1G.-Y. Niu, 1Z.-L. Yang, 2K. E. Mitchell, 3F. Chen, 2M. B. Ek, 3M. Barlage, et al.

1
Noah Land Surface Model Development and Its
Hydrological Simulations
1G.-Y. Niu, 1Z.-L. Yang, 2K. E. Mitchell, 3F.
Chen, 2M. B. Ek, 3M. Barlage, et al. 1 DGS,
The University of Texas at Austin, Austin 2 NCEP,
NOAA-NWS, Camp Springs, Maryland 3 RAL, NCAR,
Boulder, Colorado and others
2
The Noah Land Surface Model

• 1. A land surface model numerically describes
• heat, water, carbon, etc. stored in vegetation,
  snow, soil, and aquifer and their associated
  fluxes to the atmosphere.
• 2. A land surface model serves as
• lower boundary condition of weather and climate
  models
• upper boundary condition of hydrological models
• interface for coupled atmospheric/hydrological/eco
  logical models
• 3. The Noah LSM is one of LSMs out of 100
  existing models
• Used in weather research and forecast model (WRF)
  by NCAR
• Used in weather and short-term climate prediction
  models (GFS, CFS, and Eta) by NCEP
• A long history development by NCEP, Oregon State
  Univ., Air Force, Hydrology Lab-NWS

3
New Developments by UT

• Major Flaws of Noah LSM
• A combined layer of vegetation and soil.
• A bulk layer of snow and soil.
• A too-shallow soil layer (2 m).
• The impeding effect of frozen soil on
  infiltration is too strong.
• A serious cold bias (20K) during noon hours in
  Western US.
• New Developments
• A separated canopy layer
• A modified two-stream radiation transfer scheme
• A Ball-Berry type stomatal resistance scheme
• A short-term dynamic vegetation model
• A simple groundwater model
• A TOPMODEL-based runoff scheme
• A physically-based 3-L snow model
• A more permeable frozen soil.

4
History of Representing Runoff in Atmospheric
models
Bucket or Leaky Bucket Models 1960s-1970s (Manabe
1969)
Soil Vegetation Atmosphere Transfer Schemes
(SVATs) 1980s-1990s (BATS and SiB)
150mm
100km
5
Recent Developments in Representing Runoff

• Representing topographic effects on subgrid
  distribution of soil moisture and its impacts on
  runoff generation
• (Famiglietti and Wood, 1994 Stieglitz et
  al. 1997 Koster et al. 2000 Chen and Kumar,
  2002 Niu et al., 2005)
• Representing groundwater and its impacts on
  runoff generation, soil moisture, and ET
• (Liang et al., 2003 Maxwell and Miller,
  2004 Niu et al., 2007 Fan et al., 2007)

6
Relationship Between Saturated Area and Water
Table Depth
The saturated area showing expansion during a
single rainstorm. Dunne and Leopold, 1978
zwt
fsat F (zwt, ?)
fsat
? wetness index derived from DEM
7
Wetness Index ? ln(a/tanß) ln(a) ln(S)

The higher the wetness index, the potentially
wetter the pixel
8
Surface Runoff Formulation and Derivation of
Topographic Parameters
Lowland
upland
zm ?m
The Maximum Saturated Fraction of the Grid-Cell
Fmax CDF ?i gt ?m
fsat Fmaxe C (?i ?m) ? fsat Fmaxe
C f zwt (Niu et al. 2005)
9
A Simple TOPMODEL-Based Runoff Scheme (SIMTOP)
Surface Runoff Rs P Fmax e C f zwt p
precipitation zwt the depth to water table f
the runoff decay parameter that determines
recession curve Subsurface Runoff Rsb
Rsb,maxe f zwt Rsb,max the maximum subsurface
runoff when the grid-mean water table is zero. It
should be related to lateral hydraulic
conductivity of an aquifer and local slopes (e-?)
. SIMTOP parameters Two calibration
parameters Rsb,max (10mm/day) and f (1.02.0)
Two topographic parameters Fmax (0.37) and C
(0.6) Niu et al. (2005) JGR
10
A Simple Groundwater Model (Niu et al., 2007, JGR)
Water storage in an unconfined aquifer
Recharge Rate
2.0m
Buffer Zone
Modified to consider macropore effects Cmic
?bot Cmic ? fraction of micropore content
0.0 1.0 (0.0
free drainage)
11
Runoff Options

• Options for runoff and groundwater
• TOPMODEL with groundwater (Niu et al. 2007 JGR)
• TOPMODEL with an equilibrium water table (Niu et
  al. 2005 JGR)
• Original surface and subsurface runoff (free
  drainage) (Schaake et al, 1996)
• BATS surface and subsurface runoff (free
  drainage) (Yang and Dickinson, 1999)

12
Global Energy and Water balance
Global land (60S-90N) 10-year mean energy (W/m2)
and water fluxes (mm/year) ----------------------
--------------------------------------------------
---- SWnet LWnet Rnet SH
LH P ET R (Rs Rb)
------------------------------------------------
--------------------------- OLD 133
-65 68 37 30 769 376 388 (84
305) NEW 137 -64 73 37
34 769 430 339 (91 248) -------------------
-------------------------------------------------
------- GSWP2 142 -68 74 35
37 827 471 322 (119 203)
-------------------------------------------------
--------------------------- GRDC

280 ----------------------------------------------
------------------------------ GSWP2 (Global Soil
Wetness Project Phase 2) 12 model
averages. Noah-V3 produces too much
runoff. Noah_UT is comparable to 12 model
average, 21 greater than GRDC runoff estimates.
13
Evaluation of Runoff
OLD GRDC
NEW OLD
NEW GRDC
14
Evaluation of Runoff Seasonality
15
Evaluation of Runoff Seasonality
OLD
NEW
16
Application to Texas rivers
Micropore fraction Cmic 0.6
17
Application to Texas rivers
Precipitation
79.4 of P
13.5 of P
18
Summary
Water balance (mm/year) (Guadalupe and San
Antonio) P
E R ?S --------------------------------
--------------------- OBS 821
? 111 ? Model1 (Cmic0.6) 821
652 111 58 Model2 (Cmic0.0) 821
606 168 47 Model3 (Cmic1.0) 821
668 91 62 ------------------------------
----------------------- Each model run span up
for two times.

• 1. Noah_UT version produces about 20 more runoff
  globally.
• 2. Runoff is only 13.5 of precipitation in the
  Guadalupe and San Antonio river basins. ET is the
  largest portion to balance precipitation.
• 3. We should first deal with ET and calibrate
  ET-related parameters.