5.3 ESTIMATING URBAN LANDSCAPE EVAPOTRANSPIRATION

Transcription

1 5.3 ESTIMATING URBAN LANDSCAPE EVAPOTRANSPIRATION Richard L. Snyder 1 * and Simon Eching 2 1 University of Caifornia, Atmospheric Science, Davis, Caifornia, 2 Caifornia Department of Water Resources, Office of Water Use Efficiency, Sacramento, Caifornia 1. INTRODUCTION Irrigation controers are now widey used to manage andscape irrigation; however, scientificay based information on when to appy water and how much to appy is imited. In Caifornia, the andscape industry is huge and there is increased competition among water users. Consequenty, managing irrigations to optimize efficient water use is criticay important to stretch existing water suppies. Therefore, the MS Exce program LIMP.XLS was written to hep andscape professionas and homeowners to cacuate ET o rates, determine andscape coefficient (K L ) vaues, estimate andscape evapotranspiration (ET L ) and determine irrigation schedues. This program not ony heps practitioners but it aso carifies what horticuturaists need to research to hep to improve urban irrigation management. Evapotranspiration from andscape vegetation is estimated by using a regiona measure of evaporative demand (e.g., reference evapotranspiration or ET o ), a microcimate coefficient (K m ) to adjust the ET o for the oca microcimate, a vegetation coefficient (K v ) that accounts for the difference in ET between we watered vegetation and the oca ET o, a density coefficient (K d ) that adjusts the ET estimate for pant density, a stress coefficient (K s ) that adjusts for reductions in ET due to water stress and an evaporation coefficient (K e ) that defines a baseine coefficient vaue. Initiay, the coefficient (K w ) to estimate ET of a we-watered vegetated cover is estimated as: K = K K K (1) w m v d Then K w is mutipied by a stress coefficient (K s ) to adjust for reductions in ET beow that of we-watered vegetation. However, the evaporation coefficient serves as a baseine, so the andscape coefficient is cacuated as: K = K K > K. (2) w s e Then the andscape evapotranspiration (ET ) for the vegetation in that ocation is cacuated as: ET = ET K. (3) o 2. MICROCLIMATE COEFFICIENT In the Weather worksheet (Fig. 1), the upper tabe is used to estimate regiona daiy ET o rates by month and to enter the coefficients used to cacuate andscape ET (ET ). The ower tabe (Fig. 1) is used to *Corresponding author address: Richard L. Snyder, Atmospheric Science, Univ. of Caifornia, Davis, CA ; emai: rsnyder@ucdavis.edu. The views expressed are those of the author, not the State input weather data representing the microcimate of the irrigation site to deveop monthy microcimate correction factors to estimate the Loca ET o rates. Either daiy mean ET o rates or weather data are input to estimate Regiona ET o rates in the upper tabe. Then the LIMP uses a smooth curve fitting technique to estimate daiy ET o rates during the year from the monthy data. Weather inputs can incude the daiy mean (1) soar radiation (MJ m -2 d -1 ), air temperature ( o C), wind speed (m s -1 ), and dew point temperature ( o C). The program cacuates ET o using the Penman-Monteith (PM) equation (Monteith, 1965) as presented in the United Nations FAO Irrigation and Drainage Paper (FAO 56) by Aen et a. (1998). If ony temperature data are input, then the Hargreaves-Samani (1982) equation is used. Figure 1. Cimate data input worksheet for microcimate, vegetation, density, stress and evaporation coefficient factors. Monthy cimate data representing the Loca site are input in the ower tabe of the Weather worksheet and ET o is cacuated using the PM or HS equations. The ratio of oca over regiona ET o is computed and dispayed in the right-hand coumn of the ower tabe. This ratio represents a monthy caibration for microcimate. Whie the microcimate (K m ) factors are shown in the ower tabe, they are ony used by the program if they are copied to the right-hand coumn of the upper tabe using Copy Paste Specia Vaues. A smooth curve fitting procedure is used to estimate daiy K m vaues for the year. A sampe pot of daiy K m using data from Figure 1 is shown in Figure 2. If no

2 vaues are input into the right-hand coumn of the upper tabe, the defaut vaue of K m = 1.0 is used. that accounts for pant density and vegetation differences from the oca (i.e., microcimate corrected) ET o rate. For exampe, Figure 4 shows K v K d for the data 1.2 Fraction of Maximum ET GC π F = sin 70 2 Figure 2. Pot of microcimate coefficient (K m ) versus date from data input into Figure VEGETATION COEFFICIENT The vegetation coefficient (K v ) is input into the Weather worksheet to adjust ET for pant canopy differences from ET o (i.e., the ET of 0.12 m ta, cooseason grass). The K v coefficient represents wewatered vegetation with a fu canopy. The K v accounts for morphoogica and physioogica differences between the vegetation and the reference surface (ET o ). For exampe, coo-season turfgrass is shorter than the 0.12 m ta, coo-season grass represented by ET o, so turfgrass ET is commony estimated using K v The K v accounts for differences in net radiation, turbuence due to surface roughness, and canopy resistance reative to ET o. It is assumed that the pant physioogy changes itte during the year, so one vaue is used for K v a year. The K v vaue is input near the top right-hand side of the Weather worksheet (Fig. 1). 4. DENSITY COEFFICIENT Sparse canopies have ower ET than dense canopies of the same vegetation and a density coefficient (K d ) is needed for the adjustment. Since there is no known universa correction for andscape vegetation, the foowing correction for immature deciduous orchards (Fig. 3) is used to estimate K d. CG π K d = sin (4) 70 2 where C G is the percentage of ground covered by green growing vegetation. It is assumed that this reationship accounts for differences in ight interception by canopies with cover ess than 70 %. For canopies with more than 70 % cover, K d = 1.0. The percentage ground cover is input by month in the upper tabe of the weather worksheet, the monthy K d vaues are cacuated and curve fitting is used to estimate the daiy K d vaues. If the ground cover ces are eft bank, the defaut vaue K d = 1.0 is used. The K d vaue is mutipied by the vegetation coefficient (K v ) to estimate the andscape coefficient (K ) Ground Shading (%) Figure 3. Pot of the density (K d ) correction or fraction of maximum ET versus ground cover (C G ) percentage. Figure 4. Pot of the product of the vegetation and density coefficient factors from data entered in Figure STRESS COEFFICIENT Monthy stress coefficient (K s ) vaues are input into the upper tabe of the Weather worksheet (Fig. 1). A coefficient of K s = 0 woud force ET = 0 and a K s = 1.0 impies no reduction in ET due to water stress. After entering the monthy data, daiy K s vaues are computed for the entire year using a curve fitting technique. In oder iterature, it was common to tak about water use differences between vegetation and a species coefficient was used to estimate the vegetation ET from ET o. However, in LIMP, the vegetation coefficient (K v ) is used to estimate the ET of vegetation at the maximum ET rate and the K s coefficient is used to estimate the ET when the vegetation is stressed. For exampe, warmseason turfgrass has ET rates at about 75% of cooseason turfgrass during the summer but the ET rate is near zero during the winter when the grass is dormant. Therefore, reasonabe estimates of the stress coefficient (K s ) by month were input into the Weather worksheet (Fig. 1) and the daiy vaues were estimated and potted (Fig. 5). Then, the daiy andscape coefficient vaues for

3 a warm-season turfgrass woud be cacuated as K = K v K d K s. Figure 5. Pot of the daiy stress coefficient based on data 6. EVAPORATION COEFFICIENT Bare soi evaporation is estimated for each day of the year using daiy ET o estimates and the number-ofrainy-days per month (NRD), which are input into the Weather worksheet (Fig. 1). The NRD is used to estimate the rainfa frequency for each month and the resuts are used with ET o to estimate bare soi evaporation (E s ) using a 2-stage mode. A pot of the evaporation coefficient estimates as a function of ET o rate and rainfa frequency (days) is shown in Figure 6. The evaporation coefficient mode is expained in Snyder et a. (2000). Then the estimated soi evaporation (E s ) is used to cacuate a daiy mean K e = E s /ET o vaue for bare soi for each month. Curve fitting is used to estimate daiy K e vaues over the year (Fig. 7). The K vaues are cacuated using Eqs. 1 and 2, but the vaues must be greater than or equa to K e (Fig. 7). Figure 7. Pot of the andscape coefficient (K ) and evaporation (bare soi) coefficient (K e ) based on data 7. OUTPUT & SCHEDULING Daiy vaues from each of the coefficients are potted in the charts Km_pot, Kd_pot, Ks_pot and K_pot and are isted in worksheets Km, Kd, KvKd, Ks, Ke and K. The andscape (K ) and baseine K e coefficients are potted in Figure 7. The daiy andscape coefficient is cacuated using Eqs. 1 and 2 and ET is cacuated using Eq. 3. The ET o and ET rates are potted in the chart ET (Fig. 8) and the cumuative ET o and ET are potted in the chart CET (Fig. 9). ET o (inches day -1 ) Evaporation Coefficient (K e ) day 2 day 4 day 7 day 10 day 20 day Figure 8. Pot of daiy ET o and ET using the data from Figure ET o (mm day -1 ) Figure 6. Evaporation (K e ) coefficient as a function of ET o rate and wetting frequency.

4 The CRT worksheet (Fig. 11) shows the cumuative runtime minutes to repace ET osses during the year. If any character is input in the sma ce immediatey eft of a cumuative vaue, the cumuative runtime is reset to zero on that date and the runtime wi accumuate unti the end of the year. If one knows the maximum runtime possibe to avoid runoff, entering characters on dates with that runtime or ess wi provide a schedue during the year. Figure 9. Pot of cumuative ET o and ET using the data The OUTPUT worksheet (Fig. 10) contains a row of a coefficient and ET cacuations for each day of the year. The LIMP program aso suppies information for irrigation scheduing in the worksheet RT (Fig. 11). Daiy sprinker runtimes needed to repace the ET osses and account for appication efficiency are dispayed. The appication rate and efficiency are input at the top of the worksheet and the runtime minutes to efficienty irrigate are dispayed in the tabe. When the appication area is input, the tota runtime hours and appication amount for the year are dispayed at the top of the tabe. Figure 11. Sampe of the CRT worksheet using data The worksheet K_Mut (Fig. 12) is used the K vaues for up to 20 watering zones. to input Figure 10. Sampe of the first 27 days of the Output worksheet using data Figure 12. Sampe of the K_Mut worksheet with andscape coefficients entered for the first two zones. Figure 11. Sampe the RT worksheet using data from Figure 1. To input the K vaues, create the K vaues for the vegetation of interest using the Weather worksheet and then copy the daiy K coumn from the OUTPUT worksheet to the appropriate coumn in K1_Mut. When a coumn of K vaues is copied to the worksheet, a coumn of runtime vaues is created in the RT_Mut worksheet (Fig. 13). Then the appication rate and appication efficiency are input at the tops of the coumns in the RT_Mut worksheet. Assuming itte or no runoff, the distribution uniformity can be used to estimate the appication efficiency. The runtime needed

5 to repace daiy water osses on each day of the year by zone is dispayed under the appication efficiency. Figure 13. Sampe RT_Mut worksheet using the K vaues from the K_Mut worksheet (Fig. 12). Vaues in the tabe are daiy minutes of runtime required to appy a mean depth to the ow quarter equa to the soi water depetion estimated using evapotranspiration. The CRT_Mut worksheet (Fig. 14) provides the corresponding cumuative runtime requirements for each day of the year for each of the 20 zones. Entering any character in the bue coumn to the eft of the tabe wi zero the accumuation on the corresponding date and the runtimes wi begin to accumuate again on the foowing day. Figure 14. Sampe CRT_Mut worksheet using data from the RT_Mut worksheet (Fig. 13). Vaues in the tabe are cumuative minutes of runtime required to appy a mean depth to the ow quarter equa to the soi water depetion estimated using evapotranspiration. 8. UPDATING WITH CURRENT ET o RATES Figure 15. Sampe of the ETo worksheet that dispays the ET o vaues used in the ET cacuations. This worksheet is used to update ET o based on cimate data with current ET o rates. 8. REFERENCES Aen, R.G., Pereira, L.S., Raes, D., and Smith, M Crop evapotranspiration Guideines for computing crop water requirements. FAO Irrig. and Drain. Paper 56. Food and Agricuture Organization of the United Nations, Rome. pp Hargreaves, G.H., and Samani, Z.A. (1982) Estimating potentia evapotranspiration. Tech. Note, J. Irrig. and Drain. Engrg., ASCE, 108(3): Monteith, J.L Evaporation and the environment In the movement of water in iving organisms, XIXth Symposium. Soc. of Exp. Bio., Swansea, Cambridge University Press. Snyder, R.L., Bai, K., Ventura, F., and Gomez- MacPherson Estimating evaporation from bare or neary bare soi. J. Irrig. and Drain. Engng., ASCE, 126(6): Water, I.A., R.G. Aen, R. Eiott, M.E. Jensen, D. Itenfisu, B. Mecham, T.A. Howe, R. Snyder, P. Brown, S. Echings, T. Spofford, M. Hattendorf, R.H. Cuenca, J.L. Wright, D. Martin ASCE s Standardized Reference Evapotranspiration Equation. Proc. of the Watershed Management 2000 Conference, June 2000, Ft. Coins, CO, Amer. Soc. of Civi Engineers, St. Joseph, MI. The LIMP program can determine runtimes needed for irrigation of urban andscape vegetation using daiy ET o cacuated from monthy cimate data. However, one can aso input the current ET o data into the ETo worksheet (Fig. 15), which is ocated to the right of the Weather worksheet. To change ET o vaues, cick on the ce to the eft of where data are to be changed and then enter the current ET o vaue.