Modeling soil loss due to runoff in sugarcane cultivation using mixed linear models, period II semester 2019 – I semester 2021
DOI:
https://doi.org/10.5377/elhigo.v13i2.17374Keywords:
Tillage, Cumulative sheet, Vegetative developmentAbstract
The use of linear mixed models has been used in different scenarios and may have potential to describe soil loss due to runoff water. The objective of the study was to use linear mixed models to model soil loss due to runoff in a sugarcane crop on soils with sloping topography in two tillage conditions. The response variable was the loss of soil due to runoff and the explanatory variables were precipitation quantified as total accumulated depth and weeks of vegetative development of a sugar cane crop (variety CC 93 - 7711) for panela production. These data were taken from runoff plots that were installed in the municipality of Vélez, department of Santander (Colombia). A model was found that fits the loss of soil due to runoff water with a conditional coefficient of determination for linear mixed models of 0.84.
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Barton, K., & Barton, M. K. (2020). MuMIn: Multi-Model Inference. R package version 1.43.17. Version, 1(1).
Beretta-Blanco, A., & Carrasco-Letelier, L. (2017). USLE/RUSLE K-factors allocated through a linear mixed model for Uruguayan soils. Ciencia e Investigacion Agraria, 44(1), 100–112. https://doi.org/10.7764/rcia.v44i1.1622
Beroho, M., Briak, H., El Halimi, R., Ouallali, A., Boulahfa, I., Mrabet, R., Kebede, F., & Aboumaria, K. (2020). Analysis and prediction of climate forecasts in Northern Morocco: application of multilevel linear mixed effects models using R software. Heliyon, 6(10). https://doi.org/10.1016/j.heliyon.2020.e05094
Cerdà, A., Lucas Borja, M. E., Úbeda, X., Martínez-Murillo, J. F., & Keesstra, S. (2017). Pinus halepensis M. versus Quercus ilex subsp. Rotundifolia L. runoff and soil erosion at pedon scale under natural rainfall in Eastern Spain three decades after a forest fire. Forest Ecology and Management, 400. https://doi.org/10.1016/j.foreco.2017.06.038
Correa Morales, J. C., & Salazar Uribe, J. C. (2016). INTRODUCCIÓN A LOS MODELOS MIXTOS. Universidad Nacional de Colombia.
Deog Park, S., Song Lee, K., & Sook Shin, S. (2012). Statistical Soil Erosion Model for Burnt Mountain Areas in Korea—RUSLE Approach. Journal of Hydrologic Engineering, 17(2). https://doi.org/10.1061/(asce)he.1943-5584.0000441
Geissert, D., Mólgora-Tapia, A., Negrete-Yankelevich, S., & Hunter Manson, R. (2017). Effect of vegetation cover management on water erosion in shade coffee plantations. Agrociencia, 51(2).
Ghassan Abdo, H., & Mohssen Hassan, R. (2018). A statistical spatial modeling of soil erosion: case study of Al-Sen basin, Tartous, Syria. Environmental Geology, 2(2), 68–74. https://doi.org/10.14303/2591-7641.1000018
Jourgholami, M., & Labelle, E. R. (2020). Effects of plot length and soil texture on runoff and sediment yield occurring on machine-trafficked soils in a mixed deciduous forest. Annals of Forest Science, 77(1). https://doi.org/10.1007/s13595-020-00938-0
Laird, N. M., & Ware, J. H. (1982). Random-Effects Models for Longitudinal Data. Biometrics, 38(4). https://doi.org/10.2307/2529876
Leisch, F. (2004). FlexMix: A general framework for finite mixture models and latent class regression in R. Journal of Statistical Software, 11. https://doi.org/10.18637/jss.v011.i08
Barton, K., & Barton, M. K. (2020). MuMIn: Multi-Model Inference. R package version 1.43.17. Version, 1(1).
Beretta-Blanco, A., & Carrasco-Letelier, L. (2017). USLE/RUSLE K-factors allocated through a linear mixed model for Uruguayan soils. Ciencia e Investigacion Agraria, 44(1), 100–112. https://doi.org/10.7764/rcia.v44i1.1622
Beroho, M., Briak, H., El Halimi, R., Ouallali, A., Boulahfa, I., Mrabet, R., Kebede, F., & Aboumaria, K. (2020). Analysis and prediction of climate forecasts in Northern Morocco: application of multilevel linear mixed effects models using R software. Heliyon, 6(10). https://doi.org/10.1016/j.heliyon.2020.e05094
Cerdà, A., Lucas Borja, M. E., Úbeda, X., Martínez-Murillo, J. F., & Keesstra, S. (2017). Pinus halepensis M. versus Quercus ilex subsp. Rotundifolia L. runoff and soil erosion at pedon scale under natural rainfall in Eastern Spain three decades after a forest fire. Forest Ecology and Management, 400. https://doi.org/10.1016/j.foreco.2017.06.038
Correa Morales, J. C., & Salazar Uribe, J. C. (2016). INTRODUCCIÓN A LOS MODELOS MIXTOS. Universidad Nacional de Colombia.
Deog Park, S., Song Lee, K., & Sook Shin, S. (2012). Statistical Soil Erosion Model for Burnt Mountain Areas in Korea—RUSLE Approach. Journal of Hydrologic Engineering, 17(2). https://doi.org/10.1061/(asce)he.1943-5584.0000441
Geissert, D., Mólgora-Tapia, A., Negrete-Yankelevich, S., & Hunter Manson, R. (2017). Effect of vegetation cover management on water erosion in shade coffee plantations. Agrociencia, 51(2).
Ghassan Abdo, H., & Mohssen Hassan, R. (2018). A statistical spatial modeling of soil erosion: case study of Al-Sen basin, Tartous, Syria. Environmental Geology, 2(2), 68–74. https://doi.org/10.14303/2591-7641.1000018
Jourgholami, M., & Labelle, E. R. (2020). Effects of plot length and soil texture on runoff and sediment yield occurring on machine-trafficked soils in a mixed deciduous forest. Annals of Forest Science, 77(1). https://doi.org/10.1007/s13595-020-00938-0
Laird, N. M., & Ware, J. H. (1982). Random-Effects Models for Longitudinal Data. Biometrics, 38(4). https://doi.org/10.2307/2529876
Leisch, F. (2004). FlexMix: A general framework for finite mixture models and latent class regression in R. Journal of Statistical Software, 11. https://doi.org/10.18637/jss.v011.i08
Lima, P. L. T., Silva, M. L. N., Quinton, J. N., Batista, P. V. G., Cândido, B. M., & Curi, N. (2018). Relationship among crop systems, soil cover, and water erosion on a typic Hapludox. Revista Brasileira de Ciencia Do Solo, 42. https://doi.org/10.1590/18069657rbcs20170081
Martínez, D., Albín, J., Cabaleiro, J., Pena, T., Rivera, F., & Blanco, V. (2009). El Criterio de Información de Akaike en la Obtención de Modelos Estadísticos de Rendimiento. Jornadas de Paralelismo, 1(1), 439–444. https://www.researchgate.net/publication/236279245
Mohamadi, M. A., & Kavian, A. (2015). Effects of rainfall patterns on runoff and soil erosion in field plots. International Soil and Water Conservation Research, 3(4). https://doi.org/10.1016/j.iswcr.2015.10.001
Pinheiro, J. C., & Bates, D. M. (2000). Mixed-Effects Models in S and S-Plus: Statistics and Computing. In Mixed-Effects Models in S and S-PLUS.
Team, R. C. (2021). R: A Language and Environment for Statistical Computing. In R Foundation for Statistical Computing.
Vacca, A., Loddo, S., Ollesch, G., Puddu, R., Serra, G., Tomasi, D., & Aru, A. (2000). Measurement of runoff and soil erosion in three areas under different land use in Sardinia (Italy). Catena, 40(1). https://doi.org/10.1016/S0341-8162(00)00088-6
Wu, L. (2009). Mixed Effects Models for Complex Data (1st ed., Vol. 1). Chapman and Hall/CRC.
Wu, Y., Huang, W., Zhou, F., Fu, J., Wang, S., Cui, X., Wang, Q., Bo, Y., Yang, S., Wang, N., Gu, X., Chen, J., & Zhu, J. (2020). Raindrop-induced ejection at soil-water interface contributes substantially to nutrient runoff losses from rice paddies. Agriculture, Ecosystems and Environment, 304. https://doi.org/10.1016/j.agee.2020.107135
Zea, J. F., Murcia, M. A., & Poveda, F. E. (2014). Modelos mixtos aplicados a la productividad de hojarasca. Comunicaciones En Estadística, 7(2). https://doi.org/10.15332/s2027-3355.2014.0002.04
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