SEDP is Considered as ORGP after Routed to Reach

SEDP in output.hru is defined as `Mineral phosphorus attached to sediment that is transported by surface runoff into reach during time step.` in `SWAT Input Output Documentation Version 2012`

When you read this definition, you may assume that SEDP is added to MINP when it is routed to main reach (just like I did!).

However, this assumption is false.

SEDP is actually added to ORGP and reported in ORGP_IN and ORGP_OUT of output.rch.

On the other hand, ORGP in output.hru is `Organic P exported from HRU via subsurface flow (lateral+base flow) only`.

I will dig the code when I have time and provide the evidence for it when I have spare time.

Converting CORINE Land Use Classes to SWAT Land Use Classes

One of the initial challenges that you can encounter as a novice SWAT user who wants to use CORINE Land Use/Land Cover (LULC) maps  is converting the LULC to SWAT LULC:

Here is how I addressed this problem in my first SWAT project, which is on a 150-km2 watershed located in northwestern Turkey:

Corine2006 Code/Description:                                  SWAT:
121/Industrial or commercial units                                UCOM
122/Road and rail networks and associated land              UTRN
243/Land principally occupied by agriculture with significant areas of natural vegetation                                                                                                         AGRL
231/Pastures                                                                PAST
324/Transitional woodland scrub                                   RNGB
242(1)*/Complex cultivation patterns                              AGRL
311/Broad-leaved forest                                                FRSD
312/Coniferous forest                                                   FRSE
212(1)*/Permanently irrigated land                                 AGRL
313/Mixed forest                                                          FRST
321/Natural grassland                                                   RNGE
112(2)*/Discontinuous urban fabric                               URLD
211(1)*/Non-irrigated arable land                                   AGRC
512/Water bodies                                                         WATR
411/Inland marshes                                                      WETN

(*): Typical CORINE2006 LULC codes are three-digit. Some of the CORINE2006 codes in the map provided to me by my fellow researchers contained four digits. So, you can disregard the last digit given in parentheses.

You can download the small .txt that I wrote for my ArcSWAT (version 2012.10.1.15 released on 6/20/14) project from here. You can edit this file as you please and use it in your ArcSWAT project.

Please check out the following references, which helped me quite a bit during my own conversion process:

1. http://www.eea.europa.eu/publications/COR0-landcover

2. http://ec.europa.eu/agriculture/publi/landscape/about.htm

3. http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-2/corine-land-cover-classes-and/clc_legend.csv

SWAT: Custom Weather Generator Tips

This blog contains

• RAINHHMX & RAIN_YRS estimation/assumption for creating User Weather Generator
• Global Weather Data: Positive Bias in Precipitation Data

a. RAINHHMX and RAIN_YRS

SWAT users may need to create their own Weather Generator for their own project. However, maximum 0.5 hour rainfall information is usually unavailable. In my project, I addressed this problem by following Dr. Srinivasan's suggestion:

RAINHHMX of a given month = (Maximum Daily Precipitation recorded in given month)/3

Furthermore, I used RAIN_YRS = 10 in my User Weather Generator.

b. Global Weather Data

Worldwide weather data is made available to SWAT users via Global Weather Data. 

I downloaded data from Global Weather Data (GWD) for my project, which is on a lake watershed in northwestern Turkey (Fig. 1). When I compared GWD precipitation with the measured precipitation (obtained from Turkish Meteorological Service (MGM)), I noticed that GWD precipitation was substantially higher than the measured one, especially for the wet months (Fig. 2).   

Therefore, I highly recommend cautious use of GWD precipitation data due to the fact that this data can have very significant positive bias. 

 

Figure 1. Location of my study area and weather stations.

Distance between MGM Stations & GWD Stations:

- Bolu - 407319: 23 km

- Gerede - 407322: 7 km

Figure 2. Average monthly precipitation of the weather stations.

Mean Annual Precipitation Comparison:

• Bolu: 554.7 mm              407319: 1293.8 mm
• Gerede: 677.0 mm          407322: 1163.5 mm

SWAT: Soil Data for non-US Study Areas

This blog post addresses:

a. Acquiring soil data & soil map for modeling a non-US study area using ArcSWAT

b. Basic interpretation of the imported soil data using freely available online documents

a. Soil Data

Default ArcSWAT database (SWAT2012.mdb) does include the US soil data in usersoil table.

World soil data can be imported from MWSWAT database (mwswat2012.mdb). Therefore, you need to install MapWindow and MWSWAT if you want to have access to mwswat2012.mdb.

After you complete the installation, you can find mwswat2012.mdb under the MWSWAT2012 subdirectory of MapWindow directory (e.g., C:\MapWindow\Plugins\MWSWAT2012).

If you want to bypass this procedure, feel free to download custom SWAT2012.mdb I use in my project that includes the worldwide soil data in user table.

Once you download the custom SWAT2012.mdb, you can simply replace the original file with the newly downloaded custom file.

Soil Map

You can practically download soil maps in raster format for any place in the world from the download section of MWSWAT site. You may need to pre-process the raster file and clip it in a GIS software, which is beyond the scope of this post. You may refer to MWSWAT documents for pre-processing tips.

You will notice that every cell, which is also called as soil mapping unit, in the downloaded raster file has a unique value. The values refer to the specific soils listed in usersoil table of the custom SWAT2012.mdb.

For instance, if the value of a cell is 1736, that cell or soil mapping unit has Vp19-3a-1736 soil. I will explain how we can interpret the abbreviations used in the soil name below.

In ArcSWAT, you will need to link the values in your soil map with the corresponding soil data. The instructions are available in pp. 17-18 of ArcSWAT 2012 User's Guide. I share the simple soil lookup table I wrote for my project as an example.

b. Soil Data Interpretation 

Information on the soil taxonomy is typically required in the technical document preparation phase. Therefore, SWAT user needs to know what the SNAM field abbreviation in usersoil table of SWAT2012.mdb stand for.

The soil data in the custom SWAT2012.mdb is compiled from 1:5000000 scale World Soil Map (version 3.6) of the United Nations Food and Agriculture Organization (FAO).

MWSWAT site includes two documents that can be used for the data interpretation, namely readme.pdf and notes.txt.

FAO has its own web page dedicated to the World Soil Map. Two Excel files (BasicFilesSC.xls and WORLD764.xls) acquired from this web page are particularly useful for the data interpretation purposes.

Below I give an example from my own SWAT project where I extracted the taxonomic information from the abbreviations

Example:

Unique abbreviation for the soil mapping unit: Ao111-2bc-3003

Ao stands for Orthic Acrisols (Reference Used: readme.pdf)

Summary Information (Reference Used: BasicFilesSC.xls)  : Orthic Acrisols as the `dominant soil` constitutes 40% of the map unit (MU). 100% of the map unit has medium texture. 75% of the MU has rolling topography and 25% of the MU has mountainous topography.

Detailed Information (Reference Used: WORLD764.xls): Map unit consists of

20% Orthic Acrisols-2b texture-slope class
20% Orthic Acrisols-2c texture-slope class

30% Dystric Cambisols (Bd)-2b texture-slope class

10% Calcic Cambisols (Bk)-2b texture-slope class

10% RENDZINAS (E)-2b texture-slope class

10% LITHOSOLS (I) 10%  of the map unit

• 5% LITHOSOLS (I)-2b texture-slope class
• 5% LITHOSOLS (I)-2c texture-slope class

Texture, topography/slope classifications can be found in readme.pdf