This study was conducted in the South Fork of King’s Creek at Konza Prairie Biological Station, one of the most well-studied prairie streams in the world. At the USGS gage located on the mainstem (06879560; est. 1979), Kings Creek is a 5th order intermittent stream draining 1059-ha of tallgrass prairie in the Kansas Flint Hills.

This synoptic survey was designed in support of the sampling goals of the Aquatic Intermittency effects on Microbiomes in Streams (AIMS) Project. During June, July, and August 2021, a field team co-collected datasets characterizing the hydrology, biogeochemistry, and ecology across 50 locations within a sub-drainage of the South Fork of Kings’ Creek. The 50 sites were selected to balance multiple competing priorities: (i) strategically targeting existing monitoring infrastructure with long-term data (n=14); (ii) including sites near several known springs and tributary junctions (n=9); and (iii) including a range of drainage area and topographic wetness index (TWI) values (n=27), both of which have been correlated with flow permanence elsewhere. Briefly, the sites selected based on drainage area and TWI were chosen by binning drainage area into 10 bins and then binning TWI into quintiles within each drainage area bin. We then randomly selected a point in each bin after accounting for points selected based on existing infrastructure, springs, and tributaries;, and enforcing a minimum spacing of 100 m between locations. We then made minor adjustments to points to account for field conditions, for instance adjusting locations with respect to a road crossing. For a detailed description of the site selection process, please see (Swenson et al., 2023).

This is a collection of site metadata for the June 2021 Konza synoptic, and for the stretch July and August 2021 synoptic sampling campaigns. Most of this data is a collation of data from the different field datasheets. This is supplemented with data from the STIC (stream temperature intermittency conductivity) sensors as well as physical characteristics derived through GIS analysis.