Curve Number Hydrology

Hawkins, Richard H.; Ward, Timothy J.; Woodward, Donald E.; Mullem, Joseph A. Van

doi:10.1061/9780784410042

Cited by 135 publications

(8 citation statements)

References 90 publications

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“…Soil Conservation Service (SCS), 1954, 1956Ponce, 1996] based on storm-total rainfall-runoff data sets predominantly from small agricultural watersheds to help field technicians size sediment capture reservoirs and small flood control structures. As developed, the method was specifically targeted at these types of watersheds and had to be simple for a variety of reasons [see Hawkins et al, 2009;Hawkins, 2014]. The CN method was developed from a limited set of watershed observations and promulgated by the USDA-SCS without peer review.…”

Section: Origins Of the Cn Method And Reasons For Its Persistencementioning

confidence: 99%

“…Its proliferation into many simulation models [see Garen and Moore, 2005] beckons us to try and improve it. At least partly because of regulatory requirements owing to its simplicity and ease of use, the method has been extended to larger watersheds, pixels, continuous forms with discrete time steps, and situations where its use was never envisioned or intended, often incorrectly as an unjustified hasty generalization [Kleme s, 1986;Hawkins et al, 2009;Ogden and Stallard, 2013].…”

Section: Origins Of the Cn Method And Reasons For Its Persistencementioning

confidence: 99%

“…Intermittent and low intensity rainfall are problematic because the CN method ignores soil moisture redistribution [Hjelmfelt, 1980a]. In many cases where the CN method has been tested using high-quality data sets [e.g., Hawkins, 1984] it performed poorly, particularly in urbanized [Downer and Ogden, 2011], arid [Hjelmfelt, 1980b], semi-arid [Simanton et al, 1996;Puckett, 2008], tropical [Calvo Gobbetti et al, 2005], and varied constructed landscapes such as watersheds containing golf courses, that are much more hydraulically modified than pastures or grasslands [King and Water Resources Research 10.1002/2016WR020176 Balogh, 2008], forested watersheds [Hawkins et al, 2009;Tedela et al, 2011], as well as when applied to predicting forest fire effects on mountain hydrology [Chen et al, 2013]. Bartlett et al [2016] Users applying the CN method to predict land-use change effects unwittingly make the assumption of stationarity in runoff processes.…”

Section: What Can the Cn Methods Do And Not Do?mentioning

confidence: 99%

“…Bartlett et al [2016] wrote on page 4609 that the applicability of the CN method ''cannot be readily transferred to sites outside the Midwest (although many studies around the world continue to do so)''. In reality, the method was developed using data from around the continental U.S. [Mockus, 1964], but use of the method in forested catchments is not advised [Hawkins et al, 2009]. The additions and reinterpretations by Bartlett et al [2016] were aimed at extending the method to forested catchments, but we believe that it is unlikely for the following nine critical reasons (C1-C9):…”

Section: What Can the Cn Methods Do And Not Do?mentioning

confidence: 99%

“…C7. The Bartlett et al [2016] model does not allow predictions of specified (nonrandom) heterogeneity except by piecewise application, which represents a misapplication of what was developed as a watershedscale, not a pixel-scale method [Hawkins et al, 2009]. Even when spatial variability of various watershed properties is treated, how the spatial variability is organized (e.g., soil moisture deficient randomly distributed versus organized by wetness index with the same statistical properties) can have a very large impact on modeled runoff response [Grayson and Bl€ oschl, 2001].…”

Section: 1002/2016wr020176mentioning

confidence: 99%

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Comment on “Beyond the SCS‐CN method: A theoretical framework for spatially lumped rainfall‐runoff response” by M. S. Bartlett et al.

Ogden

Hawkins

Walter

et al. 2017

Water Resources Research

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Bartlett et al. (2016) performed a re‐interpretation and modification of the space‐time lumped USDA NRCS (formerly SCS) Curve Number (CN) method to extend its applicability to forested watersheds. We believe that the well documented limitations of the CN method severely constrains the applicability of the modifications proposed by Bartlett et al. (2016). This forward‐looking comment urges the research communities in hydrologic science and engineering to consider the CN method as a stepping stone that has outlived its usefulness in research. The CN method fills a narrow niche in certain settings as a parsimonious method having utility as an empirical equation to estimate runoff from a given amount of rainfall, which originated as a static functional form that fits rainfall‐runoff data sets. Sixty five years of use and multiple reinterpretations have not resulted in improved hydrological predictability using the method. We suggest that the research community should move forward by (1) identifying appropriate dynamic hydrological model formulations for different hydro‐geographic settings, (2) specifying needed model capabilities for solving different classes of problems (e.g., flooding, erosion/sedimentation, nutrient transport, water management, etc.) in different hydro‐geographic settings, and (3) expanding data collection and research programs to help ameliorate the so‐called “overparameterization” problem in contemporary modeling. Many decades of advances in geo‐spatial data and processing, computation, and understanding are being squandered on continued focus on the static CN regression method. It is time to truly “move beyond” the Curve Number method.

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Section: Origins Of the Cn Method And Reasons For Its Persistencementioning

confidence: 99%

Section: Origins Of the Cn Method And Reasons For Its Persistencementioning

confidence: 99%

Section: What Can the Cn Methods Do And Not Do?mentioning

confidence: 99%

Section: What Can the Cn Methods Do And Not Do?mentioning

confidence: 99%

Section: 1002/2016wr020176mentioning

confidence: 99%

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Comment on “Beyond the SCS‐CN method: A theoretical framework for spatially lumped rainfall‐runoff response” by M. S. Bartlett et al.

Ogden

Hawkins

Walter

et al. 2017

Water Resources Research

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Runoff of small rocky headwater catchments: Field observations and hydrological modeling

et al. 2016

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In dolomitic headwater catchments, intense rainstorms of short duration produce runoff discharges that often trigger debris flows on the scree slopes at the base of rock cliffs. In order to measure these discharges, we placed a measuring facility at the outlet (elevation 1770 m a.s.l.) of a small, rocky headwater catchment (area ∼0.032 km2, average slope ∼320%) located in the Venetian Dolomites (North Eastern Italian Alps). The facility consists of an approximately rectangular basin, ending with a sharp‐crested weir. Six runoff events were recorded in the period 2011–2014, providing a unique opportunity for characterizing the hydrological response of the catchment. The measured hydrographs display impulsive shapes, with an abrupt raise up to the peak, followed by a rapidly decreasing tail, until a nearly constant plateau is eventually reached. This behavior can be simulated by means of a distributed hydrological model if the excess rainfall is determined accurately. We show that using the Soil Conservation Service Curve‐Number (SCS‐CN) method and assuming a constant routing velocity invariably results in an underestimated peak flow and a delayed peak time. A satisfactory prediction of the impulsive hydrograph shape, including peak value and timing, is obtained only by combining the SCS‐CN procedure with a simplified version of the Horton equation, and simulating runoff routing along the channel network through a matched diffusivity kinematic wave model. The robustness of the proposed methodology is tested through a comparison between simulated and observed timings of runoff or debris flow occurrence in two neighboring alpine basins.

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Gully head modelling: A Mediterranean badland case study

Torri

Poesen

Rossi

et al. 2018

Earth Surf Processes Landf

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Predicting the location of gully heads in various environments is an important step towards predicting gully erosion rates. So far, field data collection and modelling of topographic thresholds for gully head development has mainly focused on gullies that formed in forested areas, rangelands, pastures and cropland. Such information for gullies in badlands however is very scarce. Therefore, this paper aims to extend the database on gully head topographical thresholds through data collection in a badland area and to improve the prediction of gully heads forming at sites with a very low erosion resistance value. For this, we chose a badland site located in central Italy that is characterized by biancana forms and both active and dormant gullies. The definition of the conditions under which present‐day gully heads developed allowed a better modelling of the gully head threshold equation, with modification of a previous model and the exemplification of how to use the updated model. The model shows that the resistance to gully head retreat depends on slope gradient and drainage area at gully heads, land use at the moment of gully development (as numerically expressed using parameters derived from the Runoff Curve Number method), surface rock fragment cover, presence of joints, pipes, and factors/processes affecting detachment rate. This study attempted to better understand environmental conditions that control the development of gully heads in badlands through a combination of field data collection of gully heads, an analysis of land use changes over 10 centuries, focusing on the period 1820–2005, and land use management through repeat photography and a critical examination of historical documents. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

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Curve Number Hydrology

Cited by 135 publications

References 90 publications

Comment on “Beyond the SCS‐CN method: A theoretical framework for spatially lumped rainfall‐runoff response” by M. S. Bartlett et al.

Comment on “Beyond the SCS‐CN method: A theoretical framework for spatially lumped rainfall‐runoff response” by M. S. Bartlett et al.

Runoff of small rocky headwater catchments: Field observations and hydrological modeling

Gully head modelling: A Mediterranean badland case study

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