Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands

Abstract

Abstract. Croplands are man-made ecosystems that have high net primary productivity during the growing season of crops, thus impacting carbon and other exchanges with the atmosphere. These exchanges play a~major role in nutrient cycling and climate change related issues. An accurate representation of crop phenology and physiology is important in land-atmosphere carbon models being used to predict these exchanges. To better estimate time-varying exchanges of carbon, water, and energy of croplands using the Simple Biosphere (SiB) model, we developed crop-specific phenology models and coupled them to SiB. The coupled SiB-phenology model (SiBcrop) replaces remotely-sensed NDVI information, on which SiB originally relied for deriving Leaf Area Index (LAI) and the fraction of Photosynthetically Active Radiation (fPAR) for estimating carbon dynamics. The use of the new phenology scheme within SiB substantially improved the prediction of LAI and carbon fluxes for maize, soybean, and wheat crops, as compared with the observed data at several AmeriFlux eddy covariance flux tower sites in the US mid continent region. SiBcrop better predicted the onset and end of the growing season, harvest, interannual variability associated with crop rotation, day time carbon uptake (especially for maize) and day to day variability in carbon exchange. Biomass predicted by SiBcrop had good agreement with the observed biomass at field sites. In the future, we will predict fine resolution regional scale carbon and other exchanges by coupling SiBcrop with RAMS (the Regional Atmospheric Modeling System).

Representing agriculture in Earth System Models: Approaches and priorities for development

“…Principle to this is the simulation of plant carbon assimilation, respiration, and transpiration of water. Many current LSMs use adaptations of the Faquhar-Ball-Berry model of coupled leaf-level photosynthesis and stomatal conductance-the solutions to which have proven robust for a range of environmental conditions-and a variety of scaling techniques to canopy level [Farquhar and von Caemmerer, 1982;Ball et al, 1987;Collatz et al, 1991;Cox et al, 1998;Lawrence and Slingo, 2004;Lokupitiya et al, 2009;Oleson et al, 2013;Kim et al, 2015;Liu et al, 2016]. Solving for photosynthesis and conductance requires numerous PFT-specific parameters, examples of which are shown in Kim et al [2015] for four PFTs in the Ent Terrestrial Biosphere Model, Table D1 [ Farquhar and von Caemmerer, 1982;Ball et al, 1987;Collatz et al, 1991;Luo et al, 2012;Oleson et al, 2013;Kim et al, 2015].…”

“…These parameterizations generally have dependencies on temperature, and use various growing degree day or heat accumulation formulations to determine the time to and the duration of particular growth phases. Many such crop PFTs and/or growth models have been developed, and can be as general as ''temperate cereals'' or as specific as oil palm Osborne et al, 2007;Lokupitiya et al, 2009;Levis et al, 2012;Fan et al, 2015;Liu et al, 2016]. For example, the Lund-Potsdam-Jena managed Land model (LPJmL)-a standalone DGVM-explicitly includes 13 agricultural PFTs, including 11 crops, and two managed grass types .…”

“…In their initial development, ESMs represented agriculture simply as generic crop-like grasses (sometimes distinguished by photosynthetic pathway) with an annual growth cycle [Levis, 2010]. However, recent progress now enables ESM simulations to include specific crops, cropping cycles, and management practices, as well as their regional and/or global distributions [e.g., Lokupitiya et al, 2009;Osborne et al, 2009;Levis et al, 2012;Drewniak et al, 2013;Cook et al, 2014]. On-going and new model intercomparison efforts [e.g., Lawrence et al, 2016b] will help further direct and focus ESM development in representing agriculture, while identifying robust climate impacts.…”

Investigating the impact of climate change on crop phenological events in Europe with a phenology model

“…The temperature will not drop below the crop specific threshold during the growing season except under some extreme weather conditions, such as hail. A similar method was used in other studies (Chmielewski and Koen 2000;Mitchell and Hulme 2002;Lokupitiya et al 2009). The mean temperature index was defined as follows:…”

“…The second group focuses on predicting crop planting and harvesting days on a large scale. These phenological models have been integrated into ecosystem models, such as the LPJmL (Bondeau et al 2007), Daycent (Stehfest et al 2007), SIBcrop (Lokupitiya et al 2009), ORCHIDEE-STICS (Smith et al 2010) and PIXGRO (Adiku et al 2006). The Daycent phenological model focuses on optimizing crop productivity, and it does not reflect the impact of climate on phenological events directly, and the LPJmL phenological model uses temperature and precipitation to predict planting day.…”