Towards evaluating gully erosion volume and erosion rates in the Chambal badlands, Central India
Towards evaluating gully erosion volume and erosion rates in the Chambal badlands, Central India
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DOI：
10.1002/ldr.4250
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发表时间：
2022-03
影响因子：
4.7
通讯作者：
Raveena Raj;Ali. P. Yunus;P. Pani;R. Avtar
中科院分区：
文献类型：
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作者：
Raveena Raj;Ali. P. Yunus;P. Pani;R. Avtar
高分辨率多时相数字高程模型（DEM）是准确绘制沟道侵蚀量变化研究的关键。由于缺乏高空间分辨率的多时相DEM，印度荒地的沟道发育速率和沟道侵蚀充填量变化估计研究得很少。我们的研究探讨了使用多时相TerraSAR‐X附加数字高程测量（TanDEM‐X）导出的高程模型来量化印度中部Chambal荒地的侵蚀量和沟壑敏感性绘图。研究区基于DEM减法的沟蚀平均体积为135 × 105 m3，土壤侵蚀年速率估计为~284 t hr−1 yr−1。使用机器学习模型，我们训练这些数据用于更大研究区域的沟蚀敏感性和体积预测;并使用独立样本验证结果。该模型在受试者工作曲线下面积（AUC）值方面的准确度在训练时达到0.85，在验证时达到0.87，表明模型性能令人满意。经过验证后，最佳拟合模型被应用到一个测试站点（没有多时相DEM），以预测侵蚀区和侵蚀量估计。该模型预测，约40%的地区受到沟蚀的高度影响，最大的冲沟过程在中北部，最小的在测试区的西南部。在这项研究中提出的研究框架可以是有用的，在Chambal山谷的荒地的侵蚀速率估计，并可以有效地用于峡谷复垦项目。
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 × 105 m3, and the estimated annual rate of soil erosion was ~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.