Exercise Lab: Where is the Himalaya eroding? Using GIS/DEM analysis to reconstruct surfaces, incision, and erosion

Transcription

1 Exercise Lab: Where is the Himalaya eroding? Using GIS/DEM analysis to reconstruct surfaces, incision, and erosion 1) Start ArcMap and ensure that the 3D Analyst and the Spatial Analyst are loaded and activated in the Options menu. 2) Load Hydro1K DEM of the Himalaya region: Click on plus sign and select h1k_dem (SRTM V3, 1km gridcell size) 3) Create a hillshade within ArcMap: 3D Analyst >Surface Analysis > Hillshade a. Select Output Raster, name it h1k_dem_hs and save in same directory. Use standard options, no need to change any values. [NOTE: It is essential that you give your grids and files meaningful names we will create quite a few files and you may lose track of things if you cannot identify what a grid stands for]. 4) Drag hillshade layer below ( under ) the surface DEM. Let s change the DEM properties to make it look more appealing. Double click on h1k_dem a. Select Tab Symbology, change color to something you like. b. Select Tab Display and change value of Transparen to 45% (or similar). 5) Now you have a hillshade view of the Himalaya with draped over elevation. 6) Let s import the Apatite FissionTrack data and some results from Pete Reiner s exercise. [Note: This is very useful for importing any types of data with coordinates (GPS data, field observations, Monzanite concentration, data from a paper, table, etc).] a. You will need a CSV ( comma delimited file save as option in Excel). Make sure that the first line contains the column labels without any space and or special characters ([]! etc.). This involves some editing in Excel. [I am using the file Himalaya_all_FT_data_mod.csv. In case this doesn t work for you, I also provide the file called XYHimalaya_all_FT_data_mod.shp that contains some results from Pete s exercise.] b. Open ArcCatalog and navigate to the directory in which you have saved the file. Right click on *.csv File and Select Create Feature Class >From XY Table. If there is an error opening the file is 99.9% related to not allowed characters. c. Select Longitude as X Field, Latitude as Y Field. You won t need a Z Field. Use a meaningful filename. IT is advisable to defin a spatial reference frame. The file we are using is in a Geographic projection (WGS84). Click on Advanced Geometry Options and on Edit in the next window. SELECT a predefined coordinate system by navigating to Geographic Coordinate Systems, World, WGS1984.prj. Press OK on all windows. d. If you click on Refresh (View > Refresh), you should have a new point shapefile in your folder. Add this shapefile to your ArcMap view (press plus sign in ArcMap window). e. The locations of the samples are plotted on the map. Let s change their colors to show something more meaningful: Double click on shapefile. In the Symbology Tab, select Quantities > Graduated colors. In the Fields: section, select Value: ACentralAge and a meaningful colorscale. You can change the size and layout of the points by clicking on 1

2 Symbol (below the Color Ramp:) >Properties for all symbols. Note the spatial distribution of young cooling ages. f. Let s select the calculated erate (Erosion Rate) from Pete s modeling. What are the differences along strike? 7) Load the provided shapefile (all_er_data.shp) that contains several compiled CRN and sediment flux based erosion rate data (Vance et al., 2003; Bookhagen et al., 2007; Niemi et al., 2005; Garzanti et al., 2007). Create a meaningful colorscale and visually compare the data to the long term exhumation rates and the derived topographic indices. It may make sense to chose the some colorscale, but different symbology or sizes. Do the AFT exhumation rates and CRN erosion rates correlate? Compare the data to first order topographic indices. 8) Next, we would like to create a hillslope map a. Select 3D Analyst >Surface Analysis >Slope, output measurements should be degree and the slope map will be saved in the same directory, labeled (for example) h1k_dem_sl. b. Change the color scale to stretched, and the transparent value. Turn off the DEM layer. Are the slopes realistic? Keep in mind that we are using 1 km data. 9) Local relief is slightly more complex, but also contains more valuable information a. Use the focalmin and focalmax commands that find the min (or max) elevation within a given radius. Subtracting min from max elevation gives you relief b. There are several ways of doing this, the easiest may be to start the help and select the Index Tab. Search for focal statistics tool/command and open the tool. c. Input raster is your DEM (h1k_dem), output raster is v3_mx3km, neighborhood is a circle, settings are 3 cells (3x1 km = 3 km radius), statistic type is MAXIMUM. d. Repeat this with minimum elevation (output raster is v3_mi3km, statistic type is MINIMUM. e. Repeat with a radius of 5 km (Note the larger the radius the longer the calculation takes). f. Subtract the two newly formed grids in the Raster Calculator (Spatial Analyst > Raster Calculator). Type: v3_rel3km = [v3_mx3km] [v3_mi3km] g. Repeat calculation for 5 km radius h. Change the color scale (you can use a classified color scale if you like) i. Where are the maximum relief amounts? j. Similarly, you can create a mean elevation for a 5 or 10 km circle by choosing the statistic type MEAN. You will need to change the radius to 5 or 10 pixels. [Note that the 10 pixel circle will take a while to calculate.] 10) Create an envelope surface (can be used to reconstruct eroded volume) and the geophysical relief amounts ( reconstructed surface minus present day topography). We follow Small and Anderson [1998] and define geophysical relief to be the mean elevation difference between two surfaces: a smooth surface connecting the highest points in the current landscape and the current topography itself. This difference defines the average volume of rock eroded from 2

3 beneath the topographic envelope. Geophysical relief differs from local or ordinary relief (as used in the previous sections), which is the maximum elevation difference between valley bottoms and adjacent ridge crests. a. Open the Focal statistics tool/command (described above) and calculate the maximum elevation within radii of 10, 20, and 25 km (statistic type: MAXIMUM). [Note that there are more sophisticated ways of creating an envelope surface but most of them would require significant manual editing the described method here will work very well as a first order approach.] b. Open the Raster Calculator window (see above) and subtract the present day topography from the 10, 20, and 25 km maximum surface ( envelope surfaces ): grel10km = [v3_mx10km] [h1k_dem]. Repeat this for each radius. c. In order to display the results in a meaningful way, you will have to change the colorscale. Also, you should change the Stretched Type to Histogram Equalize in the Layer Properties > Symbology section (where you change the color). This will emphasize the regions with high amounts, as there are large regions with low geophysical relief. d. Where are the regions with the largest amount of rock removed? Is the amount of rock removed homogenous along strike of the Himalaya? 11) Load the rainfall data (t9806a) and display it in a red blue scale. [Note the merging of two datasets at ~36N this is where the TRMM dataset ends and I have used a different, lower resolution satellite to fill in the gaps. There are some artifacts in the higher latitudes]. The rainfall data is processed and calibrated to m/yr. OPTIONAL (if time permits) 12) Load the rainfall data (t9806a) and display it in a red blue scale. [Note the merging of two datasets at ~36N this is where the TRMM dataset ends and I have used a different, lower resolution satellite to fill in the gaps. There are some artifacts in the higher latitudes]. The rainfall data is processed and calibrated to m/yr. We will use the rainfall data to create realistic discharge that will be converted into a specific stream power amounts (hydrologic processing). [NOTE: There are several tools available for ArcMap that make things easier, for example, the Arc Hydro Toolbox. I refrain from using them, as it helps going through these steps at least once. The following few steps are easy but powerful to create a rivernetwork from your DEM.] a. Create a hydrological correct DEM by filling all sinks in the grid. This is essential to ensure that all rivers flow downstream and that there exist no artificially closed basins. Open the Help and search for the Fill tool/command. Input surface is h1k_dem, output surface is h1k_dem_fil, no need to set a Z limit. [NOTE: This will take > 1 minute, please be patient.] b. Calculate the flow direction. Each cell flows into a neighboring cell. This is an intermediate step (you will not look at the data) and it will be used as input for the next command. It basically is a direction grid indicating in which neighboring cell the water flows. Open the Help and search for the Flow Direction tool/command, open Tool: Input surface is [h1k_dem_fil], output is [h1k_dem_fdr], no need to select any of the 3

4 optional settings. [Note that the flat areas have unrealistic values and do not represent the proper flow direction.] c. Calculate the flow accumulation. This is the integration part that integrates all data from the upstream areas. In other words, it is making rivers where the landscape converges. Open the Flow Accumulation tool/command: Input flow direction raster is [h1k_dem_fdr], output accumulation raster is: [h1k_dem_fac]. The first time we run this, we do not use a weight raster. Re run the flow accumulation with the rainfall grid as weight raster (output: [h1k_dem_fact]). This will result in actual discharge amount. [In addition and in a later step, we can use the geophysical relief as weighting factor to calculate the integrated amount of eroded rock volume (i.e., the total catchment eroded volume). ] d. [Optional] Next, we can convert the flowaccumulation grid into a stream order coverage. This will weigh the streams with larger streams having higher numbers (Strahler Order). Use the Stream Order tool/command, input stream raster is the flow accumulation grid [h1k_dem_fac], flow direction raster is [h1k_dem_fdr], output raster is [h1k_dem_sto], Method of stream ordering is STRAHLER. As an additional step, you can convert the stream order grid into a line coverage with Stream to Feature tool/command, where you select the stream order grid as stream flow grid. The resulting file is a vector file. You can then change the color scale to match the stream order (i.e., increasing stream order with darker colors). Also, you can use the command Basin tool/command to create the outlines of the drainage basins. e. In order to have discharge values in m 3 /s, you will need to multiply the rainfall weighted flowaccumulation grid with 2*1000/(60*60*24*365). (gridcell size in m 2 divided by the seconds in one year). Use the Raster calculator: h1k_dem_fatcmy = [h1k_dem_fact] * (1000 * 1000) / (60 * 60 * 24 * 365). This is used as an input for the specific stream power calculation. f. Repeat the discharge scaling for the non weighted flowaccumulation grid, assuming that there is homogenous rainfall everywhere i.e. no steep rainfall gradient and dry Tibetan Plateau. Raster calculator: h1k_dem_facmy = [h1k_dem_fac] * (1000 * 1000) / (60 * 60 * 24 * 365). This is used as an input for the specific stream power calculation. g. Convert the slope map into a slope map with units m/m. This will be used as an input into the specific stream power calculation. First, create slope map with slopes in degree (3D Analyst >Surface Analysis >Slope) or use the one already created [h1k_dem_sl]. In the Raster Calculator, take the tan of the slope in percent: h1k_dem_slp = ATan([h1k_dem_sl]). h. Create a channel width map with discharge 0.4 : in the Raster Calculator, type h1k_cw = Pow([h1k_dem_facmy], 0.4). Channel width is a power law of discharge (i.e., the higher the discharge, the wider the channel) and is for the Himalaya 6 * discharge 0.4 (taken from Craddock et al., 2007 usually an exponent between 0.3 and 0.5). i. Specific Stream Power (SSP) is defined as SSP = density * gravity * channel slope * discharge / channel width. We will use a density of 1000 kg m 3, gravity of 9.81 m s 2. We substitute channel slope with hillslope (this is not correct, but we are using 1 km data 4

5 and rivers are generally not as wide as 1km with a 90 m dataset, rivers can be more accurately depicted ), discharge is taken directly from the weighted and scaled flowaccumulation in m3 s 1, channel width is in m. In the Raster Calculator, type: ssp_t = 1000 * 9.1 * [h1k_dem_slp] * [h1k_dem_factmy] / [h1k_cw]. Similarly, create a SSP map with homogenous rainfall and discharge: ssp_nt = 1000 * 9.1 * [h1k_dem_slp] * [h1k_dem_factmy] / [h1k_cw] j. It is best to display the SSP map in a classified color scale (double click on ssp_t or ssp_nt, seect the Symbology Tagb and a classified 5