Spatial Variability in Rainfall Erosivity versus Rainfall Depth: Implications for Sediment Yield

ity in rainfall erosivity and associated sediment yield. Rainfall erosivity and sediment yield can be measured Rainfall depth within small semiarid watersheds can have high much more cost effectively than runoff, an important spatial variability, but spatial variability in rainfall erosivity, a more direct determinant of sediment yield, has not been quantified. Using consideration when studying spatial variability. 12 tipping-bucket rain gauges within a 40-ha piñon [Pinus edulis Variation in precipitation characteristics can be parEngelm)–juniper (Juniperus monosperma (Engelm.) Sarg.] woodland ticularly high in semiarid areas, which are often domiin New Mexico, we measured rainfall erosivity (EI30) and associated nated by convective thunderstorms and orographic efprecipitation and erosion metrics for 14 convective thunderstorms. fects. Semiarid environments can exhibit considerable Spatial variability in EI30 had a median CV across storms of 22% temporal variability in storm, season, and annual rainfall (range: 9–73%), exceeded the median CV for rainfall depth (15%, characteristics, all of which can vary spatially. Spatial range: 5–26%), and varied by up to a factor of five (5–25 N h 1) within variation in mean rainfall depth has been shown to vary 300 m. EI30 was better correlated with sediment yield measured in by as much as 4 to 14% within a 100-m distance (Good0.1-ha microwatersheds (r2 0.67; p 0.001) than rainfall depth rich et al., 1995). Several researchers have noted that (r2 0.43; p 0.001). Our results highlight the potential importance for erosion related assessments of spatial variability in erosivity, which measurements from a single rain gauge can lead to large can be as great or greater than spatial variability in rainfall depth. uncertainties in rainfall depth for any region, and that The spatial variability in rainfall erosivity that we document here is such variation in rainfall depth has important implicarelevant to erosion and contaminant transport issues near Los Alamos tions for modeling runoff (Schilling and Fuchs,1986; National Laboratory and may be applicable to other extensive semiKrejci and Schilling,1989; Bonacci, 1989; Faures et al., arid areas. 1995). A more direct characteristic of precipitation in determining sediment yield is rainfall erosivity—the ability S applied environmental problems require esof rain to erode soil. Rainfall erosivity has been calcutimation of soil loss and associated sediment yield lated using a number of combinations and intervals of resulting from water erosion. Assessments of soil erosion precipitation characteristics (Wischmeier and Smith, are needed to evaluate contaminant mobility (Johansen 1958; Brown and Foster, 1987). The most general and et al., 2003), archeological site stability (Sydoriak et al., most often recommended approach for estimating rain2000), soil C reserves (Breshears and Allen, 2002), postfall erosivity uses the interaction between the storm fire hydrology (Beeson et al., 2001; Johansen et al., 2001, energy (E) (MJ ha 1) and the highest continuous 302003; Wilson et al., 2001), indices of ecosystem health min rainfall intensity (I30) (mm h 1). Storm energy is (Davenport et al., 1998), and efficacy of land management determined empirically using the method of Brown and treatments (Hastings et al., 2003). Hydrological models Foster (1987). The product of these factors equals rainare often essential tools for such assessments and vary fall erosivity (N h 1), noted as EI30. EI30 has been shown greatly in the level of complexity included. Generally to be a better predictor of sediment yield than rainfall these models are quite sensitive to some attributes of depth (Wischmeier and Smith, 1958; Foster et al., 1982) the input precipitation. Consequently, variation in preand is commonly used in modeling soil loss and sediment cipitation input, spatially as well as temporally, can be yield (Renard et al., 1997). Although rainfall erosivity quite important for assessments of soil erosion and sediis recognized as an important predictor of soil loss and ment yield. associated sediment yield, and rainfall depth has been Soil erosion and sediment yield are, of course, depenshown to vary substantially over short distances within dent on runoff and its associated variability. Here we the same watershed, spatial variability in rainfall erosivfocus on the largely unaddressed issue of spatial variability has not been quantified over short distances of tens to hundreds of meters. Yet many models’ simulations B.K. Hastings, Balance Hydrologics, Inc., 841 Folger Ave., Berkeley, assume homogeneity within distances this short. Some CA 94710; D.D. Breshears, Earth and Environmental Sciences Divimodels even depend directly on an estimate of EI30, such sion, Los Alamos National Laboratory, Mail Stop J495, Los Alamos, as the simplistic Revised Universal Soil Loss Equation, NM 87545, currently, Institute for the Study of Planet Earth, School of Natural Resources, and Department of Ecology & Evolutionary which is widely applied to address a variety of erosion Biology, University of Arizona, Tucson AZ 85721-0043; F.M. Smith, problems. Department of Earth Resources, Colorado State University, Fort Our objective was to quantify spatial variability in Collins, CO 80523. Received 7 Feb. 2004. *Corresponding author rainfall erosivity within small semiarid watersheds and ([email protected]). associated variation in rainfall depth and sediment yield. Published in Vadose Zone Journal 4:500–504 (2005). We focused on the most widely used metric of rainfall Special Section: Los Alamos National Laboratory erosivity: the product of total rainfall energy and highest doi:10.2136/vzj2004.0036 30-min rainfall intensity, EI30. In the semiarid regions © Soil Science Society of America 677 S. Segoe Rd., Madison, WI 53711 USA of the southwestern USA, spatial variability in rainfall 500 Published online July 18, 2005