bayesian inversion to the Community Land Model: Case studies at flux tower sites M. Huang et al. 10.1002/2015JD024339
21. Integrating fundamental model uncertainty in policy analysis J. Ziesmer et al. 10.1016/j.seps.2023.101591
22. Improving the Capability of the SCOPE Model for Simulating Solar-Induced Fluorescence and Gross Primary Production Using Data from OCO-2 and Flux Towers H. Wang & J. Xiao 10.3390/rs13040794
23. Multi‐Objective Adaptive Surrogate Modeling‐Based Optimization for Distributed Environmental Models Based on Grid Sampling R. Sun et al. 10.1029/2020WR028740
24. Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model Z. Di et al. 10.1007/s11430-016-9021-6
25. A review of the global soil property maps for Earth system models Y. Dai et al. 10.5194/soil-5-137-2019
26. Quantification and attribution of errors in the simulated annual gross primary production and latent heat fluxes by two global land surface models J. Li et al. 10.1002/2015MS000583
27. Using a surrogate-assisted Bayesian framework to calibrate the runoff-generation scheme in the Energy Exascale Earth System Model (E3SM) v1 D. Xu et al. 10.5194/gmd-15-5021-2022
28. Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area Z. Di et al. 10.1007/s00382-017-3729-3
29. Multi-objective calibration by combination of stochastic and gradient-like parameter generation rules – the caRamel algorithm C. Monteil et al. 10.5194/hess-24-3189-2020
30. Integration of Adaptive Emulators and Sensitivity Analysis for Enhancement of Complex Hydrological Models V. Budamala & A. Baburao Mahindrakar 10.1007/s40710-020-00468-x
31. Sensitivity analysis of the convective‐scale AROME model to physical and dynamical parameters M. Wimmer et al. 10.1002/qj.4239
32. Ten strategies towards successful calibration of environmental models J. Mai 10.1016/j.jhydrol.2023.129414
33. Parametric Sensitivity and Uncertainty Quantification in the Version 1 of E3SM Atmosphere Model Based on Short Perturbed Parameter Ensemble Simulations Y. Qian et al. 10.1029/2018JD028927
34. Process refinement contributed more than parameter optimization to improve the CoLM's performance in simulating the carbon and water fluxes in a grassland Y. Li et al. 10.1016/j.agrformet.2020.108067
35. Parameter optimization for carbon and water fluxes in two global land surface models based on surrogate modelling J. Li et al. 10.1002/joc.5428
36. MULTI-OBJECTIVE PARAMETER OPTIMIZATION AND UNCERTAINTY ASSESSMENT IN A LAND SURFACE MODEL BY MULTIPLE SATELLITES’ OBSERVATIONS S. NOMURA & Y. SAWADA 10.2208/jscejhe.77.2_I_1351
37. Multi-Objective Optimization of Laminated Functionally Graded Carbon Nanotube-Reinforced Composite Plates Using Deep Feedforward Neural Networks-NSGAII Algorithm D. Ly et al. 10.1142/S0219876221500651
38. A heterogeneous computing accelerated SCE-UA global optimization method using OpenMP, OpenCL, CUDA, and OpenACC G. Kan et al. 10.2166/wst.2017.322
39. Uncertainty Quantification and Bayesian Inference of Cloud Parameterization in the NCAR Single Column Community Atmosphere Model (SCAM6) R. Pathak et al. 10.3389/fclim.2021.670740
40. Active subspaces for sensitivity analysis and dimension reduction of an integrated hydrologic model J. Jefferson et al. 10.1016/j.cageo.2015.07.001
41. Multiobjective ensemble surrogate-based optimization algorithm for groundwater optimization designs M. Wu et al. 10.1016/j.jhydrol.2022.128159
42. An adaptive surrogate modeling-based sampling strategy for parameter optimization and distribution estimation (ASMO-PODE) W. Gong & Q. Duan 10.1016/j.envsoft.2017.05.005
43. How parameter specification of an Earth system model of intermediate complexity influences its climate simulations Y. Shi et al. 10.1186/s40645-019-0294-x
44. Calibration of the E3SM Land Model Using Surrogate‐Based Global Optimization D. Lu et al. 10.1002/2017MS001134
45. Calibration of WRF model parameters using multiobjective adaptive surrogate model-based optimization to improve the prediction of the Indian summer monsoon S. Chinta & C. Balaji 10.1007/s00382-020-05288-1
46. Improved Land Evapotranspiration Simulation of the Community Land Model Using a Surrogate-Based Automatic Parameter Optimization Method C. Zhang et al. 10.3390/w12040943
47. Metaheuristic algorithms for groundwater model parameter inversion: Advances and prospects J. Chen & Z. Dai 10.1016/j.deepre.2024.100009
48. Evaluation of parameter interaction effect of hydrological models using the sparse polynomial chaos (SPC) method H. Wang et al. 10.1016/j.envsoft.2019.104612
49. Enhance the prediction of complex hydrological models by pseudo-simulators V. Budamala & A. Baburao Mahindrakar 10.1080/10106049.2019.1629646
50. A surrogate modeling method for distributed land surface hydrological models based on deep learning R. Sun et al. 10.1016/j.jhydrol.2023.129944
51. Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model Y. Qian et al. 10.1007/s00382-023-06977-3
52. In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics Y. Yang et al. 10.1029/2018WR024178
53. A Brief Review of Random Forests for Water Scientists and Practitioners and Their Recent History in Water Resources H. Tyralis et al. 10.3390/w11050910
54. Parameter Calibration to Improve the Prediction of Tropical Cyclones over the Bay of Bengal Using Machine Learning–Based Multiobjective Optimization H. Baki et al. 10.1175/JAMC-D-21-0184.1
55. A stepwise surrogate model for parameter calibration of the Variable Infiltration Capacity model: the case of the upper Brahmaputra, Tibet Plateau H. Gu et al. 10.2166/hydro.2020.010
56. An Improved Tandem Neural Network Architecture for Inverse Modeling of Multicomponent Reactive Transport in Porous Media J. Chen et al. 10.1029/2021WR030595
57. Water and heat coupling processes and its simulation in frozen soils: Current status and future research directions G. Hu et al. 10.1016/j.catena.2022.106844
58. Classification of hydrological parameter sensitivity and evaluation of parameter transferability across 431 US MOPEX basins H. Ren et al. 10.1016/j.jhydrol.2016.02.042