Degree Type

Thesis

Date of Award

2014

Degree Name

Master of Science

Department

Agronomy

First Advisor

Brian K. Hornbuckle

Abstract

The properties of the land surface affect the interaction of the surface and the atmosphere. The partitioning of absorbed shortwave radiation into emitted radiation, sensible heat flux, latent heat flux, and soil heat flux is determined by the presence of soil moisture. When the land surface is dry, there will be higher sensible heat flux, emitted radiation and soil heat flux. However, when liquid water is present, latent energy will be used to change the phase of water from solid to liquid and liquid to gas. This latent heat flux moves water and energy to a different part of the atmosphere. A contributing factor to soil moisture available for latent heat flux is the water table. With a shallow water table (< 5 m), plant roots are able to extract water for growth and generally an increase in latent heat flux is seen. In the Midwest U.S., the management of fields changes the latent heat flux through different crop choices, planting and harvest date, fertilizer application, and tile drainage. Therefore, land surface models, like Agro–IBIS, need to be simulated and evaluated at the field–scale. Agro–IBIS is an agroecosystem model that is able to incorporate changes in vegetation growth as well as management practices, which in turn impact soil moisture available for latent heat flux. Agro–IBIS has been updated with the soil physics of HYDRUS–1D in order to accurately simulate the impact of the water table. In measuring soil moisture, a consistent challenge is the representative scale of the instrument, which is often a point. A newer method of obtaining soil moisture over the field–scale is using a cosmic–ray neutron detector, which is sensitive to a diameter of 700 m and to a depth of ∼ 20 cm. I used soil moisture observed by the cosmic–ray neutron detector in an agricultural field to evaluate estimates made with the Agro–IBIS model over a growing season of maize and a growing season of soybean. Because of the large area observed by the cosmic-ray neutron detector, a soil texture sensitivity analysis was performed using Agro–IBIS to determine the texture that would produce the best hydraulic properties and therefore the best estimate of soil moisture. The maize year results show Agro–IBIS with silt loam soil texture with a RMSE of 0.037 cm3 cm-33 and bias of −0.02 cm3 cm3 cm-3 and the updated Agro–IBIS (AgroIBIS–VSF) had a RMSE of 0.033 cm3 cm-3 and bias of −0:006 cm3 cm-3 compared to the cosmic–ray neutron soil moisture. In the soybean year, sandy clay loam with Agro–IBIS had a RMSE of 0.028 cm3 cm-3 and bias of −0.014 cm3 cm-3 and AgroIBIS–VSF had a RMSE of 0.028 cm3 cm-3 and bias of 0.023 cm3 cm-3. These low values for RMSE and bias demonstrate that the models are in good agreement with the field–scale observation of soil moisture for the growing season in 2011 (maize) and 2012 (soybean). Adding a water table did not improve AgroIBIS–VSF's accuracy against the observed cosmic–ray neutron soil moisture in the top 20 cm, except with the sandy clay loam soil texture simulations. The original version of Agro–IBIS conserved water to within 1% of total precipitation, but the water balance for AgroIBIS–VSF lost close to 10%. Both the original and new version of Agro–IBIS performed poorly during the 2012 drought year as shown by their inconsistency with observed yield and

the change in soil moisture storage, as well as expected LAI and canopy height.

DOI

https://doi.org/10.31274/etd-180810-3152

Copyright Owner

Benjamin David Carr

Language

en

File Format

application/pdf

File Size

122 pages

Share

COinS