MODELING EVAPOTRANSPIRATION for C4 and C3 CROPS in the WESTERN LAKE ERIE BASIN USING REMOTE SENSING DATA

Abstract

Growing monoculture impacts not just soil properties and biodiversity but also local hydrology including evapotranspiration (ET). The Midwest region of the U.S. is known for its monoculture trend by growing and producing corn, which commonly replaces other crop types. In addition to large areas covered with corn, the photosynthetic adaptations of corn, being the C4 crop, affects ET differently than other C3 crops such as soybean, wheat, and alfalfa. This study aims to model and compare ET for C3 and C4 crops using remote sensing (Sentinel-2 data) and the Boreal Ecosystem Productivity Simulator (BEPS) model, modified to consider C3 and C4 crops. The study explores the ET rate trend for corn and soybean in an agriculture area situated in the Western Lake Erie Basin, where the balance between evapotranspiration, groundwater level, and surface runoff may play a role in agricultural runoff and Lake Erie's algal blooms caused by runoff pollution. The results suggest that the monthly average ET rates for both soybean (C3) and corn (C4) reach its maximum at the mid-to-late growing season. However, the ET rate for corn is higher than for soybean in the early season (June) (ET Combining double low line 121 mm month−1 for corn; ET Combining double low line 105 mm month−1 for soybean), while the ET rate for soybean becomes higher than for corn soon after (July) and becomes considerably higher in August (ET Combining double low line 181 mm month−1 for corn; ET Combining double low line 218 mm month−1 for soybean). It is surmised that the higher ET rate for corn in the early growing season is due to nitrogen-based fertilizer commonly applied to corn parcels at that time, whereas soybean growth is based on biological nitrogen fixation.