Hydrologic Modeling and DHSVM - PowerPoint PPT Presentation

Loading...

PPT – Hydrologic Modeling and DHSVM PowerPoint presentation | free to download - id: 13235c-YjY5Y



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Hydrologic Modeling and DHSVM

Description:

Distributed Hydrology-Soil-Vegetation Model (DHSVM) Water Balance Model Calibration ... adage: all models are wrong, but some are useful ... – PowerPoint PPT presentation

Number of Views:539
Avg rating:3.0/5.0
Slides: 37
Provided by: Peng89
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Hydrologic Modeling and DHSVM


1
Hydrologic Modeling and DHSVM
  • University of Washington
  • August 18, 2004
  • based on material from Colleen O. Doten and others

2
Outline
  • Hydrologic Modeling
  • Distributed Hydrology-Soil-Vegetation Model
    (DHSVM)
  • Water Balance Model Calibration
  • Sediment Transport Component

3
What do we need to characterize a river basin?
  • Topography
  • Soil
  • Vegetation
  • Routing

4
Topography
  • Radiation exposure of each watershed area
  • Runoff rates are influenced by slope
  • Spatial runoff patterns flow convergence and
    divergence

5
Soil Characteristics
  • Total moisture storage capacity of the watershed
  • Rate of movement of moisture from the hillside to
    the channel network
  • Moisture available to vegetation for transpiration

6
Vegetation Characteristics
  • Loss of moisture through evapotranspiration
  • Interception evaporation of precipitation
  • Shading and sheltering of underlying snow pack -
  • ROS events
  • Radiation-dominated melt

7
Routing
  • Controls movement of water from the hillslope to
    the channel and the basin mouth
  • Road networks in steep terrain remove water from
    the soil matrix to travel as concentrated flow

8
Outline
  • Hydrologic Modeling
  • Distributed Hydrology-Soil-Vegetation Model
    (DHSVM)
  • Water Balance Model Calibration
  • Sediment Transport Component

9
DHSVM model overview
  • What is DHSVM?
  • Distributed Hydrology-Soil-Vegetation Model
  • Simulated representation of the effects of
    topography, soil and vegetation on water fluxes
    throughout the landscape
  • Explicitly represents the spatial variation of
    topography, soil and vegetation over a grid mesh
    superimposed on a watershed

10
Typical Applications
  • Hydrological effects of vegetation change and
    forest roads in the PNW
  • Real-time streamflow forecasting
  • Required accuracy of digital elevation models
  • Energy balance dynamics in the boreal forest

11
General
  • Physically based hydrologic model
  • Grid-based (DEM)
  • Two layer canopy for vegetation
  • Simultaneously solves energy and water balance

12
DHSVM
Solving the water and energy balance
Water Balance
Energy Balance
P
13
Typical model set-up
  • Grid mesh resolution 10 m - 150 m
  • Time step hourly - 3 hourly
  • Basin size 5 - 10,000 km2

14
DHSVM
15
DHSVM SNOW MODEL
16
DHSVM runoff generation
17
Outline
  • Hydrologic Modeling
  • Distributed Hydrology-Soil-Vegetation Model
    (DHSVM)
  • Water Balance Model Calibration
  • Sediment Transport Component

18
Physical Models and Calibration
  • If DHSVM is a physical model, why calibrate?
  • Algorithms are approximations

19
Physical Models and Calibration
  • If DHSVM is a physical model, why calibrate?
  • Basin parameters are estimates

20
Physical Models and Calibration
  • If DHSVM is a physical model, why calibrate?
  • Forcings are uncertain
  • and a related issue
  • streamflow and other verification information is
    sparse -- or in worst case, lacking

21
Precipitation Observations
Precipitation (Daily) appears well defined,
generally since 1948
Station density within the continental U.S. 1
per 700 km2
22
Gridding Temperature and Precipitation Data
Precipitation and Temperature from gauge
observations gridded to 1/8o
Avg. Station density
  • Within the U.S.
  • Precipitation adjusted for time-of-observation
  • Precipitation re-scaled to match PRISM mean for
    1961-90

23
Derived Meteorological Variables
  • Certain meteorological variables not well
    observed
  • Use parameterizations to derive them from better
    know variables (Tmin, Tmax, P)
  • Humidity (Vapor Pressure)
  • MTCLIM - Tdew estimated from Tmin (with aridity
    index based on Pannual and Rsolar)
  • Downward Solar Radiation
  • transmissivity estimated from Tdew, Tmax Tmin
  • Downward Longwave Radiation
  • estimated from Taverage, humidity, atm.
    transmissivity
  • Wind
  • daily wind speed from NCEP/NCAR reanalysis

24
Evapotranspiration Observations
Ameriflux program (flux towers) provides some
direct measurements of E, since mid 1990s
Approximately Station Density (continental U.S.)
1 per 130,000 km2 Scattered Field Campaigns
provide some additional data
25
Snow Water Content Observations
  • About 600 SNOTEL sites in western US
  • Snow water content measured since 1977
  • Used in Water Supply Outlooks
  • Can be supplemented by satellite-derived products
    from NOHRSC, since 1990
  • Only snow areal extent
  • New instruments show better characterization

26
Soil Moisture Observations
Source A. Robock, Rutgers U.
  • Spatial coverage poor at continental scale
  • Only IL covers more than 10 years
  • Observational database is expanding

27
Runoff (Streamflow) Observations
  • Streamflow in the U.S. measured at roughly 7,000
    active gauging stations.
  • Stations can represent regulated flow conditions
  • Streamflow is a spatially integrated quantity

28
Physical Models and Cautious Optimism
  • With all the uncertainty and calibration, why
    should a model work at all?

Algorithms
DHSVM
Outputs
Forcings
Parameters
29
Typical Calibration Approach
  • generally, try to
  • leave forcings alone
  • leave best measured parameters alone
  • dont waste time calibrating insensitive
    parameters
  • work with a small number of sensitive,
    un-measured parameters, within plausible ranges
  • IDEALLY, optimize!
  • if this fails
  • revisit forcings
  • reconsider algorithms
  • if even this fails
  • reconsider model

30
Calibration Parameters SOIL
SOILS Soil
information Soil Map File Soil Depth File
pixel-varying depths Number of Soil Types
SOIL 1
Soil Description 1 SAND Lateral
Conductivity 1 0.01 Exponential Decrease 1
3.0 Maximum Infiltration 1 2.0e-4
Surface Albedo 1 0.1 Number of Soil
Layers 1 3 Porosity 1 .43 .43
.43 Pore Size Distribution 1 .24 .24
.24 Bubbling Pressure 1 .07 .07 .07 Field
Capacity 1 .08 .08 .08 Wilting Point 1
.03 .03 .03 Bulk Density 1 1492. 1492. 1492.
Vertical Conductivity 1 0.01 0.01 0.01 Thermal
Conductivity 1 7.114 6.923 6.923 Thermal
Capacity 1 1.4e6 1.4e6 1.4e6
31
Calibration Parameters VEG
  • Vegetation Description 17 Conif Forest
  • Overstory Present 17 TRUE
  • Understory Present 17 TRUE
  • Fractional Coverage 17 0.9
  • Trunk Space 17 .5
  • Aerodynamic Attenuation 17 2.0
  • Radiation Attenuation 17 0.15

Hemi Fract Coverage 17 Clumping Factor
17 Leaf Angle A 17 Leaf
Angle B 17 Scattering Parameter
17
Max Snow Int Capacity 17 0.040 Mass
Release Drip Ratio 17 0.4
Impervious Fraction 17 0.0 Snow
Interception Eff 17 0.6
Height 17 50.0 0.5
Maximum Resistance 17 5000.0 3000.0 Minimum
Resistance 17 666.6 200.0 Moisture
Threshold 17 0.33 0.13 Vapor
Pressure Deficit 17 4000 4000 Rpc
17 .108 .108 Number of Root
Zones 17 3 Root Zone Depths
17 0.10 0.25 0.40 Overstory Root Fraction
17 0.20 0.40 0.40 Understory Root Fraction
17 0.40 0.60 0.00 Overstory Monthly LAI
17 4.867 4.867 4.867 4.867 4.867 4.867 4.867
4.867 4.867 4.867 4.867 4.867 Understory Monthly
LAI 17 0.363 0.462 0.600 0.600 0.600 0.600
1.125 1.075 0.638 0.363 0.363 0.363 Overstory
Monthly Alb 17 0.2 0.2 0.2 0.2 0.2 0.2 0.2
0.2 0.2 0.2 0.2 0.2 Understory Monthly Alb 17
0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
for sample soil type 17 spatial veg type mapping
is also a parameter input
32
Calibration Parameters ROUTING
  • ROUTING Routing information. This section is
    only relevant if the Extent BASIN
  • STREAM NETWORK
  • The following three fields are only used if
    Flow Routing NETWORK
  • Stream Map File path for stream map file
  • Stream Network File path for stream
    network file
  • Stream Class File path for stream class file
  • ROAD NETWORK
  • The following three fields are only used if
    Flow Routing NETWORK and there is a road
    network
  • Road Map File path for road map file
  • Road Network File path for road network file
  • Road Class File path for road network file
  • UNIT HYDROGRAPH
  • The following two fields are only used if Flow
    Routing UNIT_HYDROGRAPH

not mentioned snow parameters
33
6 Sample Hydrographs (from VIC)
  • Good agreement of
  • Seasonal cycle
  • Low Flows
  • Peak Flows

34
Outline
  • Hydrologic Modeling
  • Distributed Hydrology-Soil-Vegetation Model
    (DHSVM)
  • Water Balance Model Calibration
  • Sediment Transport Component

35
Erosion and Sediment Transport Module
MASS WASTING
Soil Moisture Content
Sediment
Channel Flow
Sediment
DHSVM
CHANNEL ROUTING
Precipitation Leaf Drip Infiltration and
Saturation Excess Runoff
Erosion Deposition
HILLSLOPE EROSION
ROAD EROSION
36
Summary
  • Model results are only as good as the model
    inputs and algorithms
  • adage all models are wrong, but some are useful
  • DHSVM has proven useful for exploring the spatial
    and temporal variability of water and energy
    across a watershed
  • Colleen will show how this has been extended to
    support sediment budget analysis.
About PowerShow.com