Assessment of Infiltration Methodologies for Calcareous Silty Soils in Idaho’s Magic Valley

Idaho ranks in the top 10 in the U.S. for dairy, potato, barley, hay, sugar beet, corn silage, and dry bean production. The highest producing areas in the state for these commodities are in southern Idaho where irrigation is necessary. Water quality is impaired in the region but has been improving due to some best management practice implementation. To measure progress in producer efforts for reducing erosion and runoff, appropriate methods need to be identified. The soils in this region are prone to crusting, have low organic matter, and are high in calcium carbonates making these soils unique to much of the U.S. Thus, the overall goal of this project was to identify the best method for the assessment of infiltration properties. Two study sites were located on the USDA-ARS Northwest Irrigation and Soils Research Laboratory in Kimberly, Idaho, and were established in 2013 (Long-Term Manure) and 2016 (Cover Crop). A randomized complete block design with four replicates was used for the Long-Term Manure study; plots were under different manure and fertilizer treatments. Briefly, the study design consisted of eight treatments: three rates solid dairy manure applied annually or biannually, a control (no fertility additions, and inorganic fertilizer only. The cover crop study was set up as a split-plot design with four replications with tillage as the main experimental factor (direct seeding vs disk/chisel plow) and treatment as the subfactor (cover crop with manure, cover crop without manure, no cover crop with manure, no cover crop without manure). Both studies were assessed for soil physical properties in late summer 2020. All plots were assessed for saturated hydraulic conductivity using both a SATURO infiltrometer (Meter Group, Inc.), which utilizes the two ponding head method (Reynolds and Elrick, 1990) as well as a Cornell Sprinkle Infiltrometer (CSI), which more closely simulates irrigation (van Es and Schindelbeck, 2001). In addition, other infiltration characteristics were defined using the Cornell Sprinkle Infiltrometer, such as infiltration before runoff and runoff rate. Soils data were analyzed using a linear mixed-effects model (lme function) with the nlme package in R. Initial results indicate that the SATURO was not sensitive to management even in the studies that were in years eight (Long-Term Manure) and four (Cover Crop). Saturated hydraulic conductivity in Long-Term Manure ranged from 1.62E-2 to 2.03E-4 cm s^-1 with an average of 5.82E-3 cm s^-1. Saturated hydraulic conductivity in Cover Crop ranged from 8.02E-3 to 1.07E-4 cm s^-1 with an average of 1.92E-3 cm s^-1. For reference, the USDA-NRCS WebSoilSurvey indictes that Portneuf silt loam has an average saturated hydraulic conductivity of 4.55E-4 cm s^-1, while Rad silt loam has a value of 6.74E-4 cm s^-1 (http://websoilsurvey.nrcs.usda.gov). Furthermore, there were no treatment differences with the CSI in the Long-Term Manure study. For this study, saturated hydraulic conductivity ranged from 1.25E-2 to 5.59E-3 cm s^-1 with an average of 9.26E-3 cm s^-1. While saturated hydraulic conductivity did not differ by treatment or tillage using the CSI in the Cover Crop Study, there were some statistical differences between treatments in runoff rate and rainfall depth before runoff. Saturated hydraulic conductivity, as measured by the CSI, ranged from 1.07E-2 to 7.16E-3 cm s^-1 with an average of 8.89E-3 cm s^-1. For rainfall depth before runoff, tillage also did not show statistical differences but cover crop + manure had significantly greater depth before runoff than the no cover crop without manure treatment (p<0.05). Neither method for testing saturated hydraulic conductivity showed sensitivity to management in the two experiments investigated for this study. On average, the CSI method resulted in a saturated hydraulic conductivity measurement that was 43% to 80% greater than the SATURO. By using the CSI to measure saturated hydraulic conductivity, there is additional data that can be collected, such as depth of rainfall before runoff and runoff rate.