To quantify the impact of organic matter (OM) amendments on soil aggregate stability, extracellular polymeric substances (EPS), and streambank fluvial erosion rates, increasing amounts of dried and crushed (< 1 mm) cool season grass clippings were used [0 (T0), 1 (T1), and 4 g of clippings per 100 g of soil (T4)]. A total of eight samples were created per treatment (24 samples in total); the treatments were compacted into the growth containers and allowed to mature in a greenhouse (temperatures ranged from 31 to 46°C during the day and 17 to 23°C throughout the night) for 50 days before erosion testing and soil sampling. A randomized complete block design was used, with one treatment randomly placed within each block. This was done to control for variation in an experiment by accounting for spatial effects in the greenhouse (e.g. differences in sunlight, temperature, etc.). Given the time required to complete erosion testing on one block of samples, placement of blocks in the greenhouse was staggered over a three-week timeframe starting in March 2021.
The flume bed slope was held constant at 0.1% and three flow rates were used (one per subsample): 17.5, 28.5, and 48.8 L/s. The sample was covered before running the flume prevented the application of hydraulic shear on the soil surface as the flow developed in the channel. Testing started once the flow became fully developed (about 90 seconds). The ADP was set to a recording frequency of 100 Hz. Erosion testing lasted for 10 minutes, or until all of the soil had been eroded away (whichever came first). The distance of the ADP probe head to the soil surface was monitored via the Vectrino software, and the soil core was advanced back to the initial position, flush with the wall, after every millimeter of erosion (Akinola et al., 2019). This process was repeated for all three soil subsamples using a different flowrate. The erosion testing time was reduced to 5 minutes for the T0 and T1 subsamples at 48.8 L/s due to the high amount of erosion that occurred. This was done so some soil would be left over for additional analyses following erosion testing. Volumetric water content and soil temperature were measured prior to the start of erosion testing.
The velocity time series data from the ADP was processed in R. ADP data were filtered out if the signal-to noise (SNR) ratio was ≤ 10 dB and the signal correlation (COR) was ≤ 40% (Martin et al., 2002; Strom & Papanicolaou, 2007). If a bin had 30% of its velocity data removed after filtering, that entire bin was removed from further analysis. Following data filtering, all velocity time series were despiked using the phase-space threshold method developed by Goring & Nikora (2002) and modified by Wahl (2002) using Matlab code created by Ikard Scott (2016).
After testing each subsample in the flume, the soil remaining was collected for EPS, aggregate stability, and organic matter content analysis. The collected subsamples were broken apart by hand and allowed to partially dry overnight at 20°C. The following day, a portion of the moist soil was forced through a 2-mm sieve and frozen at -15°C until EPS analysis. The remaining moist soil was air dried and 50 g of 3 – 5 mm aggregates was collected for aggregate stability analysis. The remaining air-dry soil was sieved through a 2-mm sieve and stored at room temperature for organic matter content analysis (loss-on-ignition). Aggregate stability was measured following the method outlined by Le Bissonnais (1996). The EPS extraction and analysis procedures used in this study follows methods described by Redmile-Gordon et al. (2014)
Citations:
Redmile-Gordon, M. A., Brookes, P. C., Evershed, R. P., Goulding, K. W. T., & Hirsch, P. R. (2014). Measuring the soil-microbial interface: Extraction of extracellular polymeric substances (EPS) from soil biofilms. Soil Biology and Biochemistry, 72, 163–171. https://doi.org/10.1016/j.soilbio.2014.01.025
Scott, I. J. (2016). Phase-space Threshold Algorithm for Time Series Data. Researchgate. https://doi.org/10.13140/RG.2.1.1831.4325
Strom, K. B., & Papanicolaou, A. N. (2007). ADV Measurements around a Cluster Microform in a Shallow Mountain Stream. Journal of Hydraulic Engineering, 133(12), 1379–1389. https://doi.org/10.1061/(asce)0733-9429(2007)133:12(1379)
Martin, V., Fisher, T. S. R., Millar, R. G., & Quick, M. C. (2002). ADV Data Analysis for Turbulent Flows: Low Correlation Problem. Hydraulic Measurements and Experimental Methods, 770–779. https://doi.org/10.1061/40655(2002)101
Goring, D. G., & Nikora, V. I. (2002). Despiking Acoustic Doppler Velocimeter Data. Journal of Hydraulic Engineering, 128(1), 117–126. https://doi.org/10.1061/ASCE0733-94292002128:1117
Akinola, A. I., Wynn-Thompson, T., Olgun, C. G., Mostaghimi, S., & Eick, M. J. (2019). Fluvial Erosion Rate of Cohesive Streambanks Is Directly Related to the Difference in Soil and Water Temperatures. Journal of Environment Quality, 48(6), 1741. https://doi.org/10.2134/jeq2018.10.0385
Wahl, T. L. (2002). Discussion of ‘“Despiking Acoustic Doppler Velocimeter Data”’ by Derek G. Goring and Vladimir I. Nikora. International Journal of Steel Structures, 128(1), 117–126. https://doi.org/10.1007/s13296-013-2015-4
Le Bissonnais, Y. (1996). Aggregate stability and assessment of soil crustability and erodibility: I. Theory and methodology. European Journal of Soil Science, 47, 425–437. https://doi.org/10.1111/j.1365-2389.1996.tb01843.x
