riversCentralAsia

riversCentralAsia: An R package to support data pre- and postprocessing for hydrological modelling with RS MINERVE - Published in JOSS (2023)

https://github.com/hydrosolutions/riverscentralasia

Repository

Package with helper functions to load, manage and analyze hydrometeorological data from Central Asia

README.Rmd

---
output: github_document
editor_options: 
  markdown: 
    wrap: 72
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
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)
```

# riversCentralAsia

## Summary

The R package riversCentralAsia includes a set of tools to facilitate
and automate data preparation for hydrological modelling. It thus
contributes to more reproducible modeling workflows and makes
hydrological modeling more accessible to students and to interested
professional modelers.

The package has been developed within the frame of a master level course
on applied hydrological modelling in Central Asia and is extensively
used in the open-source book
Modeling of Hydrological Systems in Semi-Arid Central
Asia (Siegfried & Marti, 2022). The workflows are further validated
within the Horizon 2020 project
HYDRO4U.

While the package has been developed for the Central Asia region, most
of the functions are generic and can be used for modelling projects
anywhere in the world.

The most important functionalities of the package as well as the raw
data that can be processed with the package are described in the the
articles of the
project documentation site but the examples in the
book Modeling of Hydrological Systems in Semi-Arid Central
Asia demonstrate the full range of functions available and how to
use them in a workflow.

## Statement of need

Data preparation comes before hydrological modelling and is actually one
of the biggest work chunks in the modelling process. This package
includes a number of helper functions that can be connected to efficient
workflows that automatize the data preparation process for hydrological
modelling as shown in the figure below. This supports a more
reproducible modelling workflow and improves the scalability of
hydrological modelling.

```{r out.width='80%', echo=FALSE}
knitr::include_graphics("./man/figures/fig_01_model_chain_bw.png")
```

Figure: Overview over the modelling workflow whos R-components are
supported by the riversCentralAsia package (Image source: Marti et al.,
2022). Abbreviations are explained in the text. The workflow relies
entirely on free, publicly available data and software.

The data preparation step covered by the *riversCentralAsia* package the
derivation of hydrological response units (HRU) using a basin outline
and the [SRTM digital elevation model
(DEM)](https://doi.org/10.5067/MEaSUREs/SRTM/SRTMGL1.003){target="_blank"}.
The [derivation of the basin
outline](https://hydrosolutions.github.io/caham_book/geospatial_data.html#sec-catchment-delineation){target="_blank"}
and [processing of geospatial layers for import to RS
MINERVE](https://hydrosolutions.github.io/caham_book/geospatial_data.html#sec-preparation-of-rsminerve-input-files){target="_blank"}
in QGIS is described in detail in @CAHAM:2022.

Although the High Mountain region of Central Asia is generally perceived
as a data scarce region, a number of gridded data products are available
that form a fair basis for regional hydrological modelling at seasonal
time scales. [CHELSA v2.1](https://chelsa-climate.org/){target="_blank"}
is a weather data product at 1 km2 grid resolution. The
*riversCentralAsia* package includes the function
[*gen_HRU_Climate_CSV_RSMinerve*](https://hydrosolutions.github.io/riversCentralAsia/reference/gen_HRU_Climate_CSV_RSMinerve.html){target="_blank"}
which extracts CHELSA precipitation or temperature on the hydrological
response units and returns the data in an RS MINERVE readable format.\
[Glacier
thinning](https://www.nature.com/articles/s41586-021-03436-z){target="_blank"}
and [glacier
ablation](https://doi.org/10.1038/s41467-021-23073-4){target="_blank"}
are data sets from open-access literature which can be used to calibrate
the [GSM model
objects](https://crealp.github.io/rsminerve-releases/tech_hydrological_models.html#sec-model_gsm){target="_blank"}
(a glacier runoff model) in RS MINERVE. Data on snow water equivalents
is sourced from the [High Mountain Asia Snow Reanalysis (HMASR)
Product](https://doi.org/10.5067/HNAUGJQXSCVU){target="_blank"} and can
be used to calibrate the snow module of the [HBV model
objects](https://crealp.github.io/rsminerve-releases/tech_hydrological_models.html#sec-model_hbv)
(a rainfall-runoff model) in RS MINERVE. The *riversCentralAsia* package
site includes a [demonstration of how HMASR data can be used for model
calibration](https://hydrosolutions.github.io/riversCentralAsia/articles/05-snow-calibration.html){target="_blank"}.
The process is very similar for the calibration of glacier thinning and
discharge.\
River discharge is taken from the hydrological year books of the
HydroMeteorological Institutes in Central Asia. The package
*riversCentralAsia* includes discharge time series from the Chirchiq
river basin north-east of Tashkent (Uzbekistan) as well as several
functions for loading discharge data, aggregating and visualization of
discharge data and discharge statistics (discharge characterization)
(see the [documentation on the discharge
functions](https://hydrosolutions.github.io/riversCentralAsia/articles/01-discharge-processing-examples.html){target="_blank"}).\
And last but not least, [CMIP6 climate model results area are available
from
Copernicus](https://cds.climate.copernicus.eu/cdsapp#!/dataset/projections-cmip6?tab=form){target="_blank"}.
The *riversCentralAsia* package can be used for [downscaling climate
projections](https://hydrosolutions.github.io/riversCentralAsia/reference/doQuantileMapping.html){target="_blank"}
using CHELSA data and to produce RS MINERVE readable climate forcing. We
use quantile mapping as statistical downscaling method
([qmap](https://cran.r-project.org/web/packages/qmap/){target="_blank"}
package by L. Gudmundsson).

Hydrological modelling is done using the free hydrologic-hydraulic
modelling software
RS MINERVE.
Some alternative geoprocessing workflows are described in
[QGIS](https://www.qgis.org/en/site/){target="_blank"}.

The riversCentralAsia package functionality includes:

-   Efficient processing of present and future climate forcing,
    including hydro-meterological data from Central Asia (time series and re-analysis data) and
    down-scaling of ERA5 re-analysis data (a more advanced topic which
    is described in the
    course book)

-   The preparation of GIS layers for automated model
    generation and chapter Geospatial data in the course book

-   Volume area scaling of glaciers

-   Post-processing of simulation results, e.g. extraction and visualisation of snow water
    equivalent or computation of flow duration curves

-   I/O interface with the hydrologic-hydraulic modelling software that
    allows reading and writing of input and output files of the
    hydraulic-hydrological modelling software
    RS
    MINERVE.

While here, we focus on the description of the individual functions, the
strengths of the package comes to play mostly when the functions are
connected to automatize the data preparation process. These workflows
are extensively documented in the book
Modeling of Hydrological Systems in Semi-Arid Central
Asia.

Currently, a relatively complete dataset of the Chirchik River Basin
with decadal and monthly data on discharge, precipitation and
temperature is included.

## Related packages

The hydraulic-hydrological modelling software RS MINERVE can be accessed
through Common Language Runtime (CLR) directly from within R, thus the
use of the RS MINERVE GUI can be avoided and multiple runs of large
models can be speed up. The [github repository
RSMinerveR](https://github.com/hydrosolutions/RSMinerveR){target="_blank"}
includes examples of how to use CLR commands to use the Visual Basic
interface with RS MINERVE documented in the [technical
manual](https://crealp.github.io/rsminerve-releases/tech_scripts.html){target="\"_blank"}.
This functionality is recommended for advanced users of RS MINERVE only.

## Installation

The package requires R version \>= 4.1

The package has many dependencies which will be installed alongside
riversCentralAsia. To successfully install the package you need prior
installations of the following packages: rlang, magrittr, stringr and
purrr. Should the installation fail, test if you have the following
dependencies installed.

``` r
find.package(c("rlang", "magrittr", "stringr", "purrr"))
```

If they are not yet available on your system, please install them using
the following commands.

``` r
install.packages(c("rlang", "magrittr", "stringr", "purrr"))
```

All other dependencies are installed automatically.

**Note** that **Mac** users may have to install the binary version of
the dependency package exactextractr manually (not the more recent
source version).

**Note** that **Windows** users require a working installation of
RTools to install packages from github.

You can install the development version from
GitHub with:

``` r
# install.packages("devtools")
devtools::install_github("hydrosolutions/riversCentralAsia")
library(riversCentralAsia)
```

We recommend testing of the riversCentralAsia package before using it to
make sure all dependencies integrate with the riversCentralAsia package
as they should. The following step-by-step instructions explain how to
do this:

1.  Go to the [packages github
    repository](https://github.com/hydrosolutions/riversCentralAsia),
    click the green code button and select download zip. This will
    download a zip folder with the package code to your Download
    folder.\
2.  Extract the package files to a location of your preference. More
    detailed instructions for this step: right-click on the zip folder
    and select "extract all"in the pop-up window. Select a location to
    extract the files to and wait for the process to finish.\
3.  Navigate into the riversCentralAsia folder to in which the freshly
    downloaded package data is stored and open the riversCentralAsia R
    project file. This will open the project in your R GUI.\
4.  In the R console, type `devtools::test()` and hit enter. The tests
    will run for about a minute. If the test return
    `[ FAIL 0 | WARN 0 | SKIP 0 | PASS 86 ]` at the end, all test were
    successful and the package will run without problems on your system.
    Should one of the tests fail, please make sure all the package
    dependencies are up to date. If the problem persists, please file an
    [issue](https://github.com/hydrosolutions/riversCentralAsia/issues)
    including the error message you get so we can look at the problem
    and hopefully solve it.\
5.  If you don't need the source codes any more, you can safely delete
    the zip file and the folder with the extracted riversCentralAsia
    files.

## Community guidelines

Please consult the documentation and the examples provided in the
package documentation and in the open-source course
book Modeling of Hydrological Systems in Semi-Arid Central
Asia.

For problems using the functions of for suggestions, please use the
issue tool.

We aim for an inclusive, harassment-free environment. Please read our
[Code of
conduct](https://github.com/hydrosolutions/riversCentralAsia/blob/master/CODE_OF_CONDUCT.md){target="_blank"}.

## Contribution guidelines

We warmly welcome contributions to riversCentralAsia. Please refer to
our [Contribution
guidelines](https://hydrosolutions.github.io/riversCentralAsia/CONTRIBUTING.html){target="_blank"}
before setting out to make changes.

## How to cite

Please cite the package as:

Tobias Siegfried, & Beatrice Marti (2021): riversCentralAsia
. 

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4667421.svg)](https://doi.org/10.5281/zenodo.4667421)

## Examples

Examples are given in the Articles of the [project documentation
site](https://hydrosolutions.github.io/riversCentralAsia/){target="_blank"}.
To reproduce the examples in the articles, please download the [latest
development version from
github](https://github.com/hydrosolutions/riversCentralAsia){target="_blank"}
or [the last stable version from
zenodo](https://doi.org/10.5281/zenodo.4667421){target="_blank"} and the
[riversCentralAsia_ExampleData from
Zenodo](https://doi.org/10.5281/zenodo.7389785){target="_blank"}
and extract it to your local system, preferably on the same folder level
as the package code:  

\-\
\ |- riversCentralAsia\
\ |- riversCentralAsia_ExampleData

Alternatively to a manual download from zenodo you can download the
entire data set using the library
[zen4R](https://github.com/eblondel/zen4R){target="_blank"}.

```{r, eval=FALSE}
# To download the example files from github
# Example from https://github.com/eblondel/zen4R/wiki
# devtools::install_github("eblondel/zen4R")
library(zen4R)
library(parallel)  # Only for Windows/Unix users, Max users mclapply (see zen4R wiki)

zenodo <- ZenodoManager$new(
   token = ,  # put your token in "" here (don't share publicly!)
   logger = "INFO" # use "DEBUG" to see detailed API operation logs, use NULL if you don't want logs at all
)

# Download the files in the repository to a folder on the same level as the 
# R package riversCentralAsia which you downloaded from github.
# -
# |- riversCentralAsia
# |- riversCentralAsia_ExampleData 
dir.create("../riversCentralAsia_ExampleData")
download_zenodo(path = "../riversCentralAsia_ExampleData", 
                doi = "10.5281/zenodo.7389785", parallel = TRUE, 
                parallel_handler = parLapply, cl = makeCluster(2))

```

Here we have a small example of the hydrometeorological data set
included in the package.

```{r}
library(riversCentralAsia)
library(tidyverse)
library(timetk)

# Loading and visualising discharge data
ChirchikRiverBasin  # load data
ChirchikRiverBasin |> 
  # Filter for the data type, here discharge "Q"
  dplyr::filter(type == "Q") |> 
  drop_na() |> 
  group_by(river) |> 
  plot_time_series(
    date,
    data,
    .interactive = FALSE,
    .facet_ncol = 2,
    .smooth = FALSE, 
    .y_lab = "Discharge [m3/s]", 
    .x_lab = "Year", 
    .title = "Discharge time series in the ChirchikRiverBasin data set"
    )
```

## Mentions

The package is used extensively in the course book
Modeling of Hydrological Systems in Semi-Arid Central
Asia (Siegfried & Marti, 2022).

The workflows presented in the course book, using the riversCentralAsia
package, are further validated within the Horizon 2020 project
HYDRO4U where future
small hydro power potential is evaluated using hydrological modelling.

For R & RS MINERVE users, the package
RSMinverveR is recommended which allows the
interfacing between R and RS MINERVE (with examples based on the Visual
Basic Script examples by CREALP).

## Acknowledgement

The preparation of the course book and thus the preparation of the
package was financially supported by the Swiss Agency for Development
and Cooperation, the German Kazakh University in Almaty and
hydrosolutions. 

Vinisha Varghese and Aidar Zhumabaev @LagmanEater supported package development by applying the functions in their modelling tasks.  

This R package was submitted to the Journal of Open Source Software. We
thank @tonyewong and @mengqi-z for their valuable inputs during the
review of the package and @crvernon for their editing work.

## References

Tobias Siegfried & Beatrice Marti (2022): Modeling of Hydrological
Systems in Semi-Arid Central Asia
(https://hydrosolutions.github.io/caham_book/).
DOI: 10.5281/zenodo.6350042

Marti, B. S., Zhumabaev, A., and Siegfried, T.: A comprehensive
open-source course for teaching applied hydrological modelling in
Central Asia, EGUsphere [preprint],
https://doi.org/10.5194/egusphere-2022-966,
2022.

Owner

JOSS Publication

riversCentralAsia: An R package to support data pre- and postprocessing for hydrological modelling with RS MINERVE

Published

February 02, 2023

DOI

10.21105/joss.04805

Volume 8, Issue 82, Page 4805

Authors

Beatrice Marti
hydrosolutions GmbH, Zurich, Switzerland

Tobias Siegfried
hydrosolutions GmbH, Zurich, Switzerland

Editor

Chris Vernon

Tags

hydrology Central Asia

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