EGU25-9463, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-9463
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Wednesday, 30 Apr, 11:05–11:15 (CEST)
 
Room D2
Random forest-based prediction of gully density on farmland in the Songnen typical black soil region of the Northeast, China
Hong Liu, Chunmei Wang, Yixian Chen, Lei Ma, Chunmei Zhang, Yongqing Long, and Qinke Yang
Hong Liu et al.
  • Northwest University, College of urban and environment science, Remote Sensing and Geo-information Science, China (liured@stumail.nwu.edu.cn; cmwang@nwu.edu.cn;yxchen@nwu.edu.cn;leima@stumail.nwu.edu.cn;zhangchunmei@stumail.nwu.edu.cn;sjzxlyq@nwu.edu.cn;q
  •  Gully erosion represents one of the most severe forms of land degradation. In regional management decisions, gully density serves as a crucial metric. As an essential measure under China’s national strategy for protecting black soil, gully erosion control projects rely on accurate simulation of gully density at the regional scale to enable more efficient and precise management. Taking the northeast China’s Songnen typical black soil region as the study area, this research employed a stratified unequal probability systematic sampling method to select 977 small watershed sample units. Using sub-meter resolution Google Earth imagery, gully density on farmland was visually interpreted. To ensure the interpretation’s accuracy, 55 typical small watersheds were randomly selected as validation units for field investigations. On this basis, the RF algorithm was used with 13 selected factors to predict farmland gully length density. The results showed the following: 1) The Random Forest model demonstrated high accuracy and applicability, with an NSE exceeding 0.5. Residuals primarily centered around -0.1 km/km². 2) Slope was identified as the key influencing factor for farmland gully density, followed by multi-year average May precipitation, slope length, and multi-year average rainstorm volume. Threshold analysis revealed a significant increase in gully density when slope exceeded 1.21° and slope length surpassed 74.15 m, but a weakening effect was observed when the slope and slope length reached certain thresholds. 3) The prediction results indicated higher gully densities in low mountains and hilly areas. Regions with a density range of 0–0.05 km/km², followed by 0.05–0.25 km/km². As density increased, the proportion of area gradually declined, with areas >1 km/km² accounting for no more than 15% of the total. High-density regions were concentrated in low mountains and hilly areas, with average gully densities of 1.33 km/km² and 1.80 km/km², respectively, whereas low-density regions were concentrated in plains, with densities close to 0 km/km². This study provides theoretical and technical support for regional gully management decisions in the black soil region of Northeast China, contributing to the protection of black soil resources.
  • Keywords: Permanent gully; Songnen typical black soil region; Random Forest; Regional scale; Gully length density

How to cite: Liu, H., Wang, C., Chen, Y., Ma, L., Zhang, C., Long, Y., and Yang, Q.: Random forest-based prediction of gully density on farmland in the Songnen typical black soil region of the Northeast, China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9463, https://doi.org/10.5194/egusphere-egu25-9463, 2025.