Integrating multiple electromagnetic data to map spatiotemporal variability of soil salinity in Kairouan region, Central Tunisia

Soil salinization is a major problem affecting soils and threatening agricultural sustainability in arid and semi-arid regions,which makes it necessary to establish an efficient strategy to manage soil salinity and confront economic challenges that arise from it.Saline soil recovery involving drainage of shallow saline groundwater and the removal of soil salts by natural rainfall or by irrigation are good strategies for the reclamation of salty soil.To develop suitable management strategies for salty soil reclamation,it is essential to improve soil salinity assessment pro cess/mechanism and to adopt new approaches and techniques.T his study mapped a recovered area of 7200 m2 to assess and verify variations in soil salinity in space and time in K airouan region in Central Tunisia,taking into account the thickness of soil materials.Two electromagnetic conductivity meters(EM38 and EM31)were used to measure the electrical conductivity of saturated soil-paste extract(ECe)and apparent electrical conductivity(E Ca).Multiple linear regression was established between ECe and ECa,and it was revealed that ECa-EM38 is optimal for E Ce prediction in the surface soils.Salinity maps demonstrated that the spatial structure of soil salinity in the region of interest was relatively unchanged but varied temporally.Variation in salinity at the soil surface was greater than that at a depth.These findings can not only be used to track soil salinity variations and their significance in the field but also help to identify the spatial and temporal features of soil salinity,thus improving the efficiency of soil management.

Estimating Exchangeable Sodium Percentage from Sodium Adsorption Ratio of Salt-Affected Soil in the Songnen Plain of Northeast China

Soil exchangeable sodium percentage (ESP) and sodium adsorption ratio (SAR) are commonly used to assess soil sodicity.Correlation between ESP and SAR of saturated pasted extract (SAR e) or of 1:5 (m:m) mixture soil to water (SAR 1:5) has been documented to predict ESP from SAR.However limited studies have been undertaken to model soil ESP based on soil SAR in the Songnen Plain,Northeast China.In this study,117 soil samples were used to predict ESP from SAR e and SAR 1:5 of salt-affected soils in western Songnen Plain.Soil ESP was highly related (r 2 > 0.76,P < 0.001) with SAR e and SAR 1:5.ESP of salt-affected soils in the Songnen Plain could be predicted using a logarithmic regression equations of ESP=10.72 · ln(SAR e) 15.36 and ESP=11.44 · ln(SAR 1:5) + 5.48.