Corn, Soybeans and Winter Wheat Water Requirements over the Contiguous United States between 2013 and 2021: The Application of the SEBALIGEE v2 Global Model

Journal Article
Corn, Soybeans and Winter Wheat Water Requirements over the Contiguous United States between 2013 and 2021: The Application of the SEBALIGEE v2 Global Model
Mhawej, M., X. Gao, J.M. Reilly and Y. Abunnasr (2024)
Journal of Hydrology, 630, 130782 (doi: 10.1016/j.jhydrol.2024.130782)

Abstract/Summary:

Abstract: The open-source fully-automated Surface Energy Balance Algorithm for Land-Improved (SEBALI) Google Earth Engine (SEBALIGEE) estimates 30-m actual evapotranspiration (ET) at a monthly rate, a much needed parameter in many hydrological and agricultural applications. An improved version of the basin-based SEBALIGEE v1 is proposed in this paper.

The improvement of SEBALIGEE v1, named v2, focuses primarily on adding advanced machine learning approaches which have enabled us to implement SEBALIGEE over any scale application and enhance its performance. More particularly, an evaluation of the monthly ET estimated from the new algorithm across several fluxnet sites in the US, China, Italy, Belgium, Germany, and France, yielded a Mean Absolute Error (MAE) of 12.22 mm/month versus 14.54 mm/month in the original SEBALIGEE v1. Furthermore, we used the new any-scale capability to implement SEBALIGEE v2 over the contiguous United States (CONUS) while emphasizing on the three main crops, including corn, soybeans and winter wheat.

Our analysis indicated that all three crops presented similar ET seasonal cycles with peaks occurring in late spring to the summer (May-Aug) and between October and January, corresponding well to the key stages of crop life cycle. Moreover, corn and soybeans exhibited similar magnitudes of ET (36 ~ 168 mm/month) and higher than winter wheat (33 ~ 122 mm/month), with large standard deviations were observed in the ET estimates of all the crops. On interannual comparisons, the corn and soybeans ET and aKc showed higher values than winter wheat, with the highest and lowest years identified and discussed. Following an exploratory analysis against some of the most common interfering variables such as air temperature, dewpoint temperature, surface net solar radiation, wind speed, SPEI drought index calculated on 14 days and 30-days, it was noted that the surface net solar radiation had the most influencing factor on ET in corn and soybeans plantations with R2 values of ~0.72. The SPEI-30 stands out for winter wheat, showing a water scarcity tolerance up to a month in most of its developing stages. Different management practices are then recommended in each of these two crops’ categories (corn and soybeans vs. winter wheat).

 

Citation:

Mhawej, M., X. Gao, J.M. Reilly and Y. Abunnasr (2024): Corn, Soybeans and Winter Wheat Water Requirements over the Contiguous United States between 2013 and 2021: The Application of the SEBALIGEE v2 Global Model. Journal of Hydrology, 630, 130782 (doi: 10.1016/j.jhydrol.2024.130782) (https://www.sciencedirect.com/science/article/abs/pii/S0022169424001768)
  • Journal Article
Corn, Soybeans and Winter Wheat Water Requirements over the Contiguous United States between 2013 and 2021: The Application of the SEBALIGEE v2 Global Model

Mhawej, M., X. Gao, J.M. Reilly and Y. Abunnasr

630, 130782 (doi: 10.1016/j.jhydrol.2024.130782)
2024

Abstract/Summary: 

Abstract: The open-source fully-automated Surface Energy Balance Algorithm for Land-Improved (SEBALI) Google Earth Engine (SEBALIGEE) estimates 30-m actual evapotranspiration (ET) at a monthly rate, a much needed parameter in many hydrological and agricultural applications. An improved version of the basin-based SEBALIGEE v1 is proposed in this paper.

The improvement of SEBALIGEE v1, named v2, focuses primarily on adding advanced machine learning approaches which have enabled us to implement SEBALIGEE over any scale application and enhance its performance. More particularly, an evaluation of the monthly ET estimated from the new algorithm across several fluxnet sites in the US, China, Italy, Belgium, Germany, and France, yielded a Mean Absolute Error (MAE) of 12.22 mm/month versus 14.54 mm/month in the original SEBALIGEE v1. Furthermore, we used the new any-scale capability to implement SEBALIGEE v2 over the contiguous United States (CONUS) while emphasizing on the three main crops, including corn, soybeans and winter wheat.

Our analysis indicated that all three crops presented similar ET seasonal cycles with peaks occurring in late spring to the summer (May-Aug) and between October and January, corresponding well to the key stages of crop life cycle. Moreover, corn and soybeans exhibited similar magnitudes of ET (36 ~ 168 mm/month) and higher than winter wheat (33 ~ 122 mm/month), with large standard deviations were observed in the ET estimates of all the crops. On interannual comparisons, the corn and soybeans ET and aKc showed higher values than winter wheat, with the highest and lowest years identified and discussed. Following an exploratory analysis against some of the most common interfering variables such as air temperature, dewpoint temperature, surface net solar radiation, wind speed, SPEI drought index calculated on 14 days and 30-days, it was noted that the surface net solar radiation had the most influencing factor on ET in corn and soybeans plantations with R2 values of ~0.72. The SPEI-30 stands out for winter wheat, showing a water scarcity tolerance up to a month in most of its developing stages. Different management practices are then recommended in each of these two crops’ categories (corn and soybeans vs. winter wheat).

 

Posted to public: 

Monday, March 18, 2024 - 13:48