Application of DHSVM to Hydrologically Application of DHSVM to Hydrologically Complex Regions as Part of Phase 2 of the Complex Regions as Part of Phase 2 of the Distributed Model Intercomparison Project Distributed Model Intercomparison Project

Erin RogersErin Rogers

Dennis LettenmaierDennis Lettenmaier

Jessica LundquistJessica Lundquist

OutlineOutline

Project Overview and ContextProject Overview and Context NOAA’s NWS Distributed Model Intercomparison NOAA’s NWS Distributed Model Intercomparison

Project (DMIP) Project (DMIP)

NOAA’s ESRL Hydrometeorological Testbed program NOAA’s ESRL Hydrometeorological Testbed program

(HMT)(HMT)

The American River Basin and DHSVMThe American River Basin and DHSVM

Current Research StatusCurrent Research Status

Future WorkFuture Work

Distributed Model Intercomparison ProjectDistributed Model Intercomparison Project

Designed to help NWS make decisions about Designed to help NWS make decisions about

operational forecasting models- specifically operational forecasting models- specifically

moving from lumped to distributed modelsmoving from lumped to distributed models

Goal is to determine if distributed models Goal is to determine if distributed models

perform as well as lumped models at basin perform as well as lumped models at basin

outlets and if they have the ability to model basin outlets and if they have the ability to model basin

interior points accuratelyinterior points accurately

DMIP FormatDMIP Format

NWS picks basins and sets forth simulation NWS picks basins and sets forth simulation

requirementsrequirements

NWS makes input and forcing data availableNWS makes input and forcing data available

Participants are given a due date for submitting required Participants are given a due date for submitting required

simulationssimulations

NWS compiles and analyzes simulation resultsNWS compiles and analyzes simulation results

DMIP 2DMIP 2

American and Carson River BasinsAmerican and Carson River Basins

Hydrometeorological Testbed Program Hydrometeorological Testbed Program

Regional demonstration Regional demonstration

program focused on program focused on

improving precipitation improving precipitation

forecastingforecasting

Evaluating current Evaluating current

observational tools wrt observational tools wrt

spatial and temporal spatial and temporal

distribution of precipitationdistribution of precipitation

HMTHMT

Dense network Dense network

fixed and mobile fixed and mobile

advanced sensors advanced sensors

AR Basin 1st full AR Basin 1st full

scale deployment scale deployment

Expected to run Expected to run

from 2006-2011from 2006-2011

PRE-HMT CoveragePRE-HMT Coverage

PPrecip StationPrecip Station

Snow Station

HMT Instrumentation – Radar Locations HMT Instrumentation – Radar Locations (Polarimetric and Doppler)(Polarimetric and Doppler)

HMT Instrumentation – Rain Disdrometers HMT Instrumentation – Rain Disdrometers

HMT Instrumentation - 2875 MHz Precip HMT Instrumentation - 2875 MHz Precip ProfilersProfilers

HMT Instrumentation – Soil Moisture and HMT Instrumentation – Soil Moisture and Temperature ProbesTemperature Probes

HMT Instrumentation – Water Vapor SensorsHMT Instrumentation – Water Vapor Sensors

HMT Instrumentation – Surface Met StationsHMT Instrumentation – Surface Met Stations

HMT Instrumentation – Stream Level LoggersHMT Instrumentation – Stream Level Loggers

HMT Instrumentation - AllHMT Instrumentation - All

Pre/Post HMT InstrumentationPre/Post HMT Instrumentation

American River BasinAmerican River Basin

Critical resource for CA’s economyCritical resource for CA’s economy Water resources managementWater resources management

Hydroelectric power generationHydroelectric power generation

FisheriesFisheries

Prone to flooding due to heavy winter precipitation from Prone to flooding due to heavy winter precipitation from

‘atmospheric rivers’ originating in the tropical pacific‘atmospheric rivers’ originating in the tropical pacific

Heavily populated downstream areaHeavily populated downstream area

Basin Characteristics - ClimateBasin Characteristics - Climate

Hydrology Rain and Snow Hydrology Rain and Snow

DrivenDriven

Mean Annual Temp RangeMean Annual Temp Range

Low: -1 to 2 CLow: -1 to 2 C

High: 26 to 34 CHigh: 26 to 34 C

Mean Annual PE RangeMean Annual PE Range

~1030 mm to 1210 mm~1030 mm to 1210 mm

Basin Characteristics – DEMBasin Characteristics – DEM

Area:Area:

866 km2866 km2

Elevation Range:Elevation Range:

200-2600 m200-2600 m

Median Elevation:Median Elevation:

1270 m1270 m

Basin Characteristics - PrecipitationBasin Characteristics - Precipitation

Precipitation dominatedPrecipitation dominated

by orographic effectsby orographic effects

Mean Annual Precip:Mean Annual Precip:

813 mm (393 m elev)813 mm (393 m elev)

1651 mm (1676 m elev)1651 mm (1676 m elev)

Basin Characteristics - VegetationBasin Characteristics - Vegetation

Heavily forested basinHeavily forested basin

75-85% coverage75-85% coverage

Vegetation TypesVegetation Types

Douglas Fir Douglas Fir

Ponderosa PinePonderosa Pine

Lodgepole Pine Lodgepole Pine

Fir-SpruceFir-Spruce

Western HardwoodsWestern Hardwoods

Shrub rangelandShrub rangeland

Forest Type

Forest Percent

Basin Characteristics - GeologyBasin Characteristics - Geology

Metasedimentary rock and Metasedimentary rock and granitegranite

Shallow soils with areas of Shallow soils with areas of exposed rockexposed rock

Soils are clay loams and Soils are clay loams and coarse sandy loamscoarse sandy loams

Depth ranges from 0-2.5 mDepth ranges from 0-2.5 m

Impoundments and DiversionsImpoundments and Diversions

Basin Characteristics - Road DensityBasin Characteristics - Road Density

Pink Pink

>> 2 km/km 2 km/km22

YellowYellow

0.9 – 2.0 km/km0.9 – 2.0 km/km22

BlueBlue

0 – 0.9 km/km0 – 0.9 km/km22

Basin Characteristics - Road SystemBasin Characteristics - Road System

DHSVMDHSVM

Has successfully been Has successfully been

applied to similar applied to similar

watersheds watersheds

Has limited ability to Has limited ability to

model standing watermodel standing water

Baseflow is expected to Baseflow is expected to

be a small componentbe a small component

Current Research Status Current Research Status

No NOAA data yetNo NOAA data yet

Initially forcing with Alan’s Initially forcing with Alan’s

data set (5 stations)data set (5 stations)

Run DHSVM at 90m Run DHSVM at 90m

resolutionresolution

Soils data from SSURGO Soils data from SSURGO

soil surveysoil survey

Veg data from EPAVeg data from EPA

No roadsNo roads

Gridded Data LocationsGridded Data Locations

Future WorkFuture Work

Relating point to gridded data: compare Alan’s Relating point to gridded data: compare Alan’s data set with local station data, adjust if data set with local station data, adjust if necessarynecessary

Calibrate DHSVM with gridded forcing dataCalibrate DHSVM with gridded forcing data Model other basins in DMIP2Model other basins in DMIP2

CarsonCarson BlueBlue ElkElk IllinoisIllinois

Questions?Questions?

DMIP Phase 1 Simulation RequirementsDMIP Phase 1 Simulation Requirements

Hydrographs generated using Hydrographs generated using NEXRAD as ppt forcing NEXRAD as ppt forcing

Calibrated and uncalibrated Calibrated and uncalibrated sims requiredsims required

‘‘Blind’ simulation at prescribed Blind’ simulation at prescribed interior sub-basin pointsinterior sub-basin points

Simulations in continuous Simulations in continuous retrospective moderetrospective mode

HL conducted an analysis of HL conducted an analysis of all simulations vs observed all simulations vs observed data as well as SAC-SMA data as well as SAC-SMA simulationssimulations

Interior PointUSGS Gage

DMIP Phase 1DMIP Phase 1

DMIP1 ran from 2000-2002 DMIP1 ran from 2000-2002

Conducted in several Conducted in several

basins in the southern basins in the southern

great plainsgreat plains

Hydrologically simple, but Hydrologically simple, but

prone to flash floodingprone to flash flooding

Blue River

Illinois River

Elk River

DMIP2 Science Questions DMIP2 Science Questions

1.1. Can Distributed Models provide increased simulation accuracy compared to Can Distributed Models provide increased simulation accuracy compared to lumped models? Are improvements constrained by forcing data quality? lumped models? Are improvements constrained by forcing data quality?

2.2. What simulation improvements can be realized through the use of re-analysis What simulation improvements can be realized through the use of re-analysis forcing data? Can using the Multi-sensor precipitation estimation algorithm to forcing data? Can using the Multi-sensor precipitation estimation algorithm to process the raw NEXRAD data lead to improved simulations?process the raw NEXRAD data lead to improved simulations?

3.3. What is the performance of distributed models if they are calibrated with observed What is the performance of distributed models if they are calibrated with observed precipitation data but use forecasts of precipitation? How far out into the future can precipitation data but use forecasts of precipitation? How far out into the future can distributed models provide better forecasts than currently used lumped models?distributed models provide better forecasts than currently used lumped models?

4.4. Can distributed models reasonably predict processes such as runoff generation Can distributed models reasonably predict processes such as runoff generation and soil moisture re-distribution at interior locations? At what scale can we validate and soil moisture re-distribution at interior locations? At what scale can we validate soil moisture models given current models and sensor networks?soil moisture models given current models and sensor networks?

DMIP2 Science QuestionsDMIP2 Science Questions

5.5. In what ways do routing schemes contribute to the simulation success of In what ways do routing schemes contribute to the simulation success of distributed models? distributed models?

6.6. At what river forecast points can we expect distributed models to effectively At what river forecast points can we expect distributed models to effectively capture spatial variability so as to provide better simulations and forecasts? capture spatial variability so as to provide better simulations and forecasts?

7.7. What is the potential for distributed models set up for basin outlet simulations to What is the potential for distributed models set up for basin outlet simulations to generate meaningful hydrographs at interior locations for flash flood forecasting? generate meaningful hydrographs at interior locations for flash flood forecasting?

8.8. What are the advantages and disadvantages associated with distributed modeling What are the advantages and disadvantages associated with distributed modeling (versus lumped) in hydrologically complex areas using existing model forcings? (versus lumped) in hydrologically complex areas using existing model forcings?

DMIP2 Science QuestionsDMIP2 Science Questions

9.9. Is there a dominant constraint that limits the performance of hydrologic simulation Is there a dominant constraint that limits the performance of hydrologic simulation

and forecasting in mountainous areas? If so, is it the quality and/or amount of and forecasting in mountainous areas? If so, is it the quality and/or amount of

forcing data or is the constraint related to a knowledge gap in our understanding forcing data or is the constraint related to a knowledge gap in our understanding

of the hydrologic processes in these areas? of the hydrologic processes in these areas?

10.10. Can improvements to rain-snow partitioning be made? Can advanced sensors Can improvements to rain-snow partitioning be made? Can advanced sensors

planned for implementation in the American River lead to improved simulations planned for implementation in the American River lead to improved simulations

and forecasts? and forecasts?

11.11. What are the dominant scales (if any) in mountainous area hydrology? What are the dominant scales (if any) in mountainous area hydrology?

OK Mesonet StationsOK Mesonet Stations