Evaluating a hybrid soil temperature model in a corn-soybean agroecosystem and a tallgrass prairie in the Great plains
Simulation models of soil-related biological processes usually require soil temperature data. Frequently these soil temperatures are simulated, and the soil temperature algorithms cannot be more complicated than the original process model. This situation has led to the use of semi-empirical-type rel...
| Main Authors: | , , , , |
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| Format: | info:ar-repo/semantics/artículo |
| Language: | Inglés |
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University of Nebraska Press
2019
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| Subjects: | |
| Online Access: | https://digitalcommons.unl.edu/greatplainsresearch/1129/ http://hdl.handle.net/20.500.12123/6458 |
| _version_ | 1855035678751981568 |
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| author | Song, Feng Salvagiotti, Fernando Schmer, M.R. Wingeyer, Ana Beatriz Weiss, Albert |
| author_browse | Salvagiotti, Fernando Schmer, M.R. Song, Feng Weiss, Albert Wingeyer, Ana Beatriz |
| author_facet | Song, Feng Salvagiotti, Fernando Schmer, M.R. Wingeyer, Ana Beatriz Weiss, Albert |
| author_sort | Song, Feng |
| collection | INTA Digital |
| description | Simulation models of soil-related biological processes usually require soil temperature data. Frequently these soil temperatures are simulated, and the soil temperature algorithms cannot be more complicated than the original process model. This situation has led to the use of semi-empirical-type relationships in these process models. The objective of this study was to evaluate a hybrid soil temperature model, which combines empirical and mechanistic approaches, in an agroecosystem and a tallgrass prairie in the Great Plains. The original hybrid soil temperature model was developed and verified for a temperate forest system. This model simulated soil temperatures on a daily basis from meteorological inputs (maximum and minimum air temperatures) and soil and plant properties. This model was modified using different extinction coefficients for the plant canopy and ground litter. The agroecosystem consisted of a no-till rotation system of corn (Zea mays L.) and soybeans (Glycine max [L.] Merr.). Soil temperatures were measured at different depths in multiple years (three years and two-and-a-half years in the agroecosystem and tallgrass prairie, respectively). In the agroecosystem, the root mean square error of the modified model simulation varied from 1.41º to 2.05ºC for the four depths (0.1, 0.2, 0.3, and 0.5 m). The mean absolute error varied from 1.06º to 1.53ºC. The root mean square error and mean absolute error of the modified model were about 0.1º–0.3ºC less than the original model at the 0.2–0.5 m depths. For the tallgrass prairie, the mean absolute errors of the simulated soil temperatures were slightly greater than the agroecosystem, varying from 1.48º to 1.7ºC for all years and from 1.09º to 1.37ºC during the active growing seasons for all years. |
| format | info:ar-repo/semantics/artículo |
| id | INTA6458 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | University of Nebraska Press |
| publisherStr | University of Nebraska Press |
| record_format | dspace |
| spelling | INTA64582023-12-27T14:13:31Z Evaluating a hybrid soil temperature model in a corn-soybean agroecosystem and a tallgrass prairie in the Great plains Song, Feng Salvagiotti, Fernando Schmer, M.R. Wingeyer, Ana Beatriz Weiss, Albert Maíz Soja Agroecosistemas Modelos de Simulación Temperatura Suelo Maize Soybeans Agroecosystems Simulation Models Temperature Soil Simulation models of soil-related biological processes usually require soil temperature data. Frequently these soil temperatures are simulated, and the soil temperature algorithms cannot be more complicated than the original process model. This situation has led to the use of semi-empirical-type relationships in these process models. The objective of this study was to evaluate a hybrid soil temperature model, which combines empirical and mechanistic approaches, in an agroecosystem and a tallgrass prairie in the Great Plains. The original hybrid soil temperature model was developed and verified for a temperate forest system. This model simulated soil temperatures on a daily basis from meteorological inputs (maximum and minimum air temperatures) and soil and plant properties. This model was modified using different extinction coefficients for the plant canopy and ground litter. The agroecosystem consisted of a no-till rotation system of corn (Zea mays L.) and soybeans (Glycine max [L.] Merr.). Soil temperatures were measured at different depths in multiple years (three years and two-and-a-half years in the agroecosystem and tallgrass prairie, respectively). In the agroecosystem, the root mean square error of the modified model simulation varied from 1.41º to 2.05ºC for the four depths (0.1, 0.2, 0.3, and 0.5 m). The mean absolute error varied from 1.06º to 1.53ºC. The root mean square error and mean absolute error of the modified model were about 0.1º–0.3ºC less than the original model at the 0.2–0.5 m depths. For the tallgrass prairie, the mean absolute errors of the simulated soil temperatures were slightly greater than the agroecosystem, varying from 1.48º to 1.7ºC for all years and from 1.09º to 1.37ºC during the active growing seasons for all years. EEA Oliveros Fil: Song, Feng. University of Nebraska–Lincoln. School of Natural Resources; Estados Unidos Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Departamento de Agronomía; Argentina Fil: Schmer, M.R. University of Nebraska–Lincoln. Department of Agronomy and Horticulture; Estados Unidos Fil: Wingeyer, Ana Beatriz. University of Nebraska–Lincoln. Department of Agronomy and Horticulture; Estados Unidos Fil: Weiss, Albert. University of Nebraska–Lincoln. School of Natural Resources; Estados Unidos 2019-12-05T13:53:09Z 2019-12-05T13:53:09Z 2010 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://digitalcommons.unl.edu/greatplainsresearch/1129/ http://hdl.handle.net/20.500.12123/6458 1052-5165 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 University of Nebraska Press Great Plains Research 20 (2) : 249–260 (2010) |
| spellingShingle | Maíz Soja Agroecosistemas Modelos de Simulación Temperatura Suelo Maize Soybeans Agroecosystems Simulation Models Temperature Soil Song, Feng Salvagiotti, Fernando Schmer, M.R. Wingeyer, Ana Beatriz Weiss, Albert Evaluating a hybrid soil temperature model in a corn-soybean agroecosystem and a tallgrass prairie in the Great plains |
| title | Evaluating a hybrid soil temperature model in a corn-soybean agroecosystem and a tallgrass prairie in the Great plains |
| title_full | Evaluating a hybrid soil temperature model in a corn-soybean agroecosystem and a tallgrass prairie in the Great plains |
| title_fullStr | Evaluating a hybrid soil temperature model in a corn-soybean agroecosystem and a tallgrass prairie in the Great plains |
| title_full_unstemmed | Evaluating a hybrid soil temperature model in a corn-soybean agroecosystem and a tallgrass prairie in the Great plains |
| title_short | Evaluating a hybrid soil temperature model in a corn-soybean agroecosystem and a tallgrass prairie in the Great plains |
| title_sort | evaluating a hybrid soil temperature model in a corn soybean agroecosystem and a tallgrass prairie in the great plains |
| topic | Maíz Soja Agroecosistemas Modelos de Simulación Temperatura Suelo Maize Soybeans Agroecosystems Simulation Models Temperature Soil |
| url | https://digitalcommons.unl.edu/greatplainsresearch/1129/ http://hdl.handle.net/20.500.12123/6458 |
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