Prediction of Soil Properties Using Random Forest with Sparse Data in a Semi-Active Volcanic Mountain
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ENESIS AND GEOGRAPHY OF SOILS
Prediction of Soil Properties Using Random Forest with Sparse Data in a Semi-Active Volcanic Mountain H. Piri Sahragarda, * and M. R. Pahlavan-Radb, ** a
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Rangeland and Watershed Department, Water and Soil Faculty, University of Zabol, Zabol, Iran and Water Research Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran *e-mail: [email protected] **e-mail: [email protected] Received December 30, 2019; revised February 26, 2020; accepted April 1, 2020
Abstract—Understanding spatial variations of soil properties is necessary for the management of rangelands vegetation ecosystem. The present study aimed to assess the spatial variations of soil properties in the hillslope of the Taftan semi-active volcanic mountain, Sistan and Baluchestan Province, south-eastern Iran. The locations of 30 sampling points were determined using random - systematic method and soil samples were taken from two depths: 0–30 and 30–60 cm. Spatial distribution of soil properties and relationships between soil properties and covariates were investigated using Random forest method. Model validation was done through 10-fold cross-validation approach. Based on results elevation, channel network base level and vertical distance to channel network, were the most importance environmental variables in predicting of the some soil characteristics such as soil clay, silt, sand, SOC, and EC in two studied depths. The maps produced indicated higher clay at 30–60 depth in the higher elevations. EC amounts were increased in the lower parts of the mountain because of leaching. Furthermore, the highest map accuracy was related to EC map at both depths and clay at 30–60 depth. The prediction maps of other properties of soil had low accuracy. Keywords: DEM, environmental variables, Taftan, Random forest DOI: 10.1134/S1064229320090136
INTRODUCTION Assessing the spatial variation of organic carbon (OC), electrical conductivity (EC), and soil texture is important in rangeland ecosystems of arid environments because of their effects on soil fertility, hydraulic conductivity, infiltration rate, and erosion. These characteristics can also influence plant species distribution [31]. Furthermore, different plant species can affect various soil properties significantly through evacuating moisture, soil nutrient uptake, and carbon stabilization [27–30]. Thus, knowledge on regularities of soil spatial variation is necessary for sustainable vegetation management in the rangeland ecosystem, especially mountainous landscape. Determination of soil properties distribution in the mountainous area is difficult because of sampling limitations and the complex processes of soil formation. The mountain areas have heterogeneous environments and shallow soils [18]. Here, topography and local climate are important factors in controlling soil properties such as organic matter (OM) [15]. Due to soil carbon turnover and geomorphology relat
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