Himalaya RFR K

· features.csv contains feature data for each of the 208 quasi-steady state Himalaya catchment-averaged erosion rates used in this study. Columns are (left to right): MAP, MAT, UCS, MDSZ, NDVI, and mean longitude. · K.csv contains the erosional efficiency values for each of the quasi-steady state catchments calculated with Equation 1 in the supporting information. · RFR_routine.py is a python script to reproduce results plotted in Figure 6 of the main text. Default settings recreate the Himalaya RFR model and generate feature importance statistics. · Ero_grid_RFR_Karnali.tif (UTM Zone 44N) is the erosion rate map calculated with erosional efficiency predicted by the Himalaya RFR model in the Karnali catchment. · K_grid_RFR_Karnali.tif (UTM Zone 44N) is the erosional efficiency map predicted by the Himalaya RFR model for the Karnali catchment.· features.csv 包含本研究所用的208组准稳态喜马拉雅流域平均侵蚀速率对应的特征数据集。各列从左至右依次为：年均降水量（Mean Annual Precipitation, MAP）、年均气温（Mean Annual Temperature, MAT）、单轴抗压强度（Uniaxial Compressive Strength, UCS）、MDSZ、归一化植被指数（Normalized Difference Vegetation Index, NDVI）以及平均经度。 · K.csv 包含本研究支持信息中公式1计算得到的各准稳态流域的侵蚀效率数值。 · RFR_routine.py 为一段Python脚本，可用于复现正文中图6的绘图结果。采用默认配置即可重现喜马拉雅RFR模型，并生成特征重要性统计指标。 · Ero_grid_RFR_Karnali.tif（通用横轴墨卡托投影第44N带，UTM Zone 44N）为卡尔纳利流域内基于喜马拉雅RFR模型预测的侵蚀效率计算得到的侵蚀速率分布图。 · K_grid_RFR_Karnali.tif（通用横轴墨卡托投影第44N带，UTM Zone 44N）为喜马拉雅RFR模型针对卡尔纳利流域预测得到的侵蚀效率分布图。