3-data_preparation.dox

/**
\page data Data Preparation for mHM

\tableofcontents

\section starting Getting Started

To run mHM the user requires a number of datasets. The follwing subsection gives
a short overview and references to freely available datasets.

\subsection meteo_data Meteorological variables

Meteorological data is usually available from the weather services of the countries of modelling
interest. Freely available alternatives are the EOBS (http://www.ecad.eu/download/ensembles/download.php)
and the WATCH datasets (http://www.eu-watch.org/gfx_content/documents/README-WFDEI.pdf).

You may have difficulties
finding measurement data for Potential Evapotranspiration (PET). One possible solution,
would be to calculate PET from the much easier available variables mean, maximum and minimum
air temperature, using the Hargreaves-Samani method.

The two meteorological variables which are needed:


<b> Name                          | Unit                    | Temporal resolution </b>
| -------------------------- | -------------------------- | -------------------------- |
Precipitation                     | \f$\mathrm{mm}\f$       | hourly to daily
Average air temperature           | \f$^\circ \mathrm{C}\f$ | hourly to daily



Dependent of the specification for the potential evapotranspiration (processCase(5)) additional
meteorological variables may be need:

\li processCase(5) = 0 - PET is read from input.
\li processCase(5) = 1 - Hargreaves-Samani equation
\li processCase(5) = 2 - Priestley-Taylor equation
\li processCase(5) = 3 - Penam-Monteith equation


<b> Name                          | Unit                    | Temporal resolution </b> |
| -------------------------- | -------------------------- | -------------------------- |
0 - Potential evapotranspiration  | \f$\mathrm{mm}\f$       | hourly to daily
1 - Minimum air temperature       | \f$^\circ \mathrm{C}\f$ | daily
1 - Maximum air temperature       | \f$^\circ \mathrm{C}\f$ | daily
2 - Net radiation                 | \f$ W\;m^{-2}       \f$ | daily
3 - Net radiation                 | \f$ W\;m^{-2}       \f$ | daily
3 - Absolut vapur pressure of air | \f$ Pa              \f$ | daily
3 - Windspeed                     | \f$ m\;s^{-1}       \f$ | daily


\subsection morph_data Morphological variables

In addition to the Digital Elevation Models (DEM) usually provided by federal authorities, a number of free alternatives exists.
SRTM data is available from 60° South to 60° North in a 3" (~ 90 m) resolution (http://srtm.csi.cgiar.org/), the ASTER-GDEM
covers the entire globe with a resolution of 1" (http://gdem.ersdac.jspacesystems.or.jp/). Hydrographically corrected
SRTM data and a number of derived products in different resolutions are available from the HydroSHEDS project
(http://hydrosheds.cr.usgs.gov/index.php).

Soil and hydrogeological data is usually provided by the geological surveys. On the soil side the
Harmonized World Soil Database would be a free alternative (http://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/).


<b> Name                 | Unit  | Temporal resolution </b>
| -------------------------- | -------------------------- | -------------------------- |
Digital elevation model  | \f$\mathrm{m}\f$ | -
Soil maps with textural properties<br />(\% sand and clay contents, bulk density per horizon,<br />and root depth zone) | -  | -
Geological maps with aquifer properties<br />(specific yield, permeability, aquifer thickness)                    | -  | -
Streamflow location      | \f$(\mathrm{m}, \mathrm{m})\f$ (lat,lon)                                                | -


\subsection luse_data Land Cover

Free land cover data is available from different sources. The Corine programm provides land cover scenes for Europe
with resolutions of 100m and 250m (http://www.eea.europa.eu/publications/COR0-landcover), the Global Land Cover Map 2000
a dateset covers the entire world in a resolution of 1km.


<b> Name                 | Unit  | Temporal resolution </b>
| -------------------------- | -------------------------- | -------------------------- |
Land cover scenes        |  -    | monthly to annual
Leaf area index          |  -    |  weekly to monthly


\subsection gauge_data Gauging Station Information

Streamflow measurments should also be available from federal authorities. In addition, the Global Runoff Data Center provides
timeseries of varying length for several thousand gauging stations all over the world (http://www.bafg.de/GRDC)


| <b>Name</b>                 | <b>Unit</b>                               | <b>Temporal resolution </b> |
| -------------------------- | -------------------------- | -------------------------- |
| Streamflow  measurements | \f$\mathrm{m}^3 \mathrm{s}^{-1}\f$ | hourly to daily


\subsection optional Optional Data


|<b> Name                         | Unit                                     | Temporal resolution </b>
| -------------------------- | -------------------------- | -------------------------- |
Snow cover                       | -                                        | daily to weekly
Land surface temperature         | \f$\mathrm{K}\f$                         | daily to weekly
Groundwater station location     | \f$(\mathrm{m}, \mathrm{m})\f$ (lat,lon) |  -
Groundwater head measurements    | \f$\mathrm{m}\f$                         | weekly to monthly
Eddy covariance station location | \f$(\mathrm{m}, \mathrm{m})\f$ (lat,lon) |  -
Eddy covariance  measurements    | \f$\mathrm{m}\f$                         | hourly



\section meteo  Preparation of the Forcings

Forcing data should be available from federal databases like DWD for Germany. Be sure to bring data in the netcdf format, like
\code
    precipitation-1950-2013.nc
\endcode
These files can be edited with the CDO module package in order to select or change data.
Please read the according CDO and NCKS reference sheets for details and make sure to load the CDO modules before starting.

\subsection extractncsize Extract Data to the Size of a Catchment

Let FULLMAP.nc be the the forcing data of a region much greater than your catchment.
Let X1, X2, Y1, Y2 be the coordinates (lon and lat) of a rectangular overlapping the catchment.
The forcing data MAP.nc for your catchment can be extracted by the CDO command:
\code
    cdo sellonlatbox,X1,X2,Y1,Y2 FULLMAP.nc MAP.nc
\endcode
Optionally, certain pixels can be extracted, too:
\code
    ncks -d x,1,1 -d y,2,2 MAP.nc PIXEL.nc
\endcode

\subsection extractncdata Extact Data to the Time Period of Interest

Let MAP.nc be the forcing data including your period of interest. Let DATE1 and DATE2 be the starting and ending dates of your period, respectively.
Their date format is YYYY-MM-DD. The data PERIOD.nc can be extracted by the CDO command:
\code
    cdo seldate,DATE1,DATE2 MAP.nc PERIOD.nc
\endcode
Please note that a reference date according to DATE1 should be provided in PERIOD.nc:
\code
    cdo setreftime,DATE1,00:00:00,days PERIOD.nc FINAL.nc
\endcode

\subsection datatypes Data Types

Any data provided for mHM should be of the data type DOUBLE. You should convert all data related to a variable VAR (e.g. tavg) with the following CDO command:
\code
    cdo -b F64 selname,VAR FINAL.nc FINAL64.nc
\endcode

The only exception here is the time, its data type has to be INTEGER. This can be changed with NCAP2:
\code
    ncap2 -s 'time=int(time)' STILLNOTFINAL.nc FINAL.nc
\endcode

\subsection varnames Variable Names

In mHM the variable names of the forcing are hard-coded. They need to be
- "tavg" for average temperature
- "pre" for precipitation
- "pet" for evapotranspiration

For example, you can change the variable name TEMPERATURE in your NETCDF file with the following CDO command:
\code
    cdo chname,TEMPERATURE,tavg TEMPDATA.nc TEMPDATA-FINAL.nc
\endcode

\subsection headerfiles The Header File

Every meteorological data file should come with an additional file "header.txt" in the same directory.
In the following example, we has only one pixel of data (ncols=nrows=1) and a cell size of 4km.
The easting and northing coordinates of the lower left cornaer should be similar to the morphological data of
your catchment.
\code
ncols         1
nrows         1
xllcorner     639357.3
yllcorner     5723706.2
cellsize      4000
NODATA_value  -9999
\endcode

\subsection nodata NODATA values

In order to be consistent in your data, you should specify the same NODATA value everywhere. For example, specify "-9999" in your header file as NODATA value.
Usually, this should be changed also in NC files by the <code>ncatted</code> command. The following example overwrites or adds (o) the NODATA attribute "_FillValue"
with value "-9999" of type double (d) to the variable "pre":
\code
ncatted -O -a _FillValue,pre,o,d,-9999. INOUT.nc
\endcode

\section latlon Preparation of the LatLon Grid

As input mHM additionally needs a <code>latlon.nc</code> file specifying the geographical location of every grid cell in
WGS84 coordinates. This file has to be adjusted for every resolution of the level-1 hydrological simulations.

For creating a latlon file mHM comes with the python script <code>create_latlon.py</code>, which can be found in
<code>pre-proc/</code>. Detailed information for the usage of this python script can be found in the online help by typing:
\code
python [MHM_DIRECTORY]/pre-proc/create_latlon.py -h
\endcode
<code>create_latlon.py</code> needs several specifications via command line switches. First, the coordinate system of
the morphological and meteorological data have to be specified according to
<a href="http://www.spatialreference.org">www.spatialreference.org</a> by using the switch: <code>-c</code>.
Second, you need to specify three header files containing the corresponding information for the different spatail
resolutions connected to mHM. The three resolutions are the resoltution of 1) the morphological input (switch: <code>-f</code>),
2) the hydrological simulation (switch: <code>-g</code>), and 3) the routing (switch: <code>-e</code>).

These header files can be produced by adopting the header file of the meteorological data
Therefore, copy one of these files that you generated for meteo data (see \ref meteo):
\code
cp [INPUT_DIRECTOY]/input/meteo/pre/header.txt [INPUT_DIRECTORY]/input/latlon/
\endcode
Edit the new file <code>header.txt</code> such that <code>cellsize</code> equals your hydrologic resolution.
You have to adapt <code>ncols</code> and <code>nrows</code>
to that resolution such that it covers the whole region. For example, reducing the cell size from 2000 to 100,
the number of columns and rows should be increased by a factor of 20.

Third, you need to set the path and filename for the resulting output file by using the switch <code>-o</code>.

An example for creating a lat-lon-file looks like
\code
python [MHM_DIRECTORY]/pre-proc/create_latlon.py -c epsg:31463 -f header_100m.txt -g header_1000m.txt -e header_2000m.txt -o ../latlon/latlon.nc
\endcode

Keep in mind that you need one latlon file for each hydrologic resolution in mHM. Since the filename <code>latlon.nc</code> is hard-coded in mHM,
we recommend to create different directories for each resolution you need, containing the related header and latlon file.


\section morph  Preparation of the Morphological Data

MHM needs several morphological input datasets. All these have to be provided as raster maps in the ArcGis ascii-format, which stores the above header and the actual data
 as plain text. Some of the raster files need to be complemented by look-up tables providing additional information. The tables and their structure are described in more detail in subsection \ref tables.
 Take care of the follwing limitations to mHM input data during data processing:
 \arg All gridded input, i.e. your morphological and your meteorological data, needs to cover the same spatial domain. That means, that the values xllcorner, yllcorner,
    xllcorner+ncols*cellsize and yllcorner+nrows*cellsize have to be identical for all files!
 \arg MHM allows you to provide your meteorological forcing in a different horizontal resolution than the morphological data. The larger cellsize however needs to be a multiple of
    the smaller.

The required datasets and their corresponding filenames:


<b> Description	  	    	       	    | Raster file name  | Table file name        </b> |
| -------------------------- | -------------------------- | -------------------------- |
Sink filled Digital Elevevation Model (DEM) | dem.asc	        | -
Slope map   	        		    | slope.asc	        | -
Aspect Map			            | aspect.asc	| -
Flow Direction map		            | fdir.asc	        | -
Flow Accumulation map                       | facc.asc	   	| -
Gauge(s) position map  		       	    | idgauges.asc      | [gauge-id].txt
Soil map	     		       	    | soil_class.asc    | soil_classdefinition.txt
Hydrogeological map		       	    | geology_class.asc | geology_classdefinition.txt
Leaf Area Index (LAI) map	       	    | LAI_class.asc     | LAI_classdefinition.txt
Land use map   			       	    | your choice       | -


\section gis A possible GIS workflow

In the following paragraphs a possible GIS workflow is outlined using the software ArcMAP 10 with the Spatial Analyst Extension
 and optionally the Arc Hydro Tools (http://downloads.esri.com/blogs/hydro/AH2/ArcHydroTools_2_0.zip)

\subsection gnrl General considerations

\arg As the spatial discretizations (i.e. resolutions, origin) of your datasets will most likely differ, it is recommended to set the following envirnmental settings on every processing step outlined
   in the following paragraphs.
         \image html environments.png "Button 'Environments...' in all Toolbox windows"
      	 \anchor fig_environments \image latex environments.pdf "Button 'Environments...' in all Toolbox windows" width=14cm
   Point to the largest of your input data grids in 'Extent' and 'Snap Raster', which is usually the dataset with the coarsest horizontal resolution. In the likely case, that this is your meteorological
   input, create a grid from any of your netcdf-files first.
         \image html netcdf_to_raster.png "System Toolboxes -> Multidimension Tools -> Make NetCDF Raster Layer"
	     \anchor fig_netcdf_to_raster \image latex netcdf_to_raster.pdf "System Toolboxes -> Multidimension Tools -> Make NetCDF Raster Layer" width=14cm
   Save the output grid (right click the raster in the 'Table of Contents' -> 'Data' -> 'Export Data...').

\arg If the map projections of your datasets differ, a harmonization of these becomes necessary. Repeat the depicted step to convert all your input files. Which projection to choose is highly
   dependent on your simulation domain and size. For the current model version an equal-area projection is strongly recommended.
     \image html project.png "System Toolboxes -> Data Management Tools -> Projections and Transformations -> Raster -> Project Raster"
     \anchor fig_project \image latex project.pdf "System Toolboxes -> Data Management Tools -> Projections and Transformations -> Raster -> Project Raster" width=14cm

\arg If your input datasets are not already in the desired level-0 resolution, resample the DEM, the hydrogeological, LAI, soil and land use maps.
    Choosing an appropiate resolution depends on data quality and needed level of simulation detail, but keep in mind that:

     1. Your different input resolution levels must be multiples of each other. E.g. you should choose a level-0 resolution of 100m (instead of 90m in case you are using SRTM data) if your
        meteorological input resolution is 4km.

     2. Model runtime directly depends on the number of grid cells.

     \image html resample.png "System Toolboxes -> Data Management Tools -> Raster -> Raster Processing -> Resample"
     \anchor fig_resample \image latex resample.pdf "System Toolboxes -> Data Management Tools -> Raster -> Raster Processing -> Resample" width=14cm

\arg  It is important that all your morphological input files exactly cover the same spatial domain. That also means that if a cell contains valid data in any one of the datasets, the very same cell must
    also be definied in all the others. One possibility to solve this typical problem would be to set such 'doubtful' cells to the corresponding NODATA_value. Therefore create a mask as
    depicted below, which only contains cells, that are defined everywhere.
     \image html data_mask.png "System Toolboxes -> Spatial Analyst Tools -> Map Algebra -> Raster Calculator"
     \anchor fig_data_mask \image latex data_mask.pdf "System Toolboxes -> Spatial Analyst Tools -> Map Algebra -> Raster Calculator" width=14cm

\arg    Mask all the mentioned datasets with the output of the 'Raster Calculator' follwing the procedure described in \ref mask of this tutorial. In case the described processing step is necessary,
    accomplish it <b> before </b> you reach  subsection \ref hydro ! Masking these maps would most likely disturb the hydrological
    properties of your catchment data and result in unexpected model behaviour.

\subsection slope Slope map
     \image html slope.png "System Toolboxes -> Spatial Analyst Tools -> Surface -> Slope"
     \anchor fig_slope \image latex slope.pdf "System Toolboxes -> Spatial Analyst Tools -> Surface -> Slope" width=14cm


\subsection aspect Aspect map
     \image html aspect.png "System Toolboxes -> Spatial Analyst Tools -> Surface -> Aspect"
     \anchor fig_aspect \image latex aspect.pdf "System Toolboxes -> Spatial Analyst Tools -> Surface -> Aspect" width=14cm


\subsection fill Fill DEM sinks
     \image html fill.png "System Toolboxes -> Spatial Analyst Tools -> Hydrology -> Fill"
     \anchor fig_fill \image latex fill.pdf "System Toolboxes -> Spatial Analyst Tools -> Hydrology -> Fill" width=14cm


\subsection hydro Flow direction and flow accumulation

  Depending on quality and resolution of the DEM map, these steps can be done with the respective tools from the Spatial Anaylst Extension or by using the Arc Hydro Tools.

\subsubsection spatial_analyst Spatial Analyst

If a high quality DEM, with a resolution fine enough to represent small scale river morphology is available, you may calculate flow direction and flow accumulation directly.

\arg Flow Directon
     \image html fdir.png "System Toolboxes -> Spatial Analyst Tools -> Hydrology -> Flow Direction"
  	  \anchor fig_fdir \image latex fdir.pdf "System Toolboxes -> Spatial Analyst Tools -> Hydrology -> Flow Direction" width=14cm

\arg Flow Accumulation
     \image html facc.png "System Toolboxes -> Spatial Analyst Tools -> Hydrology -> Flow Accumulation"
     \anchor fig_facc \image latex facc.pdf "System Toolboxes -> Spatial Analyst Tools -> Hydrology -> Flow Accumulation" width=14cm

\subsubsection arc_hydro_tools Arc Hydro Tools

Using the Arc Hydro Tools is recommended in case of doubtful DEM quality and/or coarse map resolutions.

\arg In a first step the original DEM must be reconditioned, i.e. the given altitudes will be reassigned in dependence of a stream network. The latter must be given as a Line Shapefile.
In case the necessary stream network file is not available, you can get one from the USGS HydroSHEDS download portal http://hydrosheds.cr.usgs.gov/dataavail.php.
   \image html hydro_agree.png "System Toolboxes -> Arc Hydro Tools -> Terrain Preprocessing -> DEM Reconditioning"
   \anchor fig_agree \image latex hydro_agree.pdf "System Toolboxes -> Arc Hydro Tools -> Terrain Preprocessing -> DEM Reconditioning"  width=14cm

\arg Fill the sinks in the resulting reconditioned DEM
     \image html hydro_fill.png "System Toolboxes -> Arc Hydro Tools -> Terrain Preprocessing -> Fill Sinks"
     \anchor fig_hydro_fill \image latex hydro_fill.pdf "System Toolboxes -> Arc Hydro Tools -> Terrain Preprocessing -> Fill Sinks" width=14cm

\arg Calculate Flow Direction
     \image html hydro_fdir.png "System Toolboxes -> Arc Hydro Tools -> Terrain Preprocessing -> Flow Direction"
     \anchor fig_hydro_fdir \image latex hydro_fdir.pdf "System Toolboxes -> Arc Hydro Tools -> Terrain Preprocessing -> Flow Direction" width=14cm

\arg Create a Flow Accumulation map
     \image html hydro_facc.png "System Toolboxes -> Arc Hydro Tools -> Terrain Preprocessing -> Flow Accumulation"
     \anchor fig_hydro_facc \image latex hydro_facc.pdf "System Toolboxes -> Arc Hydro Tools -> Terrain Preprocessing -> Flow Accumulation" width=14cm


\subsection gauges Gauges map

  \arg Assuming that you have the positions of your gauges in a table, which has at least the colums x, y, id (in any order and/or amongst other columns), you are able to
     to convert your data into a Point Shapefile. Choose the appropiate fields and do not forget to set the coordinate system information.
      	  \image html xy_gauges.png "Right click on the table in Arc Catalog - > Create Feature Class -> From XY Table"
     	  \anchor fig_xy_gauges \image latex xy_gauges.pdf "Right click on the table in Arc Catalog - > Create Feature Class -> From XY Table" width=8cm


  \arg Check the positions of your gauges against the previously created Flow Accumulation map. If the points do not exactly match the stream-like features on the Flow Accumulation grid,
     edit the Shapefile (right click on the Point Feature in the Table of Contents -> Edit Features -> Start Editing) and move the gauges to do so. Changing the depiction of the Flow Accumulation map might
     facilitate this step (i.e. right click the Flow Accumulation map in the Table of Contents -> Properties -> Tab 'Symbology' -> Choose 'Stretched' in the 'Show' box on the left hand side and Type
     'Standard Deviations' in the center box. It might also be necessary to invert the color ramp by (un-)checking the 'Invert' check box). Remember to stop the editing process and save your edits
     (Editor Toolbar -> Editor -> Stop Editing).
     	     \image html move_gauge.png "Mismatching gauges (left) should be replaced (right)"
     	     \anchor fig_move_gauge \image latex move_gauge.pdf "Mismatching gauges (left) should be corrected (right)" width=14cm

  \arg Convert the resulting shapefile into an raster map with level-0 resolution.
            \image html point_to_raster.png "System Toolboxes -> Conversion Tools -> To Raster -> Point to Raster"
  	    \anchor fig_point_to_raster \image latex point_to_raster.pdf "System Toolboxes -> Conversion Tools -> To Raster -> Point to Raster" width=14cm


\subsection watershed Watershed delineation

\arg Edit the (possibly corrected) gauges shapefile created during the last processing step again and remove all but the outlet gauge. If you need
   the unedited file, create a copy of the original Shapefile before editing it.

\arg Delineate the basin
    	  \image html basin.png "System Toolboxes -> Spatial Analyst -> Hydrology -> Watershed"
     	  \anchor fig_basin \image latex basin.pdf "System Toolboxes -> Spatial Analyst -> Hydrology -> Watershed" width=14cm

 \subsection mask Mask the datasets

 Mask all mHM input raster files with the created watershed mask
    \image html mask.png "System Toolboxes -> Spatial Analysis Tools > Extraction > Extract by Mask"
    \anchor fig_mask \image latex mask.pdf  "System Toolboxes -> Spatial Analysis Tools > Extraction > Extract by Mask" width=14cm

\subsection format Write the ascii grids

 Convert the processed and masked raster maps into ASCII files
     \image html ascii.png "System Toolboxes -> Conversion Tools -> From Raster -> Raster to ASCII"
     \anchor fig_ascii \image latex ascii.pdf "System Toolboxes -> Conversion Tools -> From Raster -> Raster to ASCII" width=14cm


\section lcover Land Cover Data

Unlike the other classified datasets (soils, hydrogeology, LAI), where as much information as available can be added, the land use data is restricted to
three different classes, which are listed below:


Class | Description |
| -------------------------- | -------------------------- |
1     | Forest
2     | Impervious
3     | Pervious


\section tables Table Data

As previously stated, the input datasets 'soil_class.asc', 'geology_class.asc', 'idgauges.asc' and
'LAI_class.asc' need to be complemented by look-up-tables.
All these look-up tables specify the total number of classes/units to read in the very first line,
following the keywords 'nSoil_Types', 'nGeo_Formations' and 'NoLAIclasses' respectively. The second line
acts as a header describing the contents of the following data. In the subsection \ref soil_table
\ref hydrogeo_table and \ref lai_table screenshots of shorted, but sufficient table
files are presented. All fields are further listed and described in the repective tables.

\subsection soil_table The soil look-up table

\image html soil_classdefinition.png "A possible 'soil_classdefinion.txt' file"
\anchor fig_soil_classdefinition \image latex soil_classdefinition.pdf "A possible 'soil_classdefinion.txt' file" width=16cm


| Field     | Description
| -------------------------- | -------------------------- |
MU_GLOBAL | Soil id as given in the corresponding 'soil_class.asc' map. All raster map ids must be given here
HORIZON   | Horizon number starting at the top of the soil column.<br />Your are free to provide any number of horizons for each soil individually
UD[mm]    | Upper depth of the horizon in millimeter.<br />Should be 0 for the first, and the lower depth of the superimposing horizon for all others
LD[mm]    | Lower depth of the horizon in millimeter
CLAY[%]   | Clay content in percent
SAND[%]   | Sand content in percent
BD[gcm-3] | Mineral bulk density in grams per cubic centimeter


\subsection hydrogeo_table The hydrogeolgy look-up table

\image html geology_classdefinition.png "A possible 'geology_classdefinion.txt' file"
\anchor fig_geology_classdefinition \image latex geology_classdefinition.pdf "A possible 'geology_classdefinion.txt' file" width=16cm


Field        | Description
| -------------------------- | -------------------------- |
GeoParam(i)  | Parameter number of the formation, the link to 'mhm_parameter.nml'
ClassUnit    | Class id as present in the 'hydrogeology_class.asc' raster map
Karstic      | Presence of karstic formation (0: False, 1: True)
Description  | Text description of the unit


\subsection lai_table The LAI look-up table

\image html lai_classdefinition.png "A possible 'LAI_classdefinion.txt' file"
\anchor fig_lai_classdefinition \image latex lai_classdefinition.pdf "A possible 'LAI_classdefinion.txt' file" width=16cm


Field        | Description
| -------------------------- | -------------------------- |
ID           | LAI class id as given in the file LAI_class.asc
LAND-USE     | Description of the LAI class
Jan. to Dec. | Monthly LAI values


\subsection gauge_files The gauge files

\image html gauge.png "A possible gauge file"
\anchor gauge \image latex gauge.pdf "A possible gauge file" width=16cm


The structure of the gauge files is different from the look-up tables listed
so far. The following table describes its content.


Line      | Description
| -------------------------- | -------------------------- |
1         | Gives basic information about the gauging station (Station-Id:Station-Name/River-Name)
2         | Specifies the nodata value
3         | The number of measurements per day
4         | The start date of the time series in the format given in parentheses
5         | The end date of the time series in the format given in parentheses
6 to end  | The measurement data in cubic meter per second <br />preceded by the actual date in the same format as the dates of lines four and five


For every gauge id given in 'idgauges.asc' one gauge file has to be created as outlined above. The file name has to <b> exactly </b> reflect the gauge id and carry a '.txt' extension.
The table data file for a gauge with an id of 0343 in 'idgauges.asc' should
therfore be named '0343.txt'.

\section post-gis Post-GIS preparation

Make sure that all decimals are indicated with dots, not commas:
\code
    perl -i.bak -pe 's/\,/\./g' *.asc
\endcode

Make sure that accuracy of your llcorners is reasonable. For example, the following code removes all but one digits after the dot:
\code
    perl -i.bak -pe  's/(^[xy].+)\.(\d)\d+/$1\.$2/g' *.asc
\endcode

Make sure that your files cover the same spatial domain. In case your grid origins match, but you are missing rows and columns,
the perl script <code>pre-proc/enlargegrid.pl</code> will pad your data at the top and the right end of the grid.
\code
/basin/input/morph/$ ~/mhm/pre-proc/enlargegrid.pl aspect.pl
 31 rows with 47 cols.
/basin/input/morph/$ ~/mhm/pre-proc/enlargegrid.pl 50 40
 aspect.asc
 dem.asc
 facc.asc
 fdir.asc
/basin/input/morph/$ ~/mhm/pre-proc/enlargegrid.pl aspect.pl
 40 rows with 50 cols.
\endcode

If your data differs more substantially the program 'mHM/pre-proc/resize_grid.py' will harmonize your grids.
\code
	python match_grids.py source_grid target_grid out_grid
\endcode

The script takes three Input arguments:
1. The source grid to be enlarged
2. The target grid which could also be an header file as described in subsection \ref headerfiles
3. An output file

The program will fail, if your target grid is smaller than the source grid or if the cellsizes of both grids are not divisable.
If necessary the source grid will be shifted in order to make both origins match. This 'shift' is only accomplished by changing
the values of the corner coordinates, no real interpolation will be done.

*/