ESTIMATING EVAPORATION FROM WATER SURFACES• The obvious solution –move the pan site, and...
Transcript of ESTIMATING EVAPORATION FROM WATER SURFACES• The obvious solution –move the pan site, and...
ESTIMATING EVAPORATION FROM WATER SURFACES
(With emphasis on shallow water bodies)
1ET Workshop12‐Mar‐2010
INTRODUCTIONINTRODUCTION
• Evaporation is rarely measured directlyEvaporation is rarely measured directly
• Estimating methods include:ffi i t d ti– pan coefficient xmeasured pan evaporation
– water balance
– energy balance
– mass transfer
– combination techniques
• Emphasis will be practical methods
2ET Workshop12‐Mar‐2010
BACKGROUNDBACKGROUND
• Evaporation theories – to the 8th centuryEvaporation theories to the 8 century
• Dalton (1802), E = f(ū) (eo – ea)
( 926) h i h i f• Bowen (1926), the Bowen ratio, the ratio of sensible heat to latent heat gradients (Δt/Δe)
• Applications were made to lake evaporation by Cummings and Richardson 1927; McEwen 1930
3ET Workshop12‐Mar‐2010
ENERGY CONSIDERATIONSENERGY CONSIDERATIONS
• Evaporation requires a lot of energyEvaporation requires a lot of energy
• Incoming solar radiation is the main source
l d ll l di 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”gy
4ET Workshop12‐Mar‐2010
ENERGY (continued)ENERGY (continued)
• Estimating energy storage in water (Qt) canEstimating 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• Example temperature profiles in deep water:Example temperature profiles in deep water:
– profiles during increasing solar cycle– profiles during decreasing solar cyclep g g y
5ET Workshop12‐Mar‐2010
Solar Radiation Penetrates Deep in Water
Evaporation pans are two Evaporation pans are two shallow and hold too shallow and hold too much “warmth” at themuch “warmth” at themuch 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 lakes.reservoirs and lakes.
ENERGY STORAGE & RELEASEENERGY STORAGE & RELEASE
• Lake Berryessa 8 100 ha (20 000 ac ) and 58Lake Berryessa, 8,100 ha (20,000 ac.) and 58 m (190 ft) deep, average 40 m
• Little or no inflow during the summer• Little or no inflow during the summer
• Thermal profiles during increasing Rs
• Thermal profiles during decreasing Rs
• Example temperatures by depth and timep p y p
• Reason for studying evaporation—improve estimates of evaporation to calculate inflowestimates of evaporation to calculate inflow
7ET Workshop12‐Mar‐2010
Lake Berryessa
Lake Berryessa
California, USACalifornia, USA
LB 05
LB 10
LB 04
LB 12
LB 03
LB 06(New-USBR
WS)
LB 07A-E
LB 01
Old-USBR
LB 02
Portable WSLB 08
(Dam)LB 09
(USBR)
LB 11Old-USBR WS
8ET Workshop12‐Mar‐2010
Temperature Profile Data - 7/10/03
010 12 14 16 18 20 22 24 26 28
-10
-5
m
-20
-15
Dept
h, m
-30
-25
30
Temperature, C
LB 01 LB 02 LB 03 LB 04 LB 05 Avg
9ET Workshop12‐Mar‐2010
Temperature Profile Data - 10/30/03Temperature Profile Data - 10/30/03
010 12 14 16 18 20 22 24 26 28
-10
-5
20
-15
-10
Dept
h, m
-25
-20
-30
Temperature, C
LB 01 LB 02 LB 03 LB 04 LB 05 AvgLB 01 LB 02 LB 03 LB 04 LB 05 Avg
10ET Workshop12‐Mar‐2010
30.0
2005
20.0
25.0
C
15.0
Wat
er te
mp,
C
10.0
5.0
1/1
2/1
3/1
4/1
5/1
6/1
7/1
8/1
9/1
10/1
11/1
12/1
0.15 m 5.2 m 7.6 m 12.8 22.6 m
11ET Workshop12‐Mar‐2010
WHY STUDY EVAPORATION ON LB?WHY STUDY EVAPORATION ON LB?
• The pan site was moved from the original site• Measured pan evaporation x original coefficients underestimated reservoir evaporation and inflow
• Negative inflows were calculated during low and zero• Negative inflows were calculated during low and zero inflows late in the summer
• The obvious solution – move the pan site, and h k th ffi i trecheck the pan coefficients
• Data were needed to justify to the USBR the need to change the pan siteg p
• View of the evaporation pan site• Estimated rate of energy storage
12ET Workshop12‐Mar‐2010
Original USBR Pan SiteOriginal USBR Pan Site
13ET Workshop12‐Mar‐2010
Rate of Energy StorageRate of Energy Storage15.0
5.0
10.0
y-1
-5.0
0.0
Qt,
MJ
m-2
day
15 0
-10.0
-15.0
M-0
3
J-03
S-0
3
N-0
3
J-04
M-0
4
M-0
4
J-04
S-0
4
N-0
4
J-05
M-0
5
M-0
5
J-05
S-0
5
N-0
5
J-06
Est 2 Qt(rate) Meas Qt(rate) 03 Meas Qt(rate) 04 Meas Qt(rate) 05Est-2 Qt(rate) Meas-Qt(rate)-03 Meas-Qt(rate)-04 Meas-Qt(rate)-05
14ET Workshop12‐Mar‐2010
ENERGY STORAGE EXAMPLESENERGY STORAGE EXAMPLES
• Maximum energy storage rates of 5 to 10 MJ m‐2 a u e e gy sto age ates o 5 to 0 Jd‐1 to a depth of 25 m measured in Lake Berryessa and about 10 MJ m‐2 d‐1 to a depth of
d k d45 m measured in Lake Mead• Water surface temperatures reached a
i i J l i LB d i A t i L kmaximum in July in LB and in August in Lake Mead (lag is related to depth of water)
• Evaporation rate also lagged solar radiation• Evaporation rate also lagged solar radiation• Advected energy can be large in reservoirs on rivers (example along Colorado River)rivers (example along Colorado River)
15ET Workshop12‐Mar‐2010
8.0
9.0d
-1
5.0
6.0
7.0
ratio
n, m
m
2 0
3.0
4.0
ated
eva
por
0.0
1.0
2.0
Est
ima
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Davis-Parker Parker-Imperial Imperial-Morelos
16ET Workshop12‐Mar‐2010
Surface Temp ‐ Lake Berryessa
30.0
35.0
Surface Temp Lake Berryessa
25.0
15.0
20.0
°C
5.0
10.0
0.0
J‐05 F‐05 M‐05 A‐05 M‐05 J‐05 J‐05 A‐05 S‐05 O‐05 N‐05 D‐05
12‐Mar‐2010 ET Workshop 17
Surface Temp
Other MethodsOther Methods
• Water budget procedureWater budget procedure
• Aerodynamic methodsd i l l l k d i– used mainly on large lakes and reservoirs
• Example – American Falls reservoir in Idaho by Allen et al.– estimates using water and air temperature
– estimated evaporation relative to ETr• Why the low summer rate? Cold inflow water?y
12‐Mar‐2010 ET Workshop 18
Temperature of water from American Falls outfall follows Temperature of Air
(b)(b)
Year 2000
American Falls Temperatures
15202530
ture
, C
p2004
10-505
10
Tem
pera
t
Year 2004-10
24-Feb09-Mar
23-Mar
06-Apr26-Apr
11-May
25-May09-Jun
22-Jun
07-Jul20-Jul
03-Aug
17-Aug01-Sep
14-Sep
28-Sep12-Oct
26-Oct
09-Nov22-Nov
07-Dec
20-Dec
DateWater Temp 10 day mean Air Temp
Evaporation ratio for Alfalfa Reference ETReference ET
1
American Falls, Evaporation/ETr ratios2004
0.70.80.9
1
/ ETr
0 30.40.50.6
pora
tion
00.10.20.3
Eva
0 1 2 3 4 5 6 7 8 9 10 11 12Month
ETrF from Am.Falls study 2004 Aerodynamic ETrF from Tmean
SHALLOWWATER BODIESSHALLOW WATER BODIES
• Early estimating methodsEarly estimating methods– Equilibrium temperature (Edlinger et al. 1968)
– Further developed and tested by KeijmanFurther developed and tested by Keijman(1974), Fraederich et al. (1977), de Bruin (1982), and Finch (2001)
• Finite difference model (Finch and Gash, 2002)
• Pan evaporation x pan coefficientp p
• Energy balance and combination methods
• Reference ET x coefficient (E = ET x K )Reference ET x coefficient (E = ETo x Kw)
21ET Workshop12‐Mar‐2010
EVAPORATION PAN COEFFICIENTSEVAPORATION PAN COEFFICIENTS
• Pan coefficient studiesa coe c e t stud 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 Evaporation
1.20
0.80
1.00
pan
-1
0.40
0.60
ake
evap
E
0.00
0.20
La
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Lake Elsinore Lake Okeechobee
23ET Workshop12‐Mar‐2010
1
0.8
0.9
0.6
0.7
y = ‐0.000x3 + 0.016x2 ‐ 0.056x + 0.6230.4
0.5
0.2
0.3Ratio ‐ Reservoir to Class A pan, Apr‐Nov ‐ Rohwer 1931
0
0.1
3 4 5 6 7 8 9 10 11 121926 1927 1928 Avg 0 7 Poly (Avg)
24ET Workshop12‐Mar‐2010
1926 1927 1928 Avg 0.7 Poly. (Avg)
30.0
Rohwer ‐ 1931
25.0
Rohwer ‐ 1931
20.0
C
10 0
15.0
Temp, C
5.0
10.0
0.0
Sep Oct Nov Apr May Jun Jul Aug Sep Oct Nov Apr May Jun Jul Aug Sep Oct Nov
25ET Workshop12‐Mar‐2010
Air temp‐1‐inch Water temp
12.0
14.0
8.0
10.0
, mm
d1
Jun-Jul
Aug
4 0
6.0
Eva
pora
tion Aug
Sep
Oct
2.0
4.0NovDec
0.0
0 1 10 100 1000Upwind fetch of irrigated grass, m
26ET Workshop12‐Mar‐2010
ObstructionsObstructions
• FixedFixed– buildings
shelter belts– shelter belts
– other (shown in previous example)
V i bl• Variable– adjacent corn field (most common), can have a
j ff tmajor effect
– weeds and other adjacent crops
12‐Mar‐2010 ET Workshop 27
OTHER ESTIMATING METHODSOTHER ESTIMATING METHODS
• Aerodynamic (used mainly on large water bodies)y ( y g )• Energy balance (requires detailed measurements)• Combination methods: Penman (1948, 1956, 1963); Penman‐Monteith (1965); Priestley‐Taylor (1972)
• All require estimating net radiation using standard equations and estimating energy storage (moreequations and estimating energy storage (more difficult for deep water bodies)
• Reference ET x coefficient (E = ETo x Kw)( o w)– for shallow water bodies– for ice‐free water bodies
28ET Workshop12‐Mar‐2010
ENERGY STORAGE RATESENERGY STORAGE RATES
• Difficult to quantify without measurementsDifficult to quantify without measurements
• Example rates of storagek t f 5 t 10 MJ 2 d 1– peak rates can range from 5 to 10 MJ m‐2 d‐1
– equivalent to 2 to 4 mm d‐1 evaporation
• Example rates calculated from lake studies– Pretty Lake in Indiana
– Williams Lake in Minnesota
12‐Mar‐2010 ET Workshop 29
Reported Energy Storage Rates - Pretty Lake (63-65) & Williams Lake (82-86)
10.0
15.0
d-1
0.0
5.0
t, M
J m
-2 d
-10.0
-5.0
0 30 60 90 120 150 180 210 240 270 300 330 360
Q
0 30 60 90 120 150 180 210 240 270 300 330 360
Day of Year
Pretty Lake Williams Lake Poly. (Pretty Lake) Poly. (Williams Lake)y y ( y ) y ( )
30ET Workshop12‐Mar‐2010
ASCE‐EWRI REFERENCE ETASCE EWRI REFERENCE ET
• ASCE‐EWRI (2005) and Allen et al (1998)ASCE EWRI (2005) and Allen et al. (1998)
• ETref x coefficient for open ice‐free water (Kw)
h i f h ( ) d 1• where ETref is for short grass (ETos), mm d‐1
• First check input weather data for quality
0.408 Δ(Rn ‐ G) + γ [900/(T + 273)] u2 (es ‐ ea)ET f = ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ETref = ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
Δ + γ (1 + 0.34 u2)
31ET Workshop12‐Mar‐2010
EXAMPLE – HOME LAKE, COEXAMPLE HOME LAKE, CO
• Location San Luis ValleyLocation San Luis Valley– Elevation 2297 m (7536 ft) above sea level
Average depth about 1 5 m (5 ft)– Average depth, about 1.5 m (5 ft)
• Estimated energy storage
• Estimated evaporation– May‐October
– ETref x Kw also agrees with PM in November
• Results (May‐October)( y )
32ET Workshop12‐Mar‐2010
0.5
1.0
0.0
m2 d
-1
-0.5
Qt,
MJ
-1.5
-1.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Est-Qt
33ET Workshop12‐Mar‐2010
8.0Home Lake, Alamosa, CO
6 0
7.0
8.0
5.0
6.0
p, m
m d
-1
3.0
4.0
imat
ed e
vap
1.0
2.0Est
0.0
Apr May Jun Jul Aug Sep Oct
E - PM E = ETo x 1.10
34ET Workshop12‐Mar‐2010
ROHWER’S CLASS A PAN COEFFICIENTS
• K by months for Colorado:Kp by months for Colorado:
• Based on mean ratios (polynomial)A 0 60 A t 0 75– Apr 0.60 August 0.75
– May 0.63 September 0.78
– June 0.67 October 0.77
– July 0.71
– Average, April‐October 0.70
35ET Workshop12‐Mar‐2010
ESTIMATED EVAPORATION HOME LAKE – MAY‐OCT.
• PM Penman NWS‐33 ET f x 1.10PM Penman NWS 33 ETref x 1.10
• mm
• (inches)• (inches)
• 894 906 890 892
• (35.2) (35.7) (35.0) (35.1)
• Percent of PM
• 100 101 100 99.8
• All give similar values for May through Octoberg y g
36ET Workshop12‐Mar‐2010
ESTIMATED EVAPORATION ( )LAKE BERRYESSA (3 YR AVG)
• PM Penman P‐T USBR originalg• mm• (inches)• 1,325 1,425 1,277 955• (52.2) (56.1) (50.3) (37.7)• 100 108 96 72• The same Rn and Qt used for first three methodsV l fi ff f “ i ”• Values confirm effects of “poor pan site”
• P‐T equation does not have wind speed
37ET Workshop12‐Mar‐2010