News

a.z
Sepahvand, M., Khormali, F., Kiani, F., Eftekhari, K. (2018). Modeling Soil Depth and Topographic Attributes Relationship for Predicting Soil Depth in Rimeleh Catchment, Lorestan Province. , 31(4), 601-611. doi: 10.22092/ijsr.2018.115905
M. Sepahvand; F. Khormali; F. Kiani; K. Eftekhari. "Modeling Soil Depth and Topographic Attributes Relationship for Predicting Soil Depth in Rimeleh Catchment, Lorestan Province". , 31, 4, 2018, 601-611. doi: 10.22092/ijsr.2018.115905
Sepahvand, M., Khormali, F., Kiani, F., Eftekhari, K. (2018). 'Modeling Soil Depth and Topographic Attributes Relationship for Predicting Soil Depth in Rimeleh Catchment, Lorestan Province', , 31(4), pp. 601-611. doi: 10.22092/ijsr.2018.115905
Sepahvand, M., Khormali, F., Kiani, F., Eftekhari, K. Modeling Soil Depth and Topographic Attributes Relationship for Predicting Soil Depth in Rimeleh Catchment, Lorestan Province. , 2018; 31(4): 601-611. doi: 10.22092/ijsr.2018.115905

Modeling Soil Depth and Topographic Attributes Relationship for Predicting Soil Depth in Rimeleh Catchment, Lorestan Province

پژوهش های خاک
Article 11, Volume 31, Issue 4, March 2018, Pages 601-611    PDF (530.02 K)
DOI: 10.22092/ijsr.2018.115905
Authors
M. Sepahvand* 1; F. Khormali2; F. Kiani3; K. Eftekhari4
1PhD Student, Soil Sciences Department, Gorgan University of Agricultural Sciences and Natural Resources; and Scientific Staff of Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research,Education and Extension Organization
2Professor of Soil Sciences Department, Gorgan University of Agricultural Sciences and Natural Resources
3Assistant Professor., Soil Sciences Department, Gorgan University of Agricultural Sciences and Natural Resources
4Assistant Professor f., Soil and Water Research Institute, Agricultural Research, Education and Extension Organization
Abstract
Determination of soil depth and its variations is possible through soil survey and drilling. This requires budget, time, and skilled personnel. Soil – landscape relationships approach makes it possible to develop the soil depth predictor model from topographic attributes by using multiple linear regression statistic method. In this research, primary and secondary topographic attributes of the Rimeleh catchment were derived from a Digital Elevation Model (DEM). Soil depth was determined at 189 systematically randomized positions of the catchment by soil drilling. Data of soil depth and topographic attributes were analyzed using SPSS 19 software. Results showed that the soil depth predicted by the model had significant negative correlation (P<0.01) with slope gradient and elevation. The correlation coefficient of the model was 0.63. The fitted line to the scattered plot of observed soil depths and predicted soil depths had also a correlation coefficient of 0.65. Other topographic attributes affected the soil depth but their effects were not significant statistically. So, they were not included in the model.
Keywords
Digital Elevation Model; Landscape; Middle Zagros; Slope gradient
References
  1. بنایی، محمدحسن. 1356. نقشه رژیم رطوبتی و حرارتی خاک های ایران.
  2. محنت­کش، عبدالمجید. 1391. مدل­سازی خاک- زمین­نما و پیش­بینی تولید گندم دیم به کمک مدل­های مختلف در مناطقی از زاگرس مرکزی. رساله دکتری. دانشکده کشاورزی، دانشگاه صنعتی اصفهان.
  3. Boer, M., Del Barrio, G., and J. Puigdefabregas. 1996. Mapping of soil depth in dry mediterranian area using terrain attributes derived from a digital elevation model. Geoderma 72:99-118.
  4. Brubaker, S.C., Jones, A.J., Lewis, D.T., and k. Frank. 1993. Soil properties associated with landscape position. Soil. Sci. Soc. Am. J., 57: 235-239.
  5. Carter, B.J., and E.J. ciokosz. 1991. Slope gradient and aspect effects on soil developed from sandstone in Pennsylvania. Geoderma 49:199-213.
  6. Daniels, R.B., Gilliam, J.W., Cassel, D.K., and L.A. Nelson. 1985. Soil erosion class and landscape position in the North Carolina piedmont. Soil. Sci. Soc. Am. J., 49: 991-995.
  7. Florinsky, I.V., Eilers, R.G., Manning, G.R., and L.G. Fuller. 2002. Prediction of soil properties by digital terrain modeling. Environmental Modeling and Software 17:295-311.
  8. Gessler, P.E., Moore, I.D., Mckenzie, N.J., and P.J. Ryan. 1995 (Published on line 2007). Int. J. Geographical Information. Vol. 9. No. 4: 421-432.
  9. Gessler, P.E., Chadwick, O.A., and K. Holmes. 2000. Modeling soil- landscape and ecosystem properties using terrain attributes. Soil. Sci. Soc. Am. J.64:2046-2056.
  10. Jenny, H. 1941.Factors of soil formation: A system of quantitative pedology. McGraw Hill, New York.
  11. Kreznor,W.R., Olson, K.R., Banwart, W.L., and D.L. Johnson. 1989. Soil landscape and erosion relationships in a northwest Illinois WaterShed. Soil. Sci. Soc. Am. J., 53:1763-1771.
  12. Kuriakose, S.L., Devkota, S., and D.G. Rossiter. 2009. Prediction of soil depth using environmental variables in an anthropogenic landscape, a case study in the western Ghats of Kerala India. Catena 79:27-38.
  13. Mahler, P.J. 1979. Manual of land classification for irrigation. SWRI.pub.NO.205.
  14. Mcsweeney, K., Gessler, P.E., Slater, B., Hammer, D., Bell, J., and G.W. Petersen. 1994. Towards a new framework for modeling the soil- landscape continuum. P. 127-145. In R. Amundson and J.W. Harden (e.d.). Factors of soil formation: A fiftieth anniversary retrospective, SSSA Spee. Publ.33.SSSA, Madison, WI.
  15. Mehnatkesh, A.M., Ayoubi, Sh., Jalalian, A., And K.L. Sahrawat. 2013. Relationships between depth and terrain attributes in a semiarid hilly region in western Iran. J. Mt. Sci (2013) .10:163-172.
  16. Minasny, B., and A.B. Mcbrantney. 1999. A rudimentary mechanistic model for soil production and landscape development. Geoderma 90:3-21.
  17. Moore, I.D., Ladson, A.R., and R. Grayson. 1991. Digital terrain modeling: A review of hydrological, geomorphological, and biological applications. Hydro Processes 5: 3-30.
  18. Moore, I.D., Gessler, P.E., and G.A. Neilson. 1993. Soil attribute prediction using terrain analysis. Soil. Sci. Soc. Am. J. 57: 443-452.
  19. Penizek, V., and L. Boruk. 2006. Soil depth prediction supported by primary terrain attributes: A comparison of methods. Journal of Hydrology 202:158-172.
  20. Saulnier, G.M., Beven, K., and C. Obled. 1997. Including spatially variable effective soil depth in TOPMODEL. Journal of Hydrology 202:158-172.
  21. Thompson, J.A., Pena- Yewtukhiw, E.M., and J.H. Grove. 2006. Soil-landscape modeling across a physiographic region: Topographic pattern and model transportability. Geoderma 133:57-70.
  22. Tsai, C.C., Chen, Z.S., and C.T. Duh. 2001. Prediction of soil depth using soil landscape regression model: A case study on forest soils in southern Taiwan. National Science Council of the republic of China, Part B: Life Sciences 25:34-39.
  23. Van Walleghem, T., Poesen, J., and A. Mcbranty. 2010. Spatial variability of soil horizon depth in natural loess- derived soils. Geoderma 157:37-45.
  24. Walker, P.H., Hall, G.F., and R. Protz. 1968. Relation between landform parameters and soil parameters. Soil. Sci. Soc. Am. J., 32: 101-104.
  25. Ziadat, F.M. 2005, Analyzing digital terrain attributes to predict soil attributes for a relatively large area. Soil Science. Soc. Am. J. 69:1590-1598
Statistics
Article View: 966
PDF Download: 697


counter
Journal management system. designed by sinaweb