Engineering Commons^™

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

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

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 must …

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 …

Overview And Application Of The Model Optimization, Uncertainty, And Sensitivity Analysis (Mouse) Toolbox, James C. Ascough Ii, Christian Fischer, Nathan Lighthart, Olaf David, Timothy R. Green, Sven Kralisch

International Congress on Environmental Modelling and Software

For several decades, optimization and sensitivity/uncertainty analysis of environmental models has been the subject of extensive research. Although much progress has been made and sophisticated methods developed, the growing complexity of environmental models to represent real­ world systems makes it increasingly difficult to fully comprehend model behavior, sensitivities and uncertainties. This paper provides an overview of the Model Optimization, Uncertainty, and SEnsitivity Analysis (MOUSE) software application, an open-source, Java-based toolbox of visual and numerical analysis components for the evaluation of environmental models. MOUSE is based on the OPTAS model calibration system developed for the Jena Adaptable Modeling System framework, is …

Calibration Of Simulation Platforms Including Highly Interweaved Processes: The Maelia Multi-Agent Platform, Romain Lardy, Pierre Mazzega, Christophe Sibertin-Blanc, Yves Auda, José-Miguel Sanchez-Perez, Sabine Sauvage, Olivier Therond

International Congress on Environmental Modelling and Software

The MAELIA project develops an agent-based modeling and simulation platform to study the environmental, economic and social impacts of various regulations regarding water use and water management in combination with climate change. An integrated modelling approach has been used to model the investigated social-ecological system. MAELIA combines spatiotemporal models of ecologic (e.g. water flow and plant growth) and human decision-making processes (e.g. cropping plan), socio-economic dynamics (e.g. land cover changes). Due to the diversity and the interweaving of the processes considered, the calibration and evaluation of such a multi-agent platform is a scientific challenge. Indeed, many parameters can reveal to …

Transferability Of Jarvis-Type Models Developed And Re-Parameterized For Maize To Estimate Stomatal Resistance Of Soybean: Analyses On Model Calibration, Validation, Performance, Sensitivity, And Elasticity, Denis Mutiibwa, Suat Irmak

Department of Biological Systems Engineering: Papers and Publications

In a previous study by the same authors, a new modified Jarvis model (NMJ-model) was developed, calibrated, and validated to estimate stomatal resistance (rs) for maize canopy on an hourly time step. The NMJ-model’s unique subfunctions, different from the original Jarvis model (J-model), include a photosynthetic photon flux density

(PPFD)-r_s response subfunction developed from field measurements and a new physical term, Aexp(1/LAI), where A is the minimum stomatal resistance and LAI is the green leaf area index, to account for the influence of canopy development on r_s, especially during partial canopy stage in the early season and …

Sensitivity Of Grass- And Alfalfa-Reference Evapotranspiration To Weather Station Sensor Accuracy, Dana O. Porter, Prasanna H. Gowda, Thomas H. Marek, Terry A. Howell, Jerry Moorhead, Suat Irmak

Department of Biological Systems Engineering: Papers and Publications

A sensitivity analysis was conducted to determine the relative effects of measurement errors in climate data input parameters on the accuracy of calculated reference crop evapotranspiration (ET) using the ASCE-EWRI Standardized Reference ET Equation. Data for the period of 1995 to 2008 from an automated weather station located at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas were used for the analysis. Results

indicated that grass (ET_os) and alfalfa (ET_rs) reference crop ET were most sensitive to measurement errors in wind speed and air temperature followed by incoming shortwave (solar) radiation, and that data …

Sensitivity Analysis On Mapping Evapotranspiration At High Resolution Using Internal Calibration (Metric), Venkata Naga Ravi Kumar Choragudi

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Mapping EvapoTranspiration at high Resolution using Internal Calibration (METRIC) is most widely used to quantify evapotranspiration (ET) spatially and temporally. It is essential to inspect the model’s response to errors in various parameters used in the model. Landsat 5 images from May 30 2009, July 1 2009 and a Landsat 7 image from September 27 2009 are used in this study. Fourteen different fields composed of Corn, Soybeans, Alfalfa are randomly chosen for each crop type.

Two kinds of errors are addressed in this study. One, with the errors that are transferred and potentially compensated by calibration (Global error) and …