Spatial variability of micrometeorological variables in a maize field: modeling results

Land surface models and crop growth models enhance our ability to understand and predict aspects of land-air interactions at varying scales. Until recently, these models could only be used separately to predict crop growth at large scales; Specific crop plant functional types and management practices have been absent from land surface models, while crop models have traditionally been designed to simulate single plants or plots. An agricultural version of the Integrated Biosphere Simulator (IBIS), commonly known as Agro-IBIS, has been developed recently in an attempt to merge our understanding of managed landscapes into a land surface model that can run on large-scale grids. Currently, Agro-IBIS includes modules for simulating maize, wheat, and soybean, with research ongoing to add switchgrass, miscanthus, and urban settings. While Agro-IBIS has shown skill at large scales (0.5º x 0.5º resolution) and single points, validations at scales in-between are non-existent due to instrumentation and time costs needed to collect data.

A 1 km² agricultural field in Ames, IA, known as the Iowa Validation Site (IVS), has been heavily instrumented as part of an effort to validate and calibrate remotely sensed values of soil moisture. The field utilizes a maize/soybean rotation (maize in 2009) and traditional tillage practices. The instrumentation includes soil moisture and temperature at 16 locations, wind speed above canopy and air temperature and relative humidity above and within canopy at four locations, dual-rain gauges at seven locations, four component radiometers at five locations, and eddy covariance towers at two locations. Soil texture and bulk density data were also collected for 11 layers (down to 2 m) at the 16 soil moisture/temperature locations. Additionally, throughout the growing season of 2009, biomass and leaf-area index measurements were taken. The high spatial density of meteorological and soil data at the IVS provides a unique opportunity for adding to the validation of Agro-IBIS.

This study will present observations from the IVS and comparisons of these observations to Agro-IBIS output. Focus will be placed on the ability of Agro-IBIS to capture spatial variability of soil moisture and short term (e.g. one week) changes in soil moisture and plant growth. Discussion will include difficulties of consolidating multiple, non-adjacent, sub-field data sources and the ensemble approach used to determine Agro-IBIS's sensitivity to (potentially erroneous) sub-field variability of meteorological data. Future research directions, including the possibility and importance of coupling Agro-IBIS with regional climate and/or weather models to fully simulate feedbacks between managed lands and the atmosphere, will also be discussed.