ABSTRACT:

This dataset contains the codes and data used in the manuscript "Temporal hydrologic constraints on time-lapse electrical resistivity inversion in hydrogeophysics".In the first folder, Hydrology-constrain includes the three inversion codes and processed field ERT data for the inversion. In the second folder, Hydrologic modeling includes the codes for hydrologic modeling and generating synthetic datasets. Abstract for the manuscript: Time-lapse electrical resistivity method has been frequently used in hydrology to monitor dynamic water flows and storage changes in the subsurface. To construct temporal resistivity images for hydrologic interpretations, measured apparent resistivity datasets at different times need to be inverted. Traditionally, this time-lapse resistivity inversion either assumes no links between adjacent resistivity models (individual inversion) or enforces the maximum smoothness condition in the time domain (temporal smoothness-constrained inversion). While the former method applies no temporal constraint to the resistivity changes, the latter minimizes the temporal resistivity changes. Both inversions could introduce biases to the reconstructed resistivity models, especially in hillslopes where the subsurface moisture (and thus ground resistivity) is neither independent nor unchanged during a typical monitoring period (e.g., a water year). In this study, we propose to construct realistic temporal resistivity constraint from subsurface water storage data. To test this new method, we combined integrated hydrologic modeling and resistivity forward modeling to design a synthetic case. Comparing the inversion results to ground truth shows that the hydrologic data-constrained inversion captures the dynamic water flows and storage changes in the subsurface. Application of this new method to a field dataset was also performed. Compared to existing inversion methods, the new method better reveals the abrupt resistivity changes associated with some intense hydrologic events such as rainfall/snowmelt infiltration and soil drying in the summer. This study thus provides a useful tool for processing time-lapse resistivity data collected at many dynamic hydrologic systems such as hillslopes, drylands, agriculture fields, and forest land.

ABSTRACT:

This dataset contains the codes and data used in the manuscript “Influence of Subsurface Critical Zone Structure on Hydrological Partitioning in Mountainous Headwater Catchments” submitted to Geophysical Research Letters. The software requirement are summarized in requirement.txt; hydrologic modeling input data are in the folder TLnewtest2sfb2; the observation data used in the simulation are indicated as comments in the python scripts. Note that the hydrologic modeling was run in HPC (Linux system) with parallel computing.

Below are the abstract of the manuscript:
“Headwater catchments play a vital role in regional water supply and ecohydrology, and a quantitative understanding of the hydrological partitioning in these catchments is critically needed, particularly under a changing climate. Recent studies have highlighted the importance of subsurface critical zone (CZ) structure in modulating the partitioning of precipitation in mountainous catchments; however, few existing studies have explicitly taken into account the 3D subsurface CZ structure. In this study, we designed realistic synthetic catchment models based on seismic velocity-estimated 3D subsurface CZ structures. Integrated hydrologic modeling is then used to study the effect of the shape of the weathered bedrock bottom on various hydrologic fluxes and storages in mountainous headwater catchments. Numerical results show that the shape of the weathered bedrock bottom not only affects the magnitude but also the peak time of both streamflow and subsurface dynamic storage.”

ABSTRACT:

Codes and data for paper: The Role of Subsurface Critical Zone Structure on Hydrological Partitioning in a Headwater Mountainous Catchment
The paper abstract
Headwater catchments play a vital role in regional water supply, necessitating a comprehensive understanding of hydrological partitioning for sustainable management. Recent studies have highlighted the significance of fractured rock layers in hydrological partitioning. However, the influence of these fractures on hydrological partitioning, particularly in relation to regional stress fields and the distribution of fractures parallel or mirroring the surface, remains largely unknown. This study utilizes geophysics-informed hydrologic modeling to examine the impacts of subsurface structure on hydrological partitioning in a mountainous headwater catchment. Our findings underscore the substantial influence of fractured bedrock on streamflow discharge, rock storage, and deep infiltration. Notably, climate change simulations reveal that catchments with paralleling surface structures may exhibit lower resilience. These findings provide valuable insights for water resource management, emphasizing the need to consider subsurface characteristics, including bedrock fracture distributions, to effectively anticipate and adapt to changing hydrological patterns.

The code and data description:
The code-dependent package see requirement.txt
Note that the code was running in HPC (Linux system) for parallel computing purposes. We cannot promise it can work in the Windows system.
All of model input data are in folder TLnewtest2sfb2
The use of data can be seen in the comment in the python code