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Hydraulic Engineering

Sensitivity analysis

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Full-Text Articles in Computer Engineering

Spatial And Dynamic Sensitivity Analysis Of A Biophysical Model Of Nitrogen Transfers And Transformations At The Landscape Scale., Jordi Ferrer Saval, Pierre Barbillon, Cyril Benhamou, Patrick Durand, Marie-Luce Taupin, Hervé Monod, Jean-Louis Drouet Jul 2016

Spatial And Dynamic Sensitivity Analysis Of A Biophysical Model Of Nitrogen Transfers And Transformations At The Landscape Scale., Jordi Ferrer Saval, Pierre Barbillon, Cyril Benhamou, Patrick Durand, Marie-Luce Taupin, Hervé Monod, Jean-Louis Drouet

International Congress on Environmental Modelling and Software

Modelling complex systems such as agroecosystems often requires the quantification of a large number of input factors. Sensitivity analyses are useful to fix the appropriate spatial and temporal resolution of models and to reduce the number of input factors to be measured or estimated accurately. Comprehensive spatial and dynamic sensitivity analyses were applied to the Nitroscape model, a deterministic spatially distributed model describing nitrogen transfers and transformations in a rural landscape. Simulations were led on a virtual landscape that represented five years of farm management in an intensive rural area of 3 km². Cluster analyses were applied to summarize the ...


Sobol’ Sensitivity Analysis For Stressor Impacts On Honeybee Colonies, Carmen Kuan, Robert Curry, Gloria Degrandi-Hoffman, Kris Garber, Andrew Kanarek, Marcia Snyder, Tom Purucker Jul 2016

Sobol’ Sensitivity Analysis For Stressor Impacts On Honeybee Colonies, Carmen Kuan, Robert Curry, Gloria Degrandi-Hoffman, Kris Garber, Andrew Kanarek, Marcia Snyder, Tom Purucker

International Congress on Environmental Modelling and Software

We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather, colony resources, population structure, and other important variables. This allows us to test the effects of defined pesticide exposure scenarios versus controlled simulations that lack pesticide exposure. The daily resolution of the model also allows us to conditionally identify sensitivity metrics. We use the variancebased global decomposition sensitivity analysis method, Sobol’, to assess firstand secondorder parameter sensitivities within VarroaPop, allowing us to ...


A New Framework For Global Sensitivity Analysis For Environmental Modelling, Saman Razavi, Hoshin Gupta, Amin Haghnegahdar, Razi Sheikholeslami Jul 2016

A New Framework For Global Sensitivity Analysis For Environmental Modelling, Saman Razavi, Hoshin Gupta, Amin Haghnegahdar, Razi Sheikholeslami

International Congress on Environmental Modelling and Software

Global sensitivity analysis (GSA) is an effective tool for understanding the role and functioning of different model factors (e.g., model parameters, forcings, and boundary and initial conditions) in generating the model response. GSA can be helpful to improve the credibility and utility of environmental systems models, as these models are continually growing in complexity and dimensionality with continuous advances in understanding and computing power. However, conventional approaches to GSA suffer from (1) an ambiguous characterization of sensitivity, and (2) poor computational efficiency, particularly as the problem dimension grows. Here, we identify several important sensitivity-related characteristics of response surfaces that ...


Life Cycle Fragments: Development Of An Online Tool For Curating And Sharing Life, Brandon Kuczenski Jun 2014

Life Cycle Fragments: Development Of An Online Tool For Curating And Sharing Life, Brandon Kuczenski

International Congress on Environmental Modelling and Software

Increasingly, policy makers and consumers demand information on the environmental implications of industrial activities. Life cycle assessment (LCA) is a standardized methodology to relate the delivery of products and services to the potential environmental impacts from that delivery, both directly and throughout the industrial supply chain. LCA requires extensive information about industrial processes throughout the global economy, and is subject to substantial parametric and epistemic uncertainty. Moreover, results often hinge on modeling decisions, such as the selection of system outcomes. Comparative results from a single study can give policy-relevant insights only if it is possible to review the sensitivity of ...