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Home , Runoff curve number, Stormwater, Stream

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 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 Conservation Service (NRCS, formerly the 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 development industry for 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 rainfall into return period runoff for traditional agricultural in the . 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 , 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 /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

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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 , 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 is from , , sleet, or 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 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 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 resource professionals have accepted the CN methods without independently reviewing extensive real hydrologic data. One example is the concept of the Condition (AMC). When the CN was originally developed, it was well known that played a significant role on the capacity of a soil. Therefore, instead of trying to determine or predict soil

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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). The Best CN is the curve number that, when used in a NRCS runoff model, best estimates the historical peak runoff rates from a gaged watershed. The Best CN is selected such that the standard error of the peak runoff rates is minimized over the analyzed return periods. The Table, Design, or Best CN values do not represent actual rainfall-to- runoff data. The use of these CNs can allow a determination of how well existing models estimate historical peak runoff rates, but they cannot be used to determine actual differences in direct runoff volumes between or within watersheds. In order to compare differences in the runoff volume between watersheds, a data-defined volume is used that represents an actual runoff volume based on historical data from the watersheds. This data-defined CN is the CNinf, which is also referred to as the asymptotically determined CN. The origin and concept of the CNinf can be traced back to several publications: Hawkins (1990), Sneller (1985), Zevenbergen (1985), and Hjelmfelt (1980). The CNinf has been found to be an excellent variable to determine if one watershed produces greater direct runoff volume than another watershed.

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If the curve number concept and its application were perfect, then the Design CN determined from the CN array table should equal (or be very close) to the Best CN and the CNinf. Figure 3 shows each of these three CN values compared for 60 small watersheds in the United States. The x axis represents the watersheds labeled 1 to 60, which have been ranked by their Design CN for ease of observation. It is readily obvious that the three CNs are not the same and in many cases vary by more than 10 CN. Sometimes all three values will be similar, but it is more common that the Best CN and the CNinf. are similar, and vary from the Design CN. However, all three are frequently very different for the same watershed. Additionally, the Best CN shown in Figure 3 can vary because it is dependent on the return periods selected for its determination. Finally, the reader should be cautioned not to try to determine additional trends from Figure 3, since it represents numerous types of watersheds including hypothetical and wooded watersheds. The only purpose of Figure 3 is to show that the three CN are generally very different for the same watershed.

New Findings

While the original CN was only a quasi-empirical design tool and did not actually reflect any true physical runoff process, recent studies have indicated that errors in the Best CN or the CNinf appear to index physical processes. Work by numerous researchers has shown that Horton infiltration excess does not dominate the generation of overland flow in undisturbed well-vegetated humid areas of the northeastern United States (refer to Fennessey and Miller, 2001). Rather, research has shown that runoff is frequently generated in saturated areas around drainageways and expands from these areas along hollows or areas where the is close to the surface (Chorley, 1978; Hewlett and Hibbert; 1967; Ward, 1984). How a watershed in a humid region may respond during a rainfall event can be seen in Figures 4 through 6. Figure 4 shows the saturated area that could be expected at the beginning of a storm. During this time only the rainfall falling on the or those areas around the stream that are initially saturated due to the table intersecting the land surface would produce surface runoff. These areas are referred to as the initial contributing area (ICA) of a watershed (Gburek, 1990). Figure 5 shows the saturated area near the end the storm where the saturated areas that generate surface runoff have expanded. The location of an area within a watershed is significant in determining the hydrologic response of an area (Fennessey et al. 2001c). Areas near an active drainageway would become saturated at a quicker rate during the storm. Many areas of the watershed have their runoff response dependent on their ability to generate saturation excess around the drainageway. Saturation excess is defined here as the saturation of the near soil surface due to one of many causes such as a fluctuating water table, restrictive layer, etc. During storms, the watershed may or may not see an increase in the saturated areas, depending upon the of the event. However, most important is the fact that upslope areas, especially those with convex or straight contours, almost never generate saturation excess surface runoff, and therefore are most dependent on infiltration excess to generate surface runoff. Figure 6 shows an example of how the saturated areas may expand during a major rainfall event. Again, note that the upslope areas may still not generate effective surface runoff. Additionally, upslope areas may exist where infiltration excess or saturation excess occurs frequently, but effective surface runoff still does not occur. This is because, unless the area is directly connected to an active drainageway, it often will

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not become effective stormflow. In these areas localized ponding occurs which eventually evaporates or infiltrates. These areas may become connected and effective during larger runoff events. However, as in the case of karstic underlain watersheds, the ponding areas may be large closed depressions that retain runoff from even extreme events. Geomorphology, the study of the origin and development of landforms, has taken a somewhat parallel path as . Although geomorphologists have been concerned with the properties of profile form more so than its effect on runoff, their research has continued to support more contemporary ideas regarding the hydrologic process. In 1960, Hack and Goodlett noted that stream head hollows, where surface flow lines converge, were especially susceptible to surface runoff. Anderson and Burt (1977) conducted an experiment that showed the moisture conditions in a hillslope hollow over time. The study clearly showed that soil moisture was highest generally in the area around the hollow. They concluded that the results demonstrated the significant control of topography on soil moisture conditions and the resulting stream flow response. O’Loughlin (1981), in conducting a theoretical analysis, stated that “the size of saturated zones of undulating hillslopes with gradational is shown to depend strongly on topographic convergence or divergence.” Location and topographic effects are considered to some degree in physically-based models; however, these models are decades away from being used on a regular basis in engineering practice, especially for small stormwater management studies related to land development practices. One simple way to consider topographic effects is with the inflection angle. The inflection angle is the angle a makes with itself when crossing a drainageway (refer to Figure 7). As the inflection angle decreases, the volume and rate of runoff increase, all other things being equal (Fennessey, 2001c). Some scientists may argue that the inflection angle may not really affect runoff directly, but rather it describes physical differences in watersheds that do affect runoff. A small inflection angle indicates the presence and distinctness of channelization in the main drainageway. Soils near drainageways generally have a higher percent of fine soil textures, which result in lower soil permeability. Channels or hollows generally have higher soil moisture levels than similar upslope land areas and water tables are also closer to the surface, both of which play important roles in the generation of surface runoff. Additionally, the inflection angle also appears to be a refined measure of the location. Zero-order watersheds with large inflection angles are generally located on the upper slopes of watersheds, while those with small inflection angles are generally located near an active network. The inflection angle is an ideal, and relatively easy-to-define, variable when extensive site data are unavailable to account for these other factors. Fennessey (2000) was also able to show that a strong trend existed between the relative distance of a gaged zero-order watershed’s outlet to an active higher order stream (refer to Figure 8). As the relative distance (labeled D1 and D2 on Figure 8) decreases, the volume and rate of runoff also increase. The inflection angle, area location, and the relative distance from the watershed outlet to a stream are all related forms describing a watershed’s relative position within the . The relative location of a small zero-order watershed within a larger watershed was shown to be the dominant hydrologic variable of the 65 small watersheds used in the study by Fennessey (2000).

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NRCS Hydrologic Soil Group (HSG)

The use of best management practices (BMPs) in recent years has been aimed at the reduction of changes in runoff volume following development. However, in order to effectively do this, we must understand both hydrologic processes and the limitations of our data. Far to many people are relying on soil surveys or Hydrologic Soil Groups as defined by the NRCS to evaluate changes in volume for less than extreme runoff events. However, soil surveys and the data they contain are only a starting point from which to design a site plan. The soil survey is a planning level tool only, which contains excellent data that should be used to restrict development in some areas or help plan where more detailed study should be conducted. Unfortunately, the neglect of subsurface features such as fragipans or clay pans, which are well defined in the surveys, can cause flooding problems for with or without upslope development. However, this type of information in the Soil Surveys is often neglected, while to much emphasis is placed on the use of Hydrologic Soil Groups (HSG). The HSG was originally developed as an approximate average value used to estimate runoff potential. Four HSG types are used to represent thousands of soils underlain by different geology in different regions of the United States. HSG were developed considering rainfall events that produced large events. The HSG were determined by “assuming that the soil surfaces were bare, maximum swelling had taken place, and rainfall rates exceeded surface intake rates” (USDA, 1993) and after prolonged wetting using the soil B horizons. This is almost never the case for most rainfall events, especially those that BMPs are aimed at functioning during. Additionally, the HSG has nothing to do with recharge, and should not be used as an indicator of recharge, or for any other purpose that it was not originally intended for. The all-to-frequent failure of residential septic leach beds in all types of soils (and HSG) should lead one to be cautious of placing too much emphasis on Hydrologic Soil Groups or infiltration systems for large impervious developments to control radical changes in volume. When done, these systems need to be thoroughly investigated and engineered. Unfortunately, the HSG is used to determine the CN, which can compound errors when processes are neglected.

A New Concept

The last decade has seen intensive research regarding the CN using extensive gaged data from small watersheds. These analyses of data defined watershed CNs, have been used to develop a new concept for curve numbers for design analysis considering a more runoff process oriented perspective. This new concept has a significant impact on the use of the CN for land development designs for non-extreme runoff events or stormwater management purposes in well vegetated humid regions. The impacts of the concept can best be seen using an example. Figure 9 shows the land use and HSG for our example watershed where all land areas are considered to be in hydrologically good condition. The method of determining CN values for the watershed would be to use an average weighting method based on the land use/cover, HSG, and hydrologic condition as presented in Figure 9. The results of this traditional method are shown in Figure 10. The average weighted CN at the outlet is assumed to be 70. Some site designers are using site plans such as Figure 10 to locate developments and best management practices such as infiltration trenches or where to place cluster types of developments.

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However, when we consider a watershed area’s relative position within the landscape, we come up with a very different CN map for the watershed, especially for rainfall events that BMPs are designed for, or that cause nuisance flooding (refer to Figure 11). Figure 11 shows a hypothetical example of how the CN should be determined for a watershed experiencing a non-extreme runoff event (say 25mm or 1”) in a well vegetated humid region. As can be seen, the average weighted CN at the outlet is still 70; however, the stream and the saturated areas around the stream would have high CNs (98 or 100). As we move away from the active saturated areas the CN would decrease until we reached the upper slopes where the CN could realistically be best represented by a 40 or 50 for the pre-development condition. Recall that the larger the CN the more likely the estimate is surface runoff, while lower CNs have a higher proportion of (USDA, 1993). Unfortunately, the CNs in this conceptual model would vary from event to event and even during the event. However, note that little of the model is dependent on the HSG. Nonetheless, this model conceptually, is a much better representation of what commonly occurs in humid regions during non-extreme runoff events and can explain why people downstream of stormwater ponds frequently complain about both the increased rates and volumes of runoff following a development. This model, while not currently quantifiable using the CN, should be considered when trying to determine the impacts of development, or for determining where to place impervious areas or BMPs. As seen in Figure 12, if the site designer placed a high impervious cluster development on the upper slopes, downstream problems could eventually occur, even if infiltrating best management practices were employed. The reason is because, when a larger event occurs it may result in the release of a peak runoff rate from the overflow stormwater management facility that was estimated too high for the area using the traditional model. Additionally, clustering impervious areas on the upper slopes creates an unnatural point of surface runoff unless extremely effective and long infiltrating BMPs are employed. However, even if a BMP, such as an infiltration trench, was used with a high impervious area site, the trench could possibly concentrate subsurface water in an adverse way or result in rejected recharge a short distance downstream. Unfortunately, some groups are advocating practices under the guise of stormwater management that should be left to zoning or planning personnel attempting to combat urban sprawl or the loss of agricultural lands and open space, which are worthy causes in their own right. One such topic is the attack on the percentage of imperviousness in residential zones. While advocating the reduction of unnecessary impervious areas in site design is fundamentally valid and justifiable due to its potential impact on both water quantity and quality, much of the current information is misleading. Researchers know that the location of the source is one of the most critical components affecting . Additionally, knowledge of source areas of surface runoff and their dynamics is critical for water quality management (Srinivasan, 2000). However, stressing the impervious percentage alone is flawed in that it neglects hydrologic processes. To argue that one has designed an improved residential development because the site was redesigned using the traditional CN model (Figure 10) to locate impervious areas, thus reducing the post-development CN by one or two CN values is unfounded. The protection of drainageways (even minor ones) and other riparian areas should supercede all efforts or concerns regarding watershed impervious area percentages for residential areas. Removing direct connectivity of impervious areas is critical to both water quality and quantity. The conceptual CN model proposed herein allows one to readily see why pollutants around drainageways can have

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detrimental effects on water quality and can move much more rapidly through the system than expected. However, a Catch 22 condition exists. While development near drainageways may have the most adverse impact on water quality, development placed on upslope areas will almost always have the most significant impact on runoff quantity, which can affect water quality. For this reason, a much more effective development, from a stormwater perspective, would be to disperse the clustered development shown in Figure 12 intelligently along the proper slopes in conjunction with the use of infiltration BMPs, while still protecting the drainageways. However, this must still be done with caution, because soils with low CNs are also more prone to due to their loose structure and large pores spaces. Additionally, by studying Figure 11, we can see that no buildings should ever be built in any drainageway, even mild draws, because, once the rainfall is infiltrated it does not simply always percolate downward through the soil but often moves laterally through the soils towards the drainageways. This is why some can become flooded without observing surface runoff in the area. Researchers or scientists generally need to conduct extensive field investigations just to begin to understand which processes are dominant and how they change during events, with different types of events, and at different times of the year. However, there is a very simple method that can be used to prevent both nuisance or major from becoming a burden on anyone around drainageways and also protect water quality at the same time. The secret is simply, leave these drainageways undisturbed. Finally, variations in runoff processes can present real challenges for anyone trying to model water quality or design BMPs for stormwater runoff. Trying to implement recharge BMPs in areas prone to saturation will generally fail unless the designer fully understands the limitations and has incorporated them into their design goals. Additionally, trying to place water quality structures for development activities in frequently saturated areas, instead of addressing water quality in upslope areas, must be carefully considered by the designer in order to be truly effective. However, the concept proposed here should be considered when trying to address these issues.

Conclusion

The NRCS CN method has been taken at face value in the land development industry for stormwater management analyses. However, the CN methods are no more reliable or accurate than any hydrologic model used to make estimates of runoff for ungaged watersheds. However, as long as water resource professionals recognize the methods limitations and the fact that it is only a quasi-empirical design tool and does not reflect true physical processes, errors in its application can be avoided. This paper has presented a new conceptual CN model that should be considered when designing land development projects in humid regions. The model is based largely on the assumptions that runoff is only generated from a small portion of a natural undisturbed watershed (frequently the pre-development condition). This model allows one to see why the protection of waterways should be any watershed managers main concern. Additionally, site designers must stop blindly using older empirical design tools and once again start applying sound engineering judgment. For stormwater management to be truly effective, planners, designers, and regulatory agencies must stress:

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1) Consideration of the dominant hydrologic processes that occur in an area 2) Common sense 3) Simplicity 4) Sound and correctly applied science

References

Anderson, M.G. and T.P. Burt. 1977. Automatic Monitoring of Soil Moisture Conditions in a Hillslope Spur and Hollow. Journal of Hydrology 33:27-36. Fennessey, L.A. 2000d. The effect of the Inflection Angle, Soil Proximity, and Location on Runoff. Ph.D. Dissertation. The Pennsylvania State University. University Park, PA. Fennessey, L.A., J.M. Hamlett, G. Aron, and D. LaSota. 2001a. Changes in Watershed Runoff Due to Stormwater Management Pond Regulations. ASCE, Journal of Hydrologic Engineering 6(4):317-327. Fennessey, L.A., J.M. Hamlett, A.C. Miller. 2001b. Accuracy and Precision of NRCS Models for Small Watersheds. Journal of AWRA 37(4). Fennessey, L.A., J.M. Hamlett, A.C. Miller. 2001c. The Effect of Inflection Angle and Relative Location on Runoff From Zero-Order Watersheds. ASCE ERWI World Water Congress, May 20-24. Fennessey, L.A. and A.C. Miller. 2001. Hydrologic Processes During Non-Extreme Events in Humid Regions. Villanova University, Southeastern Pennsylvania Stormwater Management Symposium. Oct., 17-18, 2001. Gburek, W.J. 1990. Initial Contributing Area of a Small Watershed. Journal of Hydrology, 118:387-403. Hack, J.T and J.G. Goodlett. 1960. Geomorphology and Ecology of a Mountain Region in the Central Appalachians. US Geological Survey Professional Paper 347, pp. 66. Hawkins, R.H. 1990. Asymptotic Determination of from Data. In Symposium Proceedings of IR Conference, ASCE, Durango, Colorado. Pp67- 76. Hawkins, R.H., A.T. Hjelmfelt, and A.W. Zevenbergen. 1985. Runoff Probability, Storm Depth, and Curve Numbers. Journal of and Drainage Engineering, ASCE 111(4):330-340. Hjelmfelt, A.T. 1980. Empirical Investigation of Curve Number Technique. Journal of the Hydraulics Division, American Society of Civil Engineers 106(9):1471-1476. Hjelmfelt, A.T. 1991. Investigation of the Curve Number Procedure. Journal of , ASCE 117(6):725-737. O’Loughlin, E.M. 1981. Saturation Regions in Catchments and Their Relations to Soil and Topographic Properties. Journal of Hydrology 53:229-246. Ponce, V.M., and R.H. Hawkins. 1996. Runoff Curve Number: Has it Reached Maturity? Journal of Hydrologic Engineering, ASCE 1(1):11-18. Rallison, R.E. 1980. Origin and Evolution of the SCS Runoff Equation. Watershed Management, ASCE, pp. 912-924. Sneller, J.A. 1985. Computation of Runoff Curve Numbers for from Landsat Data. Hydrology Laboratory Technical Report HL85-2. USDA, ARS, Hydrology Laboratory, Beltsville, . ca 50pp. Srinivasan, M.S. 2000. Dynamics of Stormflow Generation: A Hillslope-Scale Field Study. Ph.D. Dissertation. The Pennsylvania State University. University Park, PA.

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United States Department of Agriculture, Soil Conservation Service. 1982. Computer Program for Project Formulation Hydrology. Technical Release No. 20. Second Edition. Washington, D.C. United States Department of Agriculture, Soil Conservation Service. 1986. Urban Hydrology for Small Watersheds. Technical Release No. 55. Second Edition. Washington, D.C. United States Department of Agriculture, Soil Conservation Service. 1993. National Engineering Handbook. Section 4, Hydrology. Washington, DC. Zevenbergen, A.T. 1985. Runoff Curve Numbers from Rangeland from Landsat Data. Hydrology Laboratory Technical Report HL85-2. USDA, ARS, Hydrology Laboratory, Beltsville, Maryland. ca 70pp.

*Senior Hydraulic Engineer, Group, Sweetland Engineering & Associates, Inc. State College, PA; 16801; PH: (814) 237-6518; Fax: (814) 237- 1488; [email protected] **Professor, Watershed Resources Program, School of Renewable Natural Resources, University of Arizona. Tuscon, AZ 85721; PH: (520) 621-7273; Fax: (520) 626-7401; [email protected]

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Figure 1. Typical Trend when Comparing Q to P Considering AMC

Figure 2. Typical Trend for CN Computed from Gaged Data

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Figure 3. Design CN, Best CN, and CNinf Compared for 60 Watersheds

Figure 4. Example of Saturated Areas at Beginning of Storm in a Humid Region

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Figure 5. Example of Saturated Areas Near the End of Storm in a Humid Region

Figure 6. Example of Saturated Areas During a Major Storm in a Humid Region

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Figure 7. Example of the Inflection Angle and its Affect

Figure 8. Example of the Relative Distance to a Drainageway

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Figure 9. Example Watershed Used for Land Development Scenario

Figure 10. Traditional Method of Determining curve numbers

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Figure 11. Hypothetical Model Showing Affect of Location on CN for a Natural Watershed in a Humid Region

Figure 12. New Model of CN Showing Upslope Cluster Development

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