C:\ Program Files\ CRHM\
QdroD
QdfoD
Qdro
Qdfo
SunMax
global
CalcHr
Qsi
calcsun
hru_t
hru_rh
hru ea
hru_ea
hru_u
hru_p
hru_rain
hru_snow
hru_SunAct
hru_tmax
hru_tmin
hru_tmean
hru_eamean
hru_umean
hru_rhmean
hru_newsnow
t
rh
ea
u
p
ppt
Qsi
Qso
Qn
Qln
SunAct
form_data
obs
net_rain
net_snow
intc p_evap
intc p
net
cum_net
netall
Rn
Qg
Qs
net_rn
hru_ev ap
transp_on
evap
The Cold Regions
g
Hydrological
y
g
Model: A Simulation Platform for
Physically Based Hydrology
pb
Objective
To develop a hydrological cycle simulation system
that:
„
is distributed such that the water balance for
selected surface areas can be computed;
„
iis sensitive
iti to
t the
th impacts
i
t off land
l d use and
d climate
li t
change;
„
does not require the presence of a stream in each
land unit;
„
is flexible: can be compiled in various forms for
specific
ifi needs;
d
„
is suitable for testing individual process algorithms.
„
DOES NOT REQUIRE CALIBRATION!
H d l i lR
Hydrological
Response U
Units
it
Sequential HRU –
landscape connectivity
HRU 1
HRU 2
HRU 3
outlfow
Grouped HRU – must drain to stream
Building
g Physically-based,
y
y
Distributed Hydrological Models
„
A HRU has 3 groups of attributes
„ biophysical structure - soils, vegetation, slope,
elevation area
elevation,
„ hydrological state – snow water equivalent,
snow internal energy, intercepted snow load,
soil
il moisture,
i t
water
t ttable
bl
„ hydrological flux - snow transport, sublimation,
p
, melt discharge,
g , infiltration,,
evaporation,
drainage, runoff
Building
g Physically-based,
y
y
Distributed Hydrological Models
Cold Regions Hydrological Model
„ uses a library of physically-based hydrological
and energy balance process modules;
„ handles the following aspects of the modelling
process:
„ data pre-processing,
„ module and model building,
„ results analysis
„ is easy to use: employs a Windows
environment with p
pull-down menus.
Cold Regions
g
Hydrological
y
g
Model
DATA COMPONENT
Preparation of spatial and meteorological data.
„
„
„
„
Spatial
p
data ((e.g.
g basin area,, elevation,, cover type)
yp ) is
analyzed using a Geographic Information System (GIS)
interface that assists the user in basin delineation,
characterization and parameterization of Hydrological
Response Units (HRU).
(HRU)
Time-series meteorological data include air
temperature, humidity, wind speed, precipitation and
radiation.
Adjustments for elevation (lapse rate), snowfall versus
rainfall, interpolation between input observations
(
(stations)
)
Unit conversions to consistent SI units
Cold Regions Hydrological Model
MODEL COMPONENT
„
Utilizes Windows-based series of pull-down menus
li k d to
linked
t the
th system
t
features.
f t
„
Modules, or process algorithms, are selected from the
library and grouped together by the CRHM processor.
„
Modules have a set order of execution with a common
set of variables and parameters.
„
Modules are created in C++ programming language.
„
Macro modules can be created from within the model
using a simple macro language.
language
Groups and Structures to Adapt to Real
B i H
Basin
Hydrology
d l
„
Group. A collection of modules executed in
sequence for all HRUs.
HRUs
„
„
„
„
collection of modules which can be used in place of specifying
the individual modules.
if g
groups
p are defined with same modules,, then can execute
modules in parallel using different parameters or driving
observations.
If groups are defined as different ‘models’, it is possible to
execute the models in parallel using identical parameters and
driving observations to check different responses.
Structure. A parallel collection of modules or Group
assigned
g
to an HRU and run in sequence.
q
„
„
„
Comparison of algorithms
Customization of model to HRU characteristics - diverse sets
modules to be representative of the HRU and basin.
D namic structural
Dynamic
str ct ral change due
d e to e
excess
cess water
ater or lack of itit.
Groups
„
A collection of modules executed in sequence for all HRUs.
module
Define group:
Model
incorporation:
module
module
Group
Group ‘A’
Module n
Module i
Group ‘B’
B’
Groups
Group application:
1. If groups are defined with the same modules, it
is possible to execute the models in parallel using
different parameters or driving observations.
2. If groups are defined as different modules, it is
possible to execute the models in parallel using
id ti l parameters
identical
t
and
d driving
d i i observations
b
ti
to
t
check different responses.
Groups
„
E.g. estimate subsub-canopy SWE for forests of
differing leafleaf-area
area--index
Structures
„
Running
g similar modules in p
parallel
e.g. snowmelt
observation
ebsm
output
snobal
output
msm
output
t t
Structures
Structure application
pp
:
1. Algorithm comparison. Intercomparison of algorithms
with similar driving data and parameters
2. Mixed Land Use in Basin. Permits differing model
structure for differing HRU (e.g. forest versus farmland
3. Dynamical Structural Change. Permits change in model
structure in response to changing hydrological state (e.g.
change grassland to a slough when leaving a
drought). The decision about which module to use would
be made by a preceding module based upon the availability
of moisture
moisture.
Cold Regions Hydrological Model
ANALYSIS COMPONENT
„
Used to display, analyze and export results (Excel,
ASCII).
)
„
Statistical and graphical tools are used to analyze model
performance, allowing for decisions to be made on the
b t modelling
best
d lli
approach.
h
„
Sensitivity-analysis tools are provided to optimize
selected model p
parameters and evaluate the effects of
model parameters on simulation results.
„
Mapping tools use ArcGIS files to map ouputs for
geographical visualization.
visualization
CRHM Module Development
DATA
ASSIMILATION
„
„
Data from multiple sites
Interpolation to the HRUs
PROCESSES
„
„
SPATIAL
PARAMETERS
„
Basin and HRU parameters
are set. (area, latitude,
elevation, ground slope,
aspect)
„
„
„
„
„
„
„
„
„
Infiltration into soils (frozen
and unfrozen)
Snowmelt (prairie & forest)
Radiation – level, slopes
Evapotranspiration
Snow transport
Interception (snow & rain)
S
Sublimation
(dynamic
(
& static))
Soil moisture balance
Sub-surface runoff
Routing (hillslope & channel)
Advection
2007 Modules
„
Snobal-- layered physically based snow energy balance
Snobal
model ((Marks et al. 1998)) – unique
q linkage
g to PBSM
„
Trees-- new forest energy and mass balance module.
Trees
Short and longwave radiation transfer
„ Snow interception, sublimation, unloading
„ Rainfall interception,
p
, drip,
p, evaporation
p
„ Sub
Sub--canopy turbulent transfer parameterisation
Wamsley WindWind- wind speed correction for topography
Evap - greater variety of evaporation models. Penman
Penman-Monteith,, Bulk Transfer
Monteith
„
„
„
Trees
ees
Basic model schematic
Effect of forest cover on snow accumulation and melt
SnowMIP2 runs: Alptal, Switzerland:
2002--03
2002
open site
forest site
2003--04
2003
CRHM Test - Yukon
Modular structure
HRU based
INF = 5 ⋅ (1 − θp ) ⋅ SWE 0.584
INF = C ⋅ S
2.92
0
⋅ (1 − S I )
1.64
⎛ 273.15 − TI ⎞
⋅⎜
⎟
⎝ 273.15 ⎠
−0.45
⋅ t0
0.44
M d lli A
Modelling
Approach
h
Aggregated vs. Distributed
Basin Areal SWE
NF, SF, and VB
2002
2003
180
250
160
Obs SWE
Aggregated
Distributed
120
200
SWE
E [mm]
SWE
E [mm]
140
100
80
Obs SWE
Aggregated
Distributed
150
100
60
40
50
20
0
4/17/02 4/24/02
0
5/1/02
5/8/02
5/15/02 5/22/02 5/29/02
Time [days]
6/5/02
4/17/03
4/26/03
5/05/03
5/14/03
Time [days]
5/23/03
6/01/03
Basin discharge
2002
2003
1.0
Obs
Aggregated
Distributed
0.4
Q [m3/s]
Q [m3/s]
0.8
0.5
0.6
04
0.4
Obs
Aggregated
Distributed
0.3
02
0.2
0.2
0.1
0.0
5/01/02 5/09/02 5/17/02 5/25/02 6/02/02 6/10/02
0.0
4/17/03 4/26/03 5/05/03 5/14/03 5/23/03 6/01/03
Time [days]
Time [days]
Conclusions
„
„
„
„
„
Process algorithms can form the basis for physicallybased hydrological model structure and parameter
selection
Flexible model structure and physically based
components
t can lead
l d tto appropriate
i t and
d robust
b t
hydrological simulation
Errors in simulation identifyy g
gaps
p in understanding
g of
processes, structure or parameters
A process based modular model is able to simulate key
components of the cold regions hydrological cycle from
an understanding of principles, and without calibration of
parameters except for routing
Modular models are relatively simple to update as our
science advances.