Zoning and Identification of Environmental Characteristics Affecting Soil Organic Carbon Storage in Gonbad Paired-Watershed

Attaeian, Behnaz; Badrestani, Ali; Khosrobeigi Bozchelui, Saeid; Artimani, Mohammad Mehdi

doi:10.22059/jrwm.2024.362517.1716

Document Type : Research Paper

Authors

¹ Department of Nature Engineering, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran

² Department of Nature Engineering, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran.

³ General Department of Natural Resources of Markazi Province, Arak, Iran

⁴ General Department of Natural Resources of Hamedan Province, Hamedan, Iran.

10.22059/jrwm.2024.362517.1716

Abstract

Soil organic carbon as a key factor in soil stability and fertility is considered as one of the important environmental challenges in the context of climate change. The aim of this study was to determine soil organic carbon zonation in Gonbad paired-watershed, Hamedan province. In this research, the information of meteorology, soil science and erosion and sedimentation study of Gombad watershed was used, including the information of 49 profiles in the 0-15 cm soil layer. After collecting data, tests of normality (Shapiro-Wilkα test <0.05), homogeneity of variance, and then the relationship between independent variables and organic carbon were performed using Pearson's linear correlation in SAS software. Also, determining the most effective independent variable using multivariate analysis, PCA factor analysis was used in XlStat 2.1 software. In order to determine the distribution and amount of soil organic carbon in the Gonbad representative watershed, modeling using SVM support vector machine learning algorithms and RF random forest was used in R software.The results showed that 78.18% of soil organic carbon changes depend on four components. Clay and nitrogen percentage were selected as the most effective variables on soil organic carbon content, so that the first component of clay content explained 34% and the second component nitrogen explained 18% of variations. According to the results of the implementation of the SVM and RF Models, the SVM model with a CE factor of 0.86 and RMSE of 0.05 in the test stage is a more accurate model in this study.

Keywords

References

Abdulkadir, A., Mohammed, I., & Daudu, C. K. (2021). Organic Carbon in Tropical Soils: Current Trends and Potential for Carbon Sequestration in Nigerian Cropping Systems. In Handbook of Climate Change Management: Research, Leadership, Transformation (pp. 1-23). Cham: Springer International Publishing.

Allison, L.E. (1975). Wet combustion apparatus and procedure for organic and inorganic carbon in soil. Soil Science Socety America Proceeding, 24, 36-40.

Attaeian, B., Farrokhzadeh, B., & Akhzari, D. (1394). Carbon sequestration potential zoning and study of physiographic factors affecting it in Gonbad watershed. Master's thesis, Faculty of Natural Resources and Environment, Malayer University. (In Persian).

Benke, K. K., Norng, S., Robinson, N. J., Chia, K., Rees, D. B., & Hopley, J. (2020). Development of pedotransfer functions by machine learning for prediction of soil electrical conductivity and organic carbon content. Geoderma, 366, 114210.

Blake, G. R., & Hartge, K. H. (1986). Bulk density. P 363-375. Methods of Soil Analysis: Part, 1(10.2136).

Boone, L. E., Kurtz, D. L., & Berston, S. (2019). Contemporary business. John Wiley & Sons.

Fathalolomi, S., Vaezi, A., Alavi Panah, S.K., & Ghorbani, A. (2019). Modeling soil organic carbon changes using remote sensing indicators in the Balikhali watershed of Ardabil tea. Iran Water and Soil Research, 51 (9), 2417- 2429. (In Persian).

Fathi Gerdelidani, A., & Rahimzadeh, B. (2017). The role of clay fraction in retention of dissolved organic carbon in soil. Water and Soil Science, 26(4.2), 273-285. (In Persian).

Gee, G. W., & Bauder, J. W. (1986). Particle‐size analysis. Methods of soil analysis: Part 1 Physical and mineralogical methods, 5, 383-411.

Hernandez, R., Koohafkan, P., & Antoine, J. (2004). Assessing carbon stocks and modelling win-win scenarios of carbon sequestration through land-use changes (Vol. 1). Food & Agriculture Org.

Hojati, S. M., Tafazoli, M., Asadian, M., & Baluee, A. (2022). Estimation of carbon sequestration and forest soil respiration using machine learning ‎‎models in Eastern Forests of Mazandaran Province. Forest Research and Development, 8(4), 371-388.

ILRI, I. (2021). UNEP and ILC. 2021. Rangelands Atlas. Nairobi Kenya: ILRI For more information on the Atlas please contact: Fiona Flintan, Senior Scientist, ILRI f. flintan@ cgiar. org BY CC, 4.

Jafari, A., Sefidi, H., & Rahimi, M. (2021). Investigating the relationship between spatial changes of soil carbon deposition with climatic elements of temperature and precipitation in recent years (Ahangaran basin study area). Journal of Climate Change Research, 3 (12), 1-20. (In Persian).

Kamali, N., & Sadeghipour, A. (2017). Investigating the impact of some environmental factors on soil carbon storage (case study: Hashtgerd Alborz). The 7th National Conference on Pasture and Pasture Management of Iran. May 18-19, 2018.

Khamoshi, S. E., Sarmadian, F., & Omid, M. (2023). Predicting and Mapping of Soil Organic Carbon Stock Using Machin Learning Algorithm, Iranian Journal of Soil and Water Research, 53 (11), 2671-2681.

Keshavarz, P., Zngiabadi, M., & Abbaszadeh, M. (2013). Relationship between soil organic carbon and wheat grain yield as affected by soil clay content and salinity. Iranian Journal of Soil Research, 27(3), 359-371.

Khan, N., Jhariya, M. K., Raj, A., Banerjee, A., & Meena, R. S. (2021). Soil carbon stock and sequestration: implications for climate change adaptation and mitigation. Ecological intensification of natural resources for sustainable agriculture, 461-489.

Lahooti, P., Emadi, L., Bahmanyar, L.U., & Qajar Sepanlu, M. (2017). Zoning of soil organic carbon using geostatistical methods and artificial neural network (Kohgilouye and Boyer Ahmad provinces). Water and Soil, 32(6), 1135-1148. (In Persian).

Lekzian, A., Fadeli, M., Astarai, A., & Fatut, A. (2012). Estimation and zoning of soil organic carbon by using land effects analysis (case study: a part of land in Mashhad city). Water and Soil Journal, 27 (1), 180-192. (In Persian).

Mahmoudzadeh, H., Matinfar, H.R., & Taghizadeh Mehrjardi, R. (2019). Digitization of soil organic carbon (case study: Kamiyaran city, Kurdistan province). Journal of Soil Management and Sustainable Production, 10 (4), 77-98. (In Persian).

Naghibi, S. A., Pourghasemi, H. R., Pourtaghi, Z. S., & Rezaei, A. (2015). Groundwater qanat potential mapping using frequency ratio and Shannon’s entropy models in the Moghan watershed, Iran. Earth Science Informatics, 8, 171-186. (In Persian).

Pussinen, A. (2002). Stemwood volume increment changes in European forests due to climate change—a simulation study with the EFISCEN model. Global change biology. 8(4):304-316.

Radhika, Y., & Shashi, m. (2009). Atmospheric Temperature Prediction using Support Vector Machines. Iternational Journal of Computer Theory and Engineering, 1(1), 55-58.

Rousta, M. J., Suleimanpour, M., Enayati, M., & Pak Parvar, M. (2020). Comparison of soil carbon and nitrogen storage in Garbaigan Fasa plain in two conditions of flood spreading and without flood spreading. Watershed Management Research, 12 (24), 170-181. (In Persian).

Schlesinger, W. H., & Bernhardt, E. S. (2013). Biogeochemistry: an analysis of global change. Waltham, MA.

Sheyday Karkaj, E., Sepehri, A., Barani, H., & Motamedi, J. (2017). Relationship between Soil Organic Carbon Storage and some Soil Properties in the Pastures of East Azerbaijan. Journal of Rangeland Research, 11(2), 125-138. (In Persian).

Taghizadeh-Mehrjardi, R., Schmidt, K., Amirian-Chakan, A., Rentschler, T., Zeraatpisheh, M., Sarmadian, F., & Scholten, T. (2020). Improving the spatial prediction of soil organic carbon content in two contrasting climatic regions by stacking machine learning models and rescanning covariate space. Remote Sensing, 12(7), 1095. (In Persian).

Torkmani, F., Piri Sahragard, H., Pahlavan Rad, M.R., & Nahtani, M. (2018). Determining the spatial distribution of soil organic carbon and the factors affecting it using the random forest model in Rawang Minab watershed. Agricultural Engineering (Agricultural Scientific Journal), 42(4), 89-104. (In Persian).

Wang, M., Liao, L., Zhang, X., & Li, Z. (2012). Adsorption of low concentration humic acid from water by palygorskite. Applied Clay Science, 67, 164-168.

Wilding, L. P., & Dress, L. R. (1983). Spatial variability and pedology, P 83-116. Pedogensis and soil taxonomy. I. Concepts and interactions. Elsevier Science Publication of North Holland.

Zhu, L., Zhou, X., Liu, W., & Kong, Z. (2023). Total organic carbon content logging prediction based on machine learning: A brief review. Energy Geoscience, 4(2), 100098.

Journal of Range and Watershed Managment

Zoning and Identification of Environmental Characteristics Affecting Soil Organic Carbon Storage in Gonbad Paired-Watershed

References

References

Volume 78, Issue 1
February 2025
Pages 1-16

Zoning and Identification of Environmental Characteristics Affecting Soil Organic Carbon Storage in Gonbad Paired-Watershed

References

References

Volume 78, Issue 1February 2025Pages 1-16

Volume 78, Issue 1
February 2025
Pages 1-16