US Long-Term Ecological Research Network

Modeled Organic Carbon, Dissolved Oxygen, and Secchi for six Wisconsin Lakes, 1995-2014

Abstract
This data package contains model output data, driving data, and supplemental information for a two-layer modeling study that investigated organic carbon and oxygen dynamics within six Wisconsin lakes over a twenty-year period (1995-2014). The six lakes are Lake Mendota, Lake Monona, Trout Lake, Allequash Lake, Big Muskellunge Lake, and Sparkling Lake. The model output includes daily predictions of six state variables: labile particulate organic carbon, recalcitrant particulate organic carbon, labile dissolved organic carbon, recalcitrant dissolved organic carbon, dissolved oxygen, and Secchi depth. The output also includes daily predictions of physical and metabolism fluxes that were used in the prediction of the state variables. This data package also contains model driving data for each lake and other supplemental information that was calculated during the modeling runs.<br/>
Core Areas
Creator
Dataset ID
421
Date Range
-
Methods
Data included in this package include output, driving data, and supplemental calculated information for a modeling study.<br/>
NTL Themes
Version Number
1

WSC - Yield and water table depth shapefiles from Wibu field site

Abstract
Yield data from the Wibu field site combined with a variety of water table depth metrics (mean, percentiles, sum exceedance values, moving averages). It was collected as part of a study of the impacts of water table depth, soil texture, and growing season weather conditions on corn production at the Wibu field site, described in Zipper et al. (in review). The Wibu field site is a commercial agricultural field, which grew corn in the 2012, 2013, and 2014 growing seasons. See Zipper and Loheide (2014) Ag. For. Met. for more information about the field site.
Dataset ID
317
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Yield data was collected at the time of harvest following the 2012 and 2013 growing season using a John Deere 9660 combine equipped with a Greenstar yield monitoring system. Yield data was cleaned by removing any polygons collected during pre-harvest check strips, turn-around at the end of rows, any polygons less than 6 m2, and any polygons where yield exceeded the record reported yield for Dane County WI (327 bu ac-1). Yield was normalized by calculating z-scores (the number of standard deviations away from the mean) within each field and each year. 2012 data was resampled to the 2013 polygon boundaries by taking the mean of all 2012 polygons with their centroid within each 2013 polygon. For each polygon, 2013 interpolated groundwater metrics were extracted using ArcMAP 10.2 software. A full description of this methodology is contained in Zipper et al. (in review).
Version Number
16
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