Estimation of saturated hydraulic conductivity of the soil surface layer by combining transfer functions and remote sensing (Case Study: South of Ahwaz Lands)

Document Type : Research Paper

Authors

1 Department of Irrigation and Drainage, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran

2 Department of Irrigation and Drainage, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

Abstract

Hydraulic conductivity is one of the most important physical properties of soil, and knowing it plays a vital role in investigating the transport of solutes and pollutants in porous environments such as soil. This study aims to obtain saturated hydraulic conductivity pedotransfer functions (PTFs) using soil properties and satellite images. In this regard, the hydraulic conductivity of soil saturation was performed using the Inversed augerhole method in a part of the southwestern lands of Khuzestan province at 50 points. Then, at these points, surface samples of the soil were taken and soil properties such as soil texture, electrical conductivity, soil organic carbon, and saturated moisture were determined in the laboratory. In the next step, the indices of Sentinel-2 satellite images were calculated in three categories of soil, vegetation, and moisture indices and 11 PTFs, (PTF1-PTF11) for saturated hydraulic conductivity were obtained in four stages by combining soil properties and these indices. Finally, the spatial distribution of saturated soil hydraulic conductivity was obtained using the random forest model. The results of the modeling of PTFs of saturated hydraulic conductivity showed that among the 11 models with which PTFs of hydraulic conductivity were performed, the combination of three vegetation indices with soil-found early properties was the most effective for estimating the saturated hydraulic conductivity (PTF7). The values of R2, RMSE and MAE for this case were equal to 0.83, 0.40 and 0.166 respectively. Finally, the spatial distribution of saturated hydraulic conductivity using the Random Forest model showed that this model performs the spatial distribution of saturated soil hydraulic conductivity of soil well. Based on the obtained results, it can be found that the combination of soil properties with the indices obtained from the Sentinel-2 satellite images, creates PTFs of saturated hydraulic conductivity of the soil with very high accuracy.

Keywords

Main Subjects


EXTENDED ABSTRACT

Introduction:

 In order to absorb water, the plant needs a suitable environment. During the irrigation, the environment becomes saturated. After depletion of gravity water from the plant root zone, unsaturated state in the soil occured. Based on this, the study and measurement of soil hydraulic conductivity and penetration are the essential parameters of the soil and water resources management. Hydraulic conductivity is one of the most important physical properties of the soil, which plays a vital role in solute and pollutant transport in the porous environments such as soil.

 

Objective:

 This study aims to obtain pedotransfer functions (PTFs) for saturated and unsaturated hydraulic conductivity using soil properties and satellite images.

 

Materials and methods:

 In this regard, soil sampling was performed in some parts of the southwest of Khuzestan province at 50 points. After that, soil samples were passed through a 2 mm sieve for homogenizing, and soil properties such as soil texture, electrical conductivity, soil organic carbon, and saturated moisture were determined in the laboratory. Then, saturated hydraulic conductivity was determined at the same sampling points in the field. Then after, indicators of Sentinel-2 satellite images were obtained. For this purpose, visible, infrared, mid-infrared, and short-infrared satellite images were prepared with a spatial resolution of 20 m2, and the indices of Sentinel-2 satellite images were calculated in three categories of soil, vegetation, and moisture. Finally, 11 PTFs, (PTF1-PTF11) for saturated hydraulic conductivity were obtained in four stages by combining soil properties and the aformentioned indices.

 

Results and discussion:

 The results of the PTFs models for saturated hydraulic conductivity showed that among the 11 models, the combination of three vegetation indices with easily measured soil properties was the most effective PTF model for estimating the saturated hydraulic conductivity (with R2 = 0.57, RMSE = 0.63 and MAE = 0.40). While the PTF7 model obtained by combination of the vegetation cover index and soil properties had R2 = 0.83, RMSE = 0.4 and MAE = 0.166. Finally, the spatial distribution of saturated hydraulic conductivity using the Random Forest model showed a better performance, as compared to the others.

 

Conclusion:

Based on the obtained results, it was found that PTFs obtained from soil properties alone cannot estimate the soil hydraulic conductivity with appropriate accuracy. Therefore, it is suggested in addition of soil properties, satellite images indices are used for modeling PTFs, in order to improve estimation of saturated hydraulic conductivity in the soil.

 

 Keywords: Sentinel-2,  Soil properties,  Soil texture,  Vegetation index.

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