Evapotranspiration. Andy Black. CCRN Processes Workshop, Hamilton, ON, Sept Importance of evapotranspiration (E)

Transcription

1 Evapotranspiration Andy Black CCRN Processes Workshop, Hamilton, ON, Sept 213 Importance of evapotranspiration (E) This process is important in CCRN goals because 1. Major component of both terrestrial water and energy balances 2. It is spatially highly variable over western Canada as a result of a heterogeneous landscape 3. It is sensitive to changing climate and the impact of landscape disturbance. How does E respond to the change? 4. Significant challenges remain in modelling and measuring E 1

2 Outline 1. Importance of the P-M and P-T equations in estimating E 2. Examples of canopy conductance and P-T s for boreal forests and grassland 3. Importance of the decoupling coefficient ( ) in understanding the responses to changing weather variables 4. Parameterizing canopy conductance locally & using remotely-sensed LAI 5. Effect of E on the contribution to groundwater (i.e., P E) 6. Suary Penman-Monteith equation Penman (1948) used the surface latent heat exchange, sensible heat exchange, and energy balance equations to derived the Penman equation. Monteith(1965) established the form of the equation with the canopy resistance, r c, and the concept of the big-leaf model. The P-M eq. is E = s R n G + ρc p (e T a e a ) s + γ(1 + r c ra ) where R n G = A (available energy flux) and e * (T s ) e a ) = D the vapour pressure deficit or the saturation deficit. D will likely rise with climate warming. Since r c increases with D it s difficult to predict how much E will increase. 2

3 Equilibrium evaporation & the Priestley-Taylor equation For moist surfaces, the P-M equation can be written as the sum of the equilibrium evaporation ( E eq = [s/(s + )]A) and an advection term involving D. Priestley and Taylor (1972) proposed that moist surface E be expressed as E = E eq with =1.26 has been coonly observed for moist aerodynamically smooth surfaces,e.g., grassland. has also been used as a parameter to characterize E from ecosystems with limited water supply i.e., << Relationship between and r c McNaughton and Spriggs (1989) modelled the interaction between land surface ET and the diurnally-changing planetary boundary layer (PBL) to show that reached a limit near 1.26 as r c approached zero. 3

4 g c ( s -1 ) 9/18/213 Examples of E, g c (r c ) and for boreal forest and grassland ecosystems 125 r c 25 (s m-1 ) Dry years: 3 OA,OBS & OJP; 1 GRL Wet year: 5 all sites From Zha et al. 21 Decoupling coefficient ( ) The sensitivity of E to changes in A and D can be better understood by writing the P-M equation in the following form s E = ( )A + (1 s + γ ) ρc pd γr c where is the decoupling coefficient. sets the relative importance of E eq (the rate of E if there were total isolation from the mixed layer) and a term representing the E that would occur if mixed-layer D m were imposed on the surface with no equilibration. γ r = [1 + c ] -1 (s+γ) r a m McNaughton and Jarvis (1983) 4

5 Decoupling coefficient ( ) This concept explains differences in response of forests and grasslands since for forests is low e.g.,.2 and for grasslands it s high, e.g.,.8. Strong coupling - low E tends to follow D. Weak coupling - high E tends to follow R n. Parameterizing r c : empirical models A major challenge in using the P-M equation is developing reliable relationships between r c and environmental variables (PAR, D, soil water content ( ), T a, etc.) and stand characteristics (LAI). Examples are the Jarvis-Stewart multiplicative approach 1/ rc (1/ rc _ max ) f ( LAI ) f ( D) f ( Ta ) f ( PAR) f ( ) and the Ball-Woodrow-Berry approach AP 1/ rc 1/ rc _ max m Wu et al () C D s where A p is the ecosystem assimilation rate (GEP), C s is the CO 2 concentration at the leaf surface and m is a plantfunctional-type and -dependent parameter. 5

6 Relationship of 1/r c (i.e., g c ) to LAI at Old Aspen Linear relationship with LAI Wu et al () LAI D Estimating regional E using remote sensing and the P-M equation Cleugh et al. (7) found the following relationship between 1/r c and a MODIS-derived LAI 1/r c = 1/r c_max + C L LAI They found that the coefficient (C L ) was remarkably similar in value despite a strong contrasts in vegetation and climate. 6

7 Remote sensing and the P-M equation (cont.) Success (see fig. below) appears to be due to reliable r c parameterization, constraint by the surface energy balance and insensitivity to errors in R n - G, D, r a and r c. Australian Fluxnet sites Contributions to ground water (P E) The following shows calculation of P E at the 3 BERMS forest sites and GRL Zha et al 21 It shows during wet years the greatest contributions were from OJP and OBS. 7

8 9/18/213 OA water fluxes to E P (P-E) J F M A M J J A S O N D Cumulative fluxes 1999 to Sept 213 OBS water fluxes to P 3 E (P-E) 1-1 J F M A M J J A S O N D Cumulative fluxes 1999 to Sept 213 8

9 Concluding coents Long-term observed ET and climate data sets exist These datasets can be used to test the robustness of ET models needed to predict responses to climate change Desirability of measuring C fluxes for estimating water use efficiency and evaluating impacts of climate change on ecosystems Availability of remote sensing products for regional water balances Thank you. Questions? 9

10 Regional E applications 1. Satellite directional radiometric surface temp. approach E is obtained as a residual using the energy balance E = R n - H - G where H is calculated using H = c p (T r - T a )/r a John Norman pioneered this approach which has shown promising results using one- and two-source versions (e.g. Norman et al. 1995). Canopy + soil E Canopy E c Soil E s Methods of measuring E Micrometeorological: eddy covariance Energy balance residual after estimating sensible heat flux (H) Sap-flow measurements (heat pulse, etc.) valuable in quantifying transpiration rate Chambers measure leaf-atmosphere and soil-atmosphere water vapour exchange. Porometers and LI-64 systems important in measuring stomatal conductance. Lysimeters (small useful for measuring E soil, large for ecosystem precipitation and E, e.g at OA). 1