Simulating Soybean–Rice Rotation and Irrigation Strategies in Arkansas, USA Using APEX

Sam R. Carroll, Kieu Ngoc Le, Beatriz Moreno-García and Benjamin R. K. Runkle
Additional contact information
Sam R. Carroll: Department of Biological and Agricultural Engineering, College of Engineering, University of Arkansas, Fayetteville, AR 72701, USA
Kieu Ngoc Le: Department of Biological and Agricultural Engineering, College of Engineering, University of Arkansas, Fayetteville, AR 72701, USA
Beatriz Moreno-García: Department of Biological and Agricultural Engineering, College of Engineering, University of Arkansas, Fayetteville, AR 72701, USA
Benjamin R. K. Runkle: Department of Biological and Agricultural Engineering, College of Engineering, University of Arkansas, Fayetteville, AR 72701, USA

Sustainability, 2020, vol. 12, issue 17, 1-17

Abstract: With population growth and resource depletion, maximizing the efficiency of soybean ( Glycine max [L.] Merr.) and rice ( Oryza sativa L.) cropping systems is urgently needed. The goal of this study was to shed light on precise irrigation amounts and optimal agronomic practices via simulating rice–rice and soybean–rice crop rotations in the Agricultural Policy/Environmental eXtender (APEX) model. The APEX model was calibrated using observations from five fields under soybean–rice rotation in Arkansas from 2017 to 2019 and remote sensing leaf area index (LAI) values to assess modeled vegetation growth. Different irrigation practices were assessed, including conventional flooding (CVF), known as cascade, multiple inlet rice irrigation with polypipe (MIRI), and furrow irrigation (FIR). The amount of water used differed between fields, following each field’s measured or estimated input. Moreover, fields were managed with either continuous flooding (CF) or alternate wetting and drying (AWD) irrigation. Two 20-year scenarios were simulated to test yield changes: (1) between rice–rice and soybean–rice rotation and (2) under reduced irrigation amounts. After calibration with crop yield and LAI, the modeled LAI correlated to the observations with R 2 values greater than 0.66, and the percent bias (PBIAS) values were within 32%. The PBIAS and percent difference for modeled versus observed yield were within 2.5% for rice and 15% for soybean. Contrary to expectation, the rice–rice and soybean–rice rotation yields were not statistically significant. The results of the reduced irrigation scenario differed by field, but reducing irrigation beyond 20% from the original amount input by the farmers significantly reduced yields in all fields, except for one field that was over-irrigated.

Keywords: crop rotation; irrigation management; flood irrigation; cascade irrigation; multiple inlet rice irrigation; furrow; calibrate; LAI (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/12/17/6822/pdf (application/pdf)
https://www.mdpi.com/2071-1050/12/17/6822/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:17:p:6822-:d:402661

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().