Recipient Organization
IOWA STATE UNIVERSITY
2229 Lincoln Way
AMES,IA 50011
Performing Department
Agronomy
Non Technical Summary
Iowa's updates in soil survey have not kept pace with scientifically validated improvements globally, and the demand for spatially detailed soil interpretations is skyrocketing due to the big data demands of crop and environmental modelers, agronomists, and policy makers. In Iowa the most sought after interpretation is CSR2, which is a metric for inherent crop productivity.This project will provide the State of Iowa a 21st century update of the National Cooperative Soil Survey maps and their interpretations in a manner that aligns with the current state of knowledge and quantitative technologies (GIS, modeling, soil analytical protocals, soil productive indices). It addresses the very real and pressing problem facing Iowa landowners and government agencies wherein the currently available maps do not provide spatially explicit assessments of soil properties and interpretations. This problem is magnified by the increased state of flooding, ponding, erosion and other integrated natural/human modified soil-land issues.The methods being used are a blend of traditional pedological mapping and laboratory analyses and state of the art geospatial technologies and science.
Animal Health Component
40%
Research Effort Categories
Basic
40%
Applied
40%
Developmental
20%
Goals / Objectives
This project's goal is the creation ofan up-to-date soil map of Iowa that complements and integrates with Web Soil Survey while permitting and providing the State of Iowa the level of detailed information needed for equitable land assessment and field-scale level modeling of cropping potential. In doing so it will support research that advances pedological knowledge for Iowa and for the larger scientific community.The objectives of this project are to:Quantify optimal soil mapping practices in order to best identify the pedology and pedological variability across Iowa; and,Improve major soil map interpretations especially as related to inherent crop productivity.
Project Methods
The general design of this project is a 21st century update of benchmark locations for use in soil mapping and interpretations consistent with the methods and objectives broadly explained in the Soil Survey Manual (Soil Survey Staff, 1937;1951; 1993). More specifically our method for creating soil maps and making pedological identifications is to examine the variety of major soilscapes across Iowa using the techniques developed for traditional through modern soil mapping. For the traditional projects we will identify individual soil map units (SMU) and then delineate individual polygons using approximately a 1:15840 air photograph base map coupled with on-site interpretations of landscape positions, soil morphology and Soil Taxonomic classifications as outlined in Soil Survey Staff (1993, 2019). For these projects we will also include transect and grid mapping (Burras and Scholtes, 1987; Langner et al, 2011; Richter and Burras, 2017; Streeter and Schilling, 2015; Walker and Ruhe, 1968; Wills et al., 2007) in order to quantify representative pedon and SMU properties. For many projects our primary approach will be using contemporary geospatial mapping techniques such as digital hillslope position, terrain analysis, digital elevation models that integrate digital terrain derivatives, and multivariate linear regression (Cambule et al, 2013; Lawler, 2016; Miller et al, 2015; Miller et al, 2016). When available we will use drones and multispectral analysis to quantitatively document field properties and conditions (Brummel, 2019). A critical advantage of the contemporary approaches is that individual soil properties will have statistically validated geospatial attributes, although the cost (i.e., extra sampling, need for sophisticated computing power and specialized training to optimally use machine learning in geospatial analyses) is a potential drawback and limitation. This limitation is a central reason ( potential "pitfall") that explains why we will use a combination of traditional and sophisticated approaches. There will be two initial benchmark locations. One will be in the Missouri River floodplain and extend into the nearby uplands. The second will be on the Northwest Iowa Till Plain. The validation fieldwork will occur at the field scale and then be geospatially evaluated to establish the degree to which it can be applied across appropriate Major Land Resource Areas (MLRA). Laboratory analyses of soil samples will include morphological description (Schoeneberger and others, 2012) and standard soil analyses for bulk density, particle size analysis, pH and - on occasion - soil organic carbon content, calcium carbonate equivalent, cation exchange capacity, and exchangeable base content. The detailed protocols for each soil analysis are given in Burras and Scholtes (1987), Langner and others (2011), and Wills and others (2007). These analyses are critical because they allow for the proper classification of each soil, especially at the Soil Order and again at the family level of Soil Taxonomy.Our primary method for interpreting the soils of Iowa for inherent crop productivity is to review and assess the CSR2 algorithm of Burras (2018) and Burras and others (2015) by comparing its values when used with Web Soil Survey data (as currently done) as well as the modern soil survey data that we gain in all soil mapping projects. We will validate the yield by CSR2 interpretations using regression techniques explained in Woli and others (2014). We will do using a range of yet to be identified yield data sets, preferably with some coming from private sector sources. We will return to sites previously used by Woli and others (2014) and Lawler (2016). Simultaneously we will compare the productivity predications of CSR2 with the National Commodity Crop Productivity Index (NCCPI) (Soil Survey Staff, 2019) as well as selected statewide systems from the US cornbelt (Sassman and Burras, 2016; 2015). A pitfall with all inherent crop productivity indices is they are akin to "IQ" in humans. There is a protocol in how to quantify a value that is widely accepted; however, there is little scientific consensus about the true value and meaning in doing so. However, in the case of CSR2 economic and legal value is well understood. It is the basis for rural land taxation in the State of Iowa when used in conjunction with modern soil maps.