Implications of the 2015–2016 El Niño on Coastal Mississippi-Alabama Streamflow and Agriculture

Abstract

In this paper, we evaluate the impacts of historic strong El Niño events on the coastal Mississippi-Alabama (MS-AL) hydroclimate. The normal physical association is that the increase in soil moisture, as a result of greater precipitation, is also associated with increased streamflow. When compared to the historic (1960–2015) long-term average, January through August streamflow volumes for five unimpaired streamflow gages located in coastal MS-AL exhibit an average increase of ~20% following a strong El Niño event. This overall increase was due to above-average precipitation during the winter-spring (January through April) season, with the corresponding average increase in streamflow volume for the five gages ~32%. In evaluating the temporal (monthly) variability of streamflow, we observe that the summer (June through August) season was dry following strong El Niño events, with streamflow volumes for the five gages decreasing by an average of ~21%. The agricultural industry in coastal MS-AL produces a variety of crops including cotton and peanuts. The typical planting season for these crops ends in mid-June with harvesting occurring in early September. Thus, the primary growing season for these crops is June–August. Given the lack of impoundments and irrigated lands in coastal MS-AL, the agricultural sector would be severely impacted by an El Niño driven drier summer. When evaluating the influence of the 2015–2016 El Niño on January through August 2016 streamflow, a similar pattern was observed in which high winter–spring streamflow was followed by diminished summer streamflow.

Monitoring Crop Status in the Continental United States Using the SMAP Level-4 Carbon Product

“…For example, the L4C accounts for dry soil restrictions on GPP, but not the potential negative impacts contributed from wet soil events which occur more commonly in humid climate areas Li et al (2019) . The impact of wet soil events is highlighted by a major El Niño event that occurred in 2015–2016 which coincided with delayed planting due to intensive rainfall-driven flooding early in the season resulting in diminished yields in that year ( Sadeghi et al, 2019 ). Negative impacts from this event would only partially be reflected in a reduction in fPAR indicated from the MODIS observational inputs to the L4C model and its associated effect on the GPP calculations; thus, the negative impact on yield would likely be underestimated from L4C relative to the CCI and reported crop yields.…”