256 citations as recorded by crossref.

1. What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling T. Wagener & F. Pianosi 10.1016/j.earscirev.2019.04.006
2. An experimental approach to reduce the parametric dimensionality for rainfall–runoff models J. Chen et al. 10.2166/nh.2016.145
3. Assessment of combined sewer overflows impacts under flooding in coastal cities H. Abbasi et al. 10.2166/wcc.2021.322
4. Temporal dynamics of model parameter sensitivity for computationally expensive models with the Fourier amplitude sensitivity test D. Reusser et al. 10.1029/2010WR009947
5. A comprehensive framework for HSPF hydrological parameter sensitivity, optimization and uncertainty evaluation based on SVM surrogate model- A case study in Qinglong River watershed, China L. Xingpo et al. 10.1016/j.envsoft.2021.105126
6. Issues of experimental design for comparing the performance of hydrologic models R. Clarke 10.1029/2007WR005927
7. Global sensitivity analysis of an energy–economy model of the residential building sector F. Branger et al. 10.1016/j.envsoft.2015.03.021
8. Determination of the saturated film conductivity to improve the EMFX model in describing the soil hydraulic properties over the entire moisture range Y. Wang et al. 10.1016/j.jhydrol.2017.03.063
9. An Urban Sociohydrologic Model for Exploration of Beijing's Water Sustainability Challenges and Solution Spaces B. Li et al. 10.1029/2018WR023816
10. Identifying sensitive sources and key control handles for the reduction of greenhouse gas emissions from wastewater treatment C. Sweetapple et al. 10.1016/j.watres.2014.06.002
11. Sensitivity analysis of Takagi-Sugeno-Kang rainfall-runoff fuzzy models A. Jacquin & A. Shamseldin 10.5194/hess-13-41-2009
12. Assessment of the parameter sensitivity for the ORYZA model at the regional scale - A case study in the Yangtze River Basin Q. Yu et al. 10.1016/j.envsoft.2022.105575
13. Parameter sensitivity analysis of a sea ice melt pond parametrisation and its emulation using neural networks S. Driscoll et al. 10.1016/j.jocs.2024.102231
14. Variance‐Based Global Sensitivity Analysis: A Methodological Framework and Case Study for Microkinetic Modeling B. van den Boorn et al. 10.1002/adts.202200615
15. Retrofitting low-performance units to abate sewer overflow pollution based on mathematical model and Sobol algorithm Z. Zhao et al. 10.1007/s42241-023-0048-5
16. Validation of a microalgal growth model accounting with inorganic carbon and nutrient kinetics for wastewater treatment B. Decostere et al. 10.1016/j.cej.2015.09.111
17. Advancing Diagnostic Model Evaluation to Better Understand Water Shortage Mechanisms in Institutionally Complex River Basins A. Hadjimichael et al. 10.1029/2020WR028079
18. Changes of potential evapotranspiration and its sensitivity across China under future climate scenarios P. Zeng et al. 10.1016/j.atmosres.2021.105763
19. Global Sensitivity Analysis of environmental models: Convergence and validation F. Sarrazin et al. 10.1016/j.envsoft.2016.02.005
20. Seasonal Hydrologic Forecasting: Do Multimodel Ensemble Averages Always Yield Improvements in Forecast Skill? T. Bohn et al. 10.1175/2010JHM1267.1
21. Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models T. Khan & J. Perlinger 10.5194/gmd-10-3861-2017
22. How much can we gain with increasing model complexity with the same model concepts? H. Li et al. 10.1016/j.jhydrol.2015.05.044
23. A Process‐Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services Z. Niu et al. 10.1029/2020MS002451
24. Evaluation of water quality of Chahnimeh as natural reservoirs from Sistan region in southwestern Iran: a Monte Carlo simulation and Sobol sensitivity assessment H. Kamani et al. 10.1007/s11356-023-26879-5
25. A modified Sobol′ sensitivity analysis method for decision-making in environmental problems A. Ganji et al. 10.1016/j.envsoft.2015.10.001
26. Quantifying the impacts of land cover change on hydrological responses in the Mahanadi river basin in India S. Naha et al. 10.5194/hess-25-6339-2021
27. Parameter sensitivity of a distributed enhanced temperature-index melt model M. Heynen et al. 10.3189/2013AoG63A537
28. Learning from model improvement: On the contribution of complementary data to process understanding F. Fenicia et al. 10.1029/2007WR006386
29. Isolating parameter sensitivity in reach scale transient storage modeling N. Schmadel et al. 10.1016/j.advwatres.2015.12.020
30. Assessing global parameters of slope stability model using Earth data observations for forecasting rainfall – induced shallow landslides J. Thomas et al. 10.1016/j.jappgeo.2023.104994
31. Experimental and Model-Based Analysis to Optimize Microalgal Biomass Productivity in a Pilot-Scale Tubular Photobioreactor T. Weise et al. 10.3389/fbioe.2020.00453
32. Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins R. Arsenault et al. 10.1016/j.advwatres.2015.08.014
33. Improving structure identifiability of hydrological processes by temporal sensitivity with a flexible modeling framework L. Zhou et al. 10.1016/j.jhydrol.2022.128843
34. Are we unnecessarily constraining the agility of complex process-based models? P. Mendoza et al. 10.1002/2014WR015820
35. Advances and visions in large-scale hydrological modelling: findings from the 11th Workshop on Large-Scale Hydrological Modelling P. Döll et al. 10.5194/adgeo-18-51-2008
36. A downward structural sensitivity analysis of hydrological models to improve low-flow simulation R. Pushpalatha et al. 10.1016/j.jhydrol.2011.09.034
37. A post audit and inverse modeling in reactive transport: 50years of artificial recharge in the Amsterdam Water Supply Dunes R. Karlsen et al. 10.1016/j.jhydrol.2012.05.019
38. Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods P. Vanrolleghem et al. 10.1016/j.jhydrol.2014.12.056
39. Three complementary methods for sensitivity analysis of a water quality model X. Sun et al. 10.1016/j.envsoft.2012.04.010
40. Parameter sensitivity analysis and optimization for a satellite‐based evapotranspiration model across multiple sites using Moderate Resolution Imaging Spectroradiometer and flux data K. Zhang et al. 10.1002/2016JD025768
41. Application of a pseudo simulator to evaluate the sensitivity of parameters in complex watershed models K. Sudheer et al. 10.1016/j.envsoft.2010.07.007
42. Sensitivity analysis, calibration and validation of EPIC for modelling soil phosphorus dynamics in Swiss agro-ecosystems R. Della Peruta et al. 10.1016/j.envsoft.2014.08.018
43. On selection of the optimal data time interval for real-time hydrological forecasting J. Liu & D. Han 10.5194/hess-17-3639-2013
44. Assessing Uncertainty in Multicriteria Evaluation of Centralized and Decentralized Dual Water Supply Strategies J. Cole et al. 10.1061/(ASCE)WR.1943-5452.0001572
45. Time scale dependent sensitivities of the XinAnJiang model parameters M. Lu & X. Li 10.3178/hrl.8.51
46. How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model E. Rouzies et al. 10.5194/gmd-16-3137-2023
47. Integrating UAV and Freely Available Space-Borne Data to Describe Tree Decline Across Semi-arid Mountainous Forests M. Ghasemi et al. 10.1007/s10666-023-09911-3
48. A two-step sensitivity analysis for hydrological signatures in Jinhua River Basin, East China S. Pan et al. 10.1080/02626667.2017.1388917
49. Estimating the Increase in Regional Evaporative Water Consumption as a Result of Vegetation Restoration Over the Loess Plateau, China R. Shao et al. 10.1029/2019JD031295
50. Characterization of watershed model behavior across a hydroclimatic gradient K. van Werkhoven et al. 10.1029/2007WR006271
51. Estimation of soil loss by the WATEM/SEDEM model using an automatic parameter estimation procedure N. Bezak et al. 10.1007/s12665-015-4534-0
52. Free vibration analysis and multi-objective robust optimization of three-dimensional pyramidal truss core sandwich plates with interval uncertain parameters Y. Chen et al. 10.1016/j.euromechsol.2024.105401
53. An empirical workflow to integrate uncertainty and sensitivity analysis to evaluate agent-based simulation outputs C. Abreu & C. Ralha 10.1016/j.envsoft.2018.06.013
54. Evaluation of an urban drainage system and its resilience using remote sensing and GIS G. Guptha et al. 10.1016/j.rsase.2021.100601
55. Foodweb modeling for polychlorinated biphenyls (PCBs) in the Twelvemile Creek Arm of Lake Hartwell, South Carolina, USA B. Rashleigh et al. 10.1016/j.ecolmodel.2008.09.007
56. Parameter regionalization of a monthly water balance model for the conterminous United States A. Bock et al. 10.5194/hess-20-2861-2016
57. Assessing effects of model complexity and structure on predictions of hydrological responses using serial and parallel model design H. Chien & D. Mackay 10.1002/hyp.13594
58. Sources of uncertainty in modeling the glaciohydrological response of a Karakoram watershed to climate change S. Ragettli et al. 10.1002/wrcr.20450
59. Parameter Sensitivity of a Surface Water Quality Model of the Lower South Saskatchewan River—Comparison Between Ice-On and Ice-Off Periods N. Hosseini et al. 10.1007/s10666-016-9541-3
60. Calibration and validation of fatigue lifetime model in complex structures based on multi-level data X. Liu et al. 10.1016/j.ijfatigue.2022.106783
61. Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1 J. Zhu & M. Young 10.1111/j.1752-1688.2009.00312.x
62. 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
63. Impacts of Climate Change on the Water Quality of a Regulated Prairie River N. Hosseini et al. 10.3390/w9030199
64. How to Tailor My Process‐Based Hydrological Model? Dynamic Identifiability Analysis of Flexible Model Structures T. Pilz et al. 10.1029/2020WR028042
65. A new multimedia contaminant fate model for China: How important are environmental parameters in influencing chemical persistence and long-range transport potential? Y. Zhu et al. 10.1016/j.envint.2014.03.020
66. Quantification of predictive uncertainty with a metamodel: toward more efficient hydrologic simulations V. Tran & J. Kim 10.1007/s00477-019-01703-0
67. A simple and efficient method for global sensitivity analysis based on cumulative distribution functions F. Pianosi & T. Wagener 10.1016/j.envsoft.2015.01.004
68. Model‐based analysis of the influence of catchment properties on hydrologic partitioning across five mountain headwater subcatchments C. Kelleher et al. 10.1002/2014WR016147
69. Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River basin, Australia T. van Emmerik et al. 10.5194/hess-18-4239-2014
70. Quantifying plasticity in simulation models R. Confalonieri et al. 10.1016/j.ecolmodel.2011.11.022
71. A general framework for Dynamic Emulation Modelling in environmental problems A. Castelletti et al. 10.1016/j.envsoft.2012.01.002
72. Modified DNDC model to improve performance of soil temperature simulation under plastic film mulching and snow cover W. Zhao et al. 10.1016/j.compag.2023.108354
73. Calibration of Rainfall-Runoff Model in Urban Watersheds for Stormwater Management Assessment N. Mancipe-Munoz et al. 10.1061/(ASCE)WR.1943-5452.0000382
74. Distribution-based sensitivity analysis from a generic input-output sample F. Pianosi & T. Wagener 10.1016/j.envsoft.2018.07.019
75. Characterization of process-oriented hydrologic model behavior with temporal sensitivity analysis for flash floods in Mediterranean catchments P. Garambois et al. 10.5194/hess-17-2305-2013
76. Sensitivity analysis of effective population size to demographic parameters in house sparrow populations M. Stubberud et al. 10.1111/mec.14057
77. Simulating typhoon-induced storm hydrographs in subtropical mountainous watershed: an integrated 3-layer TOPMODEL J. Huang et al. 10.5194/hess-13-27-2009
78. Sensitivity analysis of environmental models: A systematic review with practical workflow F. Pianosi et al. 10.1016/j.envsoft.2016.02.008
79. Assessing parameter importance of the Common Land Model based on qualitative and quantitative sensitivity analysis J. Li et al. 10.5194/hess-17-3279-2013
80. A General Probabilistic Framework for uncertainty and global sensitivity analysis of deterministic models: A hydrological case study G. Baroni & S. Tarantola 10.1016/j.envsoft.2013.09.022
81. Sensitivity analysis of the DeNitrification and Decomposition model for simulating regional carbon budget at the wetland-grassland area on the Zoige Plateau, china J. Wang et al. 10.1007/s11629-015-3520-z
82. Modeling the Compression Stiffness Degradation in Circular Elastomeric Bearings due to Fatigue P. Deng & G. Warn 10.1061/(ASCE)EM.1943-7889.0000947
83. A Matlab toolbox for Global Sensitivity Analysis F. Pianosi et al. 10.1016/j.envsoft.2015.04.009
84. Estimating parameters of the variable infiltration capacity model using ant colony optimization J. Yue et al. 10.2166/wst.2016.282
85. Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain M. Sadki et al. 10.5194/gmd-16-427-2023
86. An efficient integrated approach for global sensitivity analysis of hydrological model parameters C. Zhan et al. 10.1016/j.envsoft.2012.10.009
87. Sensitivity analysis of spatial models L. Lilburne & S. Tarantola 10.1080/13658810802094995
88. Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model F. Khorashadi Zadeh et al. 10.1016/j.envsoft.2017.02.001
89. Characterizing parameter sensitivity and uncertainty for a snow model across hydroclimatic regimes M. He et al. 10.1016/j.advwatres.2010.10.002
90. Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding C. Kelleher et al. 10.5194/hess-21-3325-2017
91. Screening‐Level Sensitivity Analysis for the Design of Pump‐and‐Treat Systems L. Matott 10.1111/j.1745-6592.2011.01375.x
92. Development of a calibration approach using DNDC and PEST for improving estimates of management impacts on water and nutrient dynamics in an agricultural system A. Bhattarai et al. 10.1016/j.envsoft.2022.105494
93. Understanding hydrological flow paths in conceptual catchment models using uncertainty and sensitivity analysis E. Mockler et al. 10.1016/j.cageo.2015.08.015
94. Improvements to the hydrological processes of the Town Energy Balance model (TEB-Veg, SURFEX v7.3) for urban modelling and impact assessment X. Stavropulos-Laffaille et al. 10.5194/gmd-11-4175-2018
95. Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment D. Kavetski et al. 10.1029/2010WR009525
96. Significant variables affecting the performance of concrete panels impacted by wind-borne projectiles: A global sensitivity analysis S. Zamanian et al. 10.1016/j.ijimpeng.2020.103650
97. Variance-based sensitivity analysis of a forest growth model X. Song et al. 10.1016/j.ecolmodel.2012.08.005
98. Parameter sensitivity analysis and optimization of Noah land surface model with field measurements from Huaihe River Basin, China T. Hou et al. 10.1007/s00477-015-1033-5
99. A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions C. Schürz et al. 10.5194/hess-23-1211-2019
100. Stepwise sensitivity analysis from qualitative to quantitative: Application to the terrestrial hydrological modeling of a Conjunctive Surface‐Subsurface Process (CSSP) land surface model Y. Gan et al. 10.1002/2014MS000406
101. An Improved Approach for Estimating Pan Evaporation Using a New Aerodynamic Mechanism Model G. Qiu et al. 10.1029/2020WR027870
102. Assimilation of AMSR-E snow water equivalent data in a spatially-lumped snow model D. Dziubanski & K. Franz 10.1016/j.jhydrol.2016.05.046
103. Numerical model of the irradiance field surrounding a UV disinfection robot L. De Matteis et al. 10.1088/2057-1976/ac7e6e
104. Innovative Digital Stochastic Methods for Multidimensional Sensitivity Analysis in Air Pollution Modelling V. Todorov & I. Dimov 10.3390/math10122146
105. Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model S. Ragettli et al. 10.1016/j.advwatres.2015.01.013
106. Evaluation of TOPLATS on three Mediterranean catchments J. Loizu et al. 10.1016/j.jhydrol.2016.05.025
107. A Bayesian-based multilevel factorial analysis method for analyzing parameter uncertainty of hydrological model Y. Liu et al. 10.1016/j.jhydrol.2017.08.048
108. Future potential evapotranspiration changes and contribution analysis in Zhejiang Province, East China Y. Xu et al. 10.1002/2013JD021245
109. Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models J. Herman et al. 10.5194/hess-17-2893-2013
110. Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction J. Chu et al. 10.5194/hess-19-3557-2015
111. An approach for global sensitivity analysis of a complex environmental model to spatial inputs and parameters: A case study of an agro-hydrological model P. Moreau et al. 10.1016/j.envsoft.2013.04.006
112. MODIS-Based Potential Evapotranspiration Demand Curves for the Sacramento Soil Moisture Accounting Model A. Bowman et al. 10.1061/(ASCE)HE.1943-5584.0001261
113. Sensitivity analysis and estimation using a hierarchical Bayesian method for the parameters of the FvCB biochemical photosynthetic model T. Han et al. 10.1007/s11120-019-00684-z
114. Modified calibration strategies and parameter regionalization potential for streamflow estimation using a hydrological model S. Guniganti et al. 10.1080/02626667.2024.2335294
115. Uncertainty, sensitivity analysis and the role of data based mechanistic modeling in hydrology M. Ratto et al. 10.5194/hess-11-1249-2007
116. Integration of Remote Sensing Evapotranspiration into Multi-Objective Calibration of Distributed Hydrology–Soil–Vegetation Model (DHSVM) in a Humid Region of China S. Pan et al. 10.3390/w10121841
117. A new approach to evaluate spatiotemporal dynamics of controlling parameters in distributed environmental models Z. Chen et al. 10.1016/j.envsoft.2016.10.005
118. The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support S. Razavi et al. 10.1016/j.envsoft.2020.104954
119. An increasing trend in the ratio of transpiration to total terrestrial evapotranspiration in China from 1982 to 2015 caused by greening and warming Z. Niu et al. 10.1016/j.agrformet.2019.107701
120. Stability mechanism and control of the pumpable supports in longwall recovery room D. Zhang et al. 10.1016/j.ijmst.2024.07.006
121. Global sensitivity analysis for a prediction model of soil solute transfer into surface runoff C. Huang et al. 10.1016/j.jhydrol.2021.126342
122. Many-objective de Novo water supply portfolio planning under deep uncertainty J. Kasprzyk et al. 10.1016/j.envsoft.2011.04.003
123. Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest B. Bahrami et al. 10.5194/gmd-15-6957-2022
124. Global sensitivity analysis of a model related to memory formation in synapses: Model reduction based on epistemic parameter uncertainties and related issues D. Kulasiri et al. 10.1016/j.jtbi.2017.02.003
125. Evaluation of a new observationally based channel parameterization for the National Water Model A. Heldmyer et al. 10.5194/hess-26-6121-2022
126. An approach to measure parameter sensitivity in watershed hydrological modelling T. Ranatunga et al. 10.1080/02626667.2016.1174335
127. Regional analysis of parameter sensitivity for simulation of streamflow and hydrological fingerprints S. Höllering et al. 10.5194/hess-22-203-2018
128. Sobol′’s sensitivity analysis for a distributed hydrological model of Yichun River Basin, China C. Zhang et al. 10.1016/j.jhydrol.2012.12.005
129. Sensitivity analysis and calibration of a dynamic physically based slope stability model T. Zieher et al. 10.5194/nhess-17-971-2017
130. Modeling and uncertainty analysis of carbon and water fluxes in a broad-leaved Korean pine mixed forest based on model-data fusion X. Ren et al. 10.1016/j.ecolmodel.2018.03.013
131. Auswahl der Modellkomplexität für die Beschreibung der Sauerstoffverhältnisse in Fließgewässern und Poldern während Hochwasserereignissen I. Pech et al. 10.1007/s00506-008-0020-1
132. A systematic assessment and reduction of parametric uncertainties for a distributed hydrological model Y. Gan et al. 10.1016/j.jhydrol.2018.07.055
133. Identification of the Controlling Mechanism for Predicting Critical Loads in Elastomeric Bearings X. Han et al. 10.1061/(ASCE)ST.1943-541X.0000811
134. Use of a scenario-neutral approach to identify the key hydro-meteorological attributes that impact runoff from a natural catchment D. Guo et al. 10.1016/j.jhydrol.2017.09.021
135. Application of distributed hydrological models for predictions in ungauged basins: a method to quantify predictive uncertainty R. Cibin et al. 10.1002/hyp.9721
136. Temporal Scale‐Dependent Sensitivity Analysis for Hydrological Model Parameters Using the Discrete Wavelet Transform and Active Subspaces D. Bittner et al. 10.1029/2020WR028511
137. Lumped parameter sensitivity analysis of a distributed hydrological model within tropical and temperate catchments L. Cuo et al. 10.1002/hyp.8017
138. Variance Based Sensitivity Analysis of FLake Lake Model for Global Land Surface Modeling A. Bernus et al. 10.1029/2019JD031928
139. Identifiability of transient storage model parameters along a mountain stream C. Kelleher et al. 10.1002/wrcr.20413
140. Parameter Analysis and Estimates for the MODIS Evapotranspiration Algorithm and Multiscale Verification K. Zhang et al. 10.1029/2018WR023485
141. Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework M. Raleigh et al. 10.5194/hess-19-3153-2015
142. Transferability of a Conceptual Hydrological Model across Different Temporal Scales and Basin Sizes S. Sheng et al. 10.1007/s11269-020-02594-5
143. Practical Use of Computationally Frugal Model Analysis Methods M. Hill et al. 10.1111/gwat.12330
144. Data-Driven Sensitivity Analysis for Static Mechanical Properties of Additively Manufactured Ti–6Al–4V A. Sharma et al. 10.1115/1.4051799
145. Proposal for the Introduction of the Spatial Perspective in the Application of Global Sensitivity Analysis W. Plata-Rocha et al. 10.4236/jgis.2012.46055
146. Exploring the potential for parameter transfer from daily to hourly time step in the HYPE model for Sweden D. Fuentes-Andino et al. 10.1080/02626667.2022.2121165
147. 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
148. Sensitivity analysis and auto-calibration of ORYZA2000 using simulation-optimization framework B. Soundharajan & K. Sudheer 10.1007/s10333-011-0293-z
149. DGSA: A Matlab toolbox for distance-based generalized sensitivity analysis of geoscientific computer experiments J. Park et al. 10.1016/j.cageo.2016.08.021
150. A comprehensive assessment and comparison of the impacts of storage parameters on solute transport in streams using a novel framework S. Khodambashi Emami & M. Mazaheri 10.1016/j.jhydrol.2024.130873
151. Potential evapotranspiration changes in Lancang River Basin and Yarlung Zangbo River Basin, southwest China D. Ma et al. 10.1080/02626667.2018.1524147
152. Modelling bidirectional modulations in synaptic plasticity: A biochemical pathway model to understand the emergence of long term potentiation (LTP) and long term depression (LTD) Y. He et al. 10.1016/j.jtbi.2016.05.015
153. Bioenergetic and water quality modeling for eutrophication assessment of El Pañe Reservoir, Peru A. Mamani Larico et al. 10.1016/j.ecohyd.2020.08.004
154. Exploring snow model parameter sensitivity using Sobol' variance decomposition E. Houle et al. 10.1016/j.envsoft.2016.11.024
155. Data-driven multi-objective affective product design integrating three-dimensional form and color Z. Wang et al. 10.1007/s00521-022-07232-2
156. Hydrological Simulation and Parameter Optimization Based on the Distributed Xin’anjiang Model and the Particle Swarm Optimization Algorithm: A Case Study of Xunhe Watershed in Shandong, China Z. Wang et al. 10.3390/w16223168
157. Assessing the predictive impact of factor fixing with an adaptive uncertainty-based approach Q. Wang et al. 10.1016/j.envsoft.2021.105290
158. 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
159. 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
160. Flood hazard mapping for data-scarce and ungauged coastal river basins using advanced hydrodynamic models, high temporal-spatial resolution remote sensing precipitation data, and satellite imageries M. Trinh & F. Molkenthin 10.1007/s11069-021-04843-1
161. Improved Understanding of River Ice Processes Using Global Sensitivity Analysis Approaches R. Sheikholeslami et al. 10.1061/(ASCE)HE.1943-5584.0001574
162. A non-stationary cost-benefit analysis approach for extreme flood estimation to explore the nexus of ‘Risk, Cost and Non-stationarity’ W. Qi 10.1016/j.jhydrol.2017.09.009
163. Increasing parameter identifiability through clustered time-varying sensitivity analysis L. Wang et al. 10.1016/j.envsoft.2024.106189
164. Global Sensitivity of Penman–Monteith Reference Evapotranspiration to Climatic Variables in Mato Grosso, Brazil M. Sabino & A. de Souza 10.3390/earth4030038
165. Quantifying uncertainty in urban flooding analysis considering hydro-climatic projection and urban development effects I. Jung et al. 10.5194/hess-15-617-2011
166. Sensitivity and Interaction Analysis Based on Sobol’ Method and Its Application in a Distributed Flood Forecasting Model H. Wan et al. 10.3390/w7062924
167. Evaluating the fate of six common pharmaceuticals using a reactive transport model: Insights from a stream tracer test J. Riml et al. 10.1016/j.scitotenv.2013.03.077
168. Sobol's sensitivity analysis for a fuel cell stack assembly model with the aid of structure-selection techniques W. Zhang et al. 10.1016/j.jpowsour.2015.08.076
169. How can expert knowledge increase the realism of conceptual hydrological models? A case study based on the concept of dominant runoff process in the Swiss Pre-Alps M. Antonetti & M. Zappa 10.5194/hess-22-4425-2018
170. Environmental risk of dissolved oxygen depletion of diverted flood waters in river polder systems – A quasi-2D flood modelling approach K. Lindenschmidt et al. 10.1016/j.scitotenv.2008.11.024
171. Evaluating Hydrologic Behavior of Hydrology Simulation using Time Area (HYSTAR) Model through Sensitivity Analysis Y. Her 10.5389/KSAE.2015.57.3.041
172. Parameters Sensitivity Analysis of the Xin’anjiang Model under Different Temporal and Spatial Scales 晟. 盛 10.12677/JWRR.2018.76061
173. Evaluation of statistical models for forecast errors from the HBV model K. Engeland et al. 10.1016/j.jhydrol.2010.01.018
174. Diagnostic Assessment of Search Controls and Failure Modes in Many-Objective Evolutionary Optimization D. Hadka & P. Reed 10.1162/EVCO_a_00053
175. Understanding catchment behavior through stepwise model concept improvement F. Fenicia et al. 10.1029/2006WR005563
176. A primer on thermodynamic-based models for deciphering transcriptional regulatory logic J. Dresch et al. 10.1016/j.bbagrm.2013.04.011
177. Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis J. Yang 10.1016/j.envsoft.2010.10.007
178. Inferring model structural deficits by analyzing temporal dynamics of model performance and parameter sensitivity D. Reusser & E. Zehe 10.1029/2010WR009946
179. Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models O. Rakovec et al. 10.1002/2013WR014063
180. Historical pan evaporation changes in the Qiantang River Basin, East China Y. Xu et al. 10.1002/joc.4470
181. Development and application of a hybrid artificial neural network model for simulating future stream flows in catchments with limited in situ observed data S. Mugume et al. 10.2166/hydro.2024.066
182. Epistemic uncertainties and natural hazard risk assessment – Part 2: What should constitute good practice? K. Beven et al. 10.5194/nhess-18-2769-2018
183. Modeling risk analysis for forecasting peak discharge during flooding prevention and warning operation S. Wu et al. 10.1007/s00477-010-0436-6
184. Robust high-dimensional screening A. Kim et al. 10.1016/j.envsoft.2021.105270
185. Modeling the relationship between air temperature and grapefruit quality traits C. Zhang et al. 10.1002/jsfa.12219
186. Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications X. Song et al. 10.1016/j.jhydrol.2015.02.013
187. Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation S. Camici et al. 10.5194/gmd-15-6935-2022
188. Fuzzy-Based Model for Predicting Failure of Oil Pipelines A. Senouci et al. 10.1061/(ASCE)IS.1943-555X.0000181
189. Human Health Implication of Major and Trace Elements Present in Commercial Crustaceans of a Traditional Seafood Marketing Region, Egypt G. El-Said et al. 10.1007/s12011-020-02126-7
190. Contribution of the satellite-data driven snow routine to a karst hydrological model S. Çallı et al. 10.1016/j.jhydrol.2022.127511
191. Identifying key sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment C. Sweetapple et al. 10.1016/j.watres.2013.05.021
192. What drives uncertainty surrounding riverine flood risks? I. Hosseini-Shakib et al. 10.1016/j.jhydrol.2024.131055
193. Analysis of the behavior of a rainfall–runoff model using three global sensitivity analysis methods evaluated at different temporal scales C. Massmann & H. Holzmann 10.1016/j.jhydrol.2012.09.026
194. 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
195. Sensitivity and identifiability of stream flow generation parameters of the SWAT model R. Cibin et al. 10.1002/hyp.7568
196. Time‐varying sensitivity analysis clarifies the effects of watershed model formulation on model behavior J. Herman et al. 10.1002/wrcr.20124
197. Modeling Soil Organic Carbon Changes under Alternative Climatic Scenarios and Soil Properties Using DNDC Model at a Semi-Arid Mediterranean Environment I. Lembaid et al. 10.3390/cli10020023
198. Sobol’ sensitivity analysis of a complex environmental model J. Nossent et al. 10.1016/j.envsoft.2011.08.010
199. Iterative integration of deep learning in hybrid Earth surface system modelling M. Chen et al. 10.1038/s43017-023-00452-7
200. Valuing carbon assets for high-tech with application to the wind energy industry L. Han et al. 10.1016/j.enpol.2015.09.025
201. Deep Uncertainties in Sea‐Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management P. Oddo et al. 10.1111/risa.12888
202. Sobol sensitivity approach for the appraisal of geomedical health risks associated with oral intake and dermal pathways of groundwater fluoride in a semi-arid region of south India D. Karunanidhi et al. 10.1016/j.ecoenv.2020.110438
203. Cloud computing for integrated stochastic groundwater uncertainty analysis Y. Liu et al. 10.1080/17538947.2012.687778
204. Evaluation of global sensitivity analysis methods for computational structural mechanics problems C. Crusenberry et al. 10.1017/dce.2023.23
205. Perceptions of how occupants adopt water conservation behaviors under psychosocial processes: A complementary dual-stage SEM-ANN perspective S. Shahangian et al. 10.1016/j.scs.2024.105354
206. Evaluation of Sentinel-1, SMAP and SMOS surface soil moisture products for distributed eco-hydrological modelling in Mediterranean forest basins J. Gomis-Cebolla et al. 10.1016/j.jhydrol.2022.127569
207. A novel linear spectral unmixing-based method for tree decline monitoring by fusing UAV-RGB and optical space-borne data M. Ghasemi et al. 10.1080/01431161.2024.2305630
208. Improving risk assessment in financial feasibility of international engineering projects: A risk driver perspective J. Liu et al. 10.1016/j.ijproman.2016.11.004
209. Sensitivity of Simulating Hydrologic Processes to Gauge and Radar Rainfall Data in Subtropical Coastal Catchments J. Diaz-Ramirez et al. 10.1007/s11269-012-0088-z
210. An analysis of parameter sensitivities of preference-inspired co-evolutionary algorithms R. Wang et al. 10.1080/00207721.2015.1008600
211. Vegetation controls on surface energy partitioning and water budget over China X. Lan et al. 10.1016/j.jhydrol.2020.125646
212. Inaction and climate stabilization uncertainties lead to severe economic risks M. Butler et al. 10.1007/s10584-014-1283-0
213. Global sensitivity analysis for an integrated model for simulation of nitrogen dynamics under the irrigation with treated wastewater H. Sun et al. 10.1007/s11356-015-4860-5
214. A dynamic parameter identification method for the 5-DOF hybrid robot based on sensitivity analysis Z. Luo et al. 10.1108/IR-08-2023-0178
215. Multi-method global sensitivity analysis of flood inundation models F. Pappenberger et al. 10.1016/j.advwatres.2007.04.009
216. Identifying parametric controls and dependencies in integrated assessment models using global sensitivity analysis M. Butler et al. 10.1016/j.envsoft.2014.05.001
217. Time-dependent global sensitivity analysis of the C-RIVE biogeochemical model in contrasted hydrological and trophic contexts S. Wang et al. 10.1016/j.watres.2018.07.033
218. Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones D. Guo et al. 10.5194/hess-21-2107-2017
219. A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model Y. Gan et al. 10.1016/j.envsoft.2013.09.031
220. Analysis of parameter sensitivity on surface heat exchange in the Noah land surface model at a temperate desert steppe site in China G. Zhang et al. 10.1007/s13351-017-7050-1
221. Emulation techniques for the reduction and sensitivity analysis of complex environmental models M. Ratto et al. 10.1016/j.envsoft.2011.11.003
222. Identification of the dominant hydrological process and appropriate model structure of a karst catchment through stepwise simplification of a complex conceptual model Y. Chang et al. 10.1016/j.jhydrol.2017.02.050
223. Uncertainty analysis of modeled carbon and water fluxes in a subtropical coniferous plantation X. Ren et al. 10.1002/2013JG002402
224. Gross primary production-coupled evapotranspiration in the global arid and semi-arid regions based on the NIRv index Y. Su et al. 10.1016/j.jhydrol.2024.132012
225. Sensitivity Analysis‐Based Automatic Parameter Calibration of the VIC Model for Streamflow Simulations Over China J. Gou et al. 10.1029/2019WR025968
226. Robust Subsampling ANOVA Methods for Sensitivity Analysis of Water Resource and Environmental Models F. Wang et al. 10.1007/s11269-020-02608-2
227. Quantifying parameter sensitivity, interaction, and transferability in hydrologically enhanced versions of the Noah land surface model over transition zones during the warm season E. Rosero et al. 10.1029/2009JD012035
228. Calibration and Validation of Watershed Models and Advances in Uncertainty Analysis in TMDL Studies E. Ahmadisharaf et al. 10.1061/(ASCE)HE.1943-5584.0001794
229. Sampling Design of Hydraulic and Quality Model Calibration Based on a Global Sensitivity Analysis Method V. Abbasi Moghaddam & M. Tabesh 10.1061/(ASCE)WR.1943-5452.0001390
230. Sobol’ sensitivity analysis of parameters in the common land model for simulation of water and energy fluxes J. Xu et al. 10.1007/s12145-012-0105-z
231. Sensitivity and Uncertainty Analysis of the L-THIA-LID 2.1 Model Y. Liu et al. 10.1007/s11269-016-1462-z
232. Spatiotemporal patterns and source attribution of nitrogen pollution in a typical headwater agricultural watershed in Southeastern China W. Chen et al. 10.1007/s11356-017-0685-8
233. Improving Model Performance Using Season-Based Evaluation M. Muleta 10.1061/(ASCE)HE.1943-5584.0000421
234. Significant variables for leakage and collapse of buried concrete sewer pipes: a global sensitivity analysis via Bayesian additive regression trees and Sobol’ indices S. Zamanian et al. 10.1080/15732479.2020.1762674
235. Advancing the identification and evaluation of distributed rainfall‐runoff models using global sensitivity analysis Y. Tang et al. 10.1029/2006WR005813
236. Global sensitivity analysis of a dynamic model for gene expression inDrosophilaembryos G. McCarthy et al. 10.7717/peerj.1022
237. Fatigue property prediction of additively manufactured Ti-6Al-4V using probabilistic physics-guided learning J. Chen & Y. Liu 10.1016/j.addma.2021.101876
238. ON SENSITIVITY RANKING USING ANALYTIC HIERARCHY PROCESS H. DANG 10.1142/S0218488507004613
239. Tree-based ensemble methods for sensitivity analysis of environmental models: A performance comparison with Sobol and Morris techniques M. Jaxa-Rozen & J. Kwakkel 10.1016/j.envsoft.2018.06.011
240. Semi-arid rather than arid regions of China deserve the priority in drought mitigation efforts X. Lan et al. 10.1016/j.jhydrol.2024.131791
241. Sensitivity Analysis for Hydraulic Models J. Hall et al. 10.1061/(ASCE)HY.1943-7900.0000098
242. Divergent sensitivity of surface water and energy variables to precipitation product uncertainty in the Tibetan Plateau W. Qi et al. 10.1016/j.jhydrol.2019.124338
243. Soil fungal dynamics: Parameterisation and sensitivity analysis of modelled physiological processes, soil architecture and carbon distribution K. Cazelles et al. 10.1016/j.ecolmodel.2012.08.008
244. Identification of influential proteins in the classical retinoic acid signaling pathway H. Ghaffari & L. Petzold 10.1186/s12976-018-0088-7
245. Dealing with uncertainty in ecosystem models: lessons from a complex salmon model P. McElhany et al. 10.1890/08-0625.1
246. Addressing uncertainty in modelling cumulative impacts within maritime spatial planning in the Adriatic and Ionian region E. Gissi et al. 10.1371/journal.pone.0180501
247. CMI: An online multi-objective genetic autoscaler for scientific and engineering workflows in cloud infrastructures with unreliable virtual machines D. Monge et al. 10.1016/j.jnca.2019.102464
248. Regulation of CSF and Brain Tissue Sodium Levels by the Blood-CSF and Blood-Brain Barriers During Migraine H. Ghaffari et al. 10.3389/fncom.2020.00004
249. Mathematical modeling of gene expression: a guide for the perplexed biologist A. Ay & D. Arnosti 10.3109/10409238.2011.556597
250. A model comparison study of the flowering time regulatory network in Arabidopsis C. Wang et al. 10.1186/1752-0509-8-15
251. Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects J. Dresch et al. 10.1186/1752-0509-4-142
252. Sensitivity analysis demonstrates limits to utility of lactation index for white‐tailed deer management K. Campbell et al. 10.1002/wsb.904
253. Regional Snow Parameters Estimation for Large‐Domain Hydrological Applications in the Western United States N. Sun et al. 10.1029/2018JD030140
254. Sensitivity analysis of the effects of the thermal parameters of exhaust gases on the output of a thermoelectric generator S. Mostafavi et al. 10.1002/htj.21406
255. 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
256. Assessing the investigation of streamflow source areas through uncertainty evaluation of numerical experiments in small catchments F. Soria & S. Kazama 10.1002/hyp.8304