Soil Salinity and Alkalinity Map Preparation Based on Spatial Analysis of GIS (Case Study: Tabriz Plain)

Abstract

Better management of agricultural fields is related to valuable information which can derived from soil salinity and alkalinity maps. These maps are considered as one of the most important factors which restrict plant growth as well as decline crops yield. The objective of this research was preparing of soil salinity and alkalinity maps in Tabriz plain over 50,000 hectares based on different techniques of spatial analysis in GIS software. For this mean, study area was divided in 1500 × 1500 m 2 grid cells. Then, geographical coordinate of each grid recorded in UTM system. So, they were transferred into GPS for navigating to the exact excavation location. After soil sampling and transferring to the lab, their EC and PH were measured in saturation extract of soil samples. So, spatial distribution of soil sampling points was prepared in form of point map by GIS software. Generalization of point information to surface was performed using different interpolation algorithms and based on standards of Soil and Water Research Institute. Accuracy of interpolated maps was evaluated due to the MAE and MBE values. The results showed that the lowest observed error is related to the Spline method and therefore, this method was used for spatial modeling of salinity and alkalinity maps in the intended area. The research findings demonstrated that from total of 50,000 hectares, only 3066 hectares were without salinity and alkalinity limitation (6.1%), 9066 hectares had low salinity and alkalinity (18.1%); 17,772 hectares had average limitation for salinity and alkalinity (35.6%) and the remaining 20,096 hectares had high and very high limitation for salinity and alkalinity.

Monitoring the Variations of Soil Salinity in a Palm Grove in Southern Algeria

“…In many cases, the Kriging method proved to be the best estimator, i.e., ordinary Kriging (OK), while inverse distance weighting (IDW) or splines were considered appropriate methods in other cases [33][34][35][36][37]. The interpolation based on inverse distance weight (IDW) is an accurate method for mapping saline soils, according to Farajnia and Yarahmadi (2017) [38]. In addition, many studies using soil-landscape analysis have shown that it can be a very good indicator of the distribution of soil properties in space [39].…”