Nonlinear sensitivity analysis of multiparameter model systems

Cukier, Robert I.; Levine, Howard B.; Shuler, Kurt E.

doi:10.1016/0021-9991(78)90097-9

Cited by 556 publications

(262 citation statements)

References 7 publications

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“…In this study, the FAST method was used. The FAST method considers non-linearities as an important factor in hydrology (Cukier et al, 1973(Cukier et al, , 1975(Cukier et al, , 1978 and has a high computational efficiency. In contrast with other methods such as Sobol's, the number of required model runs is lower, which is of particular relevance for complex models (Saltelli and Bolado, 1998;.…”

Section: Pfannerstill Et Al: Process Verification With Temporal Pmentioning

confidence: 99%

Process verification of a hydrological model using a temporal parameter sensitivity analysis

Pfannerstill

Guse

Reusser

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract. To ensure reliable results of hydrological models, it is essential that the models reproduce the hydrological process dynamics adequately. Information about simulated process dynamics is provided by looking at the temporal sensitivities of the corresponding model parameters. For this, the temporal dynamics of parameter sensitivity are analysed to identify the simulated hydrological processes. Based on these analyses it can be verified if the simulated hydrological processes match the observed processes of the real world.We present a framework that makes use of processes observed in a study catchment to verify simulated hydrological processes. Temporal dynamics of parameter sensitivity of a hydrological model are interpreted to simulated hydrological processes and compared with observed hydrological processes of the study catchment. The results of the analysis show the appropriate simulation of all relevant hydrological processes in relation to processes observed in the catchment. Thus, we conclude that temporal dynamics of parameter sensitivity are helpful for verifying simulated processes of hydrological models.

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Section: Pfannerstill Et Al: Process Verification With Temporal Pmentioning

confidence: 99%

Process verification of a hydrological model using a temporal parameter sensitivity analysis

Pfannerstill

Guse

Reusser

et al. 2015

Hydrol. Earth Syst. Sci.

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“….36 (Yang et al 2005) Thermal roughness length z 0h =70ν⋅u * −1 ⋅exp (−βu * 0.5 |T * | 0.25 ) β=7.2 s 0.5 m −0.5 K −0.25 (Yang et al 2008) Bare soil evaporation the model output with a sensitivity analysis (Fourier Amplitude Sensitivity Test by Cukier et al 1978). Assuming typical measurement errors for the initial parameter distribution they estimated that water temperature contributed up to 50 % of the overall error while the influence of wind velocity, air temperature and humidity are comparatively small, each contributing 10-20 % to the error.…”

Section: Application Of the Hm Model To A Shallow Lakementioning

confidence: 99%

Turbulent flux observations and modelling over a shallow lake and a wet grassland in the Nam Co basin, Tibetan Plateau

Biermann

Babel

et al. 2013

Theor Appl Climatol

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The Tibetan Plateau plays an important role in the global water cycle and is strongly influenced by climate change. While energy and matter fluxes have been more intensely studied over land surfaces, a large proportion of lakes have either been neglected or parameterised with simple bulk approaches. Therefore, turbulent fluxes were measured over wet grassland and a shallow lake with a single eddy-covariance complex at the shoreline in the Nam Co basin in summer 2009. Footprint analysis was used to split observations according to the underlying surface, and two sophisticated surface models were utilised to derive gap-free time series. Results were then compared with observations and simulations from a nearby eddy-covariance station over dry grassland, yielding pronounced differences. Observations and footprint integrated simulations compared well, even for situations with flux contributions including grassland and lake. The accessibility problem for EC measurements on lakes can be overcome by combining standard meteorological measurements at the shoreline with model simulations, only requiring representative estimates of lake surface temperature.

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“…The region in the vicinity of the third explosion limit has been particularly difficult to study in experiments.1 7# 2 12 As we discussed in Section II, both chain and thermal mechanisms seem to play a role. We have carried out two types of calculations to probe this regime; one type assumes isothermal behavior, the other assumes adiabatic behavior.…”

Section: Cmentioning

confidence: 99%

Computational kinetics and sensitivity analysis of hydrogen–oxygen combustion

Dougherty

Rabitz

1980

The Journal of Chemical Physics

101

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Kinetic modeling calculations on the H2–O2 system have been carried out with an extensive reaction set to probe the vicinity of the three explosion limits. Sensitivity analysis is used throughout this investigation to study system behavior, in particular, to elucidate mechanistic details. The concentrations and sensitivity profiles are discussed in light of the appropriate experimental results and existing theories of hydrogen combustion. The results indicate the present model to be useful over a wide pressure–temperature range. The reaction set is also used to probe the sensitivities for an experimental study designed to measure the rate constant of an important elementary reaction, H+O2+M→HO2+M, involved in this system. The versatility of the reaction set is also demonstrated by a study of a related chemical reaction, the decomposition of hydrogen peroxide. Finally, prospects for utilizing the methods and results of this study to examine other complex kinetic schemes are discussed.

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Nonlinear sensitivity analysis of multiparameter model systems

Cited by 556 publications

References 7 publications

Process verification of a hydrological model using a temporal parameter sensitivity analysis

Process verification of a hydrological model using a temporal parameter sensitivity analysis

Turbulent flux observations and modelling over a shallow lake and a wet grassland in the Nam Co basin, Tibetan Plateau

Computational kinetics and sensitivity analysis of hydrogen–oxygen combustion

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