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cryotools / matilda

Tool for modeling water resources in glacierized catchments. Combines a temperature-index melt model with the conceptual catchment model HBV and a parameterized glacier area/volume re-scaling routine.
MIT License
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glaciers hydrological-modelling hydrology melt python

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MATILDA - Modeling Water Resources in Glacierized Catchments

The MATILDA framework combines a simple positive degree-day routine (DDM) to compute glacial melt with the hydrological bucket model HBV (Bergström, 1986). The aim is to provide an easy-access open-source tool to assess the characteristics of small and medium-sized glacierized catchments and enable users to estimate future water resources for different climate change scenarios. MATILDA is an ongoing project and therefore a work in progress.

Overview

In the basic setup, MATILDA uses a modified version of the pypdd tool to calculate glacial melt based on a positive degree-day approach and a modified version of HBV from the Lumped Hydrological Models Playground (LHMP). The output contains the modeled time series for various components of the water balance, basic statistics for these variables, a choice of model effieciency coefficients (e.g. NSE, KGE...), and several plots of in- and output data.

Requirements

The tool should run with every Python3 version on most computer operating systems. It was developed on Python 3.6.9 on Ubuntu 20.04. It requires the following Python3 libraries:

The MATILDA package and dependencies can be installed to your local machine by using pip or a comparable package manager. You can either install the package by using the link to this repository:

pip install git+https://github.com/cryotools/matilda.git

...or clone this repository to you local machine, navigate to top directory and use:

pip install .

Data

The minimum input is a CSV-file containing timeseries of air temperature (°C), total precipitation (mm) and (if available) evapotranspiration data (mm) in the format shown below. If evapotranspiration is not provided it is estimated from air temperature following Oudin et.al. 2010. A series of runoff observations (mm) is used to calibrate/validate the model. All data sets need at least daily resolution.

TIMESTAMP T2 RRR PE
2011-01-01 00:00:00 -18.2 0.00 0.00
2011-01-01 01:00:00 -18.3 0.1 0.00
2011-01-01 02:00:00 -18.2 0.1 0.00
... ... ... ...
Date Qobs
2011-01-01 0.17
2011-01-01 0.19
... ...

The forcing data is scaled to the mean glacier elevation and the mean catchment elevation respectively using linear lapse rates. Reference altitudes for the input data, the whole catchment, and the glacierized fraction need to be provided. Automated routines for catchment delineation and the download of public glacier data will be added to MATILDA in future versions.

To include the deltaH parameterization from Huss and Hock 2015 within the DDM routine to calculate glacier area evolution in the study period, information on the glaciers is necessary. The routine requires an initial glacier profile containing the spatial distribution of ice over elevation bands at the beginning of the study period in form of a dataframe:

Elevation Area WE EleZone
3720 0.005 10786.061 3700
3730 0.001 13687.801 3700
3740 0.001 12571.253 3700
3750 0.002 12357.987 3800
.. ... ... ...

The deltaH parametrization routine is based on the workflow outlined by Seibert et.al. (2018).

Workflow

The MATILDA package consists of four different modules: parameter setup, data preprocessing, core simulation, and postprocessing. All modules can be used individually or via the superior MATILDA_simulation function. To use the full workflow the following steps are recommended:

Application example

An example script and 3y of sample data can be found here.

Built using

Authors

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License.

References