Comparison and Analysis of Empirical Equations For Soil Heat Flux for Different Cropping Systems and Irrigation Methods

Authors

Ayse Kilic, University of Nebraska-LincolnFollow
R. K. Singh, USGS Earth Resources Observation and Science
Elizabeth A. Walter-Shea, University of Nebraska - LincolnFollow
Shashi Verma, University of Nebraska - LincolnFollow
Andrew E. Suyker, University of Nebraska - LincolnFollow

ORCID IDs

Ayse Kilic

Date of this Version

2011

Citation

Transactions Of The Asabe, Vol. 54(1): 67-80

Abstract

We evaluated the performance of four models for estimating soil heat flux density (G) in maize (Zea mays L.) and soybean (Glycine max L.) fields under different irrigation methods (center‐pivot irrigated fields at Mead, Nebraska, and subsurface drip irrigated field at Clay Center, Nebraska) and rainfed conditions at Mead. The model estimates were compared against measurements made during growing seasons of 2003, 2004, and 2005 at Mead and during 2005, 2006, and 2007 at Clay Center. We observed a strong relationship between the G and net radiation (R_n) ratio (G/R_n) and the normalized difference vegetation index (NDVI). When a significant portion of the ground was bare soil, G/R_n ranged from 0.15 to 0.30 and decreased with increasing NDVI. In contrast to the NDVI progression, the G/R_n ratio decreased with crop growth and development. The G/R_n ratio for subsurface drip irrigated crops was smaller than for the center‐pivot irrigated crops. The seasonal average G was 13.1%, 15.2%, 10.9%, and 12.8% of R_n for irrigated maize, rainfed maize, irrigated soybean, and rainfed soybean, respectively. Statistical analyses of the performance of the four models showed a wide range of variation in G estimation. The root mean square error (RMSE) of predictions ranged from 15 to 81.3 W m^‐2. Based on the wide range of RMSE, it is recommended that local calibration of the models should be carried out for remote estimation of soil heat flux.