5.3.1 Rainfall Erosivity Factor


 The rainfall erosivity factor (R-factor) is based on kinetic energy considerations of falling rain (Whelan 1980) and represents a measure of the erosive force and intensity of rain in a normal year (Goldman et al. 1986). Two components of the factor are the total energy and the maximum 30-min intensity of storms (i.e., the EI factor as defined by Wischmeier and Smith 1978, 1958). The R-factor is the sum of the product of these two components for all major storms in the area during an average year.

  Although R-factors have been estimated for the entire United States, they only reflect regional-type conditions; as such, Goldman et al. (1986) note that irregular topography in the western portions of the United States makes use of these regional-type calculations impractical. For the western United States, they suggest basing the R-factor on rainfall data. Wischmeier and Smith (1978) report that results of an investigation at the Runoff and Soil Loss Data Center at Purdue University showed that the R-factor could be approximated with reasonable accuracy by using the 2-year, 6-hr rainfall frequency distribution. Based on this frequency distribution, regression equations were developed to define R-factors for three different storm types (i.e., Type I, Type IA, and Type II).

  A Type II storm is characterized by gradually increasing rainfall followed by a strong peak in rainfall intensity that tapers off to low-intensity rain. Type II storms occur in 1) the eastern portions of California (i.e., east of the Sierra Nevada), Washington, and Oregon (Kent 1973; Goldman et al. 1986; Mitchell and Bubenzer 1980); 2) all of Idaho, Montana, Nevada, Utah, Wyoming, Arizona, and New Mexico (Kent 1973; Goldman et al. 1986; Mitchell and Bubenzer 1980); and 3) the remaining portions of the United States not covered by-Type I and Type IA storms (Kent 1973; Mitchell and Bubenzer 1980).

  Type I and IA storms occur in the maritime climate. Type I is typical of storms that occur in southern and central western California; these storms have a milder but definite peak similar to that of Type II storms. Type IA storms, which are characteristic of storms in coastal areas of northern California, Oregon, Washington, and the western slopes of the Sierra Nevada, have a low broad peak in the rainfall distribution (Goldman et al. 1986; Mitchell and Bubenzer 1980).

  The equations that have been developed for estimating R-factors, based on storm type and rainfall-frequency distribution, are (Mitchell and Bubenzer 1980; Goldman et al. 1986):



where    P2,6 is the 2-year recurrence interval, 6-hr duration rainfall depth (cm).

 The factors (0.2232) and (0.2296) in Equation 5.50 are needed to convert Rfact from the English units used in Goldman et al. (1986) to the metric units used in this report. When the rainfall volume for the 2-year, 6-hr rainfall-frequency distribution and the corresponding R-factors are compared, it is evident that the stronger the peak intensity of the typical storm that is characteristic of a given area, the larger the rainfall erosivity factor.

  The R-factor described by Equation 5.50 does not include the erosive forces from thaw or snowmelt. Mitchell and Bubenzer (1980) note that McCool et al. (1974, 1976) show that a major erosion potential occurs in the form of low-intensity rainfall or snow during winter months. Wischmeier and Smith (1978) suggest modifying the R-factor at those sites where snowmelt may be important. To provide more discrimination between those sites that traditionally have snowmelt runoff from those where it occurs occasionally, the average-annual R-factors, as defined by Equation 5.50, are increased by an amount equaling 0.591 times the total precipitation (in cm) associated with those months having an average monthly temperature below freezing, including the first month following the last freezing month. (a)

(a)
Note that Wischmeier and Smith (1978) suggest using the precipitation total for the entire period from December through March. Because the runoff volume associated with the MEPAS methodology is based on historically averaged monthly precipitation amounts, it is difficult to determine a priori which locations will traditionally have significant snowmelt runoff. To provide some differentiation between sites, the monthly average temperature is used to help determine the effects of snowmelt runoff.