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USDA-ARS NSAR
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USDA-ARS NSAR and WSU established a long-term met and eddy covariance tower in 2017. Near-real time met data are sent to the NAL data repository as part of the LTAR efforts.
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https://www.reacchpna.org/sites/default/files/AR3_1.2.pdf Pixel classification: Classification, Stable, Dynamic, Unstable Urban, 1, 101, 202 Rangeland, 3, 103, 203 Forest, 4, 104, 204 Water, 5, 105, 205 Wetlands, 6, 106, 206 Barren, 7, 107, 207 Wilderness, 9, 109, 209 Annual, 11, 111, 211 Transition, 12, 112, 212 Grain-fallow, 13, 113, 213 Irrigated, 14, 114, 214 Orchard, 15, 115, 215 Agriculture, 50, 150, 250 Water and Other, 51, 151, 251
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Average estimated yields and associated CV values for current (2018) model runs. Based on work done by Harsimran Kaur et al in 2017. The following is from her thesis: Agro-ecological classes (AECs) of dryland cropping systems in the inland Pacific Northwest have been predicted to become more dynamic with greater use of annual fallow under projected climate change. At the same time, initiatives are being taken by growers either to intensify or diversify their cropping systems using oilseed and grain legume crops. The main objective of this study was to use a mechanistic model (CropSyst) to provide yield and soil water forecasts at regional scales which could compare fallow versus spring crop choices (flex/opportunity crop). Model simulations were based on historic weather data (1981-2010) as well as combined with actual year weather data for simulations at pre-planting dates starting in Dec. for representative years. Yield forecasts of spring pea, canola and wheat were compared to yield simulations using only weather of the representative year via linear regression analysis to assess pre-plant forecasts. Crop yield projections on pre-plant forecast date of Feb 1st had higher R2 with yield simulated using actual years weather data and lower CVs across the region as compared to forecasts based on historic weather data and other pre-season forecast dates (Dec. 1st and Jan. 1st). Therefore, Feb. 1st was considered the most reliable time to predict yield and other relevant outputs such as available water forecasts on a regional scale. Regional forecast maps of predicted spring crop yields and CVs showed ranges of 1 to 4367 kg/ha and 11 to 293% for spring canola, 72 to 2646 kg/ha and 11 to 143% for spring pea and 39 to 5330 kg/ha and 11 to 158% for spring wheat across study region for a representative year. These data combined with predicted available water after fallow and following spring crop yield as well as estimates of winter wheat yield reduction would collectively serve as information contributing to decisions related to crop intensification and diversification.
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Northwest Weather Service, Lind Station located near Lind, WA
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Northwest Weather Service, Palouse Conservation Field Station located at Palouse Conservation Field Station near Pullman, WA