From points to polygons to rasters: Accounting for soil information uncertainty in agronomic decision-making

Authors: MAYNARD, JONATHAN - University Of Colorado; BEAUDETTE, DYLAN - Natural Resources Conservation Service (NRCS, USDA); WILLS, SKYE - Natural Resources Conservation Service (NRCS, USDA); Herrick, Jeffrey - Jeff

Submitted to: Soil Science Society of America Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 7/12/2022
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Farmers require reliable information to act, where the outcome of such actions involves financial costs and implications for a farmer’s livelihood. Obtaining reliable information is complicated by the fact that soil systems are complex and often exhibit high variability in both geographic and feature space. Our understanding of this variability is limited by two key facets of uncertainty. The first arises from the intrinsic variability of the system (i.e., aleatory uncertainty) and the second from a limited understanding of the system due to incomplete or imprecise information (i.e., epistemic uncertainty). To improve the reliability of soil information we must first understand the sources of uncertainty associated with each type of soil data used in decision-making (e.g., field/lab measurement data, models, maps), so that we can: (1) identify data sources with high uncertainty, (2) improve data quality through minimizing uncertainty, and (3) account for uncertainty and error propagation in the decision-making process. Our presentation will discuss sources of soil information uncertainty within the primary data used to inform soil management, including field and laboratory-based point measurements, polygon and raster-based soil maps, and the underlying models used to derive spatially explicit soil information. We will present several case studies to illustrate how uncertainty information can be used by farmers to assess which data and information sources may be used to inform management decisions based on their tolerance to risk