|ROCATELI, ALEXANDRE - Oklahoma State University|
|WEST, CHUCK - Texas Tech University|
|BRYE, KRIS - University Of Arkansas|
|POPP, MICHAEL - University Of Arkansas|
Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/30/2019
Publication Date: 1/27/2020
Citation: Rocateli, A.C., Ashworth, A.J., West, C.P., Brye, K.R., Popp, M.P., Kiniry, J.R. 2020. Simulating switchgrass biomass productivity using ALMANAC. I. Calibration of soil water. Agronomy Journal. 112:183-193. https://doi.org/10.1002/agj2.20054.
Interpretive Summary: Switchgrass, a perennial native grass that grows well under low nutrient and drought conditions, may be used to produce liquid fuels such as ethanol. A crop simulation model developed by USDA-ARS scientists, known as ALMANAC (Agricultural Land Management Alternative with Numerical Assessment Criteria), was designed to predict growth of various row crops, but has recently been expanded to include perennial crops, including switchgrass. One issue with accurate predictions is soil moisture estimations, considering perennial species have substantially greater rooting depths compared to annual crops. This research found that with alterations of model inputs, such as site specific parameters (rather than using default settings), ALMANAC was able to mimic switchgrass growth relative to observed data. Although, ALMANAC still needs to be refined to predict plant responses to drought. Once ALMANAC has been properly modified to predict switchgrass yield across diverse environments and under water-limiting conditions, it can be used to estimate regional biomass supplies for the development of bioenergy economies.
Technical Abstract: Soil water supply plays a key role in driving nutrient availability and thus, switchgrass (Panicum virgatum L.) yield, and is therefore an important parameter for accurate crop-model growth predictions. The ALMANAC (Agricultural Land Management Alternative with Numerical Assessment Criteria) model has simulated switchgrass growth with mixed results. Our objective was to develop and test a calibration for ALMANAC simulating soil water dynamics in a switchgrass (cv. Alamo) stand under Arkansas conditions. Soil volumetric water content profiles were measured daily in switchgrass from May 2009 to February 2013. Soil, crop, and weather input files were developed based on in situ measurements. After identifying the most sensitive parameters in SW simulation, a calibration method was proposed, and the parameters FFC, U, FC, SAN, SIL, pH, and GSI were modified. Daily SW simulation outputs from default and calibrated runs were contrasted to actual SW observations. Default d-index values were 0.28, 0.30, 0.40, and 0.41, and calibrated d-index values were 0.94, 0.89, 0.83, 0.81, respectively, for 2009, 2010, 2011, and 2012. Therefore, calibration improved water dynamic simulation accuracy. Calibration accuracy was greater in 2009 and 2010 than in 2011 and 2012. Lower RMSE of calibrated vs. observed SW data confirmed the elevated d-index values. Lower accuracy in later years was related to drought periods when ALMANAC was unable to mimic switchgrass drought adaption by lowering stomatal conductance (GSI).