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).

本文件夹汇集了生成论文中所述地形指数所需的所有数据。其中包含用于数字高程模型聚合、水文校正和地形指数建模的 Python 代码。

本文件夹还包含了针对 Krycklan 河流域及其基于数字高程模型计算的地形指数与土壤湿度预测相关的 OPLS 分析加载图的交互式版本（图 2）。在交互式图形（HTML）中，通过将光标悬停在每个圆圈上方，可以清晰地查看所有标签。点击任意圆圈，所选地形指数组将被突出显示。

沿水平轴的远端，变量在相同邻近区域内紧密聚集的，是数字高程尺度下更为稳健的土壤湿度预测因子。颜色引导线连接从低分辨率到高分辨率的地形指数，其分辨率通过符号大小表示。在加载图中，预测性能随预测轴（pq[1]）上距离 0 的增加而提升。在（pq[1]）轴上的负值和正值分别对应与 Y 的负相关和正相关。正交轴（poso[1]）表示每个变量的变异中有多少未与决定因素（Y）相关。