The NRCS Curve Number, a New Look at an Old Tool
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The NRCS Curve Number, a New Look at an Old Tool Lawrence A.J. Fennessey, Ph.D., P.E. * and Richard H. Hawkins, Ph.D., P.E.** Abstract This paper reviews the Natural Resource Conservation Service Curve Number (CN) which is commonly used as the rainfall to runoff transformation term for small watershed hydrologic analyses. The CN is a hydrologic parameter that relies implicitly on the assumptions of extreme runoff events; however, during non-extreme runoff events in humid regions, the underlying assumptions are almost never valid. The CN method is only a quasi-empirical design tool and does not represent a true physical process. Therefore, the paper presents a new conceptual model of the CN based on recent hydrologic research. The paper concludes with an example of a traditional watershed analysis compared to the new conceptual model and discusses the impacts of each. Introduction The hydrologic methods developed by the Natural Resources Conservation Service (NRCS, formerly the Soil Conservation Service (SCS)) were originally developed as agency procedures and did not undergo journal review procedures (Ponce and Hawkins, 1996). The only official source documentation is the NRCS’s National Engineering Handbook, Section 4 (NEH-4). Unfortunately, NEH-4 has gone through several revisions (1956, 1964, 1965, 1969, 1972, 1985, and 1993) since first being published in 1954. The numerous revisions have resulted in confusion by people who use the methods (Hjelmfelt, 1991). One of the most misused and misunderstood NRCS parameters in the land development industry for stormwater management purposes is the curve number (CN). The origin of the original CN array tables seems to be lost; however, there also appears to be a misconception as to the scale of data that were actually used to develop the CN array table, or the CN’s accuracy for use in making peak runoff rate estimates. Although there have been no less than 100 articles discussing the CN array table values or their theoretical development since being introduced, Rallison (1980) and Fennessey (2001b) have published the only known papers indicating what watersheds the original data may have come from. The CN was initially developed as a design tool to estimate the transformation of return period rainfall into return period runoff for traditional agricultural lands in the United States. However, the CN method is now being used worldwide. The CN is now also commonly used as an abstraction term or loss model for both continuous and event simulations. These new applications have escalated in recent years, while the history and source of the original data become even more obscure. Technical Release No. 55 (TR-55) (USDA, 1986), a simplified NRCS method to estimate peak runoff rates using the CN and unit hydrographs, is now predominantly being used to model urban, pasture, meadow, and woodland areas, while the emphasis on the traditional agricultural CN values appears to be ignored. While the CN method was developed to compare the effect of land use/cover changes on runoff, some well-intentioned conservation groups, designers, and State agencies are even using the CN array table values to estimate the impact of very 1 specific land development designs as if the CN values are as reliable as, say, steam tables. Not only is the CN often considered far too reliable, but it is frequently used beyond its limitations. The curve number has a minimum recommended event size for use based on rainfall depth (in/24-hr). For example, the minimum 24-hour design rainfall depth for a CN of 65 ranges between 2.47 and 2.99 inches, depending on the reference source (USDA, 1986; Hawkins et al. 1985). Therefore, for much of Pennsylvania, CNs are not appropriate for even a 2-year return period for pre- development estimates when the land use/cover is woodland or meadow. Additionally, the CN method is not appropriate for use when surface runoff is from snowmelt, ice, sleet, or rain on frozen ground. Why do we still use the method under these conditions? Unfortunately, there is often nothing else available to use. Accuracy and Precision of CN Method Due to their ease of use, the TR-55 and Technical Release No. 20 (TR-20) (USDA, 1982) methods have gained wide acceptance not only among engineers and designers, but also by regulators and land management agencies. Fennessey et al. (2001a) conducted a random analysis of 50 Land Development and Stormwater Management Ordinances in Pennsylvania. The use of TR-55 for small watersheds was recommended or required in 49 of the 50 ordinances, while the other required TR-20. Because the methods were developed by a federal agency, the underlying assumptions by ill-informed users is that the methods must be very accurate. However, little is actually known in engineering practice about the accuracy or precision of the TR-55 and TR-20 methods for small watersheds. For large ungaged watersheds, hydrologic model accuracy for peak runoff rate estimates should be considered ± 30% at best. However, as watersheds become smaller, such as the typical size modeled for stormwater management purposes, the estimate accuracy for hydrologic models decreases. Using 37 gaged small watersheds, Fennessey et al. (2001b) showed that of 37 watersheds tested with the National Soil Conservation Service (NRCS) curve number (CN) runoff models (TR-55 (USDA, 1986) and TR-20 (USDA, 1982)), 25 were either over or under predicting the historical runoff rates by more than 30% with seven in error by several hundred percent (up to 1350%). In addition, Fennessey et al. (2001c) found that upslope hypothetical watersheds had traditionally-determined curve numbers 10 to 40 CN values too high when used in the CN runoff models, which resulted in extremely high over-estimates of runoff rates (as compared to gaged runoff rates). Hypothetical watersheds are land areas that are not true watersheds, but have been identified as a hydrologic study area. They are frequently based on property lines for land development projects, whereby a designer has placed curbing, berms, or channels along a property line to divert runoff within some boundary. The use of hypothetical watersheds is frequently justified in order to better model the effect of a development on surface runoff directly downstream. However, if the designer does not understand the limitations as well as the advantages of using these hypothetical areas, then major errors in judgment can be made. This is because hypothetical areas generally do not respond hydrologically as normal watersheds when in the undisturbed natural (pre-development) condition. Far too many water resource professionals have accepted the CN methods without independently reviewing extensive real hydrologic data. One example is the concept of the Antecedent Moisture Condition (AMC). When the CN was originally developed, it was well known that soil moisture played a significant role on the infiltration capacity of a soil. Therefore, instead of trying to determine or predict soil 2 moisture, the NRCS decided to account for the soil moisture using the amount of rainfall received in the five days preceding the storm event of interest. The NRCS defined this 5-day measurement as the antecedent moisture condition (AMC) (now called the antecedent runoff condition (ARC)). However, Hope and Schulze (1982) noted, in a personal communication with N. Miller, that the use of a 5-day index for ARC was not based on physical reality but rather on subjective judgment. Figure 1 shows the rainfall to runoff distribution for 33 years of record (where P>0.5” and Q>0.2”) for a small 19.2 acre watershed (Watkinsville, Georgia; ARS ID No. 10002) that had one land use/cover (good continuous pasture) for the entire 33 years (from 1947-1979). The AMC lines shown are based on the watershed’s computed CN (refer to Fennessey et al. 2001a). As one can observe even for these larger rainfall and runoff events, the AMC exhibits a large degree of scatter. Additionally, researchers have been unable to validate the NRCS 5-day index method. Nonetheless the concept still is frequently used by researchers and practitioners. However, many leading researchers consider the AMC to represent the variation in runoff volume (Q) from all sources such as model and data error, intensity, seasonal cover, and site moisture. In this context the AMC represents nothing more then error bands. Using the same 33-years of record as shown in Figure 1 (except using all 3,384 of the rainfall and runoff events), the CN from the Quadratic form of the CN equation using the actual rainfall/runoff data was computed. The computed CN data versus the daily rainfall are shown in Figure 2. One can readily observe from the figure that the CN is not constant, but varies from event to event. Therefore, site designers using best management practices to reduce the post development CN by a certain amount must realize that they are only dealing with an empirical design tool and not a physically based model that represents a true process. Several different ways exist to define the CN; however, this paper identifies the following four: the array table CN, the weighted “Design” CN, the “Best” CN, and the curve number infinity (CNinf). The Table CN is the curve number that is published in the NRCS CN array table. Table CNs are used with watershed land use descriptions, hydrologic condition, and hydrologic soil group (HSG) data to determine a “weighted” Design CN for the watershed. For a watershed with only one land use, a uniform hydrologic condition, and a single HSG, the Design CN for the watershed would be equal to the array table CN. The Best CN was developed from peak runoff rate data specifically for the evaluation of NRCS model peak runoff rate standard errors and biases (Fennessey, 2000).