ESTIMATING EVAPORATION FROM WATER SURFACES

1 ESTIMATING EVAPORATION FROM WATER SURFACES (With emphasis on shallow WATER bodies) 1ET Workshop12 Mar 2010 INTRODUCTIONINTRODUCTION EvaporationisrarelymeasureddirectlyEvapo ration is rarely measured directly ESTIMATING methods include:ffi i tdti pan coefficient xmeasured pan EVAPORATION WATER balance energy balance mass transfer combination techniques Emphasis will be practical methods2ET Workshop12 Mar 2010 BACKGROUNDBACKGROUND Evaporationtheories tothe8thcenturyEvaporation theories to the 8century Dalton (1802), E = f( ) (eo ea)( 926)hihif Bowen (1926), the Bowen ratio, the ratio of sensible heat to latent heat gradients ( t/ e) Applications were made to lake EVAPORATION by Cummings and Richardson 1927; McEwen 19303ET Workshop12 Mar 2010 ENERGYCONSIDERATIONSENERGY CONSIDERATIONS EvaporationrequiresalotofenergyEvaporati on requires a lot of energy Incoming solar radiation is the main sourceldllldi i In contrast to land, not all net solar radiation is absorbed on the surface In pure WATER , about 70% is adsorbed in the top 5 m (16 ft) Solar radiation adsorbed below the surface is stored energy gy4ET Workshop12 Mar 2010 ENERGY(continued)ENERGY (continued) Estimatingenergystorageinwater(Qt)canEst imating energy storage in WATER (Qt) can be more difficult than ESTIMATING soil heat flux (G) Part of solar radiation may penetrate to great depths depending on the clarity of the WATER Stored energy affects the EVAPORATION rate Exampletemperatureprofilesindeepwater:Ex ample temperature profiles in deep WATER .

2 Profiles during increasing solar cycle profiles during decreasing solar cyclepggy5ET Workshop12 Mar 2010 Solar Radiation Penetrates Deep in WaterEvaporation pans are two EVAPORATION pans are two shallow and hold too shallow and hold too much warmth atthemuch warmth atthemuch warmth at the much warmth at the surface. surface. Therefore, they can Therefore, they can overestimate the overestimate the EVAPORATION from large EVAPORATION from large reservoirs and and STORAGE & RELEASE LakeBerryessa8 100ha(20 000ac )and58 Lake Berryessa, 8,100 ha (20,000 ac.) and 58 m (190 ft) deep, average 40 m Littleornoinflowduringthesummer Little or no inflow during the summer Thermal profiles during increasing Rs Thermal profiles during decreasing Rs Example temperatures by depth and timeppyp Reason for studying EVAPORATION improve estimatesofevaporationtocalculateinflowe stimates of EVAPORATION to calculate inflow 7ET Workshop12 Mar 2010 Lake BerryessaLake BerryessaCalifornia, USAC alifornia, USALB 05LB 10LB 04LB 12LB 03LB 06(New-USBR WS)LB 07A-ELB 01 Old-USBRLB 02 Portable WSLB 08 (Dam)LB 09 (USBR)

3 LB 11 Old-USBR WS8ET Workshop12 Mar 2010 Temperature Profile Data - 7/10/03010121416182022242628-10-5m-20-15 Depth, m-30-2530 Temperature, CLB 01LB 02LB 03LB 04LB 05 Avg9ET Workshop12 Mar 2010 Temperature Profile Data - 10/30/03 Temperature Profile Da ta - 10/30/03010121416182022242628-10-520-15- 10 Depth, m-25-20-30 Temperature, CLB 01LB 02LB 03LB 04LB 05 AvgLB 01LB 02LB 03LB 04LB 05 Avg10ET Workshop12 Mar temp, m11ET Workshop12 Mar 2010 WHYSTUDYEVAPORATIONONLB?WHY STUDY EVAPORATION ON LB? The pan site was moved from the original site Measured pan EVAPORATION xoriginal coefficients underestimated reservoir EVAPORATION and inflow Negativeinflowswerecalculatedduringlowan dzero Negative inflows were calculated during low and zero inflows late in the summer The obvious solution move the pan site, and hkthffi i trecheck the pan coefficients Data were needed to justify to the USBR the need to change the pan sitegp View of the EVAPORATION pan site Estimated rate of energy storage12ET Workshop12 Mar 2010 OriginalUSBRPanSiteOriginal USBR Pan Site13ET Workshop12 Mar 2010 RateofEnergyStorageRate of Energy , MJ m-2day15 Qt(rate)MeasQt(rate)03 MeasQt(rate)04 MeasQt(rate)05 Est-2 Qt(rate)Meas-Qt(rate)-03 Meas-Qt(rate)-04 Meas-Qt(rate)

4 -0514ET Workshop12 Mar 2010 ENERGYSTORAGEEXAMPLESENERGY STORAGE EXAMPLES Maximum energy storage rates of 5 to 10 MJ m 2 aueegysto ageateso5to0Jd 1to a depth of 25 m measured in Lake Berryessa and about 10 MJ m 2 d 1to a depth of dkd45 m measured in Lake Mead WATER surface temperatures reached a iiJliLBdiAtiLkmaximum in July in LB and in August in Lake Mead (lag is related to depth of WATER ) Evaporationratealsolaggedsolarradiation EVAPORATION rate also lagged solar radiation Advected energy can be large in reservoirs on rivers(examplealongColoradoRiver)rivers (example along Colorado River)15ET Workshop12 Mar , m m Workshop12 Mar 2010 SurfaceTemp Temp Lake 05F 05 M 05 A 05 M 05 J 05 J 05 A 05 S 05 O 05 N 05 D 0512 Mar 2010ET Workshop17 Surface TempOtherMethodsOther Methods WaterbudgetprocedureWater budget procedure Aerodynamic methodsdilllkdi used mainly on large lakes and reservoirs Example American Falls reservoir in Idaho by Allen et al.

5 Estimates using WATER and air temperature estimated EVAPORATION relative to ETr Why the low summer rate? Cold inflow WATER ?y12 Mar 2010ET Workshop18 Temperature of WATER from American Falls outfall follows Temperature of Air(b)(b)Year 2000 American Falls Temperatures15202530ture, Cp200410-50510 TemperatYear 2004-1024-Feb09-Mar23-Mar06-Apr26-Apr11- May25-May09-Jun22-Jun07-Jul20-Jul03-Aug1 7-Aug01-Sep14-Sep28-Sep12-Oct26-Oct09-No v22-Nov07-Dec20-DecDateWater Temp10 day mean Air TempEvaporation ratio for Alfalfa ReferenceETReference ET1 American Falls, EVAPORATION /ETr from study 2004 Aerodynamic ETrF from TmeanSHALLOWWATERBODIESSHALLOW WATER BODIES EarlyestimatingmethodsEarly ESTIMATING methods Equilibrium temperature (Edlinger et al. 1968) FurtherdevelopedandtestedbyKeijmanFurthe r developed and tested by Keijman(1974), Fraederich et al.

6 (1977), de Bruin (1982), and Finch (2001) Finite difference model (Finch and Gash, 2002) Pan EVAPORATION xpan coefficientpp Energy balance and combination methods ReferenceETxcoefficient(E=ETxK)Reference ETx coefficient (E= ETox Kw)21ET Workshop12 Mar 2010 EVAPORATIONPANCOEFFICIENTSEVAPORATION PAN COEFFICIENTS Pan coefficient studiesacoe c e tstud es Rohwer (1931) a classic detailed study conducted on the CSU campusp Rohwer compared EVAPORATION from a Class A pan and an 85 diameter (26 m) reservoir Young (1947) also did a classic study in CA Others: Kohler (1954); Kohler et al. (1959); Farnsworth et al. (1982) Fetch effects and obstructions (fixed & variable)22ET Workshop12 Mar 2010 Ratio of Lake EVAPORATION to Class Pan evap ElsinoreLake Okeechobee23ET Workshop12 Mar = + + Reservoir to Class A pan, Apr Nov Rohwer (Avg)24ET Workshop12 Mar (Avg) , Oct Nov Apr May Jun Jul Aug Sep Oct Nov Apr May Jun Jul Aug Sep Oct Nov25ET Workshop12 Mar 2010 Air temp 1 inchWater , mm fetch of irrigated grass, m26ET Workshop12 Mar 2010 ObstructionsObstructions FixedFixed buildingsshelterbelts shelter belts other (shown in previous example)Vibl Variable adjacent corn field (most common), can have a jff tmajor effect weeds and other adjacent crops12 Mar 2010ET Workshop27 OTHERESTIMATINGMETHODSOTHER ESTIMATING METHODS Aerodynamic (used mainly on large WATER bodies)y(yg)

7 Energy balance (requires detailed measurements) Combination methods: Penman (1948, 1956, 1963); Penman Monteith (1965); Priestley Taylor (1972) All require ESTIMATING net radiation using standard equationsandestimatingenergystorage(more equations and ESTIMATING energy storage (more difficult for deep WATER bodies) Reference ET x coefficient (E= ETox Kw)(ow) for shallow WATER bodies for ice free WATER bodies28ET Workshop12 Mar 2010 ENERGYSTORAGERATESENERGY STORAGE RATES DifficulttoquantifywithoutmeasurementsDi fficult to quantify without measurements Example rates of storagektf5t10MJ2d1 peak rates can range from 5 to 10 MJ m 2d 1 equivalent to 2 to 4 mm d 1 EVAPORATION Example rates calculated from lake studies Pretty Lake in Indiana Williams Lake in Minnesota12 Mar 2010ET Workshop29 Reported Energy Storage Rates - Pretty Lake (63-65) & Williams Lake (82-86) , M J m-2 of Ye arPretty LakeWilliams LakePoly.)

8 (Pretty Lake)Poly. (Williams Lake)yy(y)y()30ET Workshop12 Mar 2010 ASCE EWRIREFERENCEETASCEEWRI REFERENCE ET ASCE EWRI(2005)andAllenetal(1998)ASCEEWRI (2005) and Allen et al. (1998) ETrefxcoefficient for open ice free WATER (Kw)hifh()d1 where ETrefis for short grass (ETos), mm d 1 First check input weather data for (Rn G) + [900/(T + 273)] u2 (es ea)ETf= ETref = + (1 + u2)31ET Workshop12 Mar 2010 EXAMPLE HOMELAKE,COEXAMPLE HOME LAKE, CO LocationSanLuisValleyLocation San luis Valley Elevation 2297 m (7536 ft) above sea levelAveragedepthabout15m(5ft) Average depth, about m (5 ft) Estimated energy storage Estimated EVAPORATION May October ETrefx Kwalso agrees with PM in November Results (May October)(y)32ET Workshop12 Mar , M J Workshop12 Mar Lake, Alamosa, , mm - PME = ETo x Workshop12 Mar 2010 ROHWER S CLASS A PAN COEFFICIENTS KbymonthsforColorado.

9 Kpby months for Colorado: Based on mean ratios (polynomial)A060At075 Apr May June July Average, April October Workshop12 Mar 2010 ESTIMATED EVAPORATION HOME LAKE MAY OCT. PMPenmanNWS mm (inches) (inches) 894 906890892 ( )( )( )( ) Percent of PM All give similar values for May through Octobergyg36ET Workshop12 Mar 2010 ESTIMATED EVAPORATION ()LAKE BERRYESSA (3 YR AVG) PMPenmanP T USBR originalg mm (inches) 1,3251,425 1,277955 ( )( ) ( )( ) 1001089672 The same Rnand Qtused for first three methodsVlfifff i Values confirm effects of poor pan site P T equation does not have wind speed37ET Workshop12 Mar 2010