Global sensitivity and uncertainty analysis of a dynamic agroecosystem model under different irrigation treatments

2012 ◽  
Vol 231 ◽  
pp. 113-125 ◽  
Author(s):  
Kendall C. DeJonge ◽  
James C. Ascough ◽  
Mehdi Ahmadi ◽  
Allan A. Andales ◽  
Mazdak Arabi
Keyword(s):  
Uncertainty Analysis ◽  
Global Sensitivity ◽  
Agroecosystem Model ◽  
Irrigation Treatments ◽  
Sensitivity And Uncertainty Analysis

Evaluating ecological resilience with global sensitivity and uncertainty analysis

2013 ◽  
Vol 263 ◽  
pp. 174-186 ◽  
Author(s):  
Stephen G. Perz ◽  
Rafael Muñoz-Carpena ◽  
Gregory Kiker ◽  
Robert D. Holt
Keyword(s):  
Uncertainty Analysis ◽  
Ecological Resilience ◽  
Global Sensitivity ◽  
Sensitivity And Uncertainty Analysis

Global sensitivity and uncertainty analysis of a microalgae model for wastewater treatment

2021 ◽  
pp. 150504
Author(s):  
Stéphanie Aparicio ◽  
Rebecca Serna García ◽  
Aurora Seco ◽  
José Ferrer ◽  
Luis Borrás Falomir ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Uncertainty Analysis ◽  
Global Sensitivity ◽  
Sensitivity And Uncertainty Analysis

scholarly journals Global sensitivity and uncertainty analysis of an atmospheric chemistry transport model: the FRAME model (v. 9.15.0) as a case study

2018 ◽  
Author(s):  
Ksenia Aleksankina ◽  
Mathew R. Heal ◽  
Anthony J. Dore ◽  
Marcel Van Oijen ◽  
Stefan Reis
Keyword(s):  
Uncertainty Analysis ◽  
Atmospheric Chemistry ◽  
Integrated Assessment Model ◽  
Pollutant Emissions ◽  
Model Output ◽  
Input Output ◽  
Global Sensitivity ◽  
Frame Model ◽  
The Uk ◽  
Sensitivity And Uncertainty Analysis

Abstract. Atmospheric chemistry transport models (ACTMs) are widely used to underpin policy decisions associated with the impact of potential changes in emissions on future pollutant concentrations and deposition. It is therefore essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input pollutant emissions. ACTMs incorporate complex and non-linear descriptions of chemical and physical processes which means that interactions and non-linearities in input–output relationships may not be revealed through the local one-at-a-time sensitivity analysis typically used. The aim of this work is to demonstrate a global sensitivity and uncertainty analysis approach for an ACTM, using as an example the FRAME model, which is extensively employed in the UK to generate source-receptor matrices for the UK Integrated Assessment Model and to estimate critical load exceedances. An optimised Latin hypercube sampling design was used to construct model runs within ±40 % variation range for the UK emissions of SO2, NOx and NH3, from which regression coefficients for each input-output combination and each model grid (> 10,000 across the UK) were calculated. Surface concentrations of SO2, NOx and NH3 (and of deposition of S and N) were found to be predominantly sensitive to the emissions of the respective pollutant, while sensitivities of secondary species such as HNO3 and particulate SO42-, NO3- and NH4+ to pollutant emissions were more complex and geographically variable. The uncertainties in model output variables were propagated from the uncertainty ranges reported by the UK National Atmospheric Emissions Inventory for the emissions of SO2, NOx and NH3 (±4 %, ±10 % and ±20 % respectively). The uncertainties in the surface concentrations of NH3 and NOx and the depositions of NHx and NOy were dominated by the uncertainties in emissions of NH3, and NOx respectively, whilst concentrations of SO2 and deposition of SOy were affected by the uncertainties in both SO2 and NH3 emissions. Likewise, the relative uncertainties in the modelled surface concentrations of each of the secondary pollutant variables (NH4+, NO3-, SO42- and HNO3) were due to uncertainties in at least two input variables. In all cases the spatial distribution of relative uncertainty was found to be geographically heterogeneous. The global methods used here can be applied to conduct sensitivity and uncertainty analyses of other ACTMs.

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