Zong-Liang Yang Guo-Yue Niu Robert E. Dickinson The University of Texas at Austin

1. Modeling Surface and Subsurface Runoff in CLM Zong-Liang Yang Guo-Yue Niu Robert E. Dickinson The University of Texas at Austin Prepared for Land Model Working Group Meeting, March 14, 2005 Funded under NASA grant NAG5-12577

2. Outline • Introduction • Current treatment of runoff in CLM and problems • Saturation area • Surface runoff • Ksat, macropores and anisotropic factor • Subsurface runoff • Constant versus exponential Ksat • Continental-scale simulations • Water table • Regional-scale simulations • Comparison with observations • Sensitivity to parameters • f • Rsub,max

3. Outline • Introduction • Current treatment of runoff in CLM and problems • Saturation area • Surface runoff • Ksat, macropores and anisotropic factor • Subsurface runoff • Constant versus exponential Ksat • Continental-scale simulations • Water table • Regional-scale simulations • Comparison with observations • Sensitivity to parameters • f • Rsub,max

4. Performance of Baseline CLM (1) Daily runoff (Sleepers River Catchment, Vermont, USA): • Negative modeling efficiency because of large spikes • Surface runoff (fast component) too high Soil moisture (Sleepers River Catchment): • Too low • Odd profile (9th layer driest)

5. Performance of Baseline CLM (2) Monthly runoff (GSWP2 Project): • Overestimated • Surface runoff (fast component) too high • Surface runoff is 80% of total runoff.

6. Parameterization of Runoff in Baseline CLM Guided by four considerations: • TOPMODEL: topographic control on the growth and decay of saturated area and groundwater flow • 1-D 10-layer soil structure: • Topographic data availability: a simple determination of the saturated area, allowing room for improvement when the topographic parameters are available globally. • BATS: success in PILPS experiments, esp. PILPS 1c (The Red-Arkansas River Basin)

7. Parameterization of Runoff in Baseline CLM Runoff = Surface runoff + Subsurface runoff Surface runoff Rs = Fsat Qwat + (1 – Fsat) ws4 Qwat TOPMODEL BATS Qwat = Input of water at the soil surface Fsat = Fractional saturated area = Fmax exp(–Dw) ws = averaged soil wetness in the top three soil layers Subsurface RunoffRsb = Fsat lb exp(–Dw) + (1 – Fsat) Kb wb2B+3 lb = maximum baseflow rate = 10-5 mm s-1 Kb = maximum drainage rate = 0.04 mm s-1 wb = averaged soil wetness in the bottom three soil layers Ksat (z) = Ksat(0) exp(–f z ) Ksat(0) = saturated hydraulic conductivity at the soil surface, determined by soil texture following Cosby et al. (1984); f = 2 (tunable parameter)

8. Problems in the Baseline CLM 1) The second term in surface runoff is redundant and too large. Rs = Fsat Qwat + (1 – Fsat) ws4 Qwat TOPMODEL BATS 2) The second term in subsurface runoff is redundant and too large. Rsb = Fsat lb exp(-Dw) + (1 – Fsat) Kb wb2B+3 3) How to determine Ksat (0) and Ksat(z)? Following Cosby et al. (1984)? Allowing macorpores? How to account for vertical and horizontal Ksat? 4) How to compute Fsat? Constrained by a global constant? By topography? 5) How to determine the water table? By the total head equilibrium? The moving boundary? An explicit groundwater model?

9. Proposed Runoff Scheme in CLM 1) Surface runoff Rs = Fsat Qwat + (1 – Fsat) max(0, Qwat – Imax) 2) Subsurface runoff Rsb = Rsb,max exp (-f zw) simplified from Rsb = [ αKsat (0) / f ] exp(- λm) exp(- f zw) α= anisotropic factor for different Ksat in vertical and horizontal directions λm= grid-cell averaged topographic index zw= grid-cell mean water table depth 3) Ksat (0) = ksat exp (f Dc) Ksat (z) = Ksat(0) exp(–f z ) ksat is determined by following Cosby et al. (1984). Allowing macropores. 4)Fsat = ∫λ≥ (λm + f*zw)pdf(λ) dλ 5) The water table is diagnosed from an equilibrium relationship ψ(z) – z = ψsat – zw (i.e., the total head is equal across the soil column layers)

10. Topography-based Runoff Scheme Runoff production mechanism • Surface runoff • Saturation excess • Infiltration excess • Subsurface runoff • Topographic control • Bottom drainage • “Over-saturated” water recharged into upper unsaturated layers Saturation Excess Infiltration Excess Water Table Depth Topography Bottom Super-saturation

11. Outline • Introduction • Current treatment of runoff in CLM and problems • Saturation area • Surface runoff • Ksat, macropores and anisotropic factor • Subsurface runoff • Constant versus exponential Ksat • Continental-scale simulations • Water table • Regional-scale simulations • Comparison with observations • Sensitivity to parameters • f • Rsub,max

12. Maximum Fractional Saturated Area (Fsat,max) Fsat = ∫λ≥ (λm + f*zw)pdf (λ) dλwhen the water table is at the surface (zw = 0) Using 1 km × 1 km topographic index (λ) Using Γ-distribution fit to the 1 km data Differences of (Middle – Top)

13. Defining the Maximum Fractional Saturated Area Topographic Index λ Fsat = ∫λ≥ (λm + f*zw)pdf (λ) dλ Fsat,max results whenthe water table is at or above the surface (zw ≤ 0)

14. Simulations over the Sleepers River Basin TOPMODEL: Fsat = ∫λ≥ (λm + f*zw)pdf (λ) dλ SIMTOP: Fsat = Fsat,max exp (–0.5 f zw) Fsat,max = 0.42

15. Outline • Introduction • Current treatment of runoff in CLM and problems • Saturation area • Surface runoff • Ksat, macropores and anisotropic factor • Subsurface runoff • Constant versus exponential Ksat • Continental-scale simulations • Water table • Regional-scale simulations • Comparison with observations • Sensitivity to parameters • f • Rsub,max

16. Ksat, macropores and anisotropic factor 10–10 m/s 10–7 m/s 10–3 m/s 0 m Baseline CLM ksat depends on soil type (Cosby et al., 1984) Stiglietz et al. (1997) : Ksat(0) = 1000 × ksat α=1, f=3.26 Chen and Kumar (2001): Ksat(0) = exp(f Dc) × ksat = 6 × ksat α=2000, f=1.8 This study: Ksat(0) = exp(f Dc) × ksat = 6 × ksat α=20, f=2 (global); =3.26 (Sleepers River) or Rsb,max = 1.45×10–7m/s Chen & Kumar 1 m Stiglietz et al. 2 m 3 m

17. 10–10 m/s 10–7 m/s 10–3 m/s 0 m Baseline CLM 1 m Chen & Kumar α = 1 Stiglietz et al. 2 m α = 20 3 m Ksat, macropores and anisotropic factor

18. Outline • Introduction • Current treatment of runoff in CLM and problems • Saturation area • Surface runoff • Ksat, macropores and anisotropic factor • Subsurface runoff • Constant versus exponential Ksat • Continental-scale simulations • Water table • Regional-scale simulations • Comparison with observations • Sensitivity to parameters • f • Rsub,max

19. Simulations over Various Regional Basins East Siberia NW Canada West Siberia Congo India Amazon C Europe W USA E USA Australia Sahara S Africa N America S Hemisphere Eurasia

20. 10–10 m/s 10–7 m/s 10–3 m/s 0 m Baseline CLM 1 m Stiglietz et al. 2 m 3 m Simulations over the Sleepers River Basin TOPMODEL: Fsat = ∫λ≥ (λm + f*zw)pdf (λ) dλ Rsb,max = 1.45 ×10–7 m/s Chen & Kumar Bottom NOT sealed Bottom sealed

21. Simulations over the Sleepers River Basin 10–10 m/s 10–7 m/s 10–3 m/s 0 m Baseline CLM Bottom NOT sealed Chen & Kumar 1 m Bottom sealed 2 m Stiglietz et al. 3 m TOPMODEL: Fsat = ∫λ≥ (λm + f*zw)pdf (λ) dλ Rsb,max = 1.45 ×10–7 m/s

22. Outline • Introduction • Current treatment of runoff in CLM and problems • Saturation area • Surface runoff • Ksat, macropores and anisotropic factor • Subsurface runoff • Constant versus exponential Ksat • Continental-scale simulations • Water table • Regional-scale simulations • Comparison with observations • Sensitivity to parameters • f • Rsub,max

23. Comparison of Simulated Water Table with Measurements in Illinois

24. Outline • Introduction • Current treatment of runoff in CLM and problems • Saturation area • Surface runoff • Ksat, macropores and anisotropic factor • Subsurface runoff • Constant versus exponential Ksat • Continental-scale simulations • Water table • Regional-scale simulations • Comparison with observations • Sensitivity to parameters • f • Rsub,max

25. Sensitivity to f: Simulations over the Sleepers River

26. Sensitivity to Rsb,max Simulations over the Sleepers River

27. Simulations over the Sleepers River

28. Simulations over the Amazon Basin

29. Soil Moisture (mm/d) Surface runoff (mm/d) ET (mm/d) Precipitation (mm/d) Coupled CAM2-CLM2 Results in Amazon 1-2mm/d Simplified TOPMODELproduced less surface runoff, allowing more water to infiltrate into deeper soil and to increase soil moisture. Transpiration increases significantly, more than compensating the decrease in the interception loss. As a result, both ET and precipitation show favorable increases.

30. Conclusions • Based on offline tests for a small catchment or global continents, the proposed runoff scheme is shown to be robust for a wide range of assumptions including • Different methods of Fsat, • Based on 1-km topographic parameters • Assuming a global constant • Constant versus exponential Ksat • In the constant profile case, results depend on whether the bottom is sealed or not • Different methods of water table. 2) The simulations of soil moisture and runoff are all improved over the baseline version. 3) In the Amazon region, canopy evaporation and surface runoff are reduced, soil is wetter, and both ET and precipitation are increased.

31. Future Work • Increase the total soil thickness to ~10 m and make it a geographic variable • Need bedrock data, • Adjust root depth and distribution, • Collect the water table data, • Compare with the GRACE data. 2) Global optimization of two calibration parameters (f and Rsub,max). 3) Include (unconfined) aquifer into CLM to study groundwater recharge, discharge, and climate-groundwater interactions.

32. Land Surface, Surface Water and Groundwater Can be detected by GRACE