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

Autor: Sam R. Carroll, Benjamin R. K. Runkle, Beatriz Moreno-García, Kieu Ngoc Le
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Sustainability
Volume 12
Issue 17
Sustainability, Vol 12, Iss 6822, p 6822 (2020)
ISSN: 2071-1050
DOI: 10.3390/su12176822
Popis: 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&ndash
rice and soybean&ndash
rice crop rotations in the Agricultural Policy/Environmental eXtender (APEX) model. The APEX model was calibrated using observations from five fields under soybean&ndash
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&rsquo
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&ndash
rice rotation and (2) under reduced irrigation amounts. After calibration with crop yield and LAI, the modeled LAI correlated to the observations with R2 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&ndash
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.
Databáze: OpenAIRE