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Title: Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas

Abstract

Crop simulation models are increasingly being used to understand the feasibility of large-scale cellulosic bio-fuel production along with the multi-dimensional impacts on environmental sustainability. However, how the uncertainty in model parameters impacts model performance for sustainability is unclear. In this case study, sensitivity analyses were conducted for three switchgrass sustainability metrics: total biomass production, nitrogen loss, and soil carbon change using the APEX (Agricultural Policy/Environmental eXtender) model. Fifteen out of the 45 parameters (25 crop growth (CROP) parameters and 20 additional model parameters (PARM)) were identified as influential for the three sustainability metrics for three lowland genotypes (WBC, AP13, and KAN) across two locations (Temple, TX, and Austin, TX). Our sensitivity results showed that parameter importance was not dependent on the genotypes but depended on the variables of interest, and differed only slightly between locations. Influential belowground-related CROP and PARM parameters were identified for each sustainability metric, indicating that belowground-related parameters are just as important as commonly measured aboveground CROP parameters. Further investigation of the linear or non-linear relationships and the two-way interactions between each of the individual influential parameters with the three sustainability metrics reflected the functions and characteristics within the APEX model and the interrelations among different processes.more » Strong interactions between the most influential parameters for total biomass, nitrogen loss, and soil carbon change also highlighted the importance of accurately setting these parameters. Identification of influential model parameters for switchgrass sustainability may help guide field measurements and provide further understanding of the interrelated processes in the APEX model. Moreover, future field experiments can be designed to measure these influential parameters and understand the non-linear relationships identified between influential parameters and response variables. More accurate model parameterization will help improve APEX model performance and our understanding of the possible underlying physiological mechanisms.« less

Authors:
ORCiD logo; ; ;
Publication Date:
Research Org.:
Univ. of Texas, Austin, TX (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF)
OSTI Identifier:
1402505
Alternate Identifier(s):
OSTI ID: 1502984; OSTI ID: 1594758
Grant/Contract Number:  
SC0014156; IOS-1444533
Resource Type:
Published Article
Journal Name:
BioEnergy Research
Additional Journal Information:
Journal Name: BioEnergy Research Journal Volume: 11 Journal Issue: 1; Journal ID: ISSN 1939-1234
Publisher:
Springer
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; Panicum virgatum; Sustainability; Total biomass; Nitrogen loss; Soil carbon change; Belowground parameters; Base temperature; Optimum temperature; Uncertainty; Crop models

Citation Formats

Zhang, Li, Juenger, Thomas E., Osorio, Javier M., and Behrman, Kathrine D.. Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas. United States: N. p., 2017. Web. https://doi.org/10.1007/s12155-017-9878-8.
Zhang, Li, Juenger, Thomas E., Osorio, Javier M., & Behrman, Kathrine D.. Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas. United States. https://doi.org/10.1007/s12155-017-9878-8
Zhang, Li, Juenger, Thomas E., Osorio, Javier M., and Behrman, Kathrine D.. Mon . "Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas". United States. https://doi.org/10.1007/s12155-017-9878-8.
@article{osti_1402505,
title = {Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas},
author = {Zhang, Li and Juenger, Thomas E. and Osorio, Javier M. and Behrman, Kathrine D.},
abstractNote = {Crop simulation models are increasingly being used to understand the feasibility of large-scale cellulosic bio-fuel production along with the multi-dimensional impacts on environmental sustainability. However, how the uncertainty in model parameters impacts model performance for sustainability is unclear. In this case study, sensitivity analyses were conducted for three switchgrass sustainability metrics: total biomass production, nitrogen loss, and soil carbon change using the APEX (Agricultural Policy/Environmental eXtender) model. Fifteen out of the 45 parameters (25 crop growth (CROP) parameters and 20 additional model parameters (PARM)) were identified as influential for the three sustainability metrics for three lowland genotypes (WBC, AP13, and KAN) across two locations (Temple, TX, and Austin, TX). Our sensitivity results showed that parameter importance was not dependent on the genotypes but depended on the variables of interest, and differed only slightly between locations. Influential belowground-related CROP and PARM parameters were identified for each sustainability metric, indicating that belowground-related parameters are just as important as commonly measured aboveground CROP parameters. Further investigation of the linear or non-linear relationships and the two-way interactions between each of the individual influential parameters with the three sustainability metrics reflected the functions and characteristics within the APEX model and the interrelations among different processes. Strong interactions between the most influential parameters for total biomass, nitrogen loss, and soil carbon change also highlighted the importance of accurately setting these parameters. Identification of influential model parameters for switchgrass sustainability may help guide field measurements and provide further understanding of the interrelated processes in the APEX model. Moreover, future field experiments can be designed to measure these influential parameters and understand the non-linear relationships identified between influential parameters and response variables. More accurate model parameterization will help improve APEX model performance and our understanding of the possible underlying physiological mechanisms.},
doi = {10.1007/s12155-017-9878-8},
journal = {BioEnergy Research},
number = 1,
volume = 11,
place = {United States},
year = {2017},
month = {10}
}

Journal Article:
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https://doi.org/10.1007/s12155-017-9878-8

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Works referenced in this record:

Simulating Switchgrass Growth and Development under Potential and Water-Limiting Conditions
journal, January 2009


The Genetic Basis of Upland/Lowland Ecotype Divergence in Switchgrass ( Panicum virgatum)
journal, September 2016

  • Milano, Elizabeth R.; Lowry, David B.; Juenger, Thomas E.
  • G3: Genes|Genomes|Genetics, Vol. 6, Issue 11
  • DOI: 10.1534/g3.116.032763

Sensitivity Anaysis as an Ingredient of Modeling
journal, November 2000

  • Campolongo, F.; Tarantola, S.; Saltelli, A.
  • Statistical Science, Vol. 15, Issue 4
  • DOI: 10.1214/ss/1009213004

Nitrogen removal in switchgrass biomass under two harvest systems
journal, November 2000


Sensitivity Analysis of apex for National Assessment
journal, January 2006


Indicators to support environmental sustainability of bioenergy systems
journal, September 2011


Factorial Sampling Plans for Preliminary Computational Experiments
journal, May 1991


Sensitivity and Uncertainty Analyses of crop Yields and soil Organic Carbon Simulated with epic
journal, January 2005


Simulated wheat growth affected by rising temperature, increased water deficit and elevated atmospheric CO2
journal, February 2004


Switchgrass as a sustainable bioenergy crop
journal, April 1996


Sensitivity analysis of a crop simulation model, STICS, in order to choose the main parameters to be estimated
journal, March 2002

  • Ruget, Françoise; Brisson, Nadine; Delécolle, Richard
  • Agronomie, Vol. 22, Issue 2
  • DOI: 10.1051/agro:2002009

Impact of second‐generation biofuel agriculture on greenhouse‐gas emissions in the corn‐growing regions of the US
journal, July 2011

  • Davis, Sarah C.; Parton, William J.; Grosso, Stephen J. Del
  • Frontiers in Ecology and the Environment, Vol. 10, Issue 2
  • DOI: 10.1890/110003

Switchgrass simulation by the ALMANAC model at diverse sites in the southern US
journal, December 2005


Perennial Biomass Grasses and the Mason–Dixon Line: Comparative Productivity across Latitudes in the Southern Great Plains
journal, September 2012


Leaf Area Development, Light Interception, and Yield among Switchgrass Populations in a Short-Season Area
journal, January 1998


The role of root architectural traits in adaptation of wheat to water-limited environments
journal, January 2006

  • Manschadi, Ahmad M.; Christopher, John; deVoil, Peter
  • Functional Plant Biology, Vol. 33, Issue 9
  • DOI: 10.1071/FP06055

Switchgrass Biomass Simulation at Diverse Sites in the Northern Great Plains of the U.S.
journal, December 2008


Carbon Sequestration by Perennial Energy Crops: Is the Jury Still Out?
journal, January 2015

  • Agostini, Francesco; Gregory, Andrew S.; Richter, Goetz M.
  • BioEnergy Research, Vol. 8, Issue 3
  • DOI: 10.1007/s12155-014-9571-0

Long-term modeling of soil C erosion and sequestration at the small watershed scale
journal, December 2006


Switchgrass for forage and bioenergy: harvest and nitrogen rate effects on biomass yields and nutrient composition
journal, April 2010


High-throughput two-dimensional root system phenotyping platform facilitates genetic analysis of root growth and development: Root phenotyping platform
journal, September 2012


Adaptation of C4 Bioenergy Crop Species to Various Environments within the Southern Great Plains of USA
journal, January 2017

  • Kim, Sumin; Kiniry, James; Williams, Amber
  • Sustainability, Vol. 9, Issue 1
  • DOI: 10.3390/su9010089

An overview of available crop growth and yield models for studies and assessments in agriculture: Overview of crop models for agriculture
journal, September 2015

  • Di Paola, Arianna; Valentini, Riccardo; Santini, Monia
  • Journal of the Science of Food and Agriculture, Vol. 96, Issue 3
  • DOI: 10.1002/jsfa.7359

Modeling Differential Growth in Switchgrass Cultivars Across the Central and Southern Great Plains
journal, March 2014

  • Behrman, Kathrine D.; Keitt, Timothy H.; Kiniry, James R.
  • BioEnergy Research, Vol. 7, Issue 4
  • DOI: 10.1007/s12155-014-9450-8

Applicability of Models to Predict Phosphorus Losses in Drained Fields: A Review
journal, January 2015

  • Radcliffe, David E.; Reid, D. Keith; Blombäck, Karin
  • Journal of Environment Quality, Vol. 44, Issue 2
  • DOI: 10.2134/jeq2014.05.0220

Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean
journal, February 2010


A quantitative review comparing the yield of switchgrass in monocultures and mixtures in relation to climate and management factors
journal, February 2010


Modeling the impacts of temperature and precipitation changes on soil CO2 fluxes from a Switchgrass stand recently converted from cropland
journal, May 2016


Development of switchgrass (Panicum virgatum) as a bioenergy feedstock in the United States
journal, June 2005


Uncertainty in simulating wheat yields under climate change
journal, June 2013

  • Asseng, S.; Ewert, F.; Rosenzweig, C.
  • Nature Climate Change, Vol. 3, Issue 9
  • DOI: 10.1038/nclimate1916

Spatial forecasting of switchgrass productivity under current and future climate change scenarios
journal, January 2013

  • Behrman, Kathrine D.; Kiniry, James R.; Winchell, Michael
  • Ecological Applications, Vol. 23, Issue 1
  • DOI: 10.1890/12-0436.1

Climatic and genetic controls of yields of switchgrass, a model bioenergy species
journal, January 2012

  • Tulbure, Mirela G.; Wimberly, Michael C.; Boe, Arvid
  • Agriculture, Ecosystems & Environment, Vol. 146, Issue 1
  • DOI: 10.1016/j.agee.2011.10.017

Sustainable bioenergy production from marginal lands in the US Midwest
journal, January 2013

  • Gelfand, Ilya; Sahajpal, Ritvik; Zhang, Xuesong
  • Nature, Vol. 493, Issue 7433
  • DOI: 10.1038/nature11811

Potential regional productivity and greenhouse gas emissions of fertilized and irrigated switchgrass in a Mediterranean climate
journal, December 2015

  • Lee, Juhwan; Pedroso, Gabriel; van Kessel, Chris
  • Agriculture, Ecosystems & Environment, Vol. 212
  • DOI: 10.1016/j.agee.2015.06.015

Development, uncertainty and sensitivity analysis of the simple SALUS crop model in DSSAT
journal, July 2013


Sensitivity analysis of environmental models: A systematic review with practical workflow
journal, May 2016


Biomass and Carbon Partitioning in Switchgrass
journal, January 2004


Future contributions of crop modelling—from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement
journal, December 2002


Growth and Yield Responses of Switchgrass Ecotypes to Temperature
journal, January 2013

  • Kandel, Tanka Prasad; Wu, Yanqi; Kakani, Vijaya Gopal
  • American Journal of Plant Sciences, Vol. 04, Issue 06
  • DOI: 10.4236/ajps.2013.46145

Radiation use efficiency and leaf CO2 exchange for diverse C4 grasses
journal, August 1999


Estimates of Biomass Yield for Perennial Bioenergy Grasses in the USA
journal, November 2014


Parameter sensitivity analysis of crop growth models based on the extended Fourier Amplitude Sensitivity Test method
journal, October 2013


Analysis of root growth from a phenotyping data set using a density-based model
journal, February 2016

  • Kalogiros, Dimitris I.; Adu, Michael O.; White, Philip J.
  • Journal of Experimental Botany, Vol. 67, Issue 4
  • DOI: 10.1093/jxb/erv573

Multivariate global sensitivity analysis for dynamic crop models
journal, September 2009

  • Lamboni, Matieyendou; Makowski, David; Lehuger, Simon
  • Field Crops Research, Vol. 113, Issue 3
  • DOI: 10.1016/j.fcr.2009.06.007

APEX Model Assessment of Variable Landscapes on Runoff and Dissolved Herbicides
journal, January 2010


Use of crop simulation modelling to aid ideotype design of future cereal cultivars
journal, March 2015

  • Rötter, R. P.; Tao, F.; Höhn, J. G.
  • Journal of Experimental Botany, Vol. 66, Issue 12
  • DOI: 10.1093/jxb/erv098

Sensitivity Analysis of the Agricultural Policy/Environmental eXtender (APEX) for Phosphorus Loads in Tile-Drained Landscapes
journal, January 2015


Parameters sensitivity analysis for a~crop growth model applied to winter wheat in the Huanghuaihai Plain in China
journal, January 2014