Use of archived data to derive soil health and water quality indicators for monitoring shifts in natural resources

Authors: Fortuna, Ann Marie; STEINER, JEAN - Retired ARS Employee; Moriasi, Daniel; Starks, Patrick

Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/9/2023
Publication Date: 4/26/2023
Citation: Fortuna, A., Steiner, J., Moriasi, D.N., Starks, P.J. 2023. Use of archived data to derive soil health and water quality indicators for monitoring shifts in natural resources. Journal of Environmental Quality. 52(30):523-536. https://doi.org/10.1002/jeq2.20476.
DOI: https://doi.org/10.1002/jeq2.20476

Interpretive Summary: An important function of soil is to protect water quality at the edge of field and watershed scales. Currently, we lack scientific information in a number of areas that would enhance the connection between soil and watershed health. Both soil health and water quality are defined using chemical, physical, and biological characteristics. Although definitions of soil health allude to its impact on water quality there are no direct links to water quality descriptions. The Fort Cobb Reservoir Experimental Watershed (FCREW) located in southwestern Oklahoma was chosen to participate in the national USDA, Natural Resource Conservation Service (NRCS) Effects Assessment Project (CEAP) begun in 2003 because it was identified as a watershed that could be improved by adoption of conservation practices by the Oklahoma Conservation Commission and Oklahoma Water Resources Board. The purpose of CEAP is to quantify the environmental effects of conservation practices and programs and to develop the science base for managing agricultural landscapes for environmental quality. The FCREW is one of 24 watersheds located across the US participating in CEAP. Additionally, research on the FCREW is conducted as a component of the Long-Term Agro-Ecosystem Research (LTAR) network, the purpose of which is to develop national strategies for the sustainable intensification of agriculture production. The goal of this research is to utilize climate, soil and water data previously collected by the Grazinglands Research Laboratory, USDA-ARS, El Reno, OK and USGS to determine whether indicators of soil health were correlated with water quality indicators within sub-watersheds of the FCREW and the full FCREW watershed using principle components analysis (PCA), a multivariate statistical approach. There were three water quality indicators and four soil health indicators that were correlated across the three sub-watersheds during the annual wet cycle. The measurements represented biological and inorganic nutrient transformations in runoff that were driven by land management and use. These soil and water indicators could be used to develop a sampling protocol to monitor water quality within the FCREW sub-watersheds and the FCREW as well as have the potential to be adapted to other CEAP watershed sites. Our intent was to utilize data that are commonly collected by soil and water researchers at existing CEAP watersheds to address research issues and to inspire new approaches and collaborations for tackling the challenge of leveraging soil health to strengthen water management.

Technical Abstract: Current gaps that impede researchers from developing a soil and watershed health nexus include the design of long-term field scale experiments to provide climate, soil and water databases and statistical methodologies to link soil point measurements with summary measures of water quality and biophysical mechanisms. Our research objectives were to: use nonparametric Spearman rank-order correlations to identify soil health (SH) and water quality (WQ) indicators that varied within areas of the larger Fort Cobb Reservoir Experimental Watershed (FCREW); use principal components analysis (PCA) to select SH and WQ indicators that represented the effects of land use, management and natural effects (soil texture, terrain attributes) on water quality for the FCREW; and utilize the statistical outcomes to assess the sustainability of previous land use, management and natural effects on water quality to maintain and improve management of the FCREW. Nonparametric Spearman rank-order correlation coefficient matrices obtained from the FCREW and Willow Creek sub-watershed provided no statistically significant interactions between SH and WQ indicators. In contrast, correlation coefficient matrices for Cobb, Five Mile and Lake Creek sub-watersheds verified statistically significant interactions between SH and WQ indicators. There were three water quality parameters (dissolved oxygen (DO), electrical conductivity (EC), oxidation reduction potential (ORP)) and four soil health parameters (nitrates (NO3-N), total soil organic C (TSOC), magnesium (Mg), phosphorus (P)) that were correlated across the three sub-watersheds during the annual wet cycle. The measurements represented biological and inorganic nutrient transformations in runoff that were driven by land management and use. The indicators could be used to develop a sampling protocol to monitor water quality within sub-watersheds and FCREW. Despite the lack of correlation between WQ and SH indicators, the PCA and factor analysis provided important information with respect to land use and cover across the FCREW. Future research should allow sufficient sample sizes to conduct multivariate analyses that could be used to group water samples within and among the sub-watersheds for determination of non-point sources of pollution.