UNCERTAINTY ASSESSMENT OF THE SOIL SALINITY BOUNDARY IN URMIA PLAIN USING BAYESIAN MAXIMUM ENTROPY METHOD

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HAMZEHPOUR N.; KARIMIAN EGHBAL M.; TOOMANIAN N.; SOKOUTI OSKOUEI R.; BOGAERT P.

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Journal: Journal of Soil Management and Sustainable Production Year:2015 | Volume:5 | Issue:2 Page(s): 131-146

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Title

UNCERTAINTY ASSESSMENT OF THE SOIL SALINITY BOUNDARY IN URMIA PLAIN USING BAYESIAN MAXIMUM ENTROPY METHOD

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Keywords

BAYESIAN MAXIMUM ENTROPY METHODQ2

UNCERTAINTYQ2

SOFT DATAQ2

HARD DATAQ2

URMIA PLAINQ1

Abstract

Background and Objectives: In recent years, decrease in depth of Urmia Lake and remain of vast saline areas has resulted in higher increase of salinity threat in agricultural lands around the Lake. The aims of this study were 1- Investigation of the spatial changes in soil salinity using the BAYESIAN MAXIMUM ENTROPY METHOD (BME); 2- prediction of the boundary between saline and agricultural lands; and 3- Assessment of the UNCERTAINTY involved with salinity boundary prediction in South Urmia Plane, North West of Iran.Materials and Methods: The research was done on a grid of 500 m, but in areas with high salinity changes, samples were taken from each 250 m. the study area contained an area of approximately 5000 ha of lands in western shores of Urmia Lake, south of URMIA PLAIN in west Azerbaijan Province. Soil samples were gathered in autumn 2009 and repeated in spring 2010.Electrical conductivity of soil samples were measured twice, once in the field, using a portable EC meter in 1: 2.5 soil to water ratio and again in the laboratory. Field measured soil salinity was considered as SOFT DATA and laboratory measurements as HARD DATA. Two third of the samples for autumn were used for modeling and prediction and the rest were used for validation. ME and MSE criteria were used for comparison of the results. Prediction error variance resulted from BME equations, was used for assessing the UNCERTAINTY of the soil salinity boundary prediction.Results and Conclusion: Results revealed that there was a significant relation between field and laboratory measurements of soil salinity and among compared models, linear method with least mean absolute error and least bias error of 0.37 and -0.72 respectively, was chosen as best fitted model. Then for each sampling campaign best covariance model was fitted and model parameters were calculated. Cross-validation results showed that BME method with ME and MSE equal to 0.42 and 0.33 for autumn 2009 and 0.2 and 0.64 for spring 2010 respectively, had a high accuracy in spatial prediction of soil salinity, considering that only probabilistic type SOFT DATA was used. A sharp boundary was detected between salty and non-salty lands in the area and the BME method had a high ability in predicting the UNCERTAINTY involved with boundary predictions. Monitoring soil property variation such as salinity is sometimes limited because it is costly and requires time to gather necessary HARD DATA. BME method has shown potential for using SOFT DATA in cases that HARD DATA are not readily available.

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APA: Copy

HAMZEHPOUR, N., KARIMIAN EGHBAL, M., TOOMANIAN, N., SOKOUTI OSKOUEI, R., & BOGAERT, P.. (2015). UNCERTAINTY ASSESSMENT OF THE SOIL SALINITY BOUNDARY IN URMIA PLAIN USING BAYESIAN MAXIMUM ENTROPY METHOD. ELECTRONIC JOURNAL OF SOIL MANAGEMENT AND SUSTAINABLE PRODUCTION, 5(2), 131-146. SID. https://sid.ir/paper/209945/en

Vancouver: Copy

HAMZEHPOUR N., KARIMIAN EGHBAL M., TOOMANIAN N., SOKOUTI OSKOUEI R., BOGAERT P.. UNCERTAINTY ASSESSMENT OF THE SOIL SALINITY BOUNDARY IN URMIA PLAIN USING BAYESIAN MAXIMUM ENTROPY METHOD. ELECTRONIC JOURNAL OF SOIL MANAGEMENT AND SUSTAINABLE PRODUCTION[Internet]. 2015;5(2):131-146. Available from: https://sid.ir/paper/209945/en

IEEE: Copy

N. HAMZEHPOUR, M. KARIMIAN EGHBAL, N. TOOMANIAN, R. SOKOUTI OSKOUEI, and P. BOGAERT, “UNCERTAINTY ASSESSMENT OF THE SOIL SALINITY BOUNDARY IN URMIA PLAIN USING BAYESIAN MAXIMUM ENTROPY METHOD,” ELECTRONIC JOURNAL OF SOIL MANAGEMENT AND SUSTAINABLE PRODUCTION, vol. 5, no. 2, pp. 131–146, 2015, [Online]. Available: https://sid.ir/paper/209945/en

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