Qantifying support practice sub-factor values for erosion-control and sediment retention devices- phase ii

Soil erosion at roadway and other construction sites (Figure 1) can be 10 to 20 times higher than soil loss from agricultural lands (e.g., U.S. Environmental Protection Agency, EPA, 2000; Faucette et al., 2006). These large losses can lead to degrading soil and water quality, as well as higher construction costs to replace the lost soil and clean up the exported sediment. To quantify soil loss and the potential mitigating ability of Erosion Prevention and Sediment Control (EPSC) practices, like silt fences and sediment tubes, transportation departments around the country have adopted the Universal Soil Loss Equation, USLE, and it revised version, RUSLE (Tennessee Department of Transportation, TDOT, Drainage Manual, 2012). Overall, RUSLE offers a solid means for predicting gross soil erosion, despite certain limitations (Risse et al., 1993; Toy et al. 1999). RUSLE captures many key parameters, albeit empirically, that are needed for determining the average annual soil loss, A, in tons/ acre/ year and is expressed as the following: A = R × K × LS × C × P (1) where R is the rainfall-runoff erosivity factor and reflects the applied energy to dislodge soil particles; K is the soil erodibility factor and represents the susceptibility of a soil to erode due to rain splash or runoff; LS is the topographic factor, which is a dimensionless term capturing the slope length and steepness. For representing the effects of erosion prevention practices, RUSLE uses the cover management factor, C, which is another dimensionless term that accounts for prior land use, type of vegetative cover, quantity of residue on the surface, surface roughness and soil moisture. RUSLE also uses a support practice factor, P, which accounts for the use of sediment control devices. Project managers often have trouble, though, choosing EPSC devices when developing an erosion management plan due to uncertainty related to the C and P factors for the practices. Since RUSLE was designed for agricultural and other natural landscapes, there is little consensus on how the cover management and support practice factors translate to non-agricultural lands such as roadway and construction sites. This results in high uncertainty when applying RUSLE for determining the effectiveness of various erosion-control and sediment retention devices at construction sites (Karpilo and Toy, 2004). In practice, the C and P factors are correction multipliers that adjust bare soil erosion rates for the presence of a particular practice. The current approach for estimating C and P factors for EPSC practices is through large-scale physical experiments that compare the measured soil loss under bare soil conditions to the measured soil loss when the EPSC practice is used (e.g., TRI/Environmental, 2012). The experiments are performed using fixed and standardized soil, slope, and rainfall conditions. The factors are then back calculated to a reference value by setting all the other factors of the RUSLE equation constant (Karpilo and Toy, 2004; TDOT, 2012). The physical experiments offer a direct means to calculate the C and P factors (Karpilo and Toy, 2004). However, since fixed and standardized soil, slope, and rainfall conditions are used, the method inherently assumes that each EPSC practice has a single and unique C or P factor that will not vary. There is a question as to how representative a single C or P factor is for a particular practice. One of the key findings from our current study (TDOT RES: #2016-20) suggests that each practice type has a range of P factor values which is dependent on the relative partitioning between the amount of rainfall that infiltrates into the soil and the amount of rainfall that runs off. This partitioning is reflected through the runoff coefficient, which is the amount of runoff divided by the delivered rainfall. The runoff coefficient accounts for both the antecedent moisture condition and the compaction of the soils, which are two key factors at roadway construction sites. Figure 2 shows that the measured P factor values of the silt fence and the mulch sediment tube increase as relatively more runoff is produced. This is expected. However, the degree to which it increases is unexpectedly high – the range is from 0.01 to nearly 0.6 for the larger runoff coefficients. Since we are using the runoff coefficient instead of the rainfall intensity or magnitude, it means that even during a smaller event with a higher recurrence interval, the silt fence may not be as effective as thought, if the runoff coefficient is high. We are currently exploring the range of runoff coefficients expected in construction sites around Tennessee in TDOT RES: #2016-20. We are also seeking to address the question “Can we determine a more representative range of P factors (by also considering runoff) for commonly used EPSC devices without requiring a multitude of physical experimental tests for the broad range of conditions found across the state?” It has been suggested that the C and P factors for any practice can be computed by multiplying together individual sub-factors that are reflective of the physical characteristics of the practices (Toy et al., 1999; Karpilo and Toy, 2004). Examples of such sub-factors include a canopy cover factor, a surface cover factor, a surface roughness factor, a root biomass factor, a soil consolidation factor, and a soil moisture factor (Toy et al., 1999). In essence, the C and P factors reflect the effects of an applied roughness, cover, and/or modification of soil characteristics (in the form of an EPSC practice) to runoff and erosion. Our recent work (Abaci and Papanicolaou, 2009; Papanicolaou et al., 2018) builds on the suggestion to consider sub-factors that are more reflective of the physical characteristics of an EPSC practice and we take it one step further by also looking at the processes occurring around the practices and developing numerical tools to simulate the processes correctly. Thus, using the tools, we can generalize our results for multiple types of practices by simulating the effects of changes in the processes associated with their roughness, cover, and soil modification, on runoff and erosion. The benefit of employing a numerical tool to determine the effectiveness of an EPSC is that it only requires a description of the EPSC’s effect on roughness, cover and soil characteristics. Since the physical processes associated with these characteristics are already encoded into the tool, it is able to adequately simulate (extrapolate) the resulting effects of the EPSC on soil erosion for different rainfall, soil and slope conditions. This avoids the need to perform time-consuming and expensive physical experiments for every EPSC and combination of rainfall and landscape characteristics across the state in order to determine their effectiveness and range of values for the C and P factors. We propose to apply a physically-based model we developed in Papanicolaou et al. (2018), which considers how roughness, cover, and soil characteristics changes (that represent EPSC practices) affect runoff and erosion, to estimate C and P factors for the wide range of rainfall and landscape characteristics found in Tennessee. We will calibrate the model using our results from TDOT RES: #2016-20 and perform a host of numerical simulations to derive more comprehensive ranges of C and P factor values for select practice types. These values will be supplied in a database and incorporated into a simple spreadsheet-based erosion calculator to be used for design purposes.


    • English


    • Status: Active
    • Funding: $124,480.
    • Contract Numbers:



    • Sponsor Organizations:

      Tennessee Department of Transportation

      James K. Polk Building
      Fifth and Deaderick Street
      Nashville, TN  United States  37243-0349
    • Managing Organizations:

      Office of Research

      1534 White Avenue
      Knoxville, TN  United States  37996
    • Project Managers:

      Jonas-Fields, Stephanie

    • Performing Organizations:

      Office of Research

      1534 White Avenue
      Knoxville, TN  United States  37996
    • Principal Investigators:

      Papanicolaou, Thanos

    • Start Date: 20190801
    • Expected Completion Date: 20201130
    • Actual Completion Date: 0
    • USDOT Program: Transportation, Planning, Research, and Development

    Subject/Index Terms

    Filing Info

    • Accession Number: 01744429
    • Record Type: Research project
    • Source Agency: Tennessee Department of Transportation
    • Contract Numbers: RES2020-24, 40100-07219
    • Files: RiP, STATEDOT
    • Created Date: Jun 29 2020 5:50PM