Runoff curve number and saturated hydraulic conductivity estimation via direct rainfall simulator measurements

Abstract

Surface runoff can be estimated directly from conceptual models such as the runoff curve number (RCN) method or indirectly from physically based infiltration models such as the Green-Ampt method (Ponce, 1989; McCuen, 2003; Mishra and Singh, 2003). Both methods are widely accepted models for predicting surface runoff in both agricultural and urbanized watersheds due to their simplicity and to the limited number of parameters required for runoff prediction. In addition, they have been integrated into many hydrologic, storm water management and water quality models such as the erosion productivity impact calculator EPIC (Sharpley and Williams, 1990), the soil and water assessment tool SWAT (Arnold et al., 1998), and the stormwater management model SWMM (Rossman et al., 2003). The key parameters involved in the RCN and the Green-Ampt methods are the runoff curve number (CN) and the saturated hydraulic conductivity (Ksat) respectively, which can be obtained from tables as functions of soil texture, management practice, and land use. The use of singular tabulated CN and Ksat values without verification can result in large errors in predicting surface runoff. Frequent flooding in the Midwest over the past two decades (e.g. 1993, 2008) has raised the need for revised CN and Ksat values to accurately estimate the surface runoff of different watersheds. In this present study, the authors estimated ranges of CN and Ksat values for the different hydrologic soil groups in Iowa, which was affected by devastating flooding in 2008 and 2011. Representative counties from Iowa with different soils were chosen to estimate the CN and Ksat values. This chapter describes detailed methodological steps to estimate in situ runoff CN and Ksat values from rainfall simulators. This is useful because the rainfall simulators eliminate the need for natural storm events, and their intensity can be adjusted during an experimental run to mimic natural rain.