1 G.-Y. Niu, 1 Z.-L. Yang, 2 K. E. Mitchell, 3 F. Chen, 2 M. B. Ek, 3 M. 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 Noah Land Surface Model Development and Its Hydrological Simulations

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 A.lower boundary condition of weather and climate models B.upper boundary condition of hydrological models C.interface for coupled atmospheric/hydrological/ecological models 3. The Noah LSM is one of LSMs out of 100 existing models: A.Used in weather research and forecast model (WRF) by NCAR B.Used in weather and short-term climate prediction models (GFS, CFS, and Eta) by NCEP C.A long history development by NCEP, Oregon State Univ., Air Force, Hydrology Lab-NWS

New Developments by UT: Major Flaws of Noah LSM: 1.A combined layer of vegetation and soil. 2.A bulk layer of snow and soil. 3.A too-shallow soil layer (2 m). 4.The impeding effect of frozen soil on infiltration is too strong. 5.A serious cold bias (20K) during noon hours in Western US. New Developments: 1.A separated canopy layer 2.A modified two-stream radiation transfer scheme 3.A Ball-Berry type stomatal resistance scheme 4.A short-term dynamic vegetation model 5.A simple groundwater model 6.A TOPMODEL-based runoff scheme 7.A physically-based 3-L snow model 8.A more permeable frozen soil.

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

Recent Developments in Representing Runoff 1.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) 2.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) Saturation in zones of convergent topography

Relationship Between Saturated Area and Water Table Depth The saturated area showing expansion during a single rainstorm. [Dunne and Leopold, 1978] zwt f sat f sat = F (zwt, λ ) λ – wetness index derived from DEM

DEM – Digital Elevation Model ln(a) – contribution area ln(S) – local slope The higher the wetness index, the potentially wetter the pixel 1˚ x 1˚ Wetness Index: λ = ln(a/tanβ) = ln(a) – ln(S)

Surface Runoff Formulation and Derivation of Topographic Parameters 1˚ The Maximum Saturated Fraction of the Grid-Cell: F max = CDF { λ i > λ m } z m λ m Lowlandupland z i, λ i λ PDF λmλm F max CDF λ λmλm f sat = F max e – C (λi – λm)  f sat = F max e – C f zwt ( Niu et al )

A Simple TOPMODEL-Based Runoff Scheme (SIMTOP) Surface Runoff : R s = P F max e – C f zwt p = precipitation zwt = the depth to water table f = the runoff decay parameter that determines recession curve Subsurface Runoff : R sb = R sb,max e –f zwt R sb,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 -λ ). SIMTOP parameters: Two calibration parameters R sb,max (~10mm/day) and f (1.0~2.0) Two topographic parameters F max (~0.37) and C (~0.6) Niu et al. (2005) JGR

A Simple Groundwater Model (Niu et al., 2007, JGR) Water storage in an unconfined aquifer: Recharge Rate: Buffer Zone 2.0m Modified to consider macropore effects: C mic * ψ bot C mic  fraction of micropore content 0.0 – 1.0 (0.0 ~ free drainage)

Runoff Options: Options for runoff and groundwater: a)TOPMODEL with groundwater (Niu et al JGR) ; b)TOPMODEL with an equilibrium water table (Niu et al JGR) ; c)Original surface and subsurface runoff (free drainage) (Schaake et al, 1996) d)BATS surface and subsurface runoff (free drainage) (Yang and Dickinson, 1999)

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 | ( ) NEW | ( ) | GSWP | ( ) GRDC 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.

Evaluation of Runoff OLD – GRDC NEW – OLD NEW – GRDC

Evaluation of Runoff Seasonality

OLD NEW

Application to Texas rivers Micropore fraction: C mic = 0.6

Precipitation 13.5% of P Application to Texas rivers 79.4% of P

Summary Water balance (mm/year) (Guadalupe and San Antonio) P E R ΔS OBS 821 ? 111 ? Model1 (C mic =0.6) Model2 (C mic =0.0) Model3 (C mic =1.0) 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.