During the 2019 growing season, Dr. Eric Hunt of Atmospheric and Environmental Research, Inc. will be providing weekly updates of the soil moisture index (SMI) from the Noah-MP land surface model in the NASA LIS framework for the eastern 3/4 of the U.S. where row-crop agriculture is more common. The Evaporative Stress Index (ESI) is now included in our analysis. The analysis is intended to provide the larger agricultural and meteorological communities insight as to areas where soil moisture is excessive or deficient compared to average for that location and what that may mean for impacts. It is my goal that these maps can be an early warning signal for flash drought development or where flash flooding could be likely in the coming week if heavy precipitation materializes. Please be advised that the SMI should be viewed as complementary, not a substitute, to the U.S. Drought Monitor (USDM) and that declarations of drought for a particular location should never be based on the SMI alone.
This blog post was partially supported by NASA grant NNH16CT05C.
Figure 1. The Soil Moisture Index (SMI) for the 7-day period ending 15 June 2019. Results are based on output from the 0-1 m (surface to 3.23 feet) layers in the Noah-Multiparameterization (Noah-MP) land surface model. Noah-MP is run in the NASA Land Information System (LIS) framework with the North American Land Data Assimilation Version 2 (NLDAS-2) forcing dataset. The SMI calculation is based on the soil moisture index created in Hunt et al. (2009) such that ‘5’(dark green) is the wettest and ‘-5’ (dark red) the driest for the period of record. The period of record used calculate the SMI for the current map is 1979-present.
Figure 2. Same as Figure 1, except Noah-MP is run with a dynamic vegetation option, instead of a climatologically driven leaf area index (LAI).
Figure 3. Comparison of this week’s SMI map the last three week’s SMI maps.
Wet conditions returned for much of the central U.S. late last week, which is reflected in the SMI over much of the Corn Belt and Great Plains. Pockets of dryness still exist in southern Alabama and Georgia and over the far northern part of the High Plains region. This is in good agreement with the latest Drought Monitor. It should be noted that the dynamic vegetation model also extends weaker negative values of the SMI into parts of South Dakota and northeast Nebraska and is drier over the southeast and Texas than the Noah-MP simulation.
The 1-month ESI shows predominantly negative values over the southeast and up along the Mississippi River into Missouri and Illinois. The former is likely a result of the dry spring and early June; the latter is likely a result of flooding that has negatively affected the vegetation and in Illinois, it could well be reflective of unplanted acres.
Speaking of acres, the USDA will release a highly anticipated report on production stocks and acreage estimates tomorrow at noon EDT. I’m not going to speculate here what they will come up with but offer up Figure 5 as a guide to where corn might be headed. The red circles show the percent of corn rated Excellent/Good minus the corn rated Poor/Very Poor (EG-PVP) from this same week in the year back to 1986 and the blue squares represent the eventual trend from that year. There is generally a decent relationship between condition in late June and the final yield, though there are notable exceptions (both positive and negative). In every year except 1988 there was a lot more corn in the Good or Excellent categories than in the Poor or Very Poor categories. This year is no exception but it should be noted that conditions (according to this metric) this year are worse than in every year except 1988 and 2012. I’m not projecting that kind of trend (you can buy AER’s commercial corn forecast if you want our outlook) but suffice to say this year isn’t in good company thus far.
Figure 5. Percent of corn rated Excellent or Good minus the percent of corn rated Poor or Very Poor for Week 25 dating back to 1986 (red circles) and the final corn trend (blue squares). Data courtesy of USDA NASS.