How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale
IntroductionAquaCrop is a water-driven crop growth model that simulates aboveground biomass production in croplands. This study aimed to identify the driving parameters of the AquaCrop model for the model calibration and simplification to fill the research gap in intermediate environmental condition...
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Frontiers Media S.A.
2024-04-01
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| Series: | Frontiers in Agronomy |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fagro.2024.1304611/full |
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| author | Elahe Akbari Ali Darvishi Boloorani Jochem Verrelst Stefano Pignatti Najmeh Neysani Samany Saeid Soufizadeh Saeid Hamzeh |
| author_facet | Elahe Akbari Ali Darvishi Boloorani Jochem Verrelst Stefano Pignatti Najmeh Neysani Samany Saeid Soufizadeh Saeid Hamzeh |
| author_sort | Elahe Akbari |
| collection | DOAJ |
| description | IntroductionAquaCrop is a water-driven crop growth model that simulates aboveground biomass production in croplands. This study aimed to identify the driving parameters of the AquaCrop model for the model calibration and simplification to fill the research gap in intermediate environmental conditions between sub-tropical sub-humid and temperate sub-humid climates for silage maize.MethodsTo this end, we applied global sensitivity analysis (GSA) by combining the Morris method and the Extended Fourier Amplitude Sensitivity Test (EFAST) on crop yield output. The process involved a field sampling of soil and crop of silage maize carried out in the agricultural fields of Ghale-Nou, southern Tehran, Iran, in the summer of 2019 in order to measure certain model parameters.Results and discussionIn compliance with the Morris method, 30 parameters were identified as the least sensitive, while results from the EFAST test showed 9 parameters as contributing to the highest sensitivities in the model. The results clearly point to the capacity of employing a combination of both methods to attain a more efficient model calibration. Particular root, soil, canopy development, and biomass production parameters were influential and merit attention during calibration. Instead, parameters describing crop responses to water stress were acting rather insensitive in this study condition. The insights gained from this study, i.e., assessing parameter ranges and distinguishing between less sensitive and more sensitive parameters based on environmental and crop conditions, have the potential to be applied to other crop growth models with caution. |
| first_indexed | 2024-04-24T08:51:49Z |
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| language | English |
| last_indexed | 2024-04-24T08:51:49Z |
| publishDate | 2024-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Agronomy |
| spelling | doaj.art-3b28dc48b90241a39aa6ceef1dd134a62024-04-16T10:01:02ZengFrontiers Media S.A.Frontiers in Agronomy2673-32182024-04-01610.3389/fagro.2024.13046111304611How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scaleElahe Akbari0Ali Darvishi Boloorani1Jochem Verrelst2Stefano Pignatti3Najmeh Neysani Samany4Saeid Soufizadeh5Saeid Hamzeh6Department of Remote Sensing and Geographic Information System (GIS), Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, IranDepartment of Remote Sensing and Geographic Information System (GIS), Faculty of Geography, University of Tehran, Tehran, IranImage Processing Laboratory (IPL), University of Valencia, Valencia, SpainInstitute of Methodologies for Environmental Analysis (CNR IMAA), Tito, ItalyDepartment of Remote Sensing and Geographic Information System (GIS), Faculty of Geography, University of Tehran, Tehran, IranDepartment of Agroecology, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, IranDepartment of Remote Sensing and Geographic Information System (GIS), Faculty of Geography, University of Tehran, Tehran, IranIntroductionAquaCrop is a water-driven crop growth model that simulates aboveground biomass production in croplands. This study aimed to identify the driving parameters of the AquaCrop model for the model calibration and simplification to fill the research gap in intermediate environmental conditions between sub-tropical sub-humid and temperate sub-humid climates for silage maize.MethodsTo this end, we applied global sensitivity analysis (GSA) by combining the Morris method and the Extended Fourier Amplitude Sensitivity Test (EFAST) on crop yield output. The process involved a field sampling of soil and crop of silage maize carried out in the agricultural fields of Ghale-Nou, southern Tehran, Iran, in the summer of 2019 in order to measure certain model parameters.Results and discussionIn compliance with the Morris method, 30 parameters were identified as the least sensitive, while results from the EFAST test showed 9 parameters as contributing to the highest sensitivities in the model. The results clearly point to the capacity of employing a combination of both methods to attain a more efficient model calibration. Particular root, soil, canopy development, and biomass production parameters were influential and merit attention during calibration. Instead, parameters describing crop responses to water stress were acting rather insensitive in this study condition. The insights gained from this study, i.e., assessing parameter ranges and distinguishing between less sensitive and more sensitive parameters based on environmental and crop conditions, have the potential to be applied to other crop growth models with caution.https://www.frontiersin.org/articles/10.3389/fagro.2024.1304611/fullglobal sensitivity analysisAquaCrop modelMorrisEFASTsilage maize |
| spellingShingle | Elahe Akbari Ali Darvishi Boloorani Jochem Verrelst Stefano Pignatti Najmeh Neysani Samany Saeid Soufizadeh Saeid Hamzeh How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale Frontiers in Agronomy global sensitivity analysis AquaCrop model Morris EFAST silage maize |
| title | How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale |
| title_full | How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale |
| title_fullStr | How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale |
| title_full_unstemmed | How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale |
| title_short | How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale |
| title_sort | how global sensitive is the aquacrop model to input parameters a case study of silage maize yield on a regional scale |
| topic | global sensitivity analysis AquaCrop model Morris EFAST silage maize |
| url | https://www.frontiersin.org/articles/10.3389/fagro.2024.1304611/full |
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