Source: UNIV OF IDAHO submitted to
PRODUCING AND INTEGRATING TIME SERIES OF GRIDDED EVAPOTRANSPIRATION FOR IRRIGATION MANAGEMENT, HYDROLOGY AND REMOTE SENSING APPLICATIONS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
HATCH
Reporting Frequency
Annual
Accession No.
0226143
Grant No.
(N/A)
Project No.
IDA01460
Proposal No.
(N/A)
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Jul 1, 2011
Project End Date
Jun 30, 2016
Grant Year
(N/A)
Project Director
Allen, R.
Recipient Organization
UNIV OF IDAHO
875 PERIMETER DRIVE
MOSCOW,ID 83844-9803
Performing Department
Biological and Agricultural Engineering
Non Technical Summary
Evapotranspiration (ET) is the second largest component of hydrologic systems and water balances, following precipitation, and is the driving component for irrigation water requirements (IWR) of agricultural crops. Quantifying ET for specific crops and regions is required for design of irrigation systems, basin water balance estimates, irrigation water management, improvement of crop yields and water-use efficiency, and review and litigation of water right applications and disputes; all of which are receiving more and more high priority attention. Current methods for estimating ET and IWR across the US and among federal and state entities are 1) typically based on sparse weather station data, some of which are in dry, nonevaporating environments; 2) have incomplete data for applying the better, physics-based ET equations; and 3) are not consistent among regions nor governmental entities and/or are not what are generally considered to be state-of-the-art. Over the past 10 to 20 years, an alternative to the traditional use of weather station based historical weather data for establishment of ET and IWR methods has become available, with the advent of gridded historical weather data derived from sophisticated land data assimilation systems (LDAS) operated by NOAA's National Centers for Environmental Prediction (NCEP) and the National Science Foundation sponsored National Center for Atmospheric Research (NCAR). However, the use of LDAS data to estimate ET and irrigation water requirements presents the challenge of containing artifacts in temperature, humidity and wind speed that stem from the dry environments from which assimilated weather data often originate, especially in the western US where ET demand can greatly exceed precipitation input. It is shown that use of air temperature and humidity data collected from non-irrigated settings can cause overestimation of reference ET by as much as 20 to 25% by ignoring the influence of feedback and conditioning of the equilibrium boundary layer (EBL) by evaporative cooling that occurs over irrigated agriculture. Reference ET is the ET from a defined reference surface (crop) that is actively growing, not limited by soil moisture, and is at full ground-cover and has defined vegetation height, surface conductance, and aerodynamic roughness. Reference ET is used to approximate the upper limit of ET expected from extensive well-watered surfaces. The proposed conditioning approach is considered to be revolutionary in transforming the gridded LDAS weather data sets into data sets that describe weather conditions that would occur over evaporating surfaces, thereby removing biases in reference ET estimates. The approach will push and evolve the state of the art in estimating reference ET over a wide range of land surfaces and will improve the value of ET estimates for irrigation water planning and management. The ET product will rectify current errors and biases committed by current applications of these weather data products for water management.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
1320210205010%
1320210207030%
1320430205020%
4050210207020%
4050420207020%
Knowledge Area
132 - Weather and Climate; 405 - Drainage and Irrigation Systems and Facilities;

Subject Of Investigation
0210 - Water resources; 0420 - Weather; 0430 - Climate;

Field Of Science
2070 - Meteorology and climatology; 2050 - Hydrology;
Goals / Objectives
The goal is to 1) develop means to transform gridded (3-hourly and daily) North American Regional Reanalysis (NARR) and North American Land Data Assimilation System (NLDAS) weather data over historical time series into "conditioned" weather data series that can be used to compute gridded reference evapotranspiration (ET) representing the special and specific equilibrium conditions that will nearly always be experienced over irrigated surfaces and 2) make these gridded reference ET data sets available for use in irrigation water management and planning, for hydrological studies, and for interpolating between satellite-based energy balance determinations of actual evapotranspiration, for example those produced by the University of Idaho METRIC model. Gridded estimates of reference ET are critical inputs to these satellite-based processes. Reference ET is defined as the ET expected from a well-watered, fully vegetated surface having defined properties of albedo, surface conductance and aerodynamic roughness and is used to approximate the upper limit of ET expected from extensive well-watered surfaces. Objectives are to: 1. Develop the means to transform gridded (3-hourly and daily) NARR and NCEP weather data over historical time series into `conditioned' weather data series that can be used to compute gridded reference evapotranspiration representing the equilibrium conditions associated with irrigated surfaces 2. Investigate and confirm the accuracy and extent of bias in the gridded data sets by extensive comparison against weather data measured over well-watered, vegetated surfaces. 3. Test the conditioning of the gridded weather data time series by comparing against hourly weather data measured over well-watered, vegetated surfaces for a number of locations throughout the United States. 4. Develop, test and refine a method for calculating `standardized', `reference' net radiation on slopes (in mountainous terrain) at the 12 km grid scale. 5. Calculate hourly and 24-hour reference ET for the time series extending from 1979 - 2008 at 12 km grid over the 17 western states using the conditioned weather data and the ASCE-EWRI (2005) standardized reference ET equation. 6. Develop a web-based delivery system to make the gridded reference ET data sets available to the public and for use in interpolating between satellite-based energy balance determinations of actual evapotranspiration. Products will include conditioned weather and reference ET across the North American continent that represent consistent and accurate assessments of water consumption by irrigated agriculture, that are based on scientifically sound and accepted state-of-the-art procedures, and that can be used as building blocks for follow-on studies. An outcome will include design and establishment of a web-based system on University of Idaho or partnering system, such as the Google Earth Engine system, to house and serve the conditioned weather and gridded reference ET data sets. The web sites will contain both scientific and lay-person languaged explanation of what the conditioned data sets represent, how they were established, and how they should be used.
Project Methods
The weather data "conditioning" procedure extrapolates air temperature (T), vapor (e) and wind speed (u) profiles to and from a blended height established 50 to few hundred meters above the surface. Ambient ET and sensible heat flux (H) are estimated based on complementary theory or soil water balance and general vegetation properties associated with the "ambient" (i.e., native, rainfed surface). The procedure is proposed for application to hourly or daily weather data from the NLDAS gridded system. The first process step determines energy balance components associated with, and that "explain" the weather data parameters of the gridded weather data. Each time step is evaluated independently. Monin-Obhukhov stability theory and buoyancy corrections are employed in making the latent and sensible heat flux estimates and vertical extrapolations. The second process step uses the fluxes of heat, H and vapor, LE for the ambient conditions represented by the gridded weather data to extrapolate T, e and u data to the blended height, where the characteristics for T, e and u are presumed to be independent of the specific characteristics for the underlying surface, and only characteristic to the larger region. During the study, sensitivity analyses will be made to determine best value(s) to use for the blended height. The third process step uses an iteratively developed reference ET estimate to determine energy balance components associated with the reference ET estimate. The reference estimate and near surface boundary layer are forced to be in equilibrium with the weather parameters at the blended height. Iteration is required during all computation steps. Preliminary analyses between desert and irrigated weather data near Kimberly, Idaho show great promise for successful conditioning. Results cooled desert T by up to 5 deg. C, increased near surface vapor content by a factor of 2, reduced wind speed by 20%, and reduced the computed reference ET by 20% compared to reference ET computed from the unconditioned data, and were validated by measurements over the irrigated surface. Gridded data from NLDAS will include T, e, u, solar radiation and precipitation. We propose to perform sensitivity of parameters and methodology by comparing conditioning results against weather data from agricultural weather networks having high integrity, including Agrimet data collected from Idaho and other Pacific Northwest states and from data sources in the SW and Midwest US. We will apply hourly and daily time step versions of the ASCE-EWRI reference ET equation. The conditioned weather and reference ET time series from 1979-near present will be made available via Google Earth Engine (a dialogue has been established with Google). The conditioning algorithm and application tool will be made public. A large benefit of the gridded reference data will be the establishment of means to support accurate computation of actual ET by various crop and vegetation types via traditional crop coefficient methods and/or satellite-based energy balance. Known biases of 20 to 30% in currently computed reference ET from the gridded weather systems will be largely eliminated.

Progress 07/01/11 to 06/30/16

Outputs
Target Audience:The direct target audiences are users of satellite-based remote sensing processes that utilize gridded weather data such as NLDAS, GLDAS and CFSV2 to estimate reference evapotranspiration (ET) that is used to both operate the energy balance process and to interpret ET in between satellite visits to account for effects of weather on ET rates. The gridded weather data sets require bias correction for aridity impacts via the developed conditioning processes. Other direct target audiences are users of point weather station data that are collected in dry settings such as from RAWS stations and many western airports. Those data sets benefit from conditioning prior to estimating reference ET and subsequently crop ET using crop coefficients. Indirect target audiences are users of ET and consumptive use information that is developed using the conditioned gridded and point weather data sets. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Five training courses on the use of the METRIC software for producing spatial ET maps from satellite imagery have been offered in the western US over the past 5 years. Those courses include description of gridded weather data sets, how to handle the data, where to access it, and how to evaluate the data for the need for conditioning. How have the results been disseminated to communities of interest?Computational procedures and computer code have been transferred to our collaborators at the Desert Research Institute (J. Huntington and others) and they have implemented the code in python for running on the NASA Nexus cloud computing system and on Google Earth Engine. DRI has also conducted additional testing of the conditioning. 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 upward bias of air temperature and downward bias of dewpoint temperature in NARR and NLDAS data sets has been demonstrated by comparing to ground-based point agricultural weather stations located in relatively well-watered settings. NLDAS, GLDAS, CFSV2 and GridMet gridded weather data sets are available on the Google Earth Engine. Those data are assessable from the Earth Engine playground and via web-based calls using python code.

Publications

  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Li, H., Shen, Y., Yang, P., Zhao, W., Allen, R.G., Shao, H. and Lei, Y., 2015. Calculation of albedo on complex terrain using MODIS data: a case study in Taihang Mountain of China. Environmental Earth Sciences, 74(7), pp.6315-6324.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Kilic, A., Allen, R., Trezza, R., Ratcliffe, I., Kamble, B., Robison, C., & Ozturk, D. (2016). Sensitivity of evapotranspiration retrievals from the METRIC processing algorithm to improved radiometric resolution of Landsat 8 thermal data and to calibration bias in Landsat 7 and 8 surface temperature. Remote Sensing of Environment, 185, 198-209.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Ortega-Far�as, S., Ortega-Salazar, S., Poblete, T., Kilic, A., Allen, R., Poblete-Echeverr�a, C., ... & Sep�lveda, D. (2016). Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV). Remote Sensing, 8(8), 638.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Hendrickx, J. M., Allen, R. G., Brower, A., Byrd, A. R., Hong, S. H., Ogden, F. L., ... & Umstot, T. G. (2016). Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools. JAWRA Journal of the American Water Resources Association, 52(1), 89-119.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Tasumi, M., Kimura, R., Allen, R. G., Moriyama, M., & Trezza, R. (2016). Development of the GCOM-C global ET index estimation algorithm. ????, 72(2), 85-94.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Huntington, J., K. McGwire, C. Morton, K. Snyder, S. Peterson, T. Erickson, R. Niswonger, R. Carroll, G. Smith, and R. Allen. (2016). "Assessing the role of climate and resource management on groundwater dependent ecosystem changes in arid environments with the Landsat archive." Remote Sensing of Environment 185:186-197.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Dhungel, R., Allen, R. G., & Trezza, R. (2016). Improving iterative surface energy balance convergence for remote sensing based flux calculation. Journal of Applied Remote Sensing, 10(2), 026033-026033.


Progress 10/01/14 to 09/30/15

Outputs
Target Audience:Idaho Department of Water Resources California State Water Resources Control Board US Geological Survey NASA Google, Inc. Irrigation Districts and State water resources management departments Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?We have provided two week long training courses on the METRIC evapotranspiration software that includes lectures and training on conditioning needs of gridded weather data products and handling and application of weather data products. How have the results been disseminated to communities of interest?We have reported progress to the American Society of Civil Engineers Committee on evapotranspiration in irrigation and hydrology. We have provided descriptions of the process to Google, Inc. as part of our implementation onto the Google Earth Engine. We have given presentations at the ASCE, ASABE and American Society of Agronomy meetings. What do you plan to do during the next reporting period to accomplish the goals?Complete programming of automated conditioning code.

Impacts
What was accomplished under these goals? Progress has been made toward an automated conditioning system that can recognize the relative dryness of the surface and then select the degree of conditioning of weather data that is required. We are using complementary theory and MODIS satellite imagery to rate the background, ambient evapotranspiration occurring from the surface. Based on those estimates, we increase the surface ET flux and recompute temperature, humidity and wind profiles.

Publications

  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Pereira, L. S., Allen, R. G., Smith, M., and Raes, D. (2015). Crop evapotranspiration estimation with FAO56: Past and future. Agricultural Water Management, 147, 4-20.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Reuter, D. C., C. M. Richardson, F. A. Pellerano, J. R. Irons, R. G. Allen, M. Anderson, M. D. Jhabvala, A. W. Lunsford, Montanaro, M., Smith, R.L. and Tesfaye, Z., 2015 "The Thermal Infrared Sensor (TIRS) on Landsat 8: Design overview and pre-launch characterization." Remote Sensing 7(1):1135-1153.
  • Type: Books Status: Awaiting Publication Year Published: 2015 Citation: Jensen, M.E. and R.G. Allen (ed.). 2015. Evaporation, Evapotranspiration and Irrigation Water Requirements. American Society of Civil Engineers Manuals on Engineering Practice, no. 70, 2nd edition. 690 p.


Progress 10/01/13 to 09/30/14

Outputs
Target Audience: State departments of water resources; US Bureau of Reclamation; US Geological Survey; Private Consulting companies involved in make water consumption assessments; USDA-NRCS to monitor and document water consumption from agriculture. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? We have collaborated with the US Bureau of Reclamation and with NOAA on adopting a weather conditioning and reference ET computation process into their operations. How have the results been disseminated to communities of interest? We have collaborated with the US Bureau of Reclamation and with NOAA on adopting a weather conditioning and reference ET computation process into their operations. We have reported progress to the American Society of Civil Engineers Committee on evapotranspiration in irrigation and hydrology. What do you plan to do during the next reporting period to accomplish the goals? Complete programming of automated conditioning code.

Impacts
What was accomplished under these goals? Progress has been made toward an automated conditioning system that can recognize the relative dryness of the surface and then select the degree of conditioning of weather data that is required.

Publications

  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Taylor, N. J., W. Mahohoma, J. T. Vahrmeijer, M. B. Gush, R.G. Allen, J. G. Annandale. 2014. Crop coefficient approaches based on fixed estimates of leaf resistance are not appropriate for estimating water use of citrus. Irrigation Science 1-14
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Dhungel, R., Richard G. Allen, Ricardo Trezza, Clarence W. Robison. 2014. Comparison of Latent Heat Flux Using Aerodynamic Methods and Using the PenmanMonteith Method with Satellite-Based Surface Energy Balance. Remote Sensing 6:8844-8877.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: P��as, Isabel, Teresa A. Pa�o, M�rio Cunha, Jos� A. Andrade, Jos� Silvestre, Ad�lia Sousa, Francisco L. Santos, Lu�s S. Pereira, Richard G. Allen. 2014. Satellite-based evapotranspiration of a super-intensive olive orchard: Application of METRIC algorithms. Biosystems Engineering 128:69-81.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Roy, David P., M.A. Wulder, T.R. Loveland, C.E. Woodcock, R.G. Allen, M.C. Anderson, D. Helder, J.R. Irons, D.M. Johnson, R. Kennedy, [......], V. Kovalskyy, P.Z. Lee, L. Lymburner, J.G. Masek, J. McCorkel, Y. Shuai, R. Trezza, J. Vogelmann, R.H. Wynne, Z. Zhu. 2014. Landsat-8: science and product vision for terrestrial global change research. Remote Sensing of Environment 145:154-172.
  • Type: Journal Articles Status: Awaiting Publication Year Published: 2014 Citation: Hendrickx, J.; Allen, R.; Brower, A.; Hong, S.; Ogden, F. Trezza, R.; Nawa, P.; Robison, C.; Toll, D.; Wilson, J.. 2014. Benchmarking Optical/Thermal Satellite Imagery for Estimation of Evapotranspiration and Soil Moisture in Decision Support Tools. J. Am. Water Resources Assoc. (JAWRA). (in press).
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Hong, S.-H., J. M. H. Hendrickx, J. Kleissl, R. G. Allen, W. G. M. Bastiaanssen, R. L. Scott, and A. L. Steinwand. 2014. Evaluation of an extreme-condition-inverse calibration remote sensing model for mapping energy balance fluxes in arid riparian areas. Hydrol. Earth Syst. Sci. 11, 13479-13539,


Progress 01/01/13 to 09/30/13

Outputs
Target Audience: Professionals who produce estimates of evapotranspiration and water consumption of irrigation water by vegetation. Scientists and professionals who employ satellite-based remote sensing. Consulting engineers, university students, federal and state government agencies involved in water resources management and research. Users of irrigation scheduling programs that may use estimates of water consumption based on weather data, users of gridded weather data sets that may not reflect well-watered environments, but who require estimates of ET from well-watered agricultural conditions; modelers of climate change impacts on crop water requirements. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Training courses on METRIC remote sensing of ET (Twin Falls, ID, Feb. 2013); Training course on applying reference ET methods and crop coefficients using gridded weather data and assessment of needs to condition weather data (Boulder, CO, March 2013). How have the results been disseminated to communities of interest? training courses; presentations at the American Society of Agronomy meeting; presentation at the American Meteorological society; presentation to the USGS/NASA Landsat Science Team What do you plan to do during the next reporting period to accomplish the goals? Finish the development of computer code that can be operated with little or no human intervention, regarding the decision on whether weather data require adjustment via the conditioning process.

Impacts
What was accomplished under these goals? A procedure has been coded and is being test to adjust measured air temperature, humidity and wind speed data from weather stations or to adjust data from gridded weather data sets such as NLDAS and NARR data sets to compensate for collection or ingestion of data collected in dry, nonirrigated settings so that the date better reflect values that would be expected to occur under irrigated conditions. So far, results look promising. Inputs to the process are precipitation and estimated irrigation. The estimation of irrigation is somewhat difficult. Research is being conducted to determine if the process can be trained to recognize when data are collected in a well-watered setting without knowledge of irrigation inputs.

Publications

  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Allen, R.G., B. Burnett, W. Kramber, J. Huntington, J. Kjaersgaard, A. Kilic, C. Kelly, R. Trezza. 2013. Automated Calibration of the METRIC-Landsat Evapotranspiration Process. J. Am. Water Resources Assoc. 49(3):563-576.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Allen, R.G., R. Trezza, A. Kilic, M. Tasumi, H. Li. 2013. Sensitivity of Landsat-scale energy balance to aerodynamic algorithms in mountains and complex terrain. J. Am. Water Resources Assoc. 49(3):592-604.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Morton, C.G., J.L. Huntington, G.M. Pohll, R.G. Allen, K.C. McGwire, S.D. Bassett. 2013. Assessing Calibration Uncertainty and Automation for Estimating Evapotranspiration from Agricultural Areas Using METRIC J. Am. Water Resources Assoc. 49(3):549562.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Burkhalter, J.P., T.C. Martin, R.G. Allen, J. Kjaersgaard, E. Wilson, R. Alvarado, and J.S. Polly. 2013. Estimating Crop Water Use via Remote Sensing Techniques vs. Conventional Methods in the South Platte River Basin, Colorado. J. Am. Water Resources Assoc. 49(3):498517.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Trezza, R., R.G. Allen, and M. Tasumi. 2013. Estimation of Actual Evapotranspiration along the Middle Rio Grande of New Mexico Using MODIS and Landsat Imagery with the METRIC Model Remote Sens. 5(10):5397-5423; doi:10.3390/rs5105397


Progress 01/01/12 to 12/31/12

Outputs
OUTPUTS: Gridded 3-hourly air temperature and 3-hourly vapor pressure from the North America Regional ReAnalysis (NARR) data set and North American Land Data Assimulation System (NLDAS) data set, have been retrieved for much of the western United States. Data from these gridded data sets have been compared to measured data from irrigated agricultural weather sites and desert sites including grid cells located near Twin Falls and Ashton, Idaho. The comparisons show close correspondence between the two data sets when close to an assimilation point and less correspondence and larger bias when far from an assimilation point. The NARR temperature overstated Agrimet air temperature by up to 5 oC, and the vapor pressure (i.e., near surface water vapor content) was understated by one-half, due to the impact of assimilation of weather data from dry airport types of locations. These types of outcomes are common, and cause overestimation of reference ET by up to 30%. A set of conditioning algorithms have been developed and tested to bring NARR and NLDAS data into closer agreement with that anticipated in an irrigated environment. The algorithms are based on blending height theory and equilibrium profiles and couple water availability conditions of the soil with fluxes and scalar profiles above those surfaces. A blending height at 50 to 200 m was tested to explore the sensitivity of profile response when conditions were fixed at the blending height and the surface conditions veried. The ASCE Penman-Monteith method is used to estimate fluxes from a well-watered surface. Gridded NARR data were compared to ET and sensible heat (H) fluxes produced by the University of Idaho METRIC satellite-driven surface energy balance. Surface temperature estimated by extrapolating 30 m air temperature from NARR to the surface using H fluxes from METRIC matched surface temperature measured by the Landsat satellite to within a few degrees for grass rangeland and irrigated agriculture, indicating relatively good robustness of the profile procedures. Results for sagebrush areas had more error caused by the influence of the sparse brush systems on roughness and near surface aerodynamic exchanges. PARTICIPANTS: Dr. Richard G. Allen, PI leads the theoretical and computational developments. Students include Ph.D. student Ramesh Dhungel, MS student Bibha Dhungara, MS student Jeremy Greth, MS student John Stewart. Post-docs include Dr. Ricardo Trezza and Wenguang Zhao. Technician Clarence Robison provides computer and coding support. Collaborators include Dr. Justin Huntington of Desert Research Institute, Dr. Jan Hendrickx of New Mexio Tech., and Dr. Ayse Kilic of Univ. Nebraska, and the US. Bureau of Reclamation, US National Weather Service, US Geological Survey. TARGET AUDIENCES: Users of irrigation scheduling programs that may use estimates of water consumption based on weather data, users of gridded weather data sets that may not reflect well-watered environments, but who require estimates of ET from well-watered agricultural conditions; modelers of climate change impacts on crop water requirements. PROJECT MODIFICATIONS: No changes

Impacts
Initial findings suggest that it may be possible to develop a nearly automated procedure to adjust air temperature, vapor pressure and wind speed data from the gridded NLDAS and NARR data sets or from surface data collected in dry, nonirrigated settings so that the date better reflect values that would be expected to occur under irrigated conditions. This adjustment is important when using the data to estimate reference crop evapotranspiration that, by definition, represents the expected flux of water vapor from a well watered, vegetated surface of a defined vegetation type where feedback between the surface fluxes and air properties near the surface is considered. The conditioning procedure is under review and consideration by the National Weather Service for employment in calculation software for reference ET using data generated during near-time weather forecasting.

Publications

  • Rosa, R.D., P. Paredes, G. C. Rodrigues, I. Alves, R.M. Fernando, L.S. Pereira, R.G. Allen. 2012. Implementing the dual crop coefficient approach in interactive software. 1. Background and computational strategy. Agricultural Water Management 103:8-24.
  • Rosa, R.D., P. Paredes, G. C. Rodrigues, R.M. Fernando, I. Alves, L.S. Pereira, R.G. Allen. 2012. Implementing the dual crop coefficient approach in interactive software: 2. Model testing. Agricultural Water Management 103:62-77.
  • Santos, C., I.J. Lorite, R.G. Allen, M. Tasumi. 2012. Aerodynamic Parameterization of the Satellite-Based Energy Balance (METRIC) Model for ET Estimation in Rainfed Olive Orchards of Andalusia, Spain, Water Resources Management 26(11):3267-3283.
  • Tasumi, M., A. Fujii, R. Kimura, M. Moriyama, R.G. Allen. 2012. Estimation of global ET-Index from satellite imagery for water resources management. Proc. SPIE 8524, Land Surface Remote Sensing, 85240K (November 21, 2012); doi:10.1117/12.976283
  • Carrasco-Benavides, M., S. Ortega-Farias, L.O. Lagos, J. Kleissl, L. Morales, C. Poblete-Echeverria, R.G. Allen. 2012. Crop coefficients and actual evapotranspiration of a drip-irrigated Merlot vineyard using multispectral satellite images. Irrigation Science, 30(6):485-497.
  • Frederiksen, H.D., R.G. Allen, C.M. Burt, and C. Perry. 2012. Responses to Gleick et al. (20112. Gleick, P.H., Christian-Smith, J. and Cooley, H. 2011. Water-use efficiency and productivity: rethinking the basin approach. Water International, 36(7): 784-798. in Water International. Special Issue: Has Water Privatization Peaked The Future of Public Water Governance, 37(2): 183-197.
  • Ryu, J.H., B. Contor, G. Johnson, R. Allen, J. Tracy. 2012. System Dynamics to Sustainable Water Resources Management in the Eastern Snake Plain Aquifer Under Water Supply Uncertainty. JAWRA Journal of the American Water Resources Association 48(6):1204-1220.
  • Pocas, I., M. Cunha, L.S. Pereira, R.G. Allen, 2012. Using remote sensing energy balance and evapotranspiration to characterize montane landscape vegetation with focus on grass and pasture lands. International Journal of Applied Earth Observation and Geoinformation. 21:159-172.


Progress 01/01/11 to 12/31/11

Outputs
OUTPUTS: Comparisons of 3-hourly air temperature and 3-hourly vapor pressure from the North America Regional ReAnalysis (NARR) data set, which is similar to the NLDAS data set, have been compared to measured data from irrigated agricultural weather sites for grid cells located near Twin Falls and Ashton, Idaho during a period during May, 2008. While there is close correspondence between the two data sets, which is a very positive indication of good assimilation of general weather data on a local scale, the NARR temperature overstate the Agrimet air temperature by up to 5 oC, and the vapor pressure (i.e., near surface water vapor content) was understated by one-half, due to the impact of assimilation of weather data in the NARR (and NLDAS) gridded data sets from dry (airport, etc.) stations. These types of outcomes are common, and again, cause overestimation of reference ET by up to 30%. A set of conditioning algorithms have been further developed and tested to bring the NARR and NLDAS data into closer agreement with that anticipated in an irrigated environment. The algoritms are based on blending height theory and equilibrium profiles. PARTICIPANTS: Dr. Richard G. Allen, PI leads the theoretical and computational developments. Students include Ph.D. student Ramesh Dhungel, MS student Bibha Dhungara, MS student Jeremy Greth. Post-docs include Dr. Ricardo Trezza and Wenguang Zhao. Technician Clarence Robison provides computer and coding support. Collaborators include Dr. Justin Huntington of Desert Research Institute, Dr. Jan Hendrickx of New Mexio Tech., and Dr. Ayse Kilic-Irmak of Univ. Nebraska, and the US. Bureau of Reclamation. TARGET AUDIENCES: Target audiences are users of reference evapotranspiration information over large spatial areas. These include users of satellite-based remote sensing processes, irrigation managers, ground-water managers, surface water managers and attorneys. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
We are getting close to being able to produce, from NARR and NLDAS data sets, weather data that are suited for estimating consumptive irrigation requirements for crops in irrigated environments. These estimates are 10 to 20% lower than those obtained using the original, unconditioned gridded data.

Publications

  • No publications reported this period