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Information Journal Paper

Title

SOIL MOISTURE ESTIMATION USING DIGITAL ELEVATION MODEL (DEM)

Pages

  61-71

Abstract

 This study was carried out in the western catchment of the Behzisty Township in Gorgan, Golestan province in order to develop the regression models of SOIL MOISTURE. In this study, the desired measurements were made in 18 locations using TDR during 6 running days after a relatively intense rainfall event at different depths of soil. The DIGITAL ELEVATION MODEL was prepared from Ultra Cam images taken in 2014 with the pixel size of 1×1 m in order to estimate the terrain properties. Finally, the regression model was developed with respect to these characteristics and SOIL MOISTURE. The results showed that important TERRAIN CHARACTERISTICS which are greatly associated with SOIL MOISTURE are horizontal curvature, slope, aspect and wetness index in the regression model. These results suggest that the diversion of material flow has controlled the amount of water in the soil, slope aspect and SOIL MOISTURE. The results showed that the developed regression models can forecast at least 44 to 60% of the total variations of SOIL MOISTURE in the watershed scale.

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  • Cite

    APA: Copy

    REZAEI MOGHADAM, H., HOSSEINALIZADEH, M., SHEIKH, V., & JAFARI, R.. (2015). SOIL MOISTURE ESTIMATION USING DIGITAL ELEVATION MODEL (DEM). JOURNAL OF RS AND GIS FOR NATURAL RESOURCES (JOURNAL OF APPLIED RS AND GIS TECHNIQUES IN NATURAL RESOURCE SCIENCE), 6(3), 61-71. SID. https://sid.ir/paper/189600/en

    Vancouver: Copy

    REZAEI MOGHADAM H., HOSSEINALIZADEH M., SHEIKH V., JAFARI R.. SOIL MOISTURE ESTIMATION USING DIGITAL ELEVATION MODEL (DEM). JOURNAL OF RS AND GIS FOR NATURAL RESOURCES (JOURNAL OF APPLIED RS AND GIS TECHNIQUES IN NATURAL RESOURCE SCIENCE)[Internet]. 2015;6(3):61-71. Available from: https://sid.ir/paper/189600/en

    IEEE: Copy

    H. REZAEI MOGHADAM, M. HOSSEINALIZADEH, V. SHEIKH, and R. JAFARI, “SOIL MOISTURE ESTIMATION USING DIGITAL ELEVATION MODEL (DEM),” JOURNAL OF RS AND GIS FOR NATURAL RESOURCES (JOURNAL OF APPLIED RS AND GIS TECHNIQUES IN NATURAL RESOURCE SCIENCE), vol. 6, no. 3, pp. 61–71, 2015, [Online]. Available: https://sid.ir/paper/189600/en

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