4.6 Article

Towards evaluating gully erosion volume and erosion rates in the Chambal badlands, Central India

期刊

LAND DEGRADATION & DEVELOPMENT
卷 33, 期 9, 页码 1495-1510

出版社

WILEY
DOI: 10.1002/ldr.4250

关键词

Chambal badlands; gully erosion; random forest; soil erosion volume; susceptibility mapping

资金

  1. Hokkaido University DX Fellowship [JPMJSP2119]
  2. Japan Society for the Promotion of Science [21K05664]
  3. Grants-in-Aid for Scientific Research [21K05664] Funding Source: KAKEN

向作者/读者索取更多资源

High-resolution multi-temporal digital elevation models (DEM) were used to quantify erosion volume and gully susceptibility mapping in the Chambal badlands, Central India. Machine learning models were used to predict gully erosion susceptibilities and volume for a larger study region, with satisfactory model performance. The model predicted that 40% of the area is highly affected by gully erosion, with the most severe gully development in the north-Central part.
High-resolution multi-temporal digital elevation model (DEM) are key to accurate mapping of gully erosion volume change studies. Owing to the lack of multi-temporal DEM at a high spatial resolution, gully development rate, and gully erosion-fill volume change estimates in the Indian badlands are poorly studied. Our study explored the use of multi-temporal TerraSAR-X add-on for digital elevation measurement (TanDEM-X) derived elevation models to quantify the erosion volume and gully susceptibility mapping in the Chambal badlands, Central India. The average volume of gully erosion based on the DEM subtraction method in the study area was found to be 135 x 10(5) m(3), and the estimated annual rate of soil erosion was similar to 284 t hr(-1) yr(-1). Using machine learning models, we trained these data for gully erosion susceptibilities and volume prediction for a larger study region; and validated the results with independent samples. The accuracy of the model in terms of area under the receiver operating curve (AUC) values has reached 0.85 for training and 0.87 for validation, indicating satisfactory model performance. After validation, the best fit model was implemented onto a testing site (no multi-temporal DEM available) in order to predict erosion zones and erosion volume estimation. The model predicted that about 40% of the area is highly affected by gully erosion, with the maximum gullying process in the north-Central and lowest in the southwest parts of the testing area. The research framework presented in this study can be useful in estimating the erosion rate in the badlands of the Chambal Valley and can be used effectively in ravine reclamation projects.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据