Field-scale water use assessment in the Lower Mississippi Alluvial Plain using OpenET

• OpenET captures detailed spatiotemporal water use patterns in the LMAP region. • Crop ET has higher variability compared with forest ET. • Monthly and seasonal water use of major crops and forests in LMAP are quantified. • ET metrics demonstrate utility for early drought warning. Water scarcity and unprecedented rapid depletion of groundwater reserves are challenges for global sustainable agricultural development. Understanding water usage is especially critical in key agricultural production regions. In this study, we focus on the Lower Mississippi Alluvial Plain (LMAP) region, one of the most important intensive agricultural regions in the United States and facing severe groundwater depletion. However, the total consumptive water use and its relationships with drought events across different land cover types remain a key unknown in this region. Here we use recently developed field-scale monthly evapotranspiration (ET) data from OpenET to investigate water use dynamics over multiple years under various drought conditions. Water use patterns for soybeans, corn, cotton, rice, and surrounding forests are analyzed, with drought impacts assessed using the U.S. Drought Monitor (USDM). The results show that the water consumption for all four crops peaks in July, but early-season patterns differ by crop type and water use practices. Rice shows the highest average total ET for the growing season (688 mm), while cotton has the lowest (612 mm). In comparison, forest ET is higher than crop ET in the LMAP and also shows a seasonal peak in July. Crops show higher variability in ET than forests during the growing season, with larger differences in standard deviation in drought years. Across the three mid-drought years during the study period, groundwater consumption by the four major crops exceeded that of forests by an average of 10 9 m 3 per growing season. Anomalies in ET normalized by reference ET (fRET), a metric of evaporative stress, exhibited rapid response to drought as USDM drought severity intensified, demonstrating the potential of remote-sensing ET metrics for early drought detection. This study utilizes the OpenET dataset to analyze vegetation water use patterns at field scale (30 m), highlighting its value for detailed, spatially explicit monitoring of crop water dynamics and drought impacts and providing critical information for regional water accounting for the development of sustainable agriculture and effective water resources management in agriculture-intensive and drought impacted regions.