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Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework
- He, Mingzhu, Kimball, John S., Yi, Yonghong, Running, Steven W., Guan, Kaiyu, Moreno, Alvaro, Wu, Xiaocui, Maneta, Marco
- Remote sensing of environment 2019 v.230 pp. 111201
- C4 plants, Landsat, agricultural management, algorithms, carbon, climate, cropland, energy, evapotranspiration, food security, models, moderate resolution imaging spectroradiometer, monitoring, remote sensing, vegetation, vegetation index, water management
- Evapotranspiration (ET) is a key variable linking the global water, carbon and energy cycles, while accurate ET estimates are crucial for understanding cropland water use in context with agricultural management. Satellite remote sensing provides spatially and temporally continuous information that can be used for global ET estimation. The NASA MODIS MOD16A2 operational product provides 500-m 8-day global ET estimates extending from 2001 to present. However, reliable estimates for delineating field level cropland ET patterns are lacking. In this investigation, we modified the MOD16 global algorithm to better represent cropland ET by calibrating model parameters according to C3 and C4 crop types, and incorporating finer scale satellite vegetation inputs to derive 30-m cropland ET estimates over the continental USA (CONUS). Similar overlapping enhanced vegetation index (EVI) records from Landsat and MODIS were used to generate a continuous 30-m 8-day fused EVI and ET record extending from 2008 to 2017 over CONUS croplands. The satellite-based ET estimates were compared with tower based ET observations over different crop types, and more traditional cropland actual ET (AET) estimates derived from reference ET and crop-specific coefficients. The new satellite based 30-m cropland ET estimates (ET30m) corresponded favorably with both tower ET observations (ETflux; R2 = 0.69, RMSE = 0.70 mm d−1, bias = 0.04 mm d−1) and the baseline global MOD16A2 ET product (ETMOD16). The ET30m results also showed better performance against the ETflux observations than ETMOD16 (R2 = 0.54, RMSE = 0.82 mm d−1) or AET (R2 = 0.52, RMSE = 2.47 mm d−1) for monitoring CONUS croplands. The spatial and temporal patterns of the ET30m results show enhanced delineation of agricultural water use, including impacts from variable climate, cropland area and diversity. The resulting ET30m record is suitable for operational applications promoting more effective agricultural water management and food security.