Reclaimed Mineland Curve Number Response to Temporal Distribution of Rainfall1

Warner, Richard C., Carmen T. Agouridis, Page T. Vingralek, and Alex W. Fogle, 2010. Reclaimed Mineland Curve Number Response to Temporal Distribution of Rainfall. Journal of the American Water Resources Association (JAWRA) 46(4): 724-732. DOI: 10.1111/j.1752-1688.2010.00444.x Abstract: The curve number (CN) method is a common technique to estimate runoff volume, and it is widely used in coal mining operations such as those in the Appalachian region of Kentucky. However, very little CN data are available for watersheds disturbed by surface mining and then reclaimed using traditional techniques. Furthermore, as the CN method does not readily account for variations in infiltration rates due to varying rainfall distributions, the selection of a single CN value to encompass all temporal rainfall distributions could lead engineers to substantially under- or over-size water detention structures used in mining operations or other land uses such as development. Using rainfall and runoff data from a surface coal mine located in the Cumberland Plateau of eastern Kentucky, CNs were computed for conventionally reclaimed lands. The effects of temporal rainfall distributions on CNs was also examined by classifying storms as intense, steady, multi-interval intense, or multi-interval steady. Results indicate that CNs for such reclaimed lands ranged from 62 to 94 with a mean value of 85. Temporal rainfall distributions were also shown to significantly affect CN values with intense storms having significantly higher CNs than multi-interval storms. These results indicate that a period of recovery is present between rainfall bursts of a multi-interval storm that allows depressional storage and infiltration rates to rebound.     

Runoff Curve Numbers at the Agricultural Field‐Scale and Implications for Continuous Simulation Modeling

This study used monitoring in the waterways of agricultural fields to understand the use of the runoff curve number (CN) in continuous simulation models. The CN has a long history as a design tool for estimating runoff volumes for large, single storms on small watersheds, but its use in continuous simulation models to describe runoff from smaller storms and relatively small areas is more recent and controversial. We examined 788 nonwinter rainfall events on four agricultural fields over five years (2004‐2008) during which runoff was generated in 87 events. The largest 20 runoff events on each field generated approximately 90% of the total runoff volume. The runoff event CNs showed an inverse correlation with storm depth that could not consistently be explained by previous precipitation. We review how small areas of higher runoff generation within larger areas will systematically increase the apparent CN of the larger area as the storm size decreases. If this variation is not incorporated into a model explicitly, continuous simulation modelers must understand that when source areas are aggregated or when runoff generation is spatially variable, the overall CN is not unique when smaller storms are included in the calibration set.     

Differences in Dissolved Organic Carbon and Nitrogen Responses to Storm‐Event and Ground‐Water Conditions in a Forested,Glaciated Watershed in Western New York1

Abstract: Differences in the storm‐event responses of dissolved organic carbon (DOC) and nitrogen (DON) in streamflow and ground water were evaluated for a glaciated forested watershed in western New York. Eight to ten storm events with varying rainfall amounts, intensities, and antecedent moisture conditions were studied for three catchments (1.6, 3.4, and 696 ha) over a three‐year period (2003‐2005). Concentrations of DOC in streamflow exiting the catchments were significantly higher for storm events following a dry period, whereas no similar response was observed for DON. Highest DON concentrations in streamflow were typically associated with storm events following wet antecedent moisture conditions. In addition to antecedent moisture conditions, DOC concentrations were also positively correlated with precipitation amounts, while DON did not reveal a consistent pattern. Streamwater and ground‐water concentrations of DOC during storm events were also strongly correlated with riparian ground‐water depths but a similar relationship was not observed for DON. Ground‐water DON concentrations were also more variable than DOC. We hypothesized that the differences in DOC and DON responses stemmed from the differences in catchment sources of these solutes. This study suggests that while DOC and DON are intrinsically linked as components of dissolved organic matter, their dynamics and exports from watersheds may be regulated by a different set of mechanisms and factors. Identifying these differences is critical for developing more reliable and robust models for transport of dissolved organic matter.     

Effects of Spatial Distribution of Prairie Vegetation in an Agricultural Landscape on Curve Number Values

The curve number (CN) method is used to calculate runoff in many hydrologic models, including the Soil and Water Assessment Tool (SWAT). The CN method does not account for the spatial distribution of land cover types, an important factor controlling runoff patterns. The objective of this study was to empirically derive CN values that reflect the strategic placement of native prairie vegetation (NPV) within row crop agricultural landscapes. CNs were derived using precipitation and runoff data from a seven‐year period for 14 small watersheds in Iowa. The watersheds were planted with varying amounts of NPV located in different watershed positions. The least squares and asymptotic least squares methods (LSM) were used to derive CNs using an initial abstraction coefficient (λ) of 0.2 and 0.05. The CNs were verified using leave‐one‐out cross‐validation and adjustment for antecedent moisture conditions (AMC) was tested. The asymptotic method produced CN values for watersheds with NPV treatment that were 8.9 and 14.7% lower than watersheds with 100% row crop at λ = 0.2 and λ = 0.05, respectively. The derived CNs produced Nash‐Sutcliffe efficiency values ranging from 0.4 to 0.7 during validation. Our analyses show the CNs verified best for the asymptotic LSM, when using λ of 0.05 and adjusting for AMC. Further, comparison of derived CNs against an area weighted CN indicated that the placement of vegetation does impact the CN value. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain1

Epps, Thomas H., Daniel R. Hitchcock, Anand D. Jayakaran, Drake R. Loflin, Thomas M. Williams, and Devendra M. Amatya, 2012. Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12000 Abstract: Hydrologic monitoring was conducted in two first‐order lower coastal plain watersheds in South Carolina, United States, a region with increasing growth and land use change. Storm events over a three‐year period were analyzed for direct runoff coefficients (ROC) and the total storm response (TSR) as percent rainfall. ROC calculations utilized an empirical hydrograph separation method that partitioned total streamflow into sustained base flow and direct runoff components. ROC ratios ranged from 0 to 0.32 on the Upper Debidue Creek (UDC) watershed and 0 to 0.57 on Watershed 80 (WS80); TSR results ranged from 0 to 0.93 at UDC and 0.01 to 0.74 at WS80. Variability in event runoff generation was attributed to seasonal trends in water table elevation fluctuation as regulated by evapotranspiration. Groundwater elevation breakpoints for each watershed were identified based on antecedent water table elevation, streamflow, ROCs, and TSRs. These thresholds represent the groundwater elevation above which event runoff generation increased sharply in response to rainfall. For effective coastal land use decision making, baseline watershed hydrology must be understood to serve as a benchmark for management goals, based on both seasonal and event‐based surface and groundwater interactions.     

A Field-Based Evaluation of Wet Retention Ponds: How Effective Are Ponds at Water Quantity Control?1

Hancock, Gregory S., Jonathan W. Holley, and Randolph M. Chambers, 2010. A Field-Based Evaluation of Wet Retention Ponds: How Effective Are Ponds at Water Quantity Control? Journal of the American Water Resources Association (JAWRA) 46(6):1145–1158. DOI: 10.1111/j.1752-1688.2010.00481.x Abstract: Wet retention ponds are widely used structural stormwater best management practices (BMPs) with the primary goals of reducing peak flows and extending flow duration. Despite widespread use, few field-based studies have evaluated the success of wet retention ponds at meeting these goals. We determined pond elevation, flow rate, and pond volume over four years in five suburban watersheds in James City County, Virginia. We selected five ponds designed under regulations requiring a 24 hour inflow-to-outflow centroid lag time for a one year, 24 hour design storm. We used pressure transducers to measure pond water surface elevation at 5 min intervals, and calculated pond outflow and volume using rating curves obtained from site stormwater management plans (SWMPs). Peak inflows, peak outflows, and runoff ratios frequently exceeded SWMP calculations in measured events. Four ponds never achieved the required 24 hour inflow-to-outflow centroid lag for storms similar to the one year, 24 hour storm. These BMPs fail to achieve regulatory goals for channel protection because of regulatory loopholes, underprediction of rainfall intensity, unrealistic predictions of postdevelopment flows in SWMPs, and the inability of wet retention ponds to reduce overall runoff volume. While specific to one locality, the shortcomings highlighted suggest similar field-based assessments of retention pond performance are needed in other locations.     

Discussion

Epps et al. (2013) derived Curve Number (CN) values for two forested headwater watersheds in the Lower Coastal Plain of South Carolina during the 2008‐2011 period from rainfall‐runoff data, resulting in 23 events for the Upper Debidue Creek (UDC) watershed and in 20 events for Watershed 80 (WS80). D'Asaro and Grillone analyzed the P, CN data of the UDC watershed finding an evident “complacent” behavior, characterized by a declining CN with increasing P but without approaching a stable value at large storms. In this case, the traditional runoff CN equation does not fit well with the rainfall‐runoff data that indicate a partial source area watershed behavior and are more aptly modeled by the equation introduced by D'Asaro and Grillone (2012), who introduced a C parameter in the well‐known runoff CN formula. The C value, that represents the source area (fraction of drainage area) of the basin that produces runoff with a fixed CN < 100, is here considered to vary with the water table elevation (WTE), to which it is well correlated.     

RELIABILITY OF THE DESIGN STORM CONCEPT IN EVALUATING RUNOFF PEAK FLOW1

A comparative study was undertaken to evaluate peak runoff flow rates using (1) a continuous series of actual rainfall events and (2) design storms. The ILLUDAS computer model was used to simulate runoff over a catchment within the city of Montreal, Canada. A ten-year period, five-minute increment rainfall data base was used to derive peak flow frequency curves. Two types of design storms were analyzed: one derived from intensity duration frequency curves (Chicago type), the other from averaging actual rainfall patterns (Huff type). Antecedent soil moisture conditions were considered in the analyses. It was found that the probability distribution of runoff peak flow was sensitive to the choice of design storm pattern and to the antecedent soil moisture condition. A symmetrical, Chicago-type design storm with antecedent dry soil moisture produced a flow frequency curve similar to the one obtained from a series of historical rainfall events.     

Runoff Curve Numbers for Small Grain Under German Cropping Conditions

The Curve Number (CN) method is used in many models to predict surface runoff depth and transport of dissolved agrochemicals. CNs were determined on 70 small plots at 8 sites and different crop stages with artificial rain. The measured CNs deviated greatly from the commonly used CNs in most cases. For growing crops, CN correlated closely with cover, regardless of whether the crop was spring or fall barley or rape. The CNs measured with artificial rain agreed well with CNs measured on larger plots with natural rain. A new table was developed that accounts for the resulting seasonal changes in CNs of different small grain crops. The use of this table will greatly improve runoff predictions under German cropping conditions. Predictions will be poor between harvest and subsequent plowing, because of the fast and unpredictable changes in CNs during this generally short period (average CN: 75; standard deviation: 15). On a very stony site, CNs were much lower than would be expected for the hydrological soil group A. If, however, stone cover (23–35%) was included in total cover, the CNs fell into the range of the regression developed for crop cover. In cases where stones are not embedded into a surface seal, but rather protect the soil as would a crop or mulch cover, they can similarly reduce runoff.     

COMPOSITE VS. DISTRIBUTED CURVE NUMBERS: EFFECTS ON ESTIMATES OF STORM RUNOFF DEPTHS1

ABSTRACT: The U.S. Department of Agriculture Curve Number (CN) method is one of the most common and widely used techniques for estimating surface runoff and has been incorporated into a number of popular hydrologic models. The CN method has traditionally been applied using compositing techniques in which the area weighted average of all curve numbers is calculated for a watershed or a small number of sub-watersheds. CN compositing was originally developed as a time saving procedure, reducing the number of runoff calculations required. However, with the proliferation of high speed computers and geographic information systems, it is now feasible to use distributed CNs when applying the CN method. To determine the effect of using composited versus distributed CNs on runoff estimates, two simulations of idealized watersheds were developed to compare runoff depths using composite and distributed CNs. The results of these simulations were compared to the results of similar analyses performed on an urbanizing watershed located in central Indiana and show that runoff depth estimates using distributed CNs are as much as 100 percent higher than when composited CNs are used. Underestimation of runoff due to CN compositing is a result of the curvilinear relationship between CN and runoff depth and is most severe for wide CN ranges, low CN values, and low precipitation depths. For larger design storms, however, the difference in runoff computed using composite and distributed CNs is minimal.     

EVALUATION OF HYDROLOGIC BENEFITS OF INFILTRATION BASED URBAN STORM WATER MANAGEMENT1

ABSTRACT: As watersheds are urbanized, their surfaces are made less pervious and more channelized, which reduces infiltration and speeds up the removal of excess runoff. Traditional storm water management seeks to remove runoff as quickly as possible, gathering excess runoff in detention basins for peak reduction where necessary. In contrast, more recently developed “low impact” alternatives manage rainfall where it falls, through a combination of enhancing infiltration properties of pervious areas and rerouting impervious runoff across pervious areas to allow an opportunity for infiltration. In this paper, we investigate the potential for reducing the hydrologic impacts of urbanization by using infiltration based, low impact storm water management. We describe a group of preliminary experiments using relatively simple engineering tools to compare three basic scenarios of development: an undeveloped landscape; a fully developed landscape using traditional, high impact storm water management; and a fully developed landscape using infiltration based, low impact design. Based on these experiments, it appears that by manipulating the layout of urbanized landscapes, it is possible to reduce impacts on hydrology relative to traditional, fully connected storm water systems. However, the amount of reduction in impact is sensitive to both rainfall event size and soil texture, with greatest reductions being possible for small, relatively frequent rainfall events and more pervious soil textures. Thus, low impact techniques appear to provide a valuable tool for reducing runoff for the events that see the greatest relative increases from urbanization: those generated by the small, relatively frequent rainfall events that are small enough to produce little or no runoff from pervious surfaces, but produce runoff from impervious areas. However, it is clear that there still needs to be measures in place for flood management for larger, more intense, and relatively rarer storm events, which are capable of producing significant runoff even for undeveloped basins.     

Dry Weather Water Quality Loadings in Arid,Urban Watersheds of the Los Angeles Basin,California, USA1

Abstract: Dry weather runoff in arid, urban watersheds may consist entirely of treated wastewater effluent and/or urban nonpoint source runoff, which can be a source of bacteria, nutrients, and metals to receiving waters. Most studies of urban runoff focus on stormwater, and few have evaluated the relative contribution and sources of dry weather pollutant loading for a range of constituents across multiple watersheds. This study assessed dry weather loading of nutrients, metals, and bacteria in six urban watersheds in the Los Angeles region of southern California to estimate relative sources of each constituent class and the proportion of total annual load that can be attributed to dry weather discharge. In each watershed, flow and water quality were sampled from storm drain and treated wastewater inputs, as well as from in‐stream locations during at least two time periods. Data were used to calculate mean concentrations and loads for various sources. Dry weather loads were compared with modeled wet weather loads under a range of annual rainfall volumes to estimate the relative contribution of dry weather load. Mean storm drain flows were comparable between all watersheds, and in all cases, approximately 20% of the flowing storm drains accounted for 80% of the daily volume. Wastewater reclamation plants (WRP) were the main source of nutrients, storm drains accounted for almost all the bacteria, and metals sources varied by constituent. In‐stream concentrations reflected major sources, for example nutrient concentrations were highest downstream of WRP discharges, while in‐stream metals concentrations were highest downstream of the storm drains with high metals loads. Comparison of wet vs. dry weather loading indicates that dry weather loading can be a significant source of metals, ranging from less than 20% during wet years to greater than 50% during dry years.     

Investigation of the Curve Number Method For Surface Runoff Estimation In Tropical Regions

This study tests the applicability of the curve number (CN) method within the Soil and Water Assessment Tool (SWAT) to estimate surface runoff at the watershed scale in tropical regions. To do this, surface runoff simulated using the CN method was compared with observed runoff in numerous rainfall‐runoff events in three small tropical watersheds located in the Upper Blue Nile basin, Ethiopia. The CN method generally performed well in simulating surface runoff in the studied watersheds (Nash‐Sutcliff efficiency [NSE] > 0.7; percent bias [PBIAS] < 32%). Moreover, there was no difference in the performance of the CN method in simulating surface runoff under low and high antecedent rainfall (PBIAS for both antecedent conditions: ~30%; modified NSE: ~0.4). It was also found that the method accurately estimated surface runoff at high rainfall intensity (e.g., PBIAS < 15%); however, at low rainfall intensity, the CN method repeatedly underestimated surface runoff (e.g., PBIAS > 60%). This was possibly due to low infiltrability and valley bottom saturated areas typical of many tropical soils, indicating that there is scope for further improvements in the parameterization/representation of tropical soils in the CN method for runoff estimation, to capture low rainfall‐intensity events. In this study the retention parameter was linked to the soil moisture content, which seems to be an appropriate approach to account for antecedent wetness conditions in the tropics.     

Sensitivity of SCS Models to Curve Number Variation1

ABSTRACT: The Soil Conservation Service (SCS) models, including the TR-20 computer program and the simplified methods in TR-55, are widely used in hydrologic design. The runoff curve number (CN), which is an important input parameter to SCS models, is defined in terms of land use tretments, hydrologic, condition, antecedent soil moisture, and soil type. The objective of this study was to evaluate the sensitivity of the SCS models to errors in CN estimates. The results show that the effects of CN variation decrease as the design rainfall depth increases, such as for the larger storm events. The value and use of the sensitivity curves are demonstrated using a comparison of Landsat and conventionally derived curve numbers for three watersheds in Pennsylvania.     

EQUIVALENCE BETWEEN TOPMODEL AND THE NRCS CURVE NUMBER METHOD IN PREDICTING VARIABLE RUNOFF SOURCE AREAS1

An equivalence is proposed between two rainfall‐runoff methods with a long history of use in the United States and Europe. In watersheds where variable source areas dominate runoff, the two methods can have comparable probability distribution functions of moisture deficit, and therefore predict similar saturated runoff source areas. A novel approach is introduced to determine the S parameter in the Natural Resources Conservation Service (NRCS) method. This approach constrains S by the physical soil and topography characteristics of the catchment and depth to water table. The NRCS curve number method is at the core of many rainfall‐runoff models in hydrology. As a simple lumped parameter method, it is often scrutinized because it is not obvious how to derive S from catchment hydromorphological characteristics. The novel approach provides a clear physical meaning for S, allowing better estimation of this parameter in humid shallow water table environments where the variable source area can be the dominant runoff mechanism.     

MODELING THE FOREST HYDROLOGY OF WETLAND-UPLAND ECOSYSTEMS IN FLORIDA1

ABSTRACT: Few hydrological models are applicable to pine flat-woods which are a mosaic of pine plantations and cypress swamps. Unique features of this system include ephemeral sheet flow, shallow dynamic ground water table, high rainfall and evapotranspiration, and high infiltration rates. A FLATWOODS model has been developed specifically for the cypress wetland-pine upland landscape by integrating a 2-D ground water model, a Variable-Source-Area (VAS)-based surface flow model, an evapotranspiration (ET) model, and an unsaturated water flow model. The FLATWOODS model utilizes a distributed approach by dividing the entire simulation domain into regular cells. It has the capability to continuously simulate the daily values of ground water table depth, ET, and soil moisture content distributions in a watershed. The model has been calibrated and validated with a 15-year runoff and a four-year ground water table data set from two different pine flat woods research watersheds in northern Florida. This model may be used for predicting hydrologic impacts of different forest management practices in the coastal regions.     

Calibration and Verification of SWMM for Low Impact Development

The Storm Water Management Model was used to simulate runoff and nutrient export from a low impact development (LID) watershed and a watershed using traditional runoff controls. Predictions were compared to observed values. Uncalibrated simulations underpredicted weekly runoff volume and average peak flow rates from the multiple subcatchment LID watershed by over 80%; the single subcatchment traditional watershed had better predictions. Saturated hydraulic conductivity, Manning's n for swales, and initial soil moisture deficit were sensitive parameters. After calibration, prediction of total weekly runoff volume for the LID and traditional watersheds improved to within 12 and 5% of observed values, respectively. For the validation period, predicted total weekly runoff volumes for the LID and traditional watersheds were within 6 and 2% of observed values, respectively. Water quality simulation was less successful, Nash–Sutcliffe coefficients >0.5 for both calibration and validation periods were only achieved for prediction of total nitrogen export from the LID watershed. Simulation of a 100‐year, 24‐h storm resulted in a runoff coefficient of 0.46 for the LID watershed and 0.59 for the traditional watershed. Results suggest either calibration is needed to improve predictions for LID watersheds or expanded look‐up tables for Green–Ampt infiltration parameter values that account for compaction of urban soil and antecedent conditions are needed.     

SIZING OF SURFACE WATER RUNOFF DETENTION PONDS FOR WATER QUALITY IMPROVEMENT1

ABSTRACT: Historically, storm water management programs and criteria have focused on quantity issues related to flooding and drainage system design. Traditional designs were based on large rainfall‐runoff events such as those having two‐year to 100‐year return periods. While these are key criteria for management and control of peak flows, detention basin designs based on these criteria may not provide optimal quality treatment of storm runoff. As evidenced by studies performed by numerous public and private organizations, the water quality impacts of storm water runoff are primarily a function of more frequent rainfall‐runoff events rather than the less frequent events that cause peak flooding. Prior to this study there had been no detailed investigations to characterize the variability of the more frequent rainfall events on Guam. Also, there was a need to develop some criteria that could be applied by designers, developers, and agency officials in order to reduce the impact of storm water runoff on the receiving bodies. The objectives of this paper were three‐fold: (1) characterize the hourly rainfall events with respect to volume, frequency, duration, and the time between storm events; (2) evaluate the rainfall‐runoff characteristics with respect to capture volume for water quality treatment; and (3) prepare criteria for sizing and designing of storm water quality management facilities. The rainfall characterization studies have provided insight into the characteristics of rainstorms that are likely to produce non‐point source pollution in storm water runoff. By far the most significant fmdings are the development of a series of design curves that can be used in the actual sizing of storm water detention and treatment facilities. If applied correctly, these design curves could lead to a reduction of non‐point source pollution to Guam's streams, estuaries, and coastal environments.     

WATER LOSS EQUATIONS AND COEFFICIENTS TO ESTIMATE RUNOFF FROM RAINFALL1

Infiltration models are based on physical characteristics of the soil and initial soil moisture. For a given soil it is based on the initial soil moisture distribution. A computer simulation model for flood runoff systems (FH-Model) was used to analyze 39 sets of rainfall-runoff data on four small watersheds ranging in size from 17 to 342 square kilometers located in the Yamaska River basin in Quebec. From these analyses, parameters and coefficients have been determined for a water loss (infiltration) equation. A method for determining the loss parameters, using a nonlinear least square curve fitting technique, is presented. Expressions were made to relate the loss parameters to antecedent precipitation. The equations were tested on 11 storm rainfall and runoff events on a watershed located in the same region and close agreements were found.     

CLASSIFYING STORM RUNOFF POTENTIAL WITH PASSIVE MICROWAVE MEASUREMENTS1

ABSTRACT: The average microwave temperature of the watershed surface as detected by an airborne Passive Microwave Imaging Scanner (PMIS) was compared with the measured Soil Conservation Service (SCS) watershed storm runoff coefficient (CN). Previous laboratory work suggested that microwave response to the watershed surface is influenced by some of the same surface characteristics that affect runoff, i.e., soil moisture, surface roughness, vegetative cover, and soil texture. In order to field test and develop relations between runoff potentfal and microwave response, several highly instrumented watersheds of approximately 1.5 to 17 km2 were scanned under wet- and dry-soil conditions in April and June 1973. The polarized (horizontal and vertical) scans at 2.8 cm wavelength provided the data base from which other values were calculated. The best relationship between runoff coefficients (CN) and PMIS temperatures was observed when horizontally polarized temperatures from the near-dormant, early-growing season flight were used. Lower SCS runoff coefficients seem to be correlated with the cross-polarized response under dry watershed conditions late in the growing season and the difference in horizontal polarized response between wet conditions early in the growing season and dry conditions late in the growing season. To apply the results, the relationships need to be verified further.