Watershed_characterisation.qmd

# Watershed Characterisation {#sec-basin-characterisation} ```{r} #| include: false ``` In this chapter, we look at **land cover** and the definition of **hydrological response units (HRU's)** and their importance in hydrological modeling. ## Land Use and Land Cover In hydrological modelling, we are transforming rainfall into a runoff called rainfall-runoff transformation. When precipitation reaches the ground it can take various pathways. It can be stored as ice or snow, directly evaporate, infiltrate into the ground etc. Land cover (LC) maps represent spatial information on different types (classes) of physical coverage of the Earth's surface, e.g. forests, grasslands, croplands, lakes, wetlands. The land cover is a key influencer for runoff generation and the estimation of evapotranspiration in the hydrology of watersheds. Therefore, it is essential to use accurate and reliable LC data in hydrological modelling. Several datasets are available globally and free of charge. Below is a brief list of the most recent land cover data products: - [WorldCover project](https://esa-worldcover.org/en), part of the European Space Agency's Earth observation program provides global land cover products for 2020 and 2021 at 10 m resolution, developed and validated in near-real time based on Sentinel-1 and Sentinel-2 data. - [Copernicus Global Land Service (CGLS)](https://land.copernicus.eu/global/products/lc) ## Exercise 2: Basin characterisation {#sec-basin-characterisation-exercise .unnumbered} The goal of the second exercise is to fill in @tbl-example-basin-characterization with data from your catchment. This table includes key characterisations relevant to hydrological modelling for your specific catchment area. In this exercise, we will also learn how to create a map visualizing your study area and a map illustrating the different land cover types, similar to the one shown in @fig-studyarea-dem and @fig-studyarea-landcover for the upper ZRB. {#fig-studyarea-dem width="600"} {#fig-studyarea-landcover width="600"} This will be done in several parts, each supported by tutorial videos in both English and Russian: - Part 1: DEM Land Cover - Part 2: Glacier outlines and Study area map - Part 3: HRU's - Part 4: Discharge data - Part 5: Climate data ### Part 1: DEM and Land Cover {#sec-basin-characterisation-exercise-Part1 .unnumbered} In this chapter, we will fill out the sections Geography and Land Cover in Table 1 and download the digital elevation model and land cover data within our catchment boundaries, which we delineated in @sec-watershed-delineation. To download the DEM and Land cover data we will use the Google Earth Engine (GEE). Google Earth Engine is a cloud-based platform for planetary-scale environmental data analysis. It hosts a vast amounts of environmental data, enabling users to download and perform various analyses and processing tasks. In this part of the exercise, we will use the GEE to download the SRTM Digital Elevation Model and Land Cover data (Source) and calculate Land cover type statistics using the [GEE Link](https://code.earthengine.google.com/c8b1300f5d547c96a5892c723e5f2532) in combination with the following tutorial. There are several other ways to download the DEM and Land Cover data. Here is a turorial how to donwload the DEM from the [Earth Explorer](https://hydrosolutions.github.io/caham_book/appendix_c_quick_guides.html#section-earth-explorer-download-srtm) or use the [QGIS Plugin](https://hydrosolutions.github.io/caham_book/appendix_c_quick_guides.html#sec-srtm-plugin). Land cover data can also be obtained directly from the [ESA WorldCover webpage](https://esa-worldcover.org/en/data-access). **English version:** ```{r} #| echo: false library(vembedr) embed_url("https://www.youtube.com/watch?v=fGmNkA1_lcg") %>% use_align("center") ``` **Russian version:** ```{r} #| echo: false library(vembedr) embed_url("https://www.youtube.com/watch?v=dn3OhQAr4a0") %>% use_align("center") ``` ### Part 2: Glacier outlines and visualization {#sec-basin-characterisation-exercise-Part2 .unnumbered} In the second part of this exercise, we'll download glacier outlines from the Randolph [Glacier Inventory (RGI) v7.0](https://www.glims.org/RGI/). For more details, refer to #sec-glacier-outlines. The tutorial videos in English and Russian explain how to download the data and import it into QGIS. They also demonstrate how to visualize the data and how to produce the study are map in @fig-studyarea-dem and the Land cover map in @fig-studyarea-landcover. **English version:** ```{r} #| echo: false library(vembedr) embed_url("https://www.youtube.com/watch?v=mw_7fV4rxXE") %>% use_align("center") ``` **Russian version:** ```{r} #| echo: false library(vembedr) embed_url("https://www.youtube.com/watch?v=1DJNviAtaSg") %>% use_align("center") ``` ### Part 3: Discharge data {#sec-basin-characterisation-exercise-Part3 .unnumbered} ### Part 4: Hydrological response units (HRUs) {#sec-basin-characterisation-exercise-Part4 .unnumbered} In the fourth part of the exercise, we will utilize elevation bands to delineate HRUs, as elevation significantly influences hydrological processes like precipitation patterns and temperature gradients. Refer to Figure [insert figure number] for an illustration of elevation bands in the upper Zarafshan River basin, as an example for this approach. {#fig-HRU width="600"} ### Part 5: Climate data {.unnumbered} ## References {#sec-basin-characterisation-references}