1 Watershed Analysis 2011

WATERSHED ANALYSIS USING GIS watershed, river network delineation and preparation of hydrological response units for watershed modelling Watershed Modelling Spring Semester 2011 Peter Molnar* and Paolo Burlando Institute of Environmental Engineering ETH Zürich * ETH Zürich, HIL D 23.1 Tel: (044) 633 29 58 [email protected]

mailto:[email protected]�

WATERSHED ANALYSIS USING GIS

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WATERSHED ANALYSIS USING GIS Exercise 1 1. Watershed Delineation 1.1 Import the provided elevation, landuse, soil and geotechnical data for your basin into a GIS. 1.2 Conduct the watershed analysis: (1) fill topographical depressions in the DEM, (2) compute

drainage directions and (3) accumulated drainage area. 1.3 Compute topographic slope and aspect of the filled DEM. 1.4 Extract and plot the river network with two different drainage area thresholds at of your choice.

Compare the results with the hydrographic network digitised from topographic maps. Discuss the differences between the networks.

1.5 Compute the drainage density for the two extracted river networks and the hydrographic

network and compare them. 1.6 Discuss in one paragraph the technique of using a constant drainage area threshold at for

river network extraction. What is the rationale behind it? Which other variables could you add to improve the river network extraction algorithm?

2. HRU Definition 2.1 Define between 5-10 Hydrological Response Units (HRUs) for your basin using the spatial

data for elevation, landuse, saturated hydraulic conductivity and geotechnical characteristics. 2.2 Explain why you chose your HRU definition procedure from the runoff generation point of

view. 2.3 Plot your HRUs and provide a table of the basic HRU properties. Report Write a report describing your work in English or German, maximum 5 pages, single-spaced A4, including figures. The report should provide a description of your work, plots of your results, discussion.


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1. Objectives The rainfall-runoff process is influenced by watershed properties, such as topography, soil and vegetation type, and by climatic driving forces, such as precipitation and temperature. In this exercise we will focus on the watershed, in particular you will learn how to analyse watershed properties and how to define hydrological response units for hydrological modelling using GIS tools. The results of your hydrological response unit analysis are going to be the basis for the rainfall-runoff modelling exercise using the Precipitation Runoff Modelling System (PRMS). This document serves as an introduction to ArcGIS and as a brief manual for solving the exercise. 1.1 Motivation A proper description of the land surface is of fundamental importance in watershed modelling. For distributed modelling we need spatial data, for example of topography, land cover, landuse, soil properties, vegetation cover, and others. In this assignment you will conduct a detailed spatial analysis of data from a mountainous, highly heterogeneous basin in Switzerland (in the Bern Oberland region) for the purposes of semi-distributed hydrological modelling. Chapter 2 gives you basic information about how to use a Geographic Information System (GIS), ArcGIS. In Chapter 3 you will then learn about some spatial datasets useful for hydrological analysis and you will import and visualise them in ArcGIS. Land surface topography is a determining variable for surface water flow, and in Chapter 4 you will analyse the topographical properties of your basin. You will determine the slope and aspect, and compute the flow direction and flow accumulation maps which determine the flow of water in your basin. Based on these analyses you will automatically extract the river network, that is determine where the rivers should be according to the basin topography. You will compare the automatically extracted river network with the “blue lines” on hydrographic maps. Topography alone is not sufficient to understand all the details of the rainfall-runoff transformation. Other spatially variable factors, such as soil type, vegetation, landuse are also important. One way to simplify distributed hydrological modelling and still account for spatial variability is to divide the basin into homogeneous hydrological response units (HRUs). These are areas that have common properties which are important from the hydrological perspective: for instance similar slope, elevation, aspect, soil type, vegetation cover, landuse, etc. Chapter 5 deals with the issue of HRU definition and gives you guidelines and an example on how to define and delineate HRUs for your basin. The motivation behind this assignment is to provide you with GIS-based tools and methods that can be used for the handling and analysis of watersheds in preparation for hydrological modelling. 1.2 GIS use To successfully complete the assignment you are expected to use the ArcGIS software. These instructions are based on ArcGIS version 9 using ArcMap. This document does not replace an ArcMap manual, but with the information contained within, you will be able to complete all of the tasks. Most importantly don’t be afraid to click around in ArcGIS and learn more about the program on your own, it will be a good experience for you.


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2. Basic Information 2.1 Preliminary steps in ArcMap Have sufficient disk space • The data you will be using is quite large. ArcGIS creates a lot of temporary files as you work.

Please make sufficient disk space free in your account before you begin. Getting your folders organized • I suggest that in the folder for the course, e.g. “WatMod” you create a “GIS” subfolder and in it

folders “data” where you will put your data and “work” which will be your working folder. Installation and starting the programme • Start the programme by clicking on ArcMap in folder ArcGIS in the Programs Menu. • You have a choice of beginning with an existing map, a template or a new map. Let us say

“new empty map” when you are beginning, later you can start your existing project. • Go to Tools-Extensions and check the extensions you want to use, in our case “Spatial

Analyst” HAS TO BE checked (you may need other extension checked as well if you do more advanced analyses). The spatial analyst extension is a collection of tools that allows you to analyse spatial data in detail.

• You should now have three windows open on your screen, the “Layers” window where you will have the themes you use shown, the “Arc Toolbox” window where you have the predefined commands and tools, and the view window where your maps will be shown. If you do not have the “Arc Toolbox” window open start it by clicking on the red toolbox icon in your icon menu (below the main menu).

Fig 1. The main menu toolbar and the “layers”, “toolbox” and “view” windows.

Setting your workspace • Set your workspace, click Tools on the main menu, then click Options. Click the Geoprocessing

tab, click the Environments button, click General Settings to view the settings. Type the path to the workspace you want to use, e.g. “…WatMod\GIS\work” or click the Browse button to navigate to the desired location. If you do not see your folder in the browse window, click on Connect to Folder button to the right of the window (with an arrow pointing right) and enter the folder or drive you want to be connected to.

• Save your project, e.g. “oberland.mxd” in “…WatMod\GIS”. Next time you may start the project by clicking on this file, or selecting it when you start ArcMap. Please remember to save your ArcGIS project (mxd file) periodically as you work.

You are now ready to start filling your project with data.


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3. Spatial Watershed Data In this assignment we will analyse the rainfall-runoff process in a mountainous Alpine basin in the Bern Oberland region of Switzerland. The region we will be studying drains into the Brienz and Thun Lakes and extends south into the main Alpine range. Most of the region is an undisturbed Alpine landscape with meadows, pastures, forest and bedrock, some high mountain areas are glacierised and there are very few large settlements. Runoff production (due to rainfall and/or snowmelt) can lead to quite dramatic flooding, which of course is a concern for the downstream population. You will analyse one of the six river basins in the course in Fig 2. There is a streamflow gauging station at the outlet of each basin, and the basins are assigned a name according to the name of the gauging station (Tab 1).

Fig 2. The Bern Oberland study region (with the Thun and Brienz Lakes) with the six studied drainage basins. The basins are labelled according to the streamflow gauging station at the outlet. Simme Basin is furthest west (Latterbach).

Tab 1. The analysed river basins. No. Name Basin Area [km2] 1 2 3 4 5 6

Latterbach Oberried Riedli Hondrich Kandersteg Gsteig

Simme Simme Simme Kander Kander Lütschine

561.7 35.4 77.1

519.5 167

384.2 Three of the studied basins lie in the Simme Basin (Latterbach, Oberried and Riedli), two lie in the Kander Basin (Hondrich and Kandersteg) and one is in the Lütschine Basin (Gsteig). Their drainage areas range from 35.4 to 561.7 km2, see Tab 1. 3.1 Basin data a) shape files of basin boundaries and hydrographic network ArcView has two main types of spatial data coverages: vector-based shape files (polygons and lines) and raster-based grid files. The basin boundaries are provided as polygon shape files. There are five files that together define each shape file, they have the same name but different extensions (.shx, .sbn., .sbx, .shp, .dbf). Download these files from the course web site for your basin and place them in your designated “data” directory. The river network derived from 1:25,000 topographic maps (blue lines) for the entire region is provided as a line shape file for you. b) raster files for spatial data We will use four spatial raster datasets for the region in this study. The primary element of all watershed analyses is a digital elevation model (DEM). For the definition of the hydrological


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response units, additional information about the land surface and soils which affect the rainfall-runoff transformation is needed. For this purpose we will use a landuse map, a map of soil properties and a geotechnical map (see Tab 2). The spatial datasets in Tab 2 use the same projection as the Swiss national cartographic maps. The projection system used in Switzerland is an oblique conformal cylindrical projection. The standard geometric definition of the data is the reference ellipsoid Bessel (1841), with point of origin at the old observatory in Bern (coordinates y=600,000 m, x=200,000 m), and with height reference at Repère Pierre du Niton (373.6 m). Tab 2. Digital spatial data for the study region. All data are at 100 metre spatial resolution in ASCII format. No. Filename Description 1 2 3 4

dem_region.asc bonu72_region.asc ksat_region.asc geotech_region.asc

Elevation data Landuse types Hydraulic conductivity of the soil Land surface geotechnical units

The ASCII raster file format is a simple file format used for easy transfer of data between various GIS applications. It is basically a few lines of header information which positions the data area, followed by an array of individual values for each cell on a rectangular grid. The header data includes the following: ncols (number of columns in the dataset) nrows (number of rows in the dataset) xllcenter or xllcorner (x-coordinate of the centre or lower-left corner of the lower-left cell) yllcenter or yllcorner (y-coordinate of the centre or lower-left corner of the lower-left cell) cellsize (cell size for the data set) nodata_value (value in the file assigned to cells whose value is undefined) For example, the header for all of the files in Tab 2 is identical: ncols 910 nrows 495 xllcorner 586700 yllcorner 134100 cellsize 100 NODATA_value -9 This means that the data in Tab 2 cover a rectangular area of 91x49.5 km covering the Bern Oberland area shown in Fig 2 and have a resolution of 100 m. Notice that as in Fig 2, the region draining into the Thun and Brienz Lakes has been masked out, cells outside of the region are set to the nodata_value (in this case -9). The masking procedure is part of the watershed analysis process, and you will learn how to do it later. DEM (dem_region.asc) Digital elevation models (DEMs) represent the three-dimensional form of the earth’s surface on a regular grid (elevation z is stored with the coordinates x and y of each point). The Federal Office of Topography (Landestopographie), http://www.swisstopo.ch, produces the DEM called DHM25 for all of Switzerland since the end of 1996. It is based on the interpolation of terrain information from the Swiss National Map in the scale 1:25,000 (basis model) into an evenly spaced grid with 25-metre spacing (matrix model). Here we will use a derived model based on a 100-metre grid spacing, which is obtained by averaging the 4x4 matrix model cell values within each 100-metre grid. You can find more detailed information about the DHM25 model, how it is obtained, its accuracy, etc., in a document from the Federal Office of Topography posted on the course website. LANDUSE (bonu72_region.asc) Landuse is generally determined from aerial photographs and more recently from satellite images of the land surface. In Switzerland, this data is provided by the Federal Statistical Office (Bundesamt für Statistik), http://www.statistik.admin.ch/. The basis landuse map which we will use

http://www.landestopographie.ch/�

http://www.statistik.admin.ch/�


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here is from 1972 (it is formally called “Arealstatistik 1972”, and usually has the designation “bonu72”, bonu for Bodennutzung), with landuse divided into 12 main categories with spatial resolution of 100 metres covering the whole area of Switzerland. The 12 categories are in Tab 3. The digital data was obtained by digitising 1:25,000 and 1:50,000 scale maps. You can find a lot of additional information about the landuse map (how it was obtained, its history etc.) in the GEOSTAT manual from the Federal Statistical Office on the course website (look for the section “Arealstatistik der Schweiz 1972”). For the purposes of the rainfall-runoff modelling exercise in this course, you will be asked to define the dominant vegetation cover for every hydrological response unit. You will have to select between bareland, grass, shrubs and trees from the landuse map. Tab 3. Landuse categories from the Arealstatistik 1972 map. These are the values that are listed in “bonu72_region.asc”. Category Description

1 2 3 4 5 6 7 8 9

10 11 12

Bareland (glacier, snow, rock, marsh, etc.) Rivers Lakes Forest Pasture Meadow, arable land, orchards Vineyards High intensity of construction Moderate intensity of construction Low intensity of construction Transportation infrastructure Industry

SOIL HYDRAULIC CONDUCTIVITY (ksat_region.asc) The Federal Statistical Office also produces the digital soil map of Switzerland (Bodeneignungskarte, we will call it “BEK”) with several soil properties for unique 144 soil classification units. Soil properties in BEK include soil depth, soil water storage capacity, permeability (saturated hydraulic conductivity), and others. In this assignment we would like to define hydrological response units also based on how much water the soil can store and transfer. A good surrogate variable for this purpose is the saturated hydraulic conductivity of the soil (ksat). The saturated hydraulic conductivity of the soil was determined by laboratory analyses of samples taken from the different soil classification units. The value of ksat assigned to each classification unit is supposed to represent the average quantity for the upper 50 cm of the soil. BEK gives the values of ksat classified into permeability classes shown in Tab 4. The ksat category number is extracted from BEK, transferred into a grid, and written into the ASCII map “ksat_region.asc”. Tab 4. Categories of ksat from the BEK map for different permeability classes. These are the values that are listed in the file“ksat_region.asc”. Category Permeability (class) ksat [m/s]

0 1 2 3 4 5 6 7

no soil extreme excessive normal moderately inhibited inhibited highly inhibited impermeable

> 10-3 10-4 - 10-3 10-5 - 10-4 10-6 - 10-5 10-7 - 10-6 10-8 - 10-7 < 10-8

The digital soil map was obtained by digitising BEK at a 1:200,000 scale. The map was updated in the year 2000 because of large geometrical shifts and errors in the original version. Here we use the new updated map. You can find additional information about the soil map in the GEOSTAT manual on the course website (look for the section “Digitale Bodeneignungskarte der Schweiz”).


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For the purposes of the rainfall-runoff modelling exercise in this course, you will be asked to define a soil type for every hydrological response unit. You will have to select between sand, loam and clay. To make this selection you will have to define the ranges of ksat for each of the three soil textures and then classify the BEK map accordingly. GEOTECHNICAL MAP (geotech_region.asc) The Federal Statistical Office also produces the geotechnical map of Switzerland. We will use here the so-called simplified geotechnical map which classifies the surficial rocks, soil, and deposits from the 1:200,000 geotechnical map into 30 different categories (see Tab 5). Tab 5. Categories of the simplified geotechnical map. This is not a complete list (for the complete list refer to the GEOSTAT manual on the course website). The categories are the values that are listed in “geotech_region.asc”. Category Description

1 2

3-7 8-30

lakes glacierised area loose surficial deposits (see GEOSTAT manual for detailed classification) rock (see GEOSTAT manual for detailed classification)

However, you can also check how the categories for loose and solid surficial deposits compare with the BEK soil map. To do this explore what the geotechnical categories mean from the GEOSTAT manual on the course website (look for the section “Vereinfachte Geotechnische Karte der Schweiz”). For the purposes of the rainfall-runoff modelling exercise in this course it is useful to define the glacierised area as a single hydrological response unit. This is what you will use the geotechnical map for. 3.2 Import the data into ArcMap First a note on georeferencing • All the files that you are using are already projected into an x,y,z coordinate system for

Swizerland (CH1903). Therefore they do not have a projection file assigned to them. This is why every time you open these files you will get a warning from ArcMap that you are missing spatial reference information. This does not concern us only because we know we have all the files in the same projection. However, remember that you will not be able to project these maps into another coordinate system without this information. If you want to add projection information to files you have to do this in the ArcCatalog programme of ArcGIS. There select the file you want to assign a projection to, choose Properties and in the tab XY Coordinate System select the correct predefined coordinate system from the Swiss national grids. After this procedure your grid has a projection (.prj) file which the program recognizes.

• Even if you do not assign a projection file, assign a map unit by clicking on Layers Properties and in the General tab choose “meters” for both map and display units.

Convert raster ASCII files into ArcMap grids • In the Arc Toolbox menu go to Conversion Tools and To Raster. Start ASCII to raster. • In the input window select your ASCII file in the “WatMod\GIS\data” folder. • In the output window select the location in the “WatMod\GIS\work” folder and give your new

grid a name. The programme will offer you a default name, keep or change this as you wish. • Choose whether the data are integers or real (float) numbers. You should use “integer” for all

maps that have categories and “float” for maps that have real numbers, for example the DEM data.

• Now your grid will be added to the Layers as a theme and you can change many of its properties (e.g. colours, ranges) from there. Right (or double) click on the theme in the Layer and click on Properties. Here you have all the basic information you need about every map you create. Remember to enter the map units as meters in the General options (see above).

• Every time you save your project (mxd file) you will now save all the themes that you have in your Layers.


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Opening shape files and imported grids • Shape files that you downloaded (.shp files) do not need to be imported anymore. Like the grid

themes that you have created in the step above, you only need to add those to your Layers. • To add existing themes click on the Add Data icon, the yellow one with a black plus (or start it

in the File Menu), then choose the Arc shape files (or grids) you want to add to your view. If you do not see your directories in the pull-down menu, you just need to click on the Connect to Folder button to the right of the window (with an arrow pointing right) and enter the folder or drive you want to be connected to. You may get a message that says that your data are missing spatial information. This is not a problem for us because we are using the same coordinate system for all datasets (see above).

At this stage you will have imported the four grids (e.g. dem_region, bonu72_region, ksat_region, geot_region) and opened the river network shapefile (hydronet_region) and the boundary file for your basin (e.g. my example is for Latterbach), and your screen should look something like Fig 3.

Fig 3. Displaying the imported maps and basin boundaries in ArcMap. All the layers are now connected to each other. If you click on the information icon (Identify) on the toolbar (the one with the “i”) and then click anywhere in your basin, you will get a window in which you can select all layers and see their properties. Try this to find out the area of your basin. The order of the layers in the view window is the same as in the Layers window, with the first layers on top. You may drag and drop the layers to change the order. 3.3 Cut (mask) out your basin Up to this point you have uploaded data for the whole region, now you need to cut out only your basin. To do this we will set a MASK, that is define an area which is our area of interest and ignore everything else in all further analyses. Your MASK is the watershed you have been assigned. Setting the MASK • Go to the Spatial Analyst TOOLBAR and click on Options. • In the Analysis Mask window select the basin MASK you want to use. For example the

“basin_latterbach” basin boundary shapefile. A mask file can be a raster or a feature file. From


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this point ALL ANALYSES you will conduct with the spatial analyst will block out everything except your basin.

• Note also that you can set here the working directory for the Spatial Analyst. What is the difference between Spatial Analyst TOOLBAR and TOOLBOX? • The spatial analyst extension is a collection of very many tools and options that allows you to

analyse spatial data in detail. We will be referring to: A) The Spatial Analyst TOOLBOX, which is in the red ArcToolbox, and which has the “HYDROLOGY” commands in it (and many others). B) The Spatial Analyst TOOLBAR you have to activate from View-Toolbars list on the main menu by checking it. The toolbar that opens can also be placed next to the other toolbars you have below the main menu simply by dragging (like in all other MS applications). The toolbar has a selection of the most commonly used functions and options for spatial analysis. Some functions you can execute from either the toolbox or the toolbar, it makes no difference.

Cutting out your basin • You can now cut out your basin from the 4 raster maps you have for the region. On the Spatial

Analyst TOOLBAR click on Raster Calculator this will start the calculator. You have a list there with all your rasters in your Layer.

• Write in the calculator window “DEM_latt=” and double-click on the dem file for the region from the list, e.g. in the calculator window you should now have an equation “DEM_latt = [dem_region]”, depending how you called the dem_region file.

• Click Evaluate. You will now have a new map in your Layers that will be called DEM_latt and will have only the altitude data for your basin.

• Repeat this step for the remaining three maps (geotech, landuse and ksat), see Fig 4.

Fig 4. After cutting out the basin you will have the spatial coverages only for your analysed basin. Here the BONU72_latt map is displayed. It is good to delete the other regional data from your project, because they take up a lot of space. To do this remove the maps in your Layers (this doesn’t actually delete the data), then start the ArcCatalog programme in ArcGIS and delete the files there. ArcCatalog is for data management, if it sometimes does not allow you to delete files it is because you are using them in ArcMap. You now have all the data files ready and can proceed to the watershed analysis.


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4. Watershed Analysis The watershed analysis is performed by a series of tasks on the digital elevation model of a watershed. In principle, the goal is to obtain the flow directions throughout the watershed, based on elevation data. With the flow direction information, the river network can be extracted and watersheds delineated. Here only the basics of watershed delineation relevant to the assignment will be explained. Feel free to explore other ArcGIS functions on your own. The basic procedure for extracting the river network and delineating a watershed from a DEM is shown in Fig 5.

Fig 5. Basic procedure for the definition of river networks and watershed boundaries.

The flow direction computations and filling of sinks need to be done in one step. In ArcGIS flow direction is computed for every cell with the D8 method which finds the steepest direction to one of 8 neighbours of a cell (diagonal flow is allowed). Other more realistic methods for defining flow directions are available. You can read about one such method in the paper by Tarboton (1997), which you can download from the course website. Once you have the flow directions, you can find the cells that do not drain anywhere, that is they are sinks or holes in the watershed. For hydrological modelling purposes these are not acceptable, although there may be reasons why such features exist in a DEM. So the common procedure is to fill these depressions by adding elevation to the cells until they are at equal elevation with the surrounding area. All of the above is done automatically by the following sequence of steps in watershed analysis. Sink filling • Click on FILL in the Spatial Analyst TOOLBOX under HYDROLOGY, enter your DEM (e.g.

DEM_latt) as the input raster, you may choose it from the pull-down menu, and enter a name for the output raster (e.g. Fill_DEM_latt). The Z limit gives you an option to stop the programme for filling in large sinks above a threshold. For us let us fill every sink, so we do not enter anything in the Z limit field. Enter OK to execute.

• Check how many sinks were identified and how much was filled by entering in the Raster Calculator: “Sinks=[Fill_DEM_latt] - [DEM_latt]”. Do the sinks correspond with lakes in the basin from the hydrographic network file?

Computing slope and aspect of filled DEM • Click on the SLOPE in the Spatial Analyst TOOLBOX under SURFACE, enter your filled DEM

(e.g. Fill_DEM_latt) as the input raster and enter a name for the output raster (e.g. Slope). For the units choose percentage rise because this is the parameter that you need for the rainfall-runoff modelling. Enter OK to execute.

• Click on the ASPECT in the Spatial Analyst TOOLBOX under SURFACE and repeat the same procedure.

Computing flow directions and flow accumulation of filled DEM • Click on the FLOW DIRECTION in the Spatial Analyst TOOLBOX under HYDROLOGY, enter

your filled DEM (e.g. Fill_DEM_latt) as the input raster and enter a name for the output raster


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(e.g. FlowDir). Enter OK to execute. You should only have numbers 1-2-4-8-16-32-64-128 as possible flow directions, see lecture for explanation.

• Click on the FLOW ACCUMULATION in the Spatial Analyst TOOLBOX under HYDROLOGY, enter the just created flow direction raster as input and an output name (e.g. Flowacc). The units of the output map are the number of cells flowing into the given cell, excluding the cell itself. To display the accumulation map better you may decide to take a logarithm of it.

Of course the cell at the outlet of the basin drains the entire area, that is 56057 (or 56058) cells in my case, or an area of about 560.6 km2. Notice that this area is slightly less than the basin boundary polygon or the basin grid mask. This is generally caused by edge effects, where cells on the drainage divide can have multiple drainage directions to choose from. Such discrepancies are usually very minor and insignificant. But it is worthwhile to check them. The stream network in ArcGIS is defined by cells that drain an area larger than a threshold (a>at). To compute where streams would lie in your basin as a function of the given topography you just have to specify the threshold at. Extracting the river network • In the Raster Calculator type “[Flowacc] >= 300”, this will create a “Calculation” which will give

you 0 when a<at and 1 when a>at, with at = 300 cells in this example. You can rename this file e.g. to STREAMS(300), repeat for various thresholds, and compare with the mapped hydrographic network.

• The stream files you get are grids, you may convert them to line features with the Stream to Feature function in HYDROLOGY, but first you would have reclassify your stream map into NoData/1 values (that is NoData for no streams and 1 for streams) instead of 0/1 which you have from the previous step. Reclassification may be found in RECLASS in the Spatial Analyst TOOLBOX (see Fig 6).

• Repeat the analysis for a different at. You can see that this automatic procedure, based on topography alone, reproduces streams in the right place. But is this visual judgment sufficient? How can we check if the river network extraction performs well? Will the threshold for channel intitiation be constatnt rhoughout the basin? Which variables other than drainage area may play a role in determining where rivers begin? Think about these questions as you work on your report.

Fig 6. Example of river network and watershed extraction with at = 300 cells for the Latterbach (Simme basin).


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5. Hydrological Response Units Hydrological response units (HRUs) are areas in a watershed that are homogeneous in terms of their hydrological response and geoclimatic characteristics. They may be subbasins or disconnected areas in the sense of runoff, but areas that have common properties which are important from the hydrological perspective: for instance similar slope, elevation, aspect, soil type, vegetation cover, landuse, etc. We will focus on this second HRU representation. The main task here is to define HRUs for your basin and to determine their basic properties important for hydrological response. In Appendix 1 you will find a list of all of the parameters that need to be defined for each HRU in the Precipitation Runoff Modelling System (PRMS) that you will be using for rainfall-runoff modelling. In preparing your own HRU definition, you may want to see how others have approached the problem, for instance look at the study of Flügel (1997) on the Bröl Catchment in Germany on the course website. 5.1 Spatial data analysis In principle, HRU definition can be done by querying the different spatial grid coverages that you now have for common properties that you decide are hydrologically significant. Some selected grids that are useful for HRU definition are listed in Tab 6. Tab 6. Examples of grid themes which may be useful for HRU definition (this is an example with Latterbach (Simme) basin data). Grid Theme Content “Fill_Dem_latt” “Slope of Fill_Dem_lat” “Aspect of Fill_Dem_lat” “Bonu72_latt” “Ksat_latt” “Geotech_latt”

Latterbach masked elevation grid with sinks filled Latterbach masked surface slope grid Latterbach masked surface aspect grid Latterbach masked landuse grid Latterbach masked soil saturated hydraulic conductivity grid Latterbach masked land surface geotechnical unit grid

As you can see in Appendix 1, there are six parameters that have to be directly defined for each HRU. These parameters are listed in Tab 7. All are self-explanatory, except perhaps the parameter IRD (index of solar radiation plane). Each HRU is assigned a solar radiation plane, that is an average slope and aspect which are used for determining incoming solar radiation for the HRU. However, when computing an average aspect for a HRU, be careful. What happens if you have a HRU which is a valley heading in the north-south direction with adjacent hillslopes facing east or west? What will the average aspect be? Is it correct? There are several ways in which one can identify the aspect of a HRU in a coherent way, for example by (a) computing the main aspect directions (E, W, N, S) for a watershed and deciding which of the four is dominant in a given HRU; or by (b) using aspect (or the main four directions) as one of the deciding factors in HRU definition in the first place. In this regard, you can also imagine that in gently sloping basins aspect hardly plays a role. Keep all this in mind when defining HRUs for your basin. Tab 7. Directly defined HRU parameters from GIS analysis of physical basin properties. These are the parameters you have to define for your HRUs. The choice for the ICOV and ISOIL parameters is given in italics. Parameter Content DARU SLP ELV ICOV ISOIL IRD

Area of HRU [km2] Average HRU slope [m/m] Average HRU elevation [m] Type of dominant vegetation cover (bareland, grass, shrubs, trees) Dominant soil type (sand, loam, clay) Solar radiation plane (defined by HRU slope and aspect)

In HRU definition you determine an average value (e.g. of slope, elevation), the cumulated total (area), or the dominant value (e.g. of vegetation, soils, radiation plane) of the factors from Tab 7.


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Although there are different ways in which average slope can be defined in a watershed, here, when we speak of average slope it is understood to be an arithmetic average of the slope in all cells of the HRU. A final comment is that it is good practice to distribute HRUs quite evenly. It makes little sense in a heterogeneous environment, such as the area you are studying, to have one HRU which covers 90% of the area and then several small HRUs. The response of the model will then be dominated by the large HRU and will hardly be able to capture the runoff dynamics due to the heterogeneous basin properties. In your report explain the choice of your chosen variables for HRU definition, and present a table with the average properties (those from Tab 7) of your defined HRUs. 5.2 Example HRU definition Actual HRU definition is best illustrated with an example. In this example landuse was taken as a primary factor for HRU definition with elevation and hydraulic conductivity as secondary factors. IMPORTANT: The purpose of this example is to give you ideas on how to go about the HRU definition. Please do not reproduce this example exactly in your work! Let us first define how we want to proceed, that is create our “HRU philosophy”: • Let us define the glacierised part of the basin as a separate unit. We expect that glaciers (and

snow accumulation on them) may be a distinctive and important element in hydrological response.

• Then let us assume that landuse and land cover reflects both soil and vegetation properties and can be the basis for the separation of different runoff generation processes in the hydrological response.

• Finally let us assume that for a large area with a single landuse or land cover, but which we know is heterogeneous, it is useful to subdivide this area by elevation or the hydraulic conductivity of the soils into smaller units.

Procedure for conducting querries Start the Raster Calculator and enter the required combination of variables that will define each HRU, repeat this for all HRUs. Let us work out our example of the Latterbach (Simme) basin. HRU 1 (glacier) This HRU will be the glacierised area in the basin. To obtain it we have to select the glacierised area from the geotechnical map of our basin, that is choose category 2 from the “Geotech_latt” grid (see Tab 5). • Enter the following in Raster Calculator: HRU1 = [Geotech_latt] == 2 HRU 2 (bareland) This HRU will be the bareland region of the basin (rocks, etc.). In terms of hydrological response, lakes will be also considered as a bareland area (however be aware that this assumption may not be good if the lake area in your basin is large). So to obtain this HRU we have to select the bareland and lake categories from the landuse map of our basin (see Tab 3), that is from the “Bonu72_latt” grid, but also make sure that the area we are choosing is not already defined in HRU 1 as glacierised. • Enter the following query by selecting from the menus: HRU2 = (([Bonu72_latt] == 1) or

([Bonu72_latt] == 3)) and ([Geot_latt] <> 2). HRU 3 (forest) This HRU will be the forested region of the basin. So all we have to do for this HRU is to select the forest category from the landuse map of our basin (see Tab 3), that is from the “Bonu72_latt” grid. • Enter the following query by selecting from the menus: HRU3 = ([Bonu72_latt] == 4).


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HRU 4 (low pasture) This HRU will be the low lying pasture region of the basin. We know by looking at the landuse map of the basin that pastures cover a large area, so we would like to divide this area into two smaller units. Since pastures also cover quite a range in altitude, let us use altitude as the separation variable. So for this HRU we select the pasture category from the landuse map of our basin (see Tab 3), and then use the elevation grid to make a division of low pastures as those below 1800 m. • Enter the following query by selecting from the menus: HRU4 = ([Bonu72_latt] == 5) and

([Fill_Dem_latt] < 1800). HRU 5 (high pasture) This HRU will then be the high lying pasture region of the basin. It is a complement of HRU 4 with elevation above 1800 m. • Enter the following query by selecting from the menus: HRU5 = ([Bonu72_latt] == 5) and

([Fill_Dem_latt] >= 1800).

Fig 7. The queary for HRU 5 on the Raster Calculator.

HRU 6 (permeable meadows/arable land) This HRU will represent the utilised land, that is meadows and arable land from the landuse map. In the Latterbach (Simme) basin we also have some low intensity construction areas, we add these here. Now, overall this area is quite large, it rests mainly in the valley floor with a high heterogeneity in soil permeability. So we will use saturated hydraulic conductivity as the separating variable to define the permeable fraction with ksat>10-5 (that is categories 1-3 in Tab 4). • Enter the following query by selecting from the menus: HRU6 = (([Bonu72_latt] == 6) or

([Bonu72_latt] == 10)) and (([Ksat_latt] == 3) or ([Ksat_latt] == 2) or ([Ksat_latt] == 1)). HRU 7 (less permeable meadows/arable land) This HRU will complement HRU 6 as the meadows/arable land and low intensity construction with less permeable soils ksat<10-5 (or in areas where there are no defined soils, if such an area exists). • Enter the following query by selecting from the menus: HRU7 = (([Bonu72_latt] == 6) or

([Bonu72_latt] == 10)) and (([Ksat_latt] > 3) or ([Ksat_latt] == 0)). Check to make sure that the HRUs you defined cover the entire area of the basin. The trick is to make sure that you choose mutually exclusive properties for your HRU definitions! You may now combine all your HRU files into one by executing HRU = [HRU1]*1 + [HRU2]*2 + [HRU3]*3 + [HRU4]*4 + [HRU5]*5 + [HRU6]*6 + [HRU7]*7. This file will then have 7 categories as VALUES, these categories will correspond to the invidual HRU numbers. The final HRU file is shown in Fig 8.


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Fig 8. Example of 7 defined HRUs in the Latterbach (Simme) Basin example.

5.3 Computing HRU properties We now need to compute the properties listed in Tab 7 for all defined HRUs. There are two different approaches that we need to use here. Some variables from Tab 7 need to be computed as averages and some as dominant variables. The resulting table is given in Tab 8. Average quantities The elevation and slope of each HRU are average quantities. To compute them do the following. • Start Zonal Statistics on the Spatial Analyst TOOLBAR. • Select HRU for the Zone dataset with the HRU number (in my case the VALUE field) as the

Zone field. • For the Value raster choose the spatial field variable that you want to summarize, for example

for the average slope select “Slope”. You may choose to chart a statistic and also to give the attribute table file a new name (if not a default name is assigned). Check the “Join output table to zone layer”.

• Click on OK. You will get a table with basic statistics of the chosen grid coverage by individual HRUs. These basic statistics are the mean, minimum, maximum, range, standard deviation and sum of elevation values. We are interested for example in the total area of each HRU and the mean slope in this case, which we enter into Tab 8. Every table you create by summarising is automatically stored in the database (dbf) file. Repeat the process for every relevant grid. Dominant quantities The vegetation cover, soil type and aspect of each HRU should be determined as dominant quantities. In other words, one does not look for an average vegetation type between forest and meadows (some kind of bush) but rather find which of the two is dominant in the HRU. The whole HRU is then assigned that vegetation type. (The same will apply to soil and aspect.) The procedure to determine dominant quantities is the same as average ones. If you are summarizing a grid that is categorical (consists of categories) you will get also a MAJORITY field in the resulting table which gives you the category with the highest frequency in each zone.


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In our example the choice for vegetation is easy, because we used landuse as the primary factor for HRU definition. So we just select between bareland, grass, shrubs and trees for the different landuse classes and enter these in Tab 8. For the soil type things are a little more complicated. For the rainfall-runoff model we will use, you need to choose between sand, loam, and clay as the dominant soil type in your HRU. We said we will use the saturated hydraulic conductivity map for this purpose. Recall from Tab 4 that ksat is categorised into 8 classes. Your task is to find out what are the ranges of ksat that define the soil types sand, loam and clay. Every “soils” book will have that information. In this example I will choose sand to be where ksat>10-4 m/s, loam where 10-6<ksat<10-4 m/s, and clay where ksat<10-6 m/s. So first I reclassify the “Ksat_latt” theme into the three soil types based on the ranges I just defined and the execute Zonal Statistics on this grid to get the majority field. Notice in Tab 8 that a soil type is also assigned to the glacier and bareland HRUs, which doesn’t at first glance make sense. But think of it in this way: there is a fraction of water that seeps into the fractured rocks (even below the glacier), the soil type then represents the capacity of the fractured rock to store and transmit water, it is not really a soil in the traditional sense. Finally, to determine the aspect of each HRU I reclassified the “Aspect” of Fill_Dem_latt theme (by “Reclassify” on the “Analysis” menu) into the four dominant directions: North, South, East, West (I kept the flat areas a separate class), and renamed the theme to “Main aspect”. Next I determined the dominant main aspect for each HRU following exactly the same steps as for soil types, by tabulating the “Main aspect” theme together with the “HRU” grid. The dominant aspect directions were then entered into Tab 8. Note that generally the dominant direction is north, which is not surprising given the orientation of the basin. Tab 8. Example of HRU definition for the Simme (Latterbach) Basin for PRMS modelling. HRU Definition Area

[km2] Elev. [m]

Slope [m/m]

Veg. Cover

Soil Type

Aspect [deg]

1 2 3 4 5 6 7

glacier bareland forest low pasture high pasture permeable meadows/arable land less permeable meadows/arable land

11.9 64.8

130.8 170 105

29.7 49.4

2715 2074 1376 1511 1963 1013 1065

0.22 0.59 0.49 0.38 0.44 0.23 0.25

bareland bareland

trees grass grass grass grass

clay clay loam loam loam loam clay

N (0) N (0) N (0) N (0)

W (270) E (90)

W (270) Total area 561.6 I hope that the above text conveys that there are many other ways that you can divide a watershed into meaningful hydrological response units. Please choose your own individual HRU definition. The only strong suggestion that I have is that you separate glaciers out (if you have glaciers in your basin) as a single separate HRU, and that you consider elevation as a dividing factor for some of your variables. The final result of your efforts should be a table for your basin HRU properties similar to the one in Tab 8. Some reading material Ely, D.M., and J.C. Risley (2001). Use of a precipitation-runoff model to simulate natural streamflow

conditions in the Methow River Basin, Washington. U.S. Geological Survey, Water-Resources Investigations Report, 01-4198, 36 pp.

Flügel, W.A. (1997). Combining GIS with regional hydrological modelling using hydrological

response units (HRUs): and application from Germany. Mathematics and Computers in Simulation, 43, 297-304.

Montgomery, D.R., and W.E. Dietrich (1992). Channel initiation and the problem of landscape

scale. Science, 255, 826-830. Tarboton, D. (1997). A new method for the determination of flow directions and upslope areas in

grid digital elevation models. Water Resources Research, 33(2), 309-319.


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Appendix 1 HYDROLOGICAL RESPONSE UNIT INFORMATION (SHADE) USED IN THE PRMS MODEL

No

Parameter

Description

Common values

1 IRU HRU identification number 2 IRD Index of solar radiation plane 3 SLP Average slope [m/m] 4 ELV Average elevation [m] 5 ICOV Type of dominant vegetation cover (bareland, grass, shrubs,

trees) 6 COVDNS Summer vegetation cover density 0.5 – 1 7 COVDNW Winter vegetation cover density 0.5 – 1 8 TRNCF Transmission coefficient for SW radiation through the

winter canopy 0 – 1

9 SNST Interception storage capacity for snow [mm] 10 RNSTS Interception storage capacity for summer rainfall [mm] 11 RNSTW Interception storage capacity for winter rainfall [mm] 12 ITST Month when transpiration starts 5 – 6 13 ITND Month when transpiration ends 11 or year-round 14 ITSW Transpiration starting value switch (dormant or

transpiring)

15 CTX Air temperature coefficient for evapotranspiration NOT USED 16 TXAJ Adjustment for maximum air temperature for slope and

aspect [C] 0

17 TNAJ Adjustment for minimum air temperature for slope and aspect [C]

0

18 ISOIL Soil type (sand, loam, clay) 19 SMAX Maximum available water holding capacity of soil

profile [mm] For different soil type

20 SMAV Current available water in soil profile [mm] For different soil type 21 REMX Maximum available water holding capacity of soil

recharge zone [mm] For different soil type

22 RECHR Current available water in soil recharge zone [m] For different soil type 23 SRX Maximum daily snowmelt infiltration capacity [mm] For different soil type 24 SCX Maximum contributing fraction of HRU area (0-1) For different vegetation cover 25 SCN Minimum contributing fraction of HRU area (0-1) For different vegetation cover 26 IMPERV Effective impervious area as fraction of HRU (0-1) For different vegetation cover 27 RETIP Maximum water retention storage on impervious area

[mm] For different vegetation cover

28 SEP Maximum daily recharge from soil moisture to groundwater [mm]

29 KRES Index of subsurface reservoir 30 KGW Index of groundwater reservoir 31 KSTOR Index of surface water detention reservoir 32 KDS Index of rain gage 1 (here just one) 33 DARU Area of HRU [km2] 34 UPCOR Rain correction for storm precipitation 1 35 DRCOR Rain correction for daily precipitation 1 - 1.2 36 DSCOR Snow correction for daily precipitation 1.1 - 1.4 37 TST Temperature index for defining start of transpiration [C] 38 KTS Index of temperature station 1 (here just one) 39 KSP Index of glacier availability (yes - no) 0 40 KSDC Index of the meterological station 1 (here just one) Shaded fields show information that should be determined from analyses in Chapter 5 and will be used the next exercise.

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1 Watershed Analysis 2011