1. Mapping of soil moisture content by SWAT and GIS programming Yuri Kim Jessica Jahnke GEOG 593

2. Procedure Preparing GIS Data Raster dataset DEM LULC Feature dataset Soil Stream Outlet Soil Moisture Map SWAT output text file Watershed Soil Lulc HRU mp (Hydrologic Response Unit) SWAT simulation Overlay Join Watershed Delineation (with DEM and outlet point) Preparing SWAT input files SWAT output text file Convert text file to dbf ExtracbyMask.py Watershed.py Feature2raster.py reclLULC.py Hrumap.py txt2dbf.py List_env.py ?

3. Environment setting (List_evn.py)  Setting up working environment for all GIS data management process  Standardized cell size, output extent, output coordination, ect. DEM raster  Check out ‘Spatial Analysis extention’

4. Watershed delineation (Watershed.py) 1. Fill  Creating a depressionless DEM  Input: DEM (dem_10mspm)  Output: filled DEM (fill_rd)  All subsequent process will be done with this filled DEM

5. Watershed delineation, cont. (Watershed.py) 2. Flow direction  Input: Filled DEM  Output: fld_rd  Direction of flow is known for each cell by this process

6. Watershed delineation, cont. (Watershed.py) 3. Flow accumulation  Input: Flow direction grid  Output: flcc_rd  Each cell has value which represents the number of cells upstream form that cell.

7. Watershed delineation, cont. (Watershed.py) 4. Watershed outlet point  Input: stream gague point shape file  Output: point grid  Convert point shapfile to grid  This new rater cells overlap with the high- flow pathway of flow accumulation raster; if not, the watershed that is created from this point will be too small.

8. Watershed delineation, cont. (Watershed.py) 5. Watershed delineation  Input: flow direction raster, outlet point raster  Output: Watershed grid  This raster zone represents the area upstream from the selected outlet point

9. Clip (ExtracbyMask.py) 1. Convert soil feature layer to raster dataset (feature2raster.py) 2. Reclassify LULC raster dataset by SWAT category (reclLulc.py) 3. Clip lulc and soil dataset with watershed boundary

10. Hydrologic Response Units (HRU)  Hydrologic response units are lumped land areas within the subbasin that are comprised of unique land cover, soil and management combinations HRU Watershed Layer Soil Type Layer Land Cover Layer

11. Making HRU map  To create a unique number which represents the watershed, soil type and LULC of an area, those three layers were overlaid using the following weights: 10000000 x watershed + 10000 x soil + LULC  This analysis results in an 8 digit number : the first digit represents the watershed, the second, third, and fourth digits represent the soil type, the fifth digit is always zero and the sixth, seventh and eighth digit represent the land cover type

12. Making HRU Map (continued) Example: _ _ _ _ WatershedSoil Type LULC 1 1 1 2 0 1 1 0

13. Resulting HRU Map

14. Convert text file to dbf file (txt2dbf.py)  Making dbf file from SWAT result file (.sbs)  Example

15. Making soil moisture map  Joining hru_lookup table (from SWAT) to the HRU map  Joining SWAT result dbf file to the HRU map  Display classified soil moisture map

16. Result – Soil Moisture map  Simulation period: 06/14/2000 – 06/22/2000  Dry period (before rainfall): 7 days Fast response area Slow response area

17. Discussion – Soil moisture balance eq. Depend on the LULC and Soil characteristics. is the final soil water content (mm H 2 O), is the initial soil water content on day i (mm H 2 O), is the amount of precipitation on day i (mm H 2 O), is the amount of surface runoff on day i (mm H 2 O), is the amount of evapotranspiration on day i (mm H 2 O), is the amount of water entering ground water zone from the soil profile on day i (mm H 2 O), and is the amount of return flow on day i (mm H 2 O).

18. Discussion – Landuse/Landcover  Agriculture - Fast response area - Shallow soil depth - Contribute to fast runoff - Sediment and nutrient problem  Forest - Slow response area - Deeper soil than any other area

19. Discussion – Soil characteristics  SSURGO soil data - Natural Resources Conservation Service (NCGC) archived and distributed SSURGO soil data from 1995 - 2003  Soil characteristic - Soil Hydrologic Group (A, B, C and D) - Maximum rooting depth - Saturated hydraulic conductivity - Avaliable water capacity - etc.

20. Further Study  GIS Programming problems 1. Joining problem - Impossible with python - With VBA (Spatial Join) 2. Classification problem (in display) - With VBA (ClassBreakRenderer)  SWAT modeling problem 1. Need more calibration to improve model accuracy