Estimation of soil depth in the Liukuei Experimental Forest by using conceptual model

The spatial distribution of soil depth is the key information of watershed planning and design, and also one of the factors that determine the classification of slope utilization. The depth of soil on hillside requires on-site survey, which is labor-intensive. In addition, there are real challenges in updating or supplementing data because surveyed data may be altered by subsequent artificial or natural forces. Based on the concept of risk assessment, this study calculated the external forces (external factors) and internal forces (location factors) on the topsoil's surface, and analyzed the soil formation relevant environmental indicators and then established a potential soil depth estimating model for the study area. Besides terrain and vegetation factors which are proved to be significant factors concerning soil genesis, plant height was also used to estimate soil depth because it is proportional to the depth of the underground root system and depth of root system is generally positively related to soil depth. Therefore, the information of Canopy Height Model (CHM) to the model can increase the model interpretation rate by 15%. The depth index value (SDI) is used to estimate soil depth by using the conversion equation (D-p = 706.5 x SDI 43.812, R-2 = 0.76, p = 0.024). The extracted environmental indicators can dynamically and accurately estimate the spatial distribution of soil depth. The correlation between soil depth and slope gradient was also studied. The results can provide reference for relevant departments in the fields of watershed management, tending and afforestation, and resource conservation.

Automated summary

The study established a potential soil depth estimating model based on the concept of risk assessment, combining environmental indicators influencing soil formation and plant height. The information from Canopy Height Model (CHM) was found to increase the model interpretation rate. The study used the depth index value (SDI) to estimate soil depth and analyzed the correlation between soil depth and slope gradient.