SavedAdd your journal

Journals / Eurasian Journal of Soil Science / 2013 / Cilt: 2 - Sayı: 2

Probability mapping of saline and sodic soils in the Harran plain using a non-linear kriging technique

Ali Volkan BİLGİLİ
Mehmet Ali ÇULLU
Salih AYDEMİR
Aydın AYDEMİR
Ahmet ALMACA
Pages
76–81
Publication Date
2013-06-01
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results of IK showed the probability distributions of risky areas under different types of soil salinity classes; nonsaline, saline, saline – sodic and sodic.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In the Harran Plain, southeastern Turkey, soil salinisation causes land degradation threatening the sustainability of agricultural production.
📊
Key Findings & Data:According to a recent survey, approximately 18000 ha area has been affected by soil salinity and sodicity at various levels.
💡
Conclusion & Impact:The results of IK showed the probability distributions of risky areas under different types of soil salinity classes; nonsaline, saline, saline – sodic and sodic.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Harran Plain · saline-sodic soils · indicator kriging

Abstract

In the Harran Plain, southeastern Turkey, soil salinisation causes land degradation threatening the sustainability of agricultural production. According to a recent survey, approximately 18000 ha area has been affected by soil salinity and sodicity at various levels. Determining the distribution of saline and sodic soils in the study area is the first step for effective management of these soils. Over 200 soil samples have been randomly selected across the plain and analyzed for selected soil salinity and sodicity variables in soil salinity laboratory. Indicator kriging (IK), a non-linear interpolation technique, was used to map the probability levels of occurrence of saline and sodic soils across the plain. The results of IK showed the probability distributions of risky areas under different types of soil salinity classes; nonsaline, saline, saline – sodic and sodic.

🔖

Cite This Article

BİLGİLİ, A. V., ÇULLU, M. A., AYDEMİR, S., AYDEMİR, A., ALMACA, A. (2013). Probability mapping of saline and sodic soils in the Harran plain using a non-linear kriging technique. Eurasian Journal of Soil Science, Cilt: 2 - Sayı: 2, 76–81. https://ajindex.com/articles/756933

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (10)

  1. Andrews, S.S., Karlen, D.L., Cambardella, C.A., 2004. The Soil Management Assessment Framework: A quantitative Soil Quality Evaluation Method. Soil Science Society of America Journal, 68, 1945-1962.
  2. Ardahanlıoglu, O., Oztas, T., Evren, S., Yılmaz, H., Yildirim, Z.N., 2003. Spatial variability of exchangeable sodium, electrical conductivity, soil pH and boron content in salt-and sodium-affected areas of the Igdir plain (Turkey). Journal of Arid Environments, 54, 495-503.
  3. Aydemir, S., Sonmez, O., 2008. Ameliorative effect of indigenous calcite on sodium- saturated clay sytems. Soil Science, 173, 96-107.
  4. Bilgili, A.V., Akis, R., Aydemir, A., Cullu, M. A., van Es, H.M., 2006. The Prediction and Extraction of Hill Slope Flow Paths and Ephemeral Gullies in a digitized Harran Watershed. Sustainable Developments and new Technologies for Agricultural Production in Gap Region. May 29-31 2006. Sanliurfa/Turkiye. Bilgili, A.V., Cullu, M. A., van Es, H., Aydemir, A., Aydemir, S., 2011. The Use of Hyperspectral Visible and Near Infrared Reflectance Spectroscopy for the Characterization of Salt-Affected Soils in the Harran Plain, Turkey. Arid Land Research and Management, 25, 19 - 37. Cambardella, C.A., Moorman, T.B., Novak, J.M., Parkin, T.B., Karlen, D.L., Turco, R.F., Konopka, A.E., 1994. Field-scale variability of soil properties in Central Iowa soils. Soil Science Society of America Journal, 58, 1501-1511.
  5. Cetin, M., Kirda, C., 2003. Spatial and temporal changes of soil salinity in a cotton field irrigated with low-quality water. Journal of Hydrology, 272, 238-249.
  6. Cullu, M.A., 2003. Estimation of the Effect of Soil Salinity on Crop Yield Using Remote Sensing and Geographic Information System. Turkish Journal Agriculture and Forestry, 27, 23-28.
  7. Dash, J.P., Sarangi, A., & Singh, D.K., 2010. Spatial Variability of Groundwater Depth and Quality Parameters in the National Capital Territory of Delhi. Environmental Management, 45, 640-650.
  8. Demir, Y., Ersahin, S., Güler, M., Cemek, B., Günal, H., Arslan, H., 2009. Spatial variability of depth and salinity of groundwater under irrigated ustifluvents in the Middle Black Sea Region of Turkey. Environmental Monitoring and Assessment, 158, 279-94.
  9. Goovaerts, P., 1997. Geostatistics for Natural Resources Evaluation.Oxford University Press,
  10. New York. Hu, K., Huang, Y., Li, B., Chen, D., White, R.E., 2005. Spatial variability of shallow groundwater level, electrical conductivity and nitrate concentration, and risk assessment of n