Abstract: Xining Basin, located on the western margin of the Loess Plateaus, is characterized by rich saline soils. This study explored the electrical conductivity characteristics of loess saline soil and the relationship between soil electrical conductivity, soil water content and soil salt content in Xining Basin. The soil samples were collected from the test area. Due to the soil saline was not evenly distributed, we prepared the samples based on the collected soil after salt-leaching. Before salt leaching, the soil was of medium degree of salinization but after salt leaching it was of weak degree of salinization. The soils after salt leaching were mixed with different content of anhydrous sodium sulfate to form samples with different salt contents (0.18%, 0.68%, 1.18%, 1.68% and 2.18%) . For each sample, different water content was designed (5%, 10%, 15%, 20% and 25%). FJA-10 soil salt sensor and CD-12 intelligent salt conductivity instrument were used to measure the electrical conductivity of loess saline soil samples under different soil water content and soil salt content conditions. The relationship between soil electrical conductivity, water content and salt content were analyzed. On this basis, the regression model between electrical conductivity, water content and salt content of loess saline soil was established. The results showed that the soil electrical conductivity increased gradually with the increase of soil water content from 5.00% to 25.00% under the conditions of 0.18% to 2.18% salt content, and the relationship between soil electrical conductivity and water content conformed to power function. With the increase of soil salt content, the increasing range of soil electrical conductivity increased with the increase of water content. For the soil with high salt content, the effect of increasing water content on soil electrical conductivity was more significant. When the soil water content increased from 5.00% to 25.00%, with the increase of soil salt content from 0.18% to 2.18%, the soil electrical conductivity also showed a gradual increase trend, and the relationship between soil electrical conductivity and salt content was in a linear function. When the soil water content was relatively low, the increase of soil salt content had a relatively small impact on soil electrical conductivity; when the soil water content was relatively high, the increase of soil salt content showed a relatively significant effect on soil electrical conductivity. A regression model based on water content, salt content and their interaction was established and the model was built with a high determination coefficient R2 of 0.995 and the t test showed that the model coefficient was significant for the model. After transformation, a salt content estimation model was obtained. By validation, the relative error of actual and calculated salt content was less than 10%, indicating that the model was reliable for salt content estimation in Xining Basin. The model can be used to estimate the soil salt content quickly and effectively when the water content was higher than 5% and less than 25% (not equal to 5.52%) and the salt content was between 0.18% and 2.18%. The results of this study provides an effective model for salt content estimation in Xining Basin. It is of guiding significance for division of salinization degree, evaluation of engineering geological characteristics and scientific prevention and control of geological hazards such as soil salinization of loess saline soil in the study area and its surrounding areas.