Dataset for Estimating soil hydraulic properties from oven-dry to full saturation using in

Toshiyuki Bandai of Lawrence Berkeley National Laboratory provides datasets to reproduce the analysis from the paper "Estimating soil hydraulic properties from oven-dry to full saturation using inverse modeling and shortwave infrared imaging." The repository includes data for inverse modeling, Python codes, and GIF movies of upward infiltration experiments. The readme file explains which data correspond to each figure in the paper.

Use Cases

• Calibrating soil hydraulic models based on data from upward infiltration experiments.
• Training inverse modeling algorithms using the provided Python codes and associated data.
• Analyzing soil moisture dynamics from oven-dry to full saturation based on shortwave infrared imaging data.
• Reproducing the figures and results from the associated research paper using the mapped data files.

Strengths

• Data is directly linked to a published research paper, providing a clear academic context.
• Includes complementary materials such as Python code for forward and inverse modeling and explanatory GIF movies.
• The readme file explicitly maps data to specific figures in the paper, aiding reproducibility.

Limitations

• Row count and dataset scale are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The description does not specify the file formats or size of the data.

Provenance

Source

Lawrence Berkeley National Laboratory

Collection Method

Data generated from upward infiltration experiments and shortwave infrared imaging, as described in the associated paper.