A New Approach for Estimating Soil Salinity Using A Low-Cost Soil Sensor In Situ: A Case Study in Saline Regions of China’s East Coast

• Main Authors: Jianjun Wang, Quan Sun, Jiali Shang, Jiahua Zhang, Fei Wu, Guisheng Zhou, Qigen Dai
• Format: Article
• Language: English
• Published: MDPI AG 2020-01-01
• Series: Remote Sensing
• Subjects: soil salinity estimation; coastal saline soils; soil apparent electrical conductivity (eca); electromagnetic soil sensor
• Online Access: https://www.mdpi.com/2072-4292/12/2/239

Accurate and timely information on soil salinity is crucial for vegetation growth and agricultural productivity in coastal regions. This study investigates the potential of using Wifi POGO, an in situ electromagnetic sensor, for soil salinity assessment over saline coastal regions in eastern China. The sensor readings, soil moisture, and temperature-corrected apparent electrical conductivity (ECa) were used to generate models for EC_1:5 (a surrogate for soil salinity) estimation. Two salty areas with distinct soil textures, sandy loam (Shuntai) and clay (Dongxin), were selected. This study revealed that the difference between soil salinity and the in situ measured soil ECa (i.e., EC_1:5-ECa) had a strong curvilinear relationship with soil moisture. Such a relationship allows for the direct estimation of soil salinity from soil ECa with the aid of soil moisture information. Both ECa and soil moisture can be measured in situ using a Wifi POGO, a low-cost ground-based soil sensor. By using the leave-one-out cross-validation (LOOCV), the achieved root mean square error (RMSE) and relative RMSE (RRMSE) in EC_1:5 estimation were 0.0109 S/m and 19.24% respectively in Shuntai, and 0.0157 S/m and 16.05%, in Dongxin. This new method offers a simple, cost-effective and reliable tool for assessing soil salinity in dynamic coastal regions.