Progress 07/01/12 to 06/30/15
Outputs
Target Audience:Agricultural water conservation agencies and districts, farmers, agricultural consultants, agricultural water management professors and students. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Besides training the doctoral student, a technical personel operating the AVRC farm were trained in instrumentation installation and operation as well as in data retrieval, storage, and pre-processing. How have the results been disseminated to communities of interest?Through conferences as reported in previous periods (reports) and presentations at Colorado State University. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
The 2005ASCE-EWRI Standardized Reference Evapotranspiration (ET) Penman-Monteith (PM) equationwas evaluated using a monolithic precision weighing lysimeter. Hourly alfalfa ET calculations were performed and compared withlysimeter ET. The sum of the hourly ET was used to compare withmeasured daily ET from lysimeter as well.The research was carried out at the Colorado State University- Arkansas Valley Research Center, Rocky Ford, Colorado. Data from 2009 to 2012were used. The performance evaluation of the PM equation was done for different atmospheric stability conditions. The statistical analysis included themean bias error (mbe), root mean squareerror (rmse), linear regression slope-intercept (and goodness of fit), and the index of agreement. The evaluation was done using days where the alfalfa was at reference conditions andfor different cutting cycles. The results showed that the ASCE EWRI ET equation underestimated measured ET forstable atmospheric condition. The ET comparison was better forunstable atmospheric condition. However,scattered ET points were observed forneutral atmospheric conditions. Nevertheless, the ASCE EWRI ET model performed well,for daily time steps, for years 2009, 2010 and 2011. The ET model did not perform as wellwasin 2012;which was an extreme hot and dry year that was thought to have causedsevere heat advection. It was also found that the ASCE EWRI ETequation overestimated ET forthe first alfalfa cutting cycle and the slightly underestimated ET for thesecond, third and fourth cutting cycles. Regarding the evaluation of the recursive method for estimating ET. The recursive combination method (RCM) is different than the explicit combination method (ECM, like the Penman Monteith method discussed above). Data from 2009 to 2012 wereused for the analysis. The result showed that RCM performed better than the ECM, for all the years in the study, when compared to lysimetric alfalfa ET measurements. Furthermore,the atmospheric stability correction did not improve the ET estimates using the RCM.The assumptions associated with the Penman Monteith equation most probable caused theunderperformance of ECM compared to the RCM. This results suggests that the assumption of neutral atmospheric condition in the calculation ofthe aerodynamic resistance, for a well irrigated alfalfa field, is a valid argument. For 2009, the linear regressionslope (between estimated and measured) for RCM was 0.98 while for ECM was 0.96. The mean biaserror foralfalfa ET estimationwas - 2.7% for RCMwhile for ECM was - 4.2%. For data from 2010,RCM performed better than the ECM. The slope of the linear regression linefor RCM wass 0.99 and for ECM wass 0.96. The ET mean biaserror for RCM was close to zero while for ECM it was-3.2 %;which suggests that the ECM approach underestimated ET by 3.2 %. As in the previous year, the index of agreement and Nash Sutcliffe coefficient of efficiency are very good for both equations.Similarly, in 2011,RCM performed better than the ECM. The slope for RCM was 0.99 while for ECM was 0.95. The mean biaserror for RCM was close to zero while for ECM was - 2.2 %. This may meanthat RCM there could be evidence that this method could be usedin place of the ECMET type of methods to improve the estimation of alfalfa ET. However, the root mean square error for RCM was slightly larger, 28.6%, than thatfor ECM (26.1%).As forthe previous years, the index of agreement and Nash Sutcliffe coefficient of efficiency were very good for both equations. For2012 data,the slope for RCM was 0.83 while for ECM was 0.79. The mean biaserror for RCM was - 7.1% while for ECM was - 11.3%. Thus a largernderestimation of ET was found in2012 compared to the previous years. The2012 year was the hottest and driest year and so there was more heat advected from the nearby warmer and drier regions.Also, as in the previous years, RCM performed better (less ET underestimation) compared to the ECM (more ET underestimation). Monolithic weighing lysimeters are considered as one of the most accurate methods to measure crop water evapotranspiration (ET) rates. The advantage of lysimeter compared to other ET measurement methods is that it can measure ET accurately andprecisely using water mass loss data records inthe soil water balance method.This study explored the possible inaccuracies associated with the lysimeter ET measurement method. Large precision monolithic weighing lysimeters were found to be non-representative of the entire field when the lysimeter surface condition was different than the field surface condition surrounding them. Based on the analysis of alfalfa ET collected from2009 to 2013 from the experimental alfalfa lysimeter field of Colorado State University (CSU) Arkansas Valley Research Center (AVRC), near Rocky Ford, Colorado, it was found that in most of the occasionscrop biomass and soil moisture content was larger inside the lysimeter box compared to the rest of the field. This reality caused larger alfalfa evapotranspiration (ETr) rates at the lysimeter box compared to the micrometeorological based ET measurement methods (viz. large aperture scintillometer (LAS), eddy covariance (EC) and surface aerodynamic tower (SAT)), which measured ETr from a larger footprint than the lysimeter. LAS, EC and SAT measurements of ETr agreed reasonably well among each other. This result suggested that the lysimeter ETr overestimated the alfalfa field ET and needed to be adjusted based on the micrometeorological methods to make it representative of the alfalfa field ET. In addition, when the air was drier, there was more discrepancy (up to 40 % mean biaserror in 2012) between lysimeter ETr and the micrometeorological methods. On the other hand, when the weather was humid, as in years 2009 and 2010, the agreement of lysimeter ETr with micrometeorological methods was good. The performance in 2009 was best among all the studied years, which is attributed to the good rainfall and the larger alfalfa field compared to the other years. Regarding the use of the aerodynamic temperature (To) in estimating ET. In 2009, the ASCE Standardized ETr equation (M1)worked very well when compared to lysimeter ETr values. The slope of the linear regressionwas 0.98, intercept was 0.01 and R2 was 0.96,mbewas 0, rmsewas 0.06 mm/h (19.5%), index of agreement (IA)was 0.99 and the Nash-Sutcliffe (NS) coefficient of efficiency was 0.96. In contrast, when To was used inthe ASCE Penman Monteith (PM,1965) or M2 methodthe statistical indicators were slightly worse. The slope was 0.9, intercept was 0.01 and R2 was 0.9, mbewas -0.02 mm/h (-5.4%), rmsewas 0.1 mm/h (31.6%), IA0.97 and the NS0.89.In 2010, forM1 the slope was 1.07, intercept was 0.01 and R2 was 0.97, mbe0.02 mm/h (5.3%), rmse0.06 mm/h (19.2%), IA0.99 and NS0.96. For M2the slope was 0.97, intercept was 0.04 and R2 was 0.93, mbe0.03 mm/h (8.6%), rmse0.09 mm/h (29.4%), IA0.98 andNS0.91. The ASCE Standardized ETr equation performed better than the ASCE PM with To,in 2010. For2011, for M1 the slope was 1.11, intercept was 0.03 and R2 was 0.97, mbe0.06 mm/h (20.8%), rmse0.09 mm/h (33%), IA0.98 and the NS0.91. For M2, the slope was 1.08, intercept was 0.04 and R2 was 0.91, mbe0.07 mm/h (24.2%), rmse0.13 mm/h (45.2%), IA0.96 and the NS 0.82. For 2012 M1,the slope was 1.11, intercept was 0.03 and R2 was 0.95, mbe0.07 mm/h (19.7%), rmse0.11 mm/h (33.6%), IA0.97 and NS0.87. For M2, the slope was 0.89, intercept was 0.05 and R20.5, mbe0.01 mm/h (3%), rmse0.3 mm/h (83.9%), IA0.82 and the NS0.21. Although the bias was improved with the M2method, the rmsewashigh and the NS was llow. Hence in overall, the ASCE Standardized ETr equation performed better than ASCE PMwith Tomethod.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2015
Citation:
Abhinaya Subedi and Jos� L. Ch�vez (2015). "Crop evapotranspiration (ET) estimation models: A review and discussion of the applicability and limitations of ET methods", Journal of Agricultural Science, V7, No 6, 2015, Submitted on 23 Feb 2015, Accepted 10 Apr 2015, On-line publication 15 May 2015. ISSN 1916-9752, E-ISSN 1916-9760.
- Type:
Theses/Dissertations
Status:
Under Review
Year Published:
2016
Citation:
Abhinaya Subedi. "Modeling a Variable Surface Resistance (rc) for Alfalfa and Assessing the ASCE rc Performance in the Reference Evapotranspiration Equation." PhD Dissertation, Colorado State University.
- Type:
Journal Articles
Status:
Submitted
Year Published:
2016
Citation:
Abhinaya Subedi, Jos� L. Ch�vez, and Allan A. Andales (2016). "Performance Evaluation of the ASCE-EWRI Standardized Penman Monteith Evapotranspiration Equation in Southeastern Colorado." (Journal) Agricultural Water Management. Submitted to the Special Issue entitled Improving Agricultural Water Use Efficiency for Food Security.
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Progress 10/01/13 to 09/30/14
Outputs
Target Audience:
Nothing Reported
Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? The research provided opportunities to train the PhD student working under this project as well as to train an undergraduate student in data analysis. How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals? To complete the data analysis, discussion and conclusions of the RCM and ASCE EWRI ET methods in the context of the reference lysimeter ET data calibration phase. To integrate and summarize all findings of the project as well as to submit for publication in peer reviewed journals the main findings.
Impacts
What was accomplished under these goals?
The recursive combination method (RCM) to estimate evapotranspiration was applied for the two lysimeter fields in the CSU Arkansas Valley Research Center, Rocky Ford, CO for the years 2009, 2010, 2011 and 2012. The two lysimeter fields were designated as large lysimeter (larger one) and reference lysimeter (smaller one). In the large lysimeter, alfalfa was grown for 2009, 2010, 2011 and 2012 whereas the reference lysimeter had alfalfa grown since the fall of 2011. The comparison was performed for different atmospheric stability conditions (stable, unstable and neutral) when the crop was at reference condition (height close to 50 cm with no water stress). Hourly ET was calculated using the RCM method and results were compared with the measured ET obtained from the precision weighing lysimeter. Results (preliminary, as discussed below) indicated that the RCM under-estimated true hourly ET. The best fit linear regression equation was Y = 0.84 x + 0.03, R2=0.92. The associated statistical errors were MBE = - 0.04 mm/h (-9.7 %) and RMSE = 0.14 mm/h (32.1 %), and d = 0.97. However, this result was highly un-expected. A comparison of lysimeter ET (converted to latent heat flux (LE)) with micro-meteorological based LE below, Table 1) indicated that all micro-met stations under-measured ET equally or that the lysimeter over estimated LE. Table 1. Comparison of LAS, SAT and EC latent heat fluxes (LE) with lysimetric LE fluxes. Difference in LE values are presented in percent. LAS (Large Aperture Scintillometer) SAT (Surface Aerodynamic Temperature Tower, Profile Method) EC (Eddy Covariance) MBE RMSE d MBE RMSE d MBE RMSE d 2009 -8.6% 34.2% 0.97 -21.1% 53.7% 0.92 NA NA NA 2010 -11.0% 30.4% 0.97 -16.8% 50.5% 0.92 NA NA NA 2011 -36.1% 63.9% 0.85 -27.6% 58.9% 0.89 -27.6% 50.4% 0.91 2012 -18.6% 41.7% 0.95 -28.0% 47.0% 0.93 -24.7% 46.4% 0.93 2013 -44.4% 71.5% 0.84 -37.2% 57.5% 0.89 -28.1% 42.6% 0.93 Where: MBE is mean bias error, RMSE is root mean square error, and d is the index of agreement. The LE fluxes from LAS, SAT and EC resulted in similar values and were smaller in magnitude compared to the lysimeter LE fluxes. The apparent underestimation of the LE flux by LAS instrument ranged from 8.6% (in 2009) to 44.4% (in 2013). Similarly, the underestimation of the LE flux by the SAT method ranged from 16.8% (in 2010) to 37.2% (in 2013). Likewise, the underestimation of the LE flux by the EC method was consistent for all 3 years of the comparison period, varying slightly from 24.7% (in 2012) to 28.1% (in 2013). As all of the "micro-meteorological" methods mentioned above agreed well and all of them gave smaller LE fluxes, it can be infered that the lysimeter LE flux or ET rates may not be representative of the whole field. The difference in crop growth (height and biomass and uniformity, i.e. sparse conditions) inside and outside the lysimeter could probably be one of the reasons behind the discrepancy between LAS, SAT, and EC LE and lysimeter measurement of ET converted to LE. The footprint of these micro-met stations is large and within the extend of the alfalfa lysimeter field. However, the lysimeter box alfalfa is rather a "point" measurement. Furthermore, the lysimeter irrigation was more frequent than that of the entire field and most likely did not suffer from water stress, while the entire alfalfa field was not irrigated in its entirety due to the nature of the irrigation method (furrows with syphons) and the available water to irrigate that was rotated among other research fields and the lysimeter alfalfa field. Thus, it was decided that an evaluation of the lysimeter field crop height and canopy temperature spatial distribution was needed. In 2012, alfalfa ET rates measured with the lysimeter presented the largest discrepancy in relation to LAS, SAT and EC ET (LE) rates. Lysimeter LE readings were almost 30 percent higher than the micro-met methods that year. It was also observed that inside the lysimeter, soil moisture and crop biomass were larger and surface temperature was lower compared to the rest of the alfalfa field values. In the summer of 2012 and 2013, field campaigns started in both fields to measure crop height and crop surface temperature of the whole field based on a grid. A grid with 32 observation sites/points was layout with a spacing of each point of 30 m by 30 m for both alfalfa fields (large and smaller). Each point location was marked with a numbered flag a coordinates were taken with a GPS. The difference of temperature and crop height between each point in the grid and similar values at the lysimeter surface was calculated. It was found that the average crop height difference was up to 20 cm for both years, mainly due to sparse crop in some parts of the field. In 2012, the mean surface temperature in the lysimeter surface was up to 3.7 °C lower than in the average field surface temperature whereas in 2013, it was up to 1.4 °C lower. This result indicated that the alfalfa field surface conditions was not homogeneous and may have experienced some water stress while the alfalfa at the lysimeter was well irrigated and showed a taller crop evapotranspiring more vigorously. The LE readings obtained with the micro-met stations are believed to be more representative of the true alfalfa field LE than ET readings recorded by the lysimeter. Hence, it is necessary to correct (adjust) the lysimeter ET values based on the micro-met LE measurements (based on values from the three stations: LAS, SAT, EC) if a good evaluation of the ASCE EWRI standardize PM ET equation and of the recursive method is desired.
Publications
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Progress 10/01/12 to 09/30/13
Outputs
Target Audience: Water resources consultants, federal and state water resources engineers, farmers, university researchers (engineers and scientists). Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? A PhD student has been working directly in the project. He has learned the different methods and instrumentation (equipment) used (available) to measure and compute crop water use. Two hourly students have particpated in the field work by assisting in instrumentation setup and maintenance as well as in data collection. A field technician also has been involved in the project and has assisted by collecting, organizing, storing, and sending research data. Other activities in which the technician helped include equipment maintenance and troubleshooting. How have the results been disseminated to communities of interest? By participating in two water management related conferences (i.g., USCID and AGU Hydrology Days) and presenting research results. What do you plan to do during the next reporting period to accomplish the goals? The coded recursive method will be applied (run) to all data collected and alfalfa ET results will be evaluated with lysimetric data. The ASCE-EWRI (2005) alfalfa ET derived values will be compared to the resursive method alfalfa ET computed values and an algorithm to improve the ET estimation will be define. The role of the aerodynamic and surface/canopy temperatures, in the computation of alfalfa reference ET, will be determined.
Impacts
What was accomplished under these goals?
The research findings under this reporting period indicate that the crop water use model (ASCE EWRI) being evaluated underestimates the true magnitude of the alfalfa water use under the presence of hot and dry air and large wind speeds. Therefore, the improvement of this method will permit the improvement of crop water management, water resources management, and will result in better crop yields. Lysimetric data were processed to compute hourly and daily alfalfa crop water use or evapotranspiration (ET). The dataset processed contained data collected during the following years: 2009, 2010, 2011, and 2012. Similarly large aperture scintillometer data collected over the alfalfa surface were processed. Soil heat fluxes were computed for the same period. The ASCE-EWRI (2005) alfalfa reference ET Penman-Monteith method was coded and was applied to weather data collected over the alfalfa surface. The ASCE-EWRI (2005) method was evaluated with the processed lysimeteric data finding underestimation of alfafa water use mainly under advective environmental conditions and when the atmospheric stability was mainly stable. The recursive method to calculate alfalfa ET was coded in MS Excel.
Publications
- Type:
Journal Articles
Status:
Submitted
Year Published:
2013
Citation:
Rambikur, E.H., and Ch�vez, J.L. Assessing inter-sensor variability and sensible heat flux derivation accuracy for a large aperture scintillometer. Submitted to Sensors (Journal, peer-reviewed).
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2013
Citation:
Abhinaya Subedi, Jos� L. Ch�vez, and Allan A. Andales. (2013). Preliminary performance evaluation of the Penman-Monteith evapotranspiration equation in southeastern Colorado. In Proceedings of 33rd Annual American Geophysical Union (AGU) Hydrology Days 2013 Conference. Fort Collins, CO. March 25 - 27, 2013.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2013
Citation:
Abhinaya Subedi, Jos� L. Ch�vez and Allan A. Andales. (2013). Effects of Surface Non-Uniformity on Penman-Monteith Equation, USCID Water Management Conference, October 22-25, Denver, CO
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2013
Citation:
Allan A. Andales, Jose Luis Chavez, Lane Simmons and Michael Bartolo. (2013). Evapotranspiration Measurements Using Weighing Lysimeters: The Rocky Ford Experience. Symposium: Accuracy, uncertainty, and limitations of evapotranspiration quantification in agriculture. ASA, CSSA, & SSSA Int'l Annual Meeting, Nov. 3-6, 2013, Tampa, Florida.
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