# Presentation: 003650

## HL-RDHM, STAT_Q, XDMS  Overview and General Features

- Lecture 3

## Lecture/Workshop Approach

- Lectures 3, 4, and 5 are intended to provide scientific, and technical background and introduce the workshops
- Details not covered in lecture are covered in the HL-RDHM 2.0 User’s Manual and other documents
- Workshops are scripted to make sure the full range of software capabilities are described given the short time we have; once a script is completed, we encourage individual experimentation with any remaining time
- THIS IS THE FIRST TIME WE’VE GIVEN THIS COURSE!  WE DON’T KNOW HOW LONG THINGS WILL TAKE.  WE WILL TRY TO ADJUST TIMES AS NEEDED

**Notes:**
DHM Overview and details will be in lecture 5

## Outline

- What are HL-RDHM, DHM, XDMS, and STAT_Q?
- HL-RDHM Overview
- Using ICP Plot-TS, STAT_QME with HL-RDHM time series files
- STAT_Q Overview
- XDMS Overview (James Paul)
- DHM Overview will be given by Lee Cajina

**Notes:**
DHM Overview and details will be in lecture 5

## Acronyms and Features Evolution

- HL-RMS
- (Koren, 2004)

- HL-RDHM
- (Research model shared as AWIPS local application)

- DMS 1.0
- (ABRFC, WGRFC prototype)

- XDMS:  GUI for grid and time series display developed at ABRFC

- Stat_Q:  Stand-alone statistical analysis program developed at OHD for analyzing time series data in NWSRFS Calibration System DATACARD Format.

- DHM
- (AWIPS operational software)

*Research*
*Track*

*Operational *
*Track*

*Core Distributed Model*

*Complementary Programs*

**Notes:**
HL-RMS:  Hydrology Laboratory - Research Modeling System
HL-RDHM:  Hydrology Laboratory Research Distributed Hydrologic Model
DHM:  Distributed Modeling System
XDMS:  X – Distributed Modeling System

You will see that because of separate development paths for HL-RDHM, DHM, and XDMS, there are some details that are not smoothly integrated but there has been substantial collaboration and data can be shared by these programs.  Various workers have gone outside of their normal duties to make coordination on these applications happen. 

## Typical RFC Forecast Basin Modeling Procedure

- Simulation/Calibration Mode

- Forecast Mode

- Step

- Available Tool

- Calibrated scalars,
- Initial states

- HL-RDHM

- DHM

**Notes:**
We will run through all of these steps in the workshops for this course.

## HL-RDHM 2.0 Features

- Designed for river forecast, flash flood, and water resources research and development
- Supports gridded connected or unconnected domain runs
- Flexible I/O in standard NWS formats
- Common programming framework for researchers
- Facilitates rapid model testing
- Promotes good (modular) programming
- Multiple modeling resolutions
- Contains models for all hydrologic cycle components:  snow, rainfall/runoff, frozen ground, overland and channel routing
- Simulation/calibration mode exists.  Forecast mode planned for HL-RDHM 2.1.

**Notes:**
DHM Overview and details will be in lecture 5

## HL-RDHM Generic Computational Flow Chart

-   Researcher defines functions for 1-3 of the gray rectangles.  System handles many tedious I/O tasks.
-   HL-RDHM Developer’s Manual available for download on the LAD

**Notes:**
We do not have time to provide training for the model development features of HL-RDHM at this workshop; however, we do welcome collaborative R&D using HL-RDHM for those who wish to take their own initiative.  The HL-RDHM Developer’s Manual and source code is available on the LAD.  

## HL-RDHM 2.0 Available Operations

- Snow-17 (snow17)
- SAC-SMA-HT (sac, calsac*)
- Continuous API (api)
- Frozen ground (frz)
- Overland and channel routing (rutpix7,rutpix9,calrutpix7,calrutpix9)
- Automatic optimization (funcOpt)

- * Operations preceded by the ‘cal’ prefix are coded to improve performance over the non-’cal’ version.  These operations are particularly useful for automatic and manual calibration runs.  The non-‘cal’ versions have their own advantages (e.g. more output options and developer flexibility).  **Cal and non-cal operations cannot be mixed.  **

**Notes:**
With the calsac and calrutpix options you can only output grids of model parameters, precipitation, and discharge.

## Default Parameter Files Provided with HL-RDHM 2.0

- xxrfc4k.con:  ASCII connectivity files (one for each CONUS RFC)

- * Grid is a template and requires local customization.
- ** All grids cover CONUS with the exception of rutpix_SLOPH, rutpix_SLOPC, rutpix_SLOPC1, hrapfa10.xmrg, and hrapfd10.xmrg which are provided separately to each CONUS RFC

- hrapfa10.xmrg**:  flow accumulation grid for display in XDMS (not used by HL-RDHM)
- hrapfd10.xmrg**:  flow direction grid for display in XDMS (not used by HL-RDHM)

- XMRG file format

**Notes:**
Say how this data can be obtained from the NOAA1 Server

## Key Words

- Selected Key Words
- time-period
- time-step
- connectivity   (used for a connected domain)
- window-in-hrap   (used for an unconnected domain)
- subwindows
- output-path
- input-path
- ignore-1d-xmrg
- operations
- window-input
- input-data (specify parameters or scale factors for specific basins)
- mask (a grid defining an irregular domain boundary for unconnected calculations can be provided)

-   Key words are used to define a model run in the Input Deck (ASCII file)
-   User Manual Chapter 8 describes all key words and syntax specifics

## Outputs

- Output Key Words
-  output-grid-before-timeloop
-  output-grid-inside-timeloop
-  output-grid-after-timeloop
-  output-grid-step
-  output-grid-last-step
-  output-timeseries-basin-average
-  output-timeseries-basin-outlet

-   Can output grids or time series for any model states in selected operations (102 different states for all operations)
-   Can output grids for any parameters in selected operations (136 different parameters for all operations)

- Output Formats
-  Grids are output as XMRG-like binary files
-  Time series are output in NWSRFS Calibration System DATACARD format

-   XDMS displays these grids and time series
-   ICP displays these time series

**Notes:**
Note:  Most of these options are not available with the calsac and calrutpix operations.  

## Example HL-RDHM Input Deck

- #simulation time period
- time-period                          = 19951001T00 20060930T23
- #
- ignore-1d-xmrg = false
- #simulation time step in the format of HH:MM:SS.XXXX
- time-step                   =  1
- #the connectivity file
- connectivity = /fs/hsmb5/hydro/rms/sequence/abrfc_var_adj2.con
- #output path
- output-path        = /fs/hsmb5/hydro/dmip2/talo2/ws1a
- #input paths
- input-path         =  /fs/hsmb5/hydro/rms/parameterslx
- input-path         =  /fs/hsmb5/hydro/Hydro_Data/ABRFC/PRECIPITATION
- #selected operations
- operations = calsac calrutpix9
- #data to be output before, inside and after timeloop in grid format
- #In number of timestep, example, 2 means output every 2 timestep
- #output-grid-step                     = 1
- #output-grid-before-timeloop          = sac_LZFPM
- #data to be output at the last time step
- #output-grid-last-step                = uztwc uzfwc lztwc lzfsc lzfpc adimpc
- #output-grid-last-step                = real_uztwc real_uzfwc real_lztwc real_lzfsc
- #output-grid-inside-timeloop      = discharge surfaceFlow
- #Time series to be averaged over every basin
- #output-timeseries-basin-average      = xmrg
- #output-timeseries-basin-average       = surfaceFlow
- #Time series at the outlet
- output-timeseries-basin-outlet       = discharge

- #basin id and factors for input data
- # basin id followed by "name=value" pairs
- #------------------
- #----- TALO2 ------
- #------------------
- input-data = TALO2
- #SAC parameters
- input-data =      sac_PCTIM=0.005
- input-data =      sac_ADIMP=0.1
- input-data =      sac_RIVA=0.03
- input-data =      sac_EFC=0.5
- input-data =      sac_SIDE=0.0
- input-data =      sac_RSERV=0.3
- input-data =      sac_UZTWM=-0.5
- input-data =      sac_UZFWM=-0.80
- input-data =      sac_UZK=-0.7
- input-data =      sac_ZPERC=-3.49
- input-data =      sac_REXP=-0.74
- input-data =      sac_LZTWM=-0.82
- input-data =      sac_LZFSM=-1.24
- input-data =      sac_LZFPM=-2.1
- input-data =      sac_LZSK=-0.51
- input-data =      sac_LZPK=-0.45
- input-data =      sac_PFREE=-0.30
- input-data =      pe_JAN=0.9  pe_FEB=1.0  pe_MAR=1.70
- input-data =      pe_APR=2.7  pe_MAY=3.7  pe_JUN=5.2
- input-data =      pe_JUL=5.6   pe_AUG=5.3  pe_SEP=4.1
- input-data =      pe_OCT=2.4  pe_NOV=1.3  pe_DEC=1.0
- input-data =      peadj_JAN=1.0  peadj_FEB=1.0  peadj_MAR=1.0
- input-data =      peadj_APR=1.0  peadj_MAY=1.0 peadj_JUN=1.0
- input-data =      peadj_JUL=1.0   peadj_AUG=1.0  peadj_SEP=1.0
- input-data =      peadj_OCT=1.0  peadj_NOV=1.0  peadj_DEC=1.0
- #SAC states
- input-data =      uztwc=0.66      uzfwc=0.0    lztwc=0.69
- input-data =	  lzfsc=0.0      lzfpc=0.57    adimpc=0.69
- #rutpix parameters
- input-data =      rutpix_Q0CHN=-1.8 rutpix_QMCHN=-0.92
- #rutpix states
- input-data =      areac=5.0 depth=0.0

## Example ICP Input Deck to Display HL-RDHM time series

- TALO2 , analize results
-    10 1996   9  2006
- DEF-TS
- TALO2      QIN     1            INPUT
- ws1a/talo2.mod2
- TALO1      SQIN    1            INPUT
- ws1a/TALO2ap_discharge.outlet_ts
- TALO2      SQIN    1            INPUT
- ws1a/TALO2_discharge.outlet_ts
- TALO2      MAPX    1            INPUT
- ws1a/TALO2_xmrg.ave_ts
- TALO2      QME    24            INTERNAL
- TALO1      SQME   24            INTERNAL
- TALO2      SQME   24            INTERNAL
- END
- MEAN-Q      TALO1
-   TALO1    SQIN    1  TALO1    SQME   24
- MEAN-Q      TALO2
-   TALO2    SQIN    1  TALO2    SQME   24
- MEAN-Q      TALO2-OBS
-   TALO2    QIN     1  TALO2    QME    24
- PLOT-TS     TALO2
-           SCE  vs. RFC       3    2    4    0
-  ARIT   30       0.0      50.0    1
-   TALO2    MAPX    1         pcp            P
-  ARIT   30       0.0    1000.0    3
-   TALO2    QIN     1         USGS           o
-   TALO1    SQIN    1         u              u
-   TALO2    SQIN    1         c              c
- STAT-QME    TALO1
- Illinois - uncali         2483. TALO1    SQME   24  TALO2    QME    24 1
-       QUAR
- STAT-QME    TALO2
- Illinois - calib          2483. TALO2    SQME   24  TALO2    QME    24 1
-       QUAR
- STOP

## Stat_q

- Statistical analysis of any two time series in single column NWSRFS Calibration Data Card format
- Similar to STAT_QME but with many more options
- Flexible analysis time step (hourly – 24 hourly)
- Yearly, monthly statistical summaries
- Flow interval statistics
- Event statistics for user defined events

## GIS Import/Export Tools

- Utilities will be made available to export grids or import grids in ESRI gridascii format.  Format can also be easily imported to GRASS software.
- xmrg2asc
- asc2xmrg

**Notes:**
If you want to know more about GIS related tools, talk to someone from your office who is participating in the GIS workshop being held this year in Wilmington, Ohio.

## Workshops Overview

- Workshop 1:  Become familiar with HL-RDHM, XDMS, ICP, and STAT-Q.  Step through some examples to demonstrate basic HL-RDHM simulation mode features, use of XDMS to examine spatial output, and use ICP and STAT-Q to examine time series outputs.
- Workshop 2:  Step through procedures for local routing parameter customization (HL-RDHM User’s Manual Chapter 9)
- Workshop 3:  Run through a simple automatic calibration exercise.  Examine hydrograph results in ICP before and after calibration.  Manually examine the impacts of parameter scalar changes for both rainfall-runoff and routing.
- Workshop 4:  Setup and run DHM through IFP.
- Workshop 5:  Demonstrate an uncalibrated run over a large area.  Revisit any questions from earlier workshops.  Continue Workshop 4 if necessary.

- Workshops assume some basic knowledge of existing RFC software applications such as IFP and ICP.  Therefore let’s try to put at least one experienced RFC person in each group.

## Workshops Overview

- Workshop exercises will focus on the ABRFC domain with most specific examples coming from the Illinois River above Tahlequah (TALO2) and two subbasins (The Illinois R. at Kansas (KNSO2) and the Illinois R. at Watts (WTTO2))

- ABRFC

**TALO2**

**WTTO2**

**KNSO2**