Assessing Variation of Soil Quality in Agroecosystem in an Arid Environment Using Digital Soil Mapping

Abstract

Monitoring the soil quality (SQ) in agricultural ecosystems is necessary for using sustainable soil and land resources. Therefore, to evaluate the SQ variation in an arid environment in the Bajestan region, northeastern Iran, two soil quality indices (weighted additive soil quality index-SQIw and nemoro soil quality index-SQIn) were applied. SQIs were assessed in two datasets (total data set-TDS and minimum data set-MDS) by linear (L) and nonlinear (NL) scoring methods. Physicochemical properties of 223 surface soil samples (0–30 cm depth) were determined. The random forest (RF) model was used to predict the spatial variation of SQIs. The results showed the maximum values of the SQIs in areas with saffron land covers, while the minimum values were acquired in the north of the study area where pistachio orchards are located due to higher EC and SAR. The environmental variables such as topographic attributes and groundwater quality parameters were the main driving factors that control SQIs distribution. These findings are beneficial for identifying suitable locations sites to plan agricultural management and sustainable usage of groundwater resources strategy to avoid further increase of soil salinity.

Keywords

• digital soil mapping
• groundwater quality
• indicator scoring system
• soil degradation
• soil health
• soil salinity