Evapotranspiration and Irrigation Water Requirements for Washington State
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1 Evapotranspiration and Irrigation Water Requirements for Washington State R. Troy Peters, PE, PhD Extension Irrigation Specialist Washington State University Irrigated Ag. Research and Extension Cntr Prosser, WA Leigh Nelson, PE WA State Irrigation Engineer USDA NRCS Ephrata, WA
2 Definitions Consumptive Use Evapotranspiration (ETc) Effective Precipitation (Pe) Irrigation Water Requirements (IWR) IWR = ETc - Pe Historical Average ET
3 Estimating Crop Water Use (Evapotranspiration) Reference ET (Weather and climate) Water use of harvestable alfalfa Crop ET ET = K c c ET Crop Coefficient (Crop and growth stage) r
4 Uses for Avg. ET Estimates Irrigation system design Simple irrigation scheduling tools Evaporation pond/wetland design Water rights transfers Water rights adjudication / litigation Hydrologic modeling River basin planning and management.
5 Blaney-Criddle equation Published 1985 Last data 1982 Actual ET and crop coefficients hidden
6 New Revision More recent and complete historical weather data Latest ETr estimation techniques (ASCE standardized Penman-Monteith equations) Take into account humidity, wind, and solar radiation, elevation, latitude as well as temperature. Expanded station coverage Inclusion of actual ET separate from IWR Inclusion of information on the variability (probability) of estimation
7
8
9 Estimating Crop Water Use (Evapotranspiration) Reference ET (Weather and climate) Water use of harvestable alfalfa Crop ET ET = K c c ET Crop Coefficient (Crop and growth stage) r
10 Reference ET: From Weather Standardized ASCE Penman-Monteith ET ref Solar Radiation = ( R n Cn G) + γ T γ (1 + C u ) d 2 u 2 ( e Temperature Wind Speed s e a ) Humidity Credit: Richard Allen, University of Idaho
11 Historical Weather Data Sources 1. NCDC COOP Stations Best coverage/longest history (>100 yrs) Temperature and precipitation only 2. NCDC ASOS Full data set Airport Tarmacs RH data only 3. Agrimet Full data set and good locations Limited coverage 4. Washington AgWeatherNet (AWN) Full data set and good locations Growing coverage Limited data history (5-20 yrs)
12 White = COOP, Blue = AWN, Pink = AgriMet, Dot = In previous WIG
13 AWN Data Cleaning Plotted and looked at: Solar radiation plotted with calculated clear sky radiation Wind speed was plotted look for anomalies T dew plotted and compared with T min T max and T min plotted look for anomalies Seasonal total rainfalls compared year to year.
14 Strategy Applied the ASCE Penman Monteith for COOP (temp and precip only) Stations. Estimate missing Solar Radiation, using the Thornton-Running (1999) Wind is from nearby station using long-term historical monthly averages Dew Point Estimated from T min with offsets as needed. Calculate for full year not just growing season.
15 Data Corrections Manipulations Missing values in NCDC (COOP or MMTS) were treated as missing instead of 0. Out of bounds data was set to missing Solar radiation visually compared to theoretical clear sky radiation RH over 100% or less than 0% Temperatures greater than 160 deg F or less than - 60 deg F
16 Data Corrections Manipulations Missing data was interpolated from stations within a 50 km radius. Weighted average based on distance. Everything except precip. Missing set to 0. Still missing values were generated by ClimGen. ASOS stations used only for avg dewpoint interpolations in stations that didn t have RH data.
17 Way Out There Stations Many COOP (MMTS) stations weren t close enough (50 km; 30 miles) to be comfortable with interpolating data from full data stations. Hargreaves equation (temp only) was calibrated using nearest full data stations. This calibrated Hargreaves equation used to make estimates for these stations.
18 Data Corrections Manipulations Over 20 different full iterations using various methods/assumptions etc. to troubleshoot (each takes 3-6hrs computation time). Final results plotted and reviewed with Leigh Nelson Specific stations were excluded. No tweaking just removal. Removed stations are listed along with the reasons that they were excluded. Best station of a close group was retained. (Eliminate redundancy) Best = best data source, location, history, results or believability.
19 Variability and Weather Station Location Issues Uninterrupted wind Green and clipped grass For a long distance surrounding station. Ideal Represents Fully Irrigated Field
20 Agrimet
21 AgWeatherNet
22 AgWeatherNet
23 COOP (MMTS)
24 COOP (MMTS)
25
26
27 ASOS Stations
28 Estimating Crop Water Use (Evapotranspiration) Reference ET (Weather and climate) Water use of harvestable alfalfa Crop ET ET = K c c ET Crop Coefficient (Crop and growth stage) r
29 Crop Coefficient = ET/ET ref K c mid K c end K c K c ini /10/2013 Time of Season, days Credit: Richard Allen, UI
30 Crop Coefficients?
31 Crop Coefficients Thorough literature review. Started with Agrimet Based on field research using lysimeters in Kimberly, ID Similar climate to development area. Well documented sources Also some from FAO-56 Some from particular research projects.
32 Conversion for Use with ASCE Standardized Penman (Kimberly/ASCE)
33 Use Average R
34 Crop Coefficients Converted for use with the ASCE Standardized Penman-Monteith Converted to be based on CGDD (crop specific) instead of DOY Missing crops filled in from FAO-56 and others as documented
35 Existing WIG
36 New Full Penman-Monteith
37 Differences from Existing WIG Grass Seasonal ET
38 Summary In general, new estimates are 10-20% lower than existing estimates. Accuracy Based on the variability between stations that should have been the same, we feel that the results are within 10-15% of actual. No way to test this.
39 Year-to-Year Variability Questions? R. Troy Peters, P.E., Ph.D.
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