Assessing soil vulnerability index classification with respect to rainfall characteristics

Authors: PHUNG, QUANG - University Of Missouri; THOMPSON, ALLEN - University Of Missouri; Baffaut, Claire; Witthaus, Lindsey; ALOYSIUS, NOEL - University Of Missouri; Veith, Tameria - Tamie; Bosch, David - Dave; McCarty, Gregory; LEE, SANGCHUL - University Of Seoul

Submitted to: Journal of Soil and Water Conservation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/30/2022
Publication Date: 3/28/2023
Citation: Phung, Q., Thompson, A., Baffaut, C., Witthaus, L.M., Aloysius, N., Veith, T.L., Bosch, D.D., McCarty, G.W., Lee, S. 2023. Assessing soil vulnerability index classification with respect to rainfall characteristics. Journal of Soil and Water Conservation. 78(3):209-221. https://doi.org/10.2489/jswc.2023.00065.
DOI: https://doi.org/10.2489/jswc.2023.00065

Interpretive Summary: The Soil Vulnerability Index (SVI) uses widely available soil survey data to classify cropland into four levels of vulnerability to sediment and nutrient losses: low, moderate, moderately high, and high. Previous work has identified inconsistencies in SVI assessments across the United States, possibly because neither precipitation amount nor intensity were included in the SVI. This study aimed to see if rainfall characteristics influence the SVI classification and which ones are most critical. The study included six Conservation Effects Assessment Project watersheds in Ohio, Missouri, Mississippi, Georgia, Maryland, and Pennsylvania, selected for their range of rainfall characteristics. Sediment yields for all the cropland units in four of the watersheds were simulated using computer simulation models and 1985-2014 precipitation data from all six areas. Similarities and differences between rainfall amount, intensity, and erosivity (a measure of the rainfall potential to cause soil erosion) were compared with the similarities and differences in simulated sediment loss. The results indicated that model-based classification of field vulnerability could shift due to changes in precipitation characteristics. The results suggest that precipitation intensity or erosivity may help improve the correspondence between vulnerability and the range of expected soil loss. These results will help soil conservationists interpret the SVI with respect to rainfall and guide further efforts to improve the SVI.

Technical Abstract: The Soil Vulnerability Index (SVI) uses widely available inputs from the SSURGO database to classify cropland into four levels of vulnerability to sediment and nutrient losses: low, moderate, moderately high, and high. Previous work has identified inconsistencies in SVI assessments across the United States, possibly because neither precipitation amount nor intensity were included in the development of SVI. This study aimed to determine if rainfall characteristics influence the SVI classification and which ones are most critical. The objectives were to: (1) evaluate the impact of precipitation characteristics on land vulnerability to sediment loss, and (2) evaluate if rainfall characteristics alter the degree of agreement between the simulated sediment yield and SVI classification. The study included six Conservation Effects Assessment Project watersheds in Ohio, Missouri, Mississippi, Georgia, Maryland, and Pennsylvania, selected for their range of rainfall characteristics. Sediment yields for all the cropland units in four of the watersheds were simulated using the Soil and Water Assessment Tool or the Annualized Agricultural Non-Point Source Pollution Model using 1985-2014 precipitation data from all six areas as inputs. Similarities and differences between precipitation characteristics such as precipitation amount, intensity, and rainfall erosivity R-factors were compared with the similarities and differences in simulated sediment loss. The results indicated that model-based classification of field vulnerability could shift due to changes in precipitation characteristics. The results suggest that precipitation intensity or annual R-factor may help improve the correspondence between vulnerability and the range of expected soil loss.