# Presentation: 685809

## Use of GIS for Hydrologic Model Parameter Estimation

- OHD/HSMB/Hydrologic Modeling Group
- Seann Reed (presenter), Ziya Zhang, Yu Zhang, Victor Koren, Fekadu Moreda, Michael Smith, Zhengtao Cui
- Presented at the RFC GIS Workshop, OHRFC
- July 17, 2007

**Notes:**
Definition of GIS?  A toolkit with high level access functions for interactive or automated management, analysis, and display of geographically referenced data.

My title should really be “GIS and custom programs”  

## Outline

- Gridded a-priori parameter estimation procedures
- SAC-SMA
- PE, PE Adjustment Factors
- Snow-17
- Distributed model routing
- Calibration Assistance Program (CAP)
- Polar stereographic/HRAP
- Xmrgtoasc, asctoxmrg

- Pre-processing

- Delivery

**Notes:**
Main reason that we haven’t gotten into using ArcGIS 9.x is our desire to share data with non-GIS models that run on Linux and strict rules in our building about networking PC.  Also, since the AWIPS move away from Linux we have halted or slowed any development to 

## A priori SAC-SMA Parameter Grids

**Victor Koren methodology inputs:**
- SCS curve number; assumed dry antecedent conditions
- total soil column depth
- texture by layer
**Three versions now being tested:**
- STATSGO only (original)
- Miller and White (1998) 1-km gridded STATSGO
- Curve numbers vary spatially as a function of hydrologic soil group but not land use; assumed “pasture or range land use”
- CONUS coverage
- STATSGO-GLCC
- GLCC:  Global Land Cover Characterization (1-km resolution)
- Explicitly account for Land Use/Land Cover variations
- CONUS coverage
- SSURGO-NLCD
- SSURGO:  State Soil Geographic Database
- NLCD:  National Land Cover Database
- Higher resolution inputs
- Parameters derived for 25 states in southern US so far

## State Soil Geographic Database (STATSGO)
A Mapunit groups similar soils and may contain several non-contiguous polygons; each polygon may contain multiple soil types
Mapunit sizes ~ 102 – 103 km2
Attribute tables contain soil property information by layer
Soil Survey Geographic Database (SSURGO)
 ~ 4 to 20 times more detail
Polygon data for all counties expected to be available in standard digital format by 2008

- A Mapunit groups similar soils and may contain several non-contiguous _polygons_; each polygon may contain multiple soil types
- Mapunit sizes ~ 102 – 103 km2
- Attribute tables contain soil property information by layer
- Soil Survey Geographic Database (SSURGO)
-  ~ 4 to 20 times more detail
- Polygon data for all counties expected to be available in standard digital format by 2008

- Surface Soil Textures in a 600 km2 Basin

**STATSGO vs. SSURGO**

**Notes:**
Soil data: 4 to 20 times more detail from STATSGO to SSURGO
Landuse data: NLCD has 30 times the resolution of GLCC

## STATSGO and SSURGO contain both spatial and tabular information.

- SSURGO data schematic from Zhang et al. (2007), in review

## Complex Soil Survey Databases Must Be Simplified

- From Zhang et al. (2007)

-   This slide describes our assumptions for SSURGO simplifications
-   Miller and White (1998) used similar assumptions to convert STATSGO polygon data to a 1 km grid and 11 standard layers for the conterminous U.S.

##   Efficient processing of large data sets using GRASS, R, K Shell and Perl scripts

-   Phases 1 and 2 run for each soil survey area and then merged to state and regional domains in Phase 3
-   Parameters aggregated to 1⁄4, 1⁄2, and 1 HRAP resolutions for hydrologic modeling Phase 3

- Zhang et al. (2007), in review

## Example SSURGO-NLCD Results:

- UZTWM

- Basic Result

- Basic with Gap Filling

**Notes:**
Annotate with 

## STATSGO-STATSGO_GLCC

- STATSGO:  UZTWM

- STATSGO_GLCC: UZTWM

- Mean: 54 mm

- Mean: 51 mm

- STATSGO – STATSGO_GLCC

- STATSGO – STATSGO/GLCC

- Forested Areas

**Notes:**
Annotate with 

## PE and PE Adjustment Factor Grids

- PE

- Koren, Schaake, Duan, Smith, and Cong (1998)

- PE Adjustment

- July

- January

**Notes:**
Gridded data delivered via CAP and HL-RDHM

PE Data are from analysis of NOAA atlas 33 and 34 data
PE Adjustment factors are from an empirical relationshop between Eric Anderson’s calibrated values and gridded NDVI vegetation (8 year mean I think)

## Gridded A-priori Estimates for Two Snow-17 Parameters

- _Derived from:_
- Aspect (500-m DEM)
- Slope
- Forest Type
- Forest Cover, %
- Anderson (2002) recommendations for MFMIN, MFMAX (Chapter 7-4)

- MFMIN

- MFMAX

**Notes:**
If ok, wil be delivered via CAP. 

Development tools:  ArcView 3.x. w/ Spatial Analyst, FORTRAN (Moreda, 2006)
Grid availability:  Via CAP and HL-RDHM

## Flow Direction Grid

- Digital Elevation Model and Derivatives (DEMs)“Out-of-the-Box” DEM Analysis

## Flow Accumulation

- “Out-of-the-Box” DEM Analysis

## Streams

- Stream links

- Sub-basins

- 2

- 3

- 4

- 5

- 6

- “Out-of-the-Box” DEM Analysis

## Customized Algorithms for Analyzing DEMs with Low Accuracy in Flat Areas

- Identify flat areas and digitized streams

- Modify elevation grid

- Compute new flow directions from
- Modified grid

## Digital Elevation Models (DEMs) and Derivatives

- NOHRSC Data (CONUS by RFC)
- 15 arc-second DEM (resampled from 3 arc-second)
- RF1 (1:500,000 stream vectors)
- Customized algorithms used to blend DEM and streamline data
- Used in IHABBS, ThreshR, CAP, and to derive first-cut HL-RDHM connectivity files
- National Elevation Dataset (NED)
- 1 arc-second (30-m resolution)
- Used NSSL derivative products for selected study areas (e.g. DMIP)
- No correction with digitized streams or basin boundaries
- NHDPlus Project DEM Derivatives
- Multi-agency effort to develop attributes for National Hydrography Data set (NHD)
- Uses several algorithms to forces consistency between DEM derivatives, NHD, and that National Basin Boundary Dataset
- Not necessarily best algorithms to correct DEMs, but looks to be the most practical and best available product for basin and stream delineation

**Notes:**
Basin boundaries for lumped models
Flow directions for distributed models
Stream characteristics
(lengths, slopes, etc.)
Hillslope slopes

## Deriving Coarse Resolution (e.g. HRAP) Flow Directions from Higher Resolution DEMs

- HRAP grid

- Cells flow to the wrong basin

- Out-of-the-Box Steepest Descent Algorithm Works Well for High Resolution DEMs but not for HRAP resolution

- Cell outlet tracing with an area threshold (COTAT), Reed (2003)

- Using networks derived from high-resolution DEMs improves the results

## HRAP Cell-to-cell Connectivity Examples

- ABRFC ~33,000 cells

- MARFC ~14,000 cells

-  OHD delivers baseline HRAP resolution connectivity, channel slope, and hillslope slope grids for each CONUS RFC on the basis of higher resolution DEM data.

**Notes:**
Strategy – pre-derive separate complex pre-processing schemes from hydrologic simulation.  Simple framework.
Using the same resolution grid as the available rainfall grids makes sense.  

Would like to work from the most accurate DEM hydro derivatives available.  

## Distributed Model Resolution Impacts the Accuracy of Basin Representation

- 1

- 2

- 3

- Must choose this cell to get only subbasin 3, losing cells in the red box.

- 2 km resolution allows more accurate delineation of subbasin 3

- 1:  2258 km2
- 2:  619 km2
- 3:  365 km2

- HRAP

- 1⁄2 HRAP

## Drainage Area Delineation Accuracies 

- Drainage Area Delineation Accuracies

-   Open squares represent errors due to resolution only.
-   Black diamonds represent errors due to resolution and connectivity.
-   We correct for these errors by adjusting cell areas in HL-RDHM implementations.
-  Both higher resolution input DEMs and use of finer resolution distributed models (e.g. 1⁄2 HRAP) can be used to increase accuracy

- Delineated from an HRAP Network Derived from 400-m Flow Directions

- Delineated directly from DEM resolution

## Representative Slopes Are Extracted from Higher Resolution DEMS

- (North Fork of the American River (850 km2))

- Slopes from 30-m DEM

- Hillslope Slope (1/2 HRAP Resolution)
- Average = 0.15
*Slopes of all DEM cells within the HRAP pixel are averaged.*

- Main Channel Slope (1/2 HRAP Resolution)
- Average = 0.06
*Channel slopes are assigned based on a representative channel with the closest drainage area.*

- Local Channel Slope (1/2 HRAP Resolution)
- Average = 0.11

- Slope (m/m)

## Main Channel Slope vs. Local Channel Slope

- Slopes of each stream segment are calculated on the DEM grid

- (2)  Model pixel slopes are assigned from representative segments (DEM cell) that most closely match either the cell’s cumulative or local drainage area.

- Segment Slopes (m/m)

- Cell slope -> pixel-wise local slopec

- Cell slope -> pixel-wise main slopec

**Notes:**
Note that these algorithms are used to preprocess data delivered with HL-RDHM.  The algorithms themselves are not yet ‘delivered’ as either LAD or AWIPS partly because they rely on Arc/Info Grid software. 

## Calibration Assistance Program (CAP) 

- Avenue-based , requires ArcView 3.x with the Spatial Analyst 1.1
- V. 1.0, 2000 (Seann Reed, Ziya Zhang, David Wang)
- Initially intended to:
- simplify initial parameter estimation for lumped modeling (assumed non-expert GIS user)
- facilitate extensibility and creative exploration for GIS experts
- V. 1.1, 2002:  Added tools to automatically define MAPX areas for OFS based on zone or basin polygons (Lee Cajina)
- 2003 – 2007 no updates
- AWIPS migrates to Linux so future of ArcView 3.x applications is unclear
- V. 1.2, 2007:  Minor enhancements
- Updated cover data from NOHRSC (1996-2003)
- Two new grids to support the frozen ground model are now provided
- Scripts updated to support new grids
- Scripts modified to allow most functions to run properly on Windows XP operating system (not functions that interact with OFS, e.g. MAPX)
- All data in Albers Equal Area Projection (equal area projection makes it easier to compute zone and basin areas)

## CAP v. 1.2 Functionality 

- Derive area-elevation curves
- Export area-elevation to MCP input deck format
- Sub-divide basins into elevation zones
- Derive elevation-precipitation plots
- Compute **basin** or **zonal** mean, max, and min values of:
- precipitation (monthly, annual, and seasonal)
- potential evaporation (monthly, annual, and seasonal)
- potential evaporation adjustment factors
- percent forest
- percent of each forest type
- soil-based estimates for 11 SAC-SMA parameters
- Mean annual temperature (C) used in the frozen ground model (TBOT)
- Compute the dominant soil texture in a basin’s upper layer (STXT) used in the frozen ground model
- Display NOHRSC historical snow images from (1990-2003)
- Display basin boundaries and defined zones on top of other data layers (e.g. snow cover, SAC parameters, etc.)
- Derive/export geographic information required to run NWSRFS-MAPX routines (must run on HP)

## CAP Example Graphics

**Notes:**
Can think of enhancements – e.g. automatically generating snow cover percentages for each elevation zone

## Future of CAP?

- Needs
- Re-engineer CAP to move out of ArcView 3.x.
- Maintain original goals:  (1) friendliness for non-GIS experts,  (2) extensible for intermediate GIS users.
- Deliver refined a-priori parameter grids as they are developed (no problem)
- Deliver parameter estimation procedures via the new CAP (as opposed to delivering only pre-processed data)
- Many others . . .

**Notes:**
CAP requires full GIS capabilities.  These capabilities are not available in the current AWIPS environment (not met by XDMS, D2D, GFE).  Should the full GIS share a GUI environment with these ‘operational’ types of tools.  What is full GIS? Will there be full GIS capabilities in AWIPSII.  CAP is a model development tool.  It is required for successful operations but it is not an ‘operational’ tool that is used on an hour by hour, day by day basis.  This is probably the main reason that it has not gotten enough priority to obtain software engineering resources.   

## Future of CAP?

- Possible Development Paths
- Organize collaborative development project by hydrologists (‘local application’ in GRASS or ArcGIS?)
- PROS:  Less expensive, short wait, easily customizable to meet local needs
- CONS:  Requires field expertise and high level of coordination (from where?), risks lack of coordination and multiple versions, informal support
- Push for official AWIPS development project by software engineers
- PROS:  Would yield a more polished user friendly application, formal AWIPS support
- CONS:  Higher cost, longer wait, greater risk of no future enhancements if funds dry up, may be difficult to get a high enough priority to receive funding

**Notes:**
CAP requires full GIS capabilities.  These capabilities are not available in the current AWIPS environment (not met by XDMS, D2D, GFE).  Should the full GIS share a GUI environment with these ‘operational’ types of tools.  What is full GIS? Will there be full GIS capabilities in AWIPSII.  CAP is a model development tool.  It is required for successful operations but it is not an ‘operational’ tool that is used on an hour by hour, day by day basis.  This is probably the main reason that it has not gotten enough priority to obtain software engineering resources.   

##      A'B' > AB

- (Basis for the HRAP coordinate system used in NEXRAD processing and distributed hydrologic modeling)

-   Points are projected from the model earth to the image plane along a straight line drawn from the South Pole
-  The “secant” image plane intersects the earth at 60 N (the standard latitude, o)

- 

- B

- Image Plane

- A

- B

- A'

- B'

- A

-   Distances between points are elongated relative to true distances at latitudes below o but shortened at latitudes above o, e.g.:
-      A'B' > AB

- South Pole

- _Elevation View_

**Notes:**
Secant means a straight line cutting a curve at two or more points.

## Although not ideal for hydrologic modeling, we can readily adjust HRAP cell areas to represent the true area when converting runoff depths to flow volumes. 

- HRAP grid is specified in the image plane of the polar stereographic map projection:

- True Side Lengths and Areas for HRAP Cells at Different Latitudes

- Although not ideal for hydrologic modeling, we can readily adjust HRAP cell areas to represent the true area when converting runoff depths to flow volumes.

- Polar Stereographic to HRAP

## ESRI Polar Stereographic Projection Example

- _ESRI Polar Stereographic Projection Example_

- See also:  http://www.nws.noaa.gov/oh/hrl/distmodel/hrap.htm

- **TRICK:  Standard latitude is adjusted so that the HRAP earth radius of 6371.2 km can be used instead of the ESRI default 6370.997 km.  As of Arc/Info 7.2, ESRI did not support a user defined radius for this projection.

- _GRASS Input and Output Location Projections_

- name: Lat/Lon
- proj: ll
- ellps: sphere

- name: Stereographic
- proj: stere
- a: 1337.784777
- es: 0.0
- f: 0.0
- lat_0: 90.0000000000
- lat_ts: 60.0000000000
- lon_0: -105.0000000000
- k_0: 1.0000000000
- x_0: 401.0
- y_0: 1601.0

- Earth radius divided by 4762.5 (size of 1 HRAP cell)

**Notes:**
Standard latitude is adjusted so that the HRAP earth radius of 6371.2 km can be used instead of the ESRI default 6370.997 km.

## HL-RDHM XMRG Grids to GIS and Back

- ncols 1060
- nrows 821
- xllcorner -1905000.000000
- yllcorner -7620000.000000
- cellsize 4762.500000
- NODATA_value -1.000000

- ncols 1060
- nrows 821
- xllcorner 1.000000
- yllcorner 1.000000
- cellsize 1.000000
- NODATA_value -1.000000

- xmrgtoasc <infilename> <outfilename> <ster|HRAP>

- Header output with ‘ster’ option:

- Header output with ‘HRAP’ option:

- Arc/Info:  asciigrid/gridascii
- GRASS:  r.in.gdal/r.out.gdal

- asctoxmrg <infilename> <outfilename> <ster|HRAP>

- Go to _[http://www.weather.gov/ohd_files/project-hydrology/index.php](http://www.weather.gov/ohd_files/project-hydrology/index.php)_
- And click on ‘dhmworkshop’ link.

- 1

- 2

- 3

## Summary

- GIS data and tools provided valuable assistance in estimating hydrologic model parameters
- Because algorithms to derive apriori parameters are complex, work cannot be done with out-of-the-box GIS functions
- Recently, products delivered to the field from OHD are derived data set rather than data and software
- Reasons include
- algorithm complexity (no need for everyone to learn)
- lack of a common GIS platform
- limited resources
- Efforts to deliver data _and programs_ should be considered in the future (potential added value by field developers and possibility of using better local data sources)
- New CAP should be considered

**Notes:**
CAP requires full GIS capabilities.  These capabilities are not available in the current AWIPS environment (not met by XDMS, D2D, GFE).  Should the full GIS share a GUI environment with these ‘operational’ types of tools.  What is full GIS? Will there be full GIS capabilities in AWIPSII.  CAP is a model development tool.  It is required for successful operations but it is not an ‘operational’ tool that is used on an hour by hour, day by day basis.  This is probably the main reason that it has not gotten enough priority to obtain software engineering resources.   

## GIS-based Parameter Estimation for Lumped and Distributed Hydrologic Models

- Calibration Assistance Program (CAP) – Arcview 3.x

- Prototype Tools Available to RFCs

- Parameter Grids
- HRAP/XMRG

- ESRI Grids and
- Shapefiles

- Hydrology Laboratory Distributed Hydrologic Model
- (HL-RDHM)

- ThreshR – ArcView 3.x

- In-house Procedures

- Tools to derive A-priori Parameter Grids
- ArcView 3.1 w/ Spatial Analyst (HP-UX)
- Arc/Info 7.x (HP-UX)
- GRASS 6.2
- R Statistical Software
- FORTRAN/C/C++

- Derived Data
- Layers

- GRASS/ArcView/ArcInfo

- Asctoxmrg, xmrgtoasc

- Parameter Grids
- HRAP/ASCII

- Edit/display
- Grids

- ABRFC’s XDMS

**Notes:**
Main reason that we haven’t gotten into using ArcGIS 9.x is our desire to share data with non-GIS models that run on Linux and strict rules in our building about networking PC.  Also, since the AWIPS move away from Linux we have halted or slowed any development to 
Future:  
Re-engineer CAP to work under new AWIPS.
Integrate distributed modeling proprocessing tools into future CAP.