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Research Article

Global sensitivity and uncertainty analysis of the AquaCrop model for maize under different irrigation and fertilizer management conditions

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Pages 1115-1133 | Received 21 Jan 2019, Accepted 16 Aug 2019, Published online: 25 Aug 2019

References

  • Akumaga U, Tarhule A, Yusuf AA. 2017. Validation and testing of the FAO AquaCrop model under different levels of nitrogen fertilizer on rainfed maize in Nigeria, West Africa. Agr Forest Meteorol. 232:225–234. doi:10.1016/j.agrformet.2016.08.011.
  • Bourazanis G, Londra P, Kargas G, Argyrokastritis I, Kerkides P. 2016. Evaluation of porous medium hydraulic properties using experimental methods and RETC code. Arch Agron Soil Sci. 62(8):1147–1157.
  • Dejonge KC, Ii JCA, Ahmadi M, Andales AA, Arabi M. 2012. Global sensitivity and uncertainty analysis of a dynamic agroecosystem model under different irrigation treatments. Ecol Model. 231(4):113–125. doi:10.1016/j.ecolmodel.2012.01.024.
  • Edreira JIR, Otegui ME. 2012. Heat stress in temperate and tropical maize hybrids: Differences in crop growth, biomass partitioning and reserves use. Field Crop Res. 130:87–98. doi:10.1016/j.fcr.2012.02.009.
  • Gaelen HV, Tsegay A, Delbecque N, Shrestha N, Garcia M, Fajardo H, Miranda R, Vanuytrecht E, Abrha B, Raes JDD. 2015. A semi-quantitative approach for modelling crop response to soil fertility: evaluation of the AquaCrop procedure. J Agr Sci. 153(7):1218–1233. doi:10.1017/S0021859614000872.
  • Gosses M, Woehling T. 2019. Simplification error analysis for groundwater predictions with reduced order models. Adv Water Resour. 125:41–56. doi:10.1016/j.advwatres.2019.01.006.
  • Guo DX, Chen CF, Guo PY, Yuan XY, Xing XG, Ma XY. 2018. Evaluation of AquaCrop model for foxtail millet (Setaria italica) growth and water use with plastic film mulching and no mulching under different weather conditions. Water-Sui. 10(7):836. doi:10.3390/w10070836.
  • Heller J, Pajdla T. 2016. GpoSolver: a Matlab/C plus plus toolbox for global polynomial optimization. Optim Method Softw. 31(2):405–434. doi:10.1080/10556788.2015.1121489.
  • Hsiao TC, Heng L, Steduto P, Rojas-Lara B, Raes D, Fereres E. 2009. AquaCrop-the FAO Crop model to simulate yield response to water: III. Parameterization and testing for maize. Agron J. 101(3):448–459. doi:10.2134/agronj2008.0218s.
  • Jin X, Li Z, Nie C, Xu X, Guo W. 2018. Parameter sensitivity analysis of the AquaCrop model based on extended fourier amplitude sensitivity under different agro-meteorological conditions and application. Field Crop Res. 226:1–15. doi:10.1016/j.fcr.2018.07.002.
  • Jones JW, Naab J, Fatondji D, Dzotsi K, Adiku S, He J. 2012. Uncertainties in simulating crop performance in degraded soils and low input production systems. Dordrecht: Springer.
  • Kassie BT, Asseng S, Porter CH, Royce FS. 2016. Performance of DSSAT-Nwheat across a wide range of current and future growing conditions. Eur J Agron. 81:27–36. doi:10.1016/j.eja.2016.08.012.
  • Katerji N, Campi P, Mastrorilli M. 2013. Productivity, evapotranspiration, and water use efficiency of corn and tomato crops simulated by AquaCrop under contrasting water stress conditions in the Mediterranean region. Agr Water Manage. 130(4):14–26. doi:10.1016/j.agwat.2013.08.005.
  • Krishnan P, Aggarwal P. 2018. Global sensitivity and uncertainty analyses of a web based crop simulation model (web InfoCrop wheat) for soil parameters. Plant Soil. 423(1–2):443–463. doi:10.1007/s11104-017-3498-0.
  • Liang H, Zhiming Q, Kendall C, DeJonge, Kelin H, Baoguo L. 2017. Global sensitivity and uncertainty analysis of nitrate leaching and crop yield simulation under different water and nitrogen management practices. Comput Electron Agr. 142:201–210. doi:10.1016/j.compag.2017.09.010.
  • Lu H-D, Xue J-Q, Guo D-W. 2017. Efficacy of planting date adjustment as a cultivation strategy to cope with drought stress and increase rainfed maize yield and water-use efficiency. Agr Water Manage. 179:227–235. doi:10.1016/j.agwat.2016.09.001.
  • Mastrucci A, Perez-Lopez P, Benetto E, Leopold U, Blanc I. 2017. Global sensitivity analysis as a support for the generation of simplified building stock energy models. Energ Buildings. 149:368–383. doi:10.1016/j.enbuild.2017.05.022.
  • Moosavi AA, Mansouri S, Zahedifar M. 2015. Effect of soil water stress and nickel application on micronutrient status of canola grown on two calcareous soils. Plant Prod Sci. 18(3):377–387. doi:10.1626/pps.18.377.
  • Moosavi AA, Mansouri S, Zahedifar M, Sadikhani MR. 2014. Effect of water stress and nickel application on yield components and agronomic characteristics of canola grown on two calcareous soils. Arch Agron Soil Sci. 60(12):1747–1764. doi:10.1080/03650340.2014.898838.
  • Moosavi AA, Zahedifar M, Mansouri S. 2018. The uptake and partitioning of nickel and some nutrient elements in canola grown in two differently textured soils as influenced by nickel and soil moisture conditions. Int J Environ Stud. 1–18. doi:10.1080/00207233.2018.1517969.
  • Mustafa SMT, Vanuytrecht E, Huysmans M. 2017. Combined deficit irrigation and soil fertility management on different soil textures to improve wheat yield in drought-prone Bangladesh. Agr Water Manage. 191:124–137. doi:10.1016/j.agwat.2017.06.011.
  • Palosuo T, Kersebaum KC, Angulo C, Hlavinka P, Moriondo M, Olesen JE, Patil RH, Ruget F, Rumbaur C, Takac J, et al. 2011. Simulation of winter wheat yield and its variability in different climates of Europe: a comparison of eight crop growth models. Eur J Agron. 35(3):103–114. doi:10.1016/j.eja.2011.05.001.
  • Qi D, Hu T, Niu X. 2017. Responses of root growth and distribution of maize to nitrogen application patterns under partial root-zone irrigation. Int J Plant Prod. 11(2):209–224.
  • Raes DS, Steduto P, Hsiao TC, Fereres E. 2016. AquaCrop version 5.0 reference manual. Rome (Italy): Annex I Food and Agriculture Organization of the United Nations.
  • Ran H, Kang SZ, Hu XT, Li FS, Du TS, Tong L, Li S, Ding RS, Zhou ZJ, Parsons D. 2019. Newly developed water productivity and harvest index models for maize in an arid region. Field Crop Res. 234:73–86. doi:10.1016/j.fcr.2019.02.009.
  • Richter GM, Acutis M, Trevisiol P, Latiri K, Confalonieri R. 2010. Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean. Eur J Agron. 32(2):127–136. doi:10.1016/j.eja.2009.09.002.
  • Shin MJ, Guillaume JHA, Croke BFW, Jakeman AJ. 2013. Addressing ten questions about conceptual rainfall–runoff models with global sensitivity analyses in R. J Hydrol. 503(11):135–152. doi:10.1016/j.jhydrol.2013.08.047.
  • Shrestha N, Raes D, Vanuytrecht E, Sah SK. 2013. Cereal yield stabilization in Terai (Nepal) by water and soil fertility management modeling. Agr Water Manage. 122(2):53–62. doi:10.1016/j.agwat.2013.03.003.
  • Silvestro PC, Pignatti S, Yang H, Yang GJ, Pascucci S, Castaldi F, Casa R. 2017. Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications. Plos One. 12(11):30. doi:10.1371/journal.pone.0187485.
  • Staff. 2010. Soil survey keys to soil taxonomy. 11th. Washington DC (USA): USDA.
  • Steduto P, Hsiao TC, Raes D, Fereres E. 2009. AquaCrop-the FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agron J. 101(3):426–437. doi:10.2134/agronj2008.0139s.
  • Tan J, Cui Y, Luo Y. 2017. Assessment of uncertainty and sensitivity analyses for ORYZA model under different ranges of parameter variation. Eur J Agron. 91:54–62. doi:10.1016/j.eja.2017.09.001.
  • Theodorec H, Lee H, Pasquale S, Basilio RL, Dirk R, Elias F. 2009. AquaCrop–the FAO Crop model to simulate yield response to water: III. Parameterization and testing for maize. Agron J. 101(3):448–459. doi:10.2134/agronj2008.0218s.
  • Vanuytrecht E, Raes D, Willems P. 2014. Global sensitivity analysis of yield output from the water productivity model. Environ Modell Softw. 51:323–332. doi:10.1016/j.envsoft.2013.10.017.
  • Wang F, Mladenoff DJ, Forrester JA, Keough C, Parton WJ. 2013. Global sensitivity analysis of a modified CENTURY model for simulating impacts of harvesting fine woody biomass for bioenergy. Ecol Model. 259(259):16–23. doi:10.1016/j.ecolmodel.2013.03.008.
  • Wannasek L, Ortner M, Amon B, Amon T. 2017. Sorghum, a sustainable feedstock for biogas production? Impact of climate, variety and harvesting time on maturity and biomass yield. Biomass Bioenerg. 106:137–145. doi:10.1016/j.biombioe.2017.08.031.
  • Xi M, Dan L, Gui D, Qi Z, Zhang G. 2017. Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization. J Hydrol. 544:456–466. doi:10.1016/j.jhydrol.2016.11.051.
  • Zhao G, Bryan BA, Song X. 2014. Sensitivity and uncertainty analysis of the APSIM-wheat model: interactions between cultivar, environmental, and management parameters. Ecol Model. 279(279):1–11. doi:10.1016/j.ecolmodel.2014.02.003.
  • Zhao X. 2009. Numerical simulation study of groundwater based on FEFLOW and GIS technology in XIANGYANG city. Yangling (China): Northwest A&F University.
  • Zheng H, Wang Z, Deng X, Herbert S, Xing B. 2013. Impacts of adding biochar on nitrogen retention and bioavailability in agricultural soil. Geoderma. 206:32–39. doi:10.1016/j.geoderma.2013.04.018.

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