https://github.com/britishgeologicalsurvey/disolv

https://github.com/britishgeologicalsurvey/disolv

Repository

https://github.com/BritishGeologicalSurvey/disolv/blob/master/

# DISOLV

The following is a brief description of the input/output structure. For a full description of the code see our paper: Collins S, Bianchi M (2020) DISOLV: A Python package for the interpretation of borehole dilution tests. *Groundwater*. [Available here](https://ngwa.onlinelibrary.wiley.com/doi/abs/10.1111/gwat.12992)

## Installation

DISOLV can be installed for Python 2.7 or Python 3 using pip:

```
pip install disolv
```

It can be used within other Python code with:

```python
import disolv
disolv.run('input_dir', 'output_dir', calibrate=True, convertFEC=True,
           method='SLSQP')
```

## Structure of input files

### in.csv
This file contains the main input parameters. Do not delete any lines from the file.

![In file 1](/Images/incsv.PNG)

### flows.csv
This file contains the depths and flow rates of the fractures. If used in forward mode, the two columns *Upper depth limit* and *Lower depth limit* are not required. Positive flows are inflows and negative flows are outflows. If using the code for FFEC logging (i.e. a pumped borehole), add the depth and flow rate of the pump to this file, as you would a fracture.

![In file 2](/Images/flowscsv.PNG)

### initialcondition.csv
This file contains the depth vs. concentration data for the initial state. DISOLV will interpolate the data onto a 1D grid with the spatial discretization given in *in.csv*. If these data are FEC data rather than concentration data (e.g. in kg/m3), DISOLV can convert them to concentration data by setting the argument *convertFEC* to 'True'. 

![In file 3](/Images/incon.PNG)

### measuredprofiles.csv

This file contains the measured profiles at the output times defined in *in.csv*. This is a required input for inversion modelling but optional for forward modelling.

![In file 4](/Images/measured.PNG)

## Running the model

DISOLV can be imported and run as follows:

```python
    import disolv
    disolv.run('input_dir', 'output_dir', calibrate=False, convertFEC=False)
```   
    
The first and second arguments are the file paths to the input and output directories. *Calibrate* refers to whether the model is being run in forward ('False') or inverse ('True') mode, and *convertFEC* indicates whether the initial condition has been given in fluid electrical conductivity (S cm1) and must be converted to concentration (in kg m3) (True) or whether it has been given as a concentration (False).

If DISOLV is run in inverse mode, the optimization method can be chosen in the final argument:

```python
    disolv.run('input_dir', 'output_dir', calibrate=True, convertFEC=False, method='SLSQP')
```
## Output

The modelled depth vs. concentration data can be found in *Output\profiles.csv*. If used in inversion mode, *Output.csv* will contain the optimized output parameters.

The modelled data and measured data (if given) are plotted in *profiles.csv*.

![In file 5](/Output/Berambadi.png)

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