Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent...
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| Format: | info:ar-repo/semantics/artículo |
| Language: | Inglés |
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2018
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| Online Access: | https://revistas.unal.edu.co/index.php/acta_agronomica/article/view/53282/57810 http://hdl.handle.net/20.500.12123/2294 https://doi.org/10.15446/acag.v66n2.53282 |
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| author | Castro Franco, Mauricio Domenech, Marisa Beatriz Costa, Jose Luis Aparicio, Virginia Carolina |
| author_browse | Aparicio, Virginia Carolina Castro Franco, Mauricio Costa, Jose Luis Domenech, Marisa Beatriz |
| author_facet | Castro Franco, Mauricio Domenech, Marisa Beatriz Costa, Jose Luis Aparicio, Virginia Carolina |
| author_sort | Castro Franco, Mauricio |
| collection | INTA Digital |
| description | The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30) and 0-90 (ECa_90) and geomorphometric indices. To do this, a Random Forest (RF) analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror) were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results. |
| format | info:ar-repo/semantics/artículo |
| id | INTA2294 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| record_format | dspace |
| spelling | INTA22942018-05-02T18:43:27Z Modelling effective soil depth at field scale from soil sensors and geomorphometric indices Castro Franco, Mauricio Domenech, Marisa Beatriz Costa, Jose Luis Aparicio, Virginia Carolina Suelo Hidrología Geomorfología Soil Hydrology Geomorphology Profundidad del Suelo The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30) and 0-90 (ECa_90) and geomorphometric indices. To do this, a Random Forest (RF) analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror) were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results. EEA Barrow EEA Balcarce Fil: Castro Franco, Mauricio. Universidad de los Llanos; Colombia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Barrow; Argentina Fil: Costa, Jose Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina Fil: Aparicio, Virginia Carolina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina 2018-04-27T14:30:42Z 2018-04-27T14:30:42Z 2017 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://revistas.unal.edu.co/index.php/acta_agronomica/article/view/53282/57810 http://hdl.handle.net/20.500.12123/2294 0120-2812 2323-0118 https://doi.org/10.15446/acag.v66n2.53282 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Acta Agronómica 66 (2) : 228-234. (2017) |
| spellingShingle | Suelo Hidrología Geomorfología Soil Hydrology Geomorphology Profundidad del Suelo Castro Franco, Mauricio Domenech, Marisa Beatriz Costa, Jose Luis Aparicio, Virginia Carolina Modelling effective soil depth at field scale from soil sensors and geomorphometric indices |
| title | Modelling effective soil depth at field scale from soil sensors and geomorphometric indices |
| title_full | Modelling effective soil depth at field scale from soil sensors and geomorphometric indices |
| title_fullStr | Modelling effective soil depth at field scale from soil sensors and geomorphometric indices |
| title_full_unstemmed | Modelling effective soil depth at field scale from soil sensors and geomorphometric indices |
| title_short | Modelling effective soil depth at field scale from soil sensors and geomorphometric indices |
| title_sort | modelling effective soil depth at field scale from soil sensors and geomorphometric indices |
| topic | Suelo Hidrología Geomorfología Soil Hydrology Geomorphology Profundidad del Suelo |
| url | https://revistas.unal.edu.co/index.php/acta_agronomica/article/view/53282/57810 http://hdl.handle.net/20.500.12123/2294 https://doi.org/10.15446/acag.v66n2.53282 |
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