Supplementary material 1 (S1) and 2 (S2): Predicting soil moisture conditions across a heterogeneous boreal catchment using terrain indices

S1: DEM preparation and terrain indice modeling, Python Code and DEM This folder contains all data needed to produce the terrain indices modeled within the paper. It contains the Python Code for DEM aggregation, hydrological correction and terrain indice modeling S2: Interactive OPLS analysis loading plot for the Krycklan catchment and DEM-derived terrain indices in respect of soil moisture predictions. This folder contains the Interactive version of the OPLS analysis loading plot (Fig 2.) for the Krycklan catchment and DEM-derived terrain indices in respect of soil moisture predictions. In the interactive version of this graph (html), all labels are visible by moving the cursor on top of each circle. By clicking on a circle the terrain chosen index group will be highlighted Variables that cluster closely within the same neighborhood along the far sides of the horizontal axis are the more robust soil moisture predictors across DEM scales. Colored guides connect terrain indices moving from small to large resolutions as depicted by the symbol size. In the loading plot, predictive performance increases with increased distance from 0 on the predictive axis (pq[1]). Negative and positive values on the (pq[1]) axis correspond to negative and positive correlations with Y. The orthogonal axis (poso[1]) represents how much of the variation for each variable was not correlated with the determinant (Y).

S1：DEM（数字高程模型，Digital Elevation Model）制备与地形指数建模、Python代码及DEM数据集 该文件夹包含生成论文中所述地形指数建模所需的全部数据，内含用于DEM聚合、水文校正及地形指数建模的Python代码。

S2：克里克兰流域交互式OPLS（正交偏最小二乘，Orthogonal Partial Least Squares）分析载荷图及基于DEM提取的地形指数土壤湿度预测 该文件夹包含针对克里克兰流域、用于土壤湿度预测的基于DEM提取地形指数的OPLS分析交互式载荷图（即图2）。该交互式图形（html格式）中，将光标悬停于每个圆形之上即可显示所有标签；点击某一圆形，即可高亮选中对应的地形指数组别。在横轴两端邻近区域聚类的变量，是跨DEM尺度下表现更稳健的土壤湿度预测因子。彩色导引线连接不同分辨率的地形指数，符号尺寸对应分辨率由小到大的变化。在该载荷图中，预测性能随预测轴（pq[1]）上与0的距离增大而提升。（pq[1]）轴上的正负值分别代表与因变量（Y）呈负相关与正相关。正交轴（poso[1]）则代表各变量中未与因变量（Y）相关的变异占比。