Charlotte I. Lee1, Lori Abendroth2, and Laura Bowling1
1Department of Agronomy, Purdue University, West Lafayette, Indiana
2Cropping Systems and Water Quality Research, USDA ARS, Columbia, Missouri
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Methods:
To evaluate the potential for the drainage water recycling practice to increase corn production across the region, precipitation during V9 and R2 development stages was summed for each year from 2000 to 2015 using one-sixteenth degree resolution gridded data derived from local weather stations1,2,3. Each grid cell was assigned a FIPS (Federal Information Processing Standards) code for the county that the majority of the grid cell is within; this code was used to link the weather data with additional information.
In addition to climate variability, this analysis considered regional differences in maize hybrid choice to identify the expected dates for V9 and R2. Maize hybrid growing degree day (GDD) statistics were extracted from a dataset containing information for 650 Midwest counties4. Counties with a planted percentage of corn equal to or greater than 2% between 2000 and 2016 were selected5,6. An additional 50 counties of maize hybrid GDD statistics were added for a total of 700 counties in the dataset by averaging values from surrounding counties (Table 1).
To create a seamless map, 23 counties with missing maize hybrid data (e.g. those with large metropolitan or forested areas and <2% corn planted) were assigned average values from the adjacent counties (Table 2). Maize hybrid GDD values from the adjoining east and west (or next nearest) counties were averaged and the mean was assigned to the missing county. This filling method was selected for these 23 counties with little to no corn production to preserve the north to south gradient in temperature/GDDs across the region4.
Temporal and spatial variability in planting date is used in calculating the annually varying V9 to R2 development stage window across the region. Planting dates for each year were assigned on the county-level and were based on the reported date of 50% or more corn acreage planted from the USDA NASS planting statistics7. The V9 through R2 development stage window was identified by a percentage of growing degree days needed for the assigned maize hybrid to reach maturity (R6). These percentages are defined as 32% and 63% for the V9 and R2 development stages, respectively8. Dates corresponding to the V9 and R2 development stages in each year were used to create a window for precipitation to be summed during these stages.
GDD was calculated daily with a base of 50°F (10°C) and maximum of 86°F (30°C). Temperatures below the base (50°F) were set to the base, and those above the maximum (86°F) were set to the maximum, before calculating GDD with the following equation:
GDD = (Maximum Daily Air Temperature + Minimum Daily Air Temperature)/2 – 50.
A check to ensure daily GDD never exceeded 36 was performed prior to calculating cumulative GDD between hybrid planting date and GDD based maturity. Precipitation was summed over the GDD values representing the period beginning at V9 and ending at R2 development stages each year and then averaged over all years (Figure 1). In addition, the frequency of years between 2000 and 2015 in which the V9 – R2 precipitation failed to meet or exceed the 5 inch critical threshold was calculated.
Figure 1. Mean annual (left) and V9 – R2 (right) precipitation in inches for 2000 – 2015.
References:
- Extension of Livneh et al. 2015’s dataset to 1915 – 2015, accessed at: ftp://livnehpublicstorage.colorado.edu/public/Livneh.2016.Dataset/
- Livneh, B., Bohn, T.J., Pierce, D.W., Munoz-Arriola, F., Nijssen, B., Vose, R., Cayan, D.R. and Brekke, L., 2015. A spatially comprehensive, hydrometeorological data set for Mexico, the US, and Southern Canada 1950–2013. Scientific data, 2(1), pp.1-12. https://doi.org/10.1038/sdata.2015.42
- Livneh, B., Rosenberg, E.A., Lin, C., Nijssen, B., Mishra, V., Andreadis, K.M., Maurer, E.P. and Lettenmaier, D.P., 2013. A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States: Update and extensions. Journal of Climate, 26(23), pp.9384-9392. https://doi.org/10.1175/JCLI-D-12-00508.1
- Abendroth, L.J., Miguez, F., Castellano, M., Carter, P., Messina, C. and Dixon, P. 2021. Lengthening of maize maturity time is not a widespread climate change adaptation strategy in the U.S. Midwest. Global Change Biology.
- USDA NASS. 2017. Quick stats. (Query: Farm Operations – Area Operated, Measured in Acres/Operation for IA, IL, IN, MO, MN, OH, SD, WI). United States Department of Agriculture, National Agricultural Statistics Service. Washington, D.C. https://quickstats.nass.usda.gov/results/9B2C3340-48D1-33A5-8C0A-77443A4EB1BB
- USDA NASS. 2018. Quick stats. (Query: Field Crop Totals - Acres Planted for IA, IL, IN, MO, MN, OH, SD, WI). United States Department of Agriculture, National Agricultural Statistics Service. Washington, D.C. https://quickstats.nass.usda.gov/results/2A7DB959-C3C6-3E25-8EE1-CFACBDEB75BF
- USDA NASS. 2019. Quick stats. (Query: “Corn - Progress, Measured in Pct Planted” for IA, IL, IN, MO, MN, OH, SD, WI). United States Department of Agriculture, National Agricultural Statistics Service. Washington, D.C. https://quickstats.nass.usda.gov/results/E216C933-2622-3E7E-9C78-AE0163BF4D4A
- Abendroth, L.J., Elmore, R.W., Boyer, M.J. and Marlay, S.K., 2011. Corn development and development. Report number: PMR 1009. Iowa State University, Extension. Ames, IA.https://store.extension.iastate.edu/product/6065
Table 1. Additional 50 counties with 2% or greater corn production not included in Abendroth et al. (2021), surrounding county maize hybrid statistics were averaged where possible.
Missing County FIPS | Filling Counties FIPS |
---|---|
17013 | 17149, 17061 |
17069 | 17059 |
17083 | 17061, 17117, 17119 |
17089 | 17111, 17093 |
17097 | 17111, 17031 |
17151 | 17127, 17087, 17165 |
17155 | 17123, 17011, 17099 |
18025 | 18117, 18123 |
18029 | 18047, 18137 |
18043 | 18019, 18061 |
18097 | 18057, 18081 |
18105 | 18109, 18093 |
18119 | 18055, 18021, 18133 |
18155 | 18077, 18115 |
18161 | 18177, 18041, 18047 |
18173 | 18163, 18125, 18147 |
18175 | 18061, 18071 |
26055 | 26113 |
26105 | 26127, 26123 |
26109 | 26041 |
26113 | 26055, 26129 |
26129 | 26011, 26051 |
26133 | 26073, 26107, 26113 |
27003 | 27019, 27059, 27025 |
27141 | 27145, 27171, 27009 |
29001 | 29199, 29121 |
29017 | 29157, 29207 |
29051 | 29151, 29135 |
29057 | 29109, 29097 |
29171 | 29129, 29211, 29199 |
29185 | 29013, 29083 |
29197 | 29111, 29103, 29171 |
38029 | 38047, 38051 |
38031 | 38027, 38093 |
38039 | 38063, 38003 |
38099 | 38035, 38067 |
39019 | 39151, 39029, 39157 |
39075 | 39031, 39169 |
39095 | 39051, 39069, 39173 |
39123 | 9173, 39143, 39095 |
46017 | 46059, 46045 |
46027 | 46135, 46127, 46125 |
46049 | 46045, 46059 |
46061 | 46067, 46111, 46035, 46097 |
46089 | 46045, 46021 |
55001 | 55057, 55137, 55077 |
55059 | 55101, 55127 |
55083 | 55067, 55115, 55075 |
55129 | 55005, 55013 |
55133 | 55131, 55127, 55055, 55027 |
Table 2. Counties with less than 2% corn production that have missing hybrid maize statistics filled by averaging adjacent east and west (or nearest) counties where possible.
Missing County FIPS | Filling Counties FIPS |
---|---|
17043 | 17089, 17031 |
18013 | 18105, 18005 |
26019 | 26089, 26055 |
26035 | 26133, 26051 |
26085 | 26105, 26133 |
26101 | 26105 |
26165 | 26113 |
26125 | 26093, 26099 |
26163 | 26161 |
27029 | 27119, 27087, 27007, 27113 |
27123 | 27003, 27053, 27163 |
29039 | 29217, 29167 |
29085 | 29185, 29029 |
29099 | 29071, 29221, 17133 |
29189, 29510 | 29183, 17163, 17119, 29071 |
39035 | 39093 |
39055 | 39093, 39007, 39155 |
39061 | 39025, 18155 |
39085 | 39007 |
39153 | 39103, 39133 |
55078 | 55067, 55115, 55083 |
55079 | 55133 |