Exploring the effects of land-use classification errors on the outputs of a coastal habitat model using global sensitivity and uncertainty analysis

2010 ◽  
Author(s):  
Ma. Librada Chu-Agor ◽  
Rafael Muñoz-Carpena ◽  
Gregory Kikerr ◽  
Igor Linkov
2013 ◽  
Vol 263 ◽  
pp. 174-186 ◽  
Author(s):  
Stephen G. Perz ◽  
Rafael Muñoz-Carpena ◽  
Gregory Kiker ◽  
Robert D. Holt

2012 ◽  
Vol 231 ◽  
pp. 113-125 ◽  
Author(s):  
Kendall C. DeJonge ◽  
James C. Ascough ◽  
Mehdi Ahmadi ◽  
Allan A. Andales ◽  
Mazdak Arabi

2018 ◽  
Vol 78 (4) ◽  
pp. 625-635 ◽  
Author(s):  
M. B. L. Simedo ◽  
A. L. M. Martins ◽  
T. C. T. Pissarra ◽  
M. C. Lopes ◽  
R. C. A. Costa ◽  
...  

Abstract The water quality is related to the hydrologic and limnologic properties of ground and surface water, and significant efforts have been made to monitor water sources to understand the effects of land use changes in agricultural areas, with significant socioeconomic activities. The objective of this study was to evaluate the qualitative aspects of surface water in subbasins related to land use. Samples were analyzed in terms of physical and chemical parameters on monthly discrete water quality sampling in four representative sites at first order subbasin streams, located at the Polo Regional Centro Norte, Pindorama County, State of São Paulo, Brazil. The land use classification was made by visual detection technique in a multispectral satellite data obtained from LandSat8- spectral bands of the OLI sensor. The watershed was classified into major land cover/use classes and overlay maps generated in ArcGIS 10 indicated a significant shift from natural vegetation to agriculture activities. Water quality monitoring was according to the brazilian protocol and the results were submitted to analysis of variance (ANOVA). The values obtained differ significantly at each sampling point - subbasins, reflecting the effects of land use on water quality. Soil conservation management is important to optimize soil use in order to contribute to the control of water pollution and the formulation of a public policy is necessary for the conservation of water and soil resources.


Author(s):  
Stéphanie Aparicio ◽  
Rebecca Serna García ◽  
Aurora Seco ◽  
José Ferrer ◽  
Luis Borrás Falomir ◽  
...  

2018 ◽  
Author(s):  
Ksenia Aleksankina ◽  
Mathew R. Heal ◽  
Anthony J. Dore ◽  
Marcel Van Oijen ◽  
Stefan Reis

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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