Runoff Storage Potential of Drained Upland Depressions on the Des Moines Lobe of Iowa

We present estimates of the volumetric storage capacities of currently drained upland depressions and catchment depressional specific storage and runoff storage indices for the Des Moines Lobe of Iowa (DML‐IA) subregion of the Prairie Pothole Region of North America. Storage capacities were determined using hydrologically enforced Light Detection and Ranging‐derived digital elevation models, and a unique geoprocessing algorithm. Depressional specific storage was estimated for each 12‐digit Hydrologic Unit Code (HUC12) watershed in the region from total catchment‐specific depressional storage volume and catchment area. Runoff storage indices were calculated using catchment depressional specific storage values and estimates of the amount of rainfall likely to fall within each watershed during sub‐annual and 1‐, 2‐, 5‐, and 10‐year 24‐h events. The 173,171 identified drained depressions in the DML‐IA can store up to 903.5 Mm³ of runoff. Most of this capacity is in depressions located in the north of the region. Specific storage varies from nearly 109 mm in the younger landscapes to <10 mm in older more eroded areas. For 95% of the HUC12 watersheds comprising the region, depressional storage will likely be exhausted by rainfall‐derived runoff in excess of a 1‐year 24‐h event. Rainfall amounts greater than a 5‐year 24‐h event will exceed all available depressional storage. Therefore, the capacity of drained depressions in the DML‐IA to mitigate flooding resulting from infrequent, but large, storm events is limited.     

Incorporating Variable Source Area Hydrology into a Spatially Distributed Direct Runoff Model1

Buchanan, Brian, Zachary M. Easton, Rebecca Schneider, and M. Todd Walter, 2011. Incorporating Variable Source Area Hydrology Into a Spatially Distributed Direct Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(1): 43‐60. DOI: 10.1111/j.1752‐1688.2011.00594.x Abstract: Few hydrologic models simulate both variable source area (VSA) hydrology, and runoff‐routing at high enough spatial resolutions to capture fine‐scale hydrologic pathways connecting VSA to the stream network. This paper describes a geographic information system‐based operational model that simulates the spatio‐temporal dynamics of VSA runoff generation and distributed runoff‐routing, including through complex artificial drainage networks. The model combines the Natural Resource Conservation Service’s Curve Number (CN) equation for estimating storm runoff with the topographic index concept for predicting the locations of VSA and a runoff‐routing algorithm into a new spatially distributed direct hydrograph (SDDH) model (SDDH‐VSA). Using a small agricultural watershed in central New York, SDDH‐VSA results were compared to those from a SDDH model using the traditional land use assumptions for the CN (SDDH‐CN). The SDDH‐VSA model generally agreed better with observed discharge than the SDDH‐CN model (average, Nash‐Sutcliffe efficiency of 0.69 vs. 0.58, respectively) and resulted in more realistic spatial patterns of runoff‐generating areas. The SDDH approach did not correctly capture the timing of runoff from small storms in dry periods. Despite this type of limitation, SDDH‐VSA extends the applicability of the SDDH technique to VSA conditions, providing a basis for new tools to help identify critical management areas and assess water quality risks due to landscape alterations.     

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.     

Mechanistic Simulation of Tree Effects in an Urban Water Balance Model1

Abstract: A semidistributed, physical‐based Urban Forest Effects – Hydrology (UFORE‐Hydro) model was created to simulate and study tree effects on urban hydrology and guide management of urban runoff at the catchment scale. The model simulates hydrological processes of precipitation, interception, evaporation, infiltration, and runoff using data inputs of weather, elevation, and land cover along with nine channel, soil, and vegetation parameters. Weather data are pre‐processed by UFORE using Penman‐Monteith equations to provide potential evaporation terms for open water and vegetation. Canopy interception algorithms modified established routines to better account for variable density urban trees, short vegetation, and seasonal growth phenology. Actual evaporation algorithms allocate potential energy between leaf surface storage and transpiration from soil storage. Infiltration algorithms use a variable rain rate Green‐Ampt formulation and handle both infiltration excess and saturation excess ponding and runoff. Stream discharge is the sum of surface runoff and TOPMODEL‐based subsurface flow equations. Automated calibration routines that use observed discharge has been coupled to the model. Once calibrated, the model can examine how alternative tree management schemes impact urban runoff. UFORE‐Hydro model testing in the urban Dead Run catchment of Baltimore, Maryland, illustrated how trees significantly reduce runoff for low intensity and short duration precipitation events.     

Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering1

Caballero, Luis A., Alon Rimmer, Zachary M. Easton, and Tammo S. Steenhuis, 2012. Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering. Journal of the American Water Resources Association (JAWRA) 48(5): 1022‐1031. DOI: 10.1111/j.1752‐1688.2012.00668.x Abstract: Understanding the basic relationships between rainfall and runoff is vital for effective management and utilization of scarce water resources. Especially, this is important in Central America with widespread potable water shortage during the dry months of the monsoon. Potential good water sources are cloud forests, but little information concerning its potential is available to water supply engineers. Our objective is to define rainfall‐runoff‐base flow relationships for a cloud forest catchment. Flumes were installed for measuring river flow in four subwatersheds in La Tigra National Park, Honduras. One of the four watersheds was a 636‐ha subwatershed (WS1) with 60% cloud forest coverage. Precipitation averaged 1,130 mm/yr over the entire basin. About half of the total rainfall became runoff for the cloud forest watershed whereas, for the adjacent undisturbed forested watershed, the total discharge was <20% of the amount of precipitation. Infiltration rates were generally greater than rainfall rates. Therefore, most rainfall infiltrated into the soil, especially in the upper, steep, and well‐drained portions of the watershed. Direct runoff was generated from saturated areas near the river and exposed bedrock. This research provides compelling evidence that base flow is the primary contributor to streamflow during both wet and dry seasons in cloud forest catchments. Protecting these flow processes over time is critical for the sustained provision of potable water.     

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.     

Curve Number Derivation for Watersheds Draining Two Headwater Streams in Lower Coastal Plain South Carolina,USA

The objective of this study was to assess curve number (CN) values derived for two forested headwater catchments in the Lower Coastal Plain (LCP) of South Carolina using a three‐year period of storm event rainfall and runoff data in comparison with results obtained from CN method calculations. Derived CNs from rainfall/runoff pairs ranged from 46 to 90 for the Upper Debidue Creek (UDC) watershed and from 42 to 89 for the Watershed 80 (WS80). However, runoff generation from storm events was strongly related to water table elevation, where seasonally variable evapotranspirative wet and dry moisture conditions persist. Seasonal water table fluctuation is independent of, but can be compounded by, wet conditions that occur as a result of prior storm events, further complicating flow prediction. Runoff predictions for LCP first‐order watersheds do not compare closely to measured flow under the average moisture condition normally associated with the CN method. In this study, however, results show improvement in flow predictions using CNs adjusted for antecedent runoff conditions and based on water table position. These results indicate that adaptations of CN model parameters are required for reliable flow predictions for these LCP catchments with shallow water tables. Low gradient topography and shallow water table characteristics of LCP watersheds allow for unique hydrologic conditions that must be assessed and managed differently than higher gradient watersheds.     

HYDROLOGIC BEHAVIOR OF VEGETATED ROOFS1

ABSTRACT: Control of stormwater runoff from impervious surfaces is an important national goal because of disruptions to downstream ecosystems, water users, and property owners caused by increased flows and degraded quality. One method for reducing stormwater is the use of vegetated (green) roofs, which efficiently detain and retain stormwater when compared to conventional (black) roofs. A paired green roof‐black roof test plot was constructed at the University of Georgia and monitored between November 2003 and November 2004 for the green roof's effectiveness in reducing stormwater flows. Stormwater mitigation performance was monitored for 31 precipitation events, which ranged in depth from 0.28 to 8.43 cm. Green roof precipitation retention decreased with precipitation depth; ranging from just under 90 percent for small storms (< 2.54 cm) to slightly less than 50 percent for larger storms (> 7.62 cm). Runoff from the green roof was delayed; average runoff lag times increased from 17.0 minutes for the black roof to 34.9 minutes for the green roof, an average increase of 17.9 minutes. Precipitation and runoff data were used to estimate the green roof curve number, CN = 86. This information can be used in hydrologic models for developing stormwater mitigation programs.     

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.     

Spatial Distribution of Water Supply in the Coterminous United States1

Abstract: Available water supply across the contiguous 48 states was estimated as precipitation minus evapotranspiration using data for the period 1953‐1994. Precipitation estimates were taken from the Parameter‐Elevation Regressions on Independent Slopes Model (PRISM). Evapotranspiration was estimated using two models, the Advection‐Aridity model and the Zhang model. The evapotranspiration models were calibrated using precipitation and runoff data for 655 hydrologically undisturbed basins, and then tested using estimates of natural runoff for the 18 water resource regions (WRR) of the 48 contiguous states. The final water supply coverage reflects a mixture of outputs from the two evapotranspiration models. Political, administrative, and land cover boundaries were mapped over the coverage of mean annual water supply. Across the entire study area, we find that 53% of the water supply originates on forested land, which covers only 29% of the surface area, and that 24% originates on federal lands, including 18% on national forests and grasslands alone. Forests and federal lands are even more important in the West (the 11 western contiguous states), where 65% of the water supply originates on forested land and 66% on federal lands, with national forests and grasslands contributing 51%.     

MONTHLY RUNOFF PREDICTIONS BASED ON RAINFALL FORECASTS IN A SMALL OKLAHOMA WATERSHED1

ABSTRACT: Conditions under which monthly rainfall forecasts translate into monthly runoff predictions that could support water resources planning and management activities were investigated on a small watershed in central Oklahoma. Runoff response to rainfall forecasts was simulated using the hydrologic model SWAT. Eighteen scenarios were examined that represented combinations of wet, average, and dry antecedent rainfall conditions, with wet, normal, and dry forecasted rainfall. Results suggest that for the climatic and physiographic conditions under consideration, rainfall forecasts could offer potential application opportunities in surface water resources but only under certain conditions. Pronounced wet and dry antecedent rainfall conditions were shown to have greater impact on runoff than forecasts, particularly in the first month of a forecast period. Large forecast impacts on runoff occurred under wet antecedent conditions, when the fraction of forecasted rainfall contributing to runoff was greatest. Under dry antecedent conditions, most of the forecasted rainfall was absorbed in the soil profile, with little immediate runoff response. Persistent three‐month forecasts produced stronger impacts on runoff than one‐month forecasts due to cumulative effects in the hydrologic system. Runoff response to antecedent conditions and forecasts suggest a highly asymmetric utility function for rainfall forecasts, with greatest decision‐support potential for persistent wet forecasts under wet antecedent conditions when the forecast signal is least dampened by soil‐storage effects. Under average and dry antecedent conditions, rainfall forecasts showed little potential value for practical applications in surface water resources assessments.     

Snowmelt Runoff and Water Yield Along Elevation and Temperature Gradients in California’s Southern Sierra Nevada1

Hunsaker, Carolyn T., Thomas W. Whitaker, and Roger C. Bales, 2012. Snowmelt Runoff and Water Yield Along Elevation and Temperature Gradients in California’s Southern Sierra Nevada. Journal of the American Water Resources Association (JAWRA) 48(4): 667‐678. DOI: 10.1111/j.1752‐1688.2012.00641.x Abstract: Differences in hydrologic response across the rain‐snow transition in the southern Sierra Nevada were studied in eight headwater catchments – the Kings River Experimental Watersheds – using continuous precipitation, snowpack, and streamflow measurements. The annual runoff ratio (discharge divided by precipitation) increased about 0.1 per 300 m of mean catchment elevation over the range 1,800‐2,400 m. Higher‐elevation catchments have lower vegetation density, shallow soils with rapid permeability, and a shorter growing season when compared with those at lower elevations. Average annual temperatures ranged from 6.8°C at 2,400 m to 8.6 at 1,950 m elevation, with annual precipitation being 75‐95% snow at the highest elevations vs. 20‐50% at the lowest. Peak discharge lagged peak snow accumulation on the order of 60 days at the higher elevations and 20 to 30 days at the lower elevations. Snowmelt dominated the daily streamflow cycle over a period of about 30 days in higher elevation catchments, followed by a 15‐day transition to evapotranspiration dominating the daily streamflow cycle. Discharge from lower elevation catchments was rainfall dominated in spring, with the transition to evapotranspiration dominance being less distinct. Climate warming that results in a longer growing season and a shift from snow to rain would result in earlier runoff and a lower runoff ratio.     

RUNOFF MODELING OF A MOUNTAINOUS CATCHMENT USING TOPMODEL: A CASE STUDY1

ABSTRACT: The rainfall‐runoff response of the Tygarts Creek Catchment in eastern Kentucky is studied using TOPMODEL, a hydrologic model that simulates runoff at the catchment outlet based on the concepts of saturation excess overland flow and subsurface flow. Unlike the traditional application of this model to continuous rainfall‐runoff data, the use of TOPMOEL in single event runoff modeling, specifically floods, is explored here. TOPMODEL utilizes a topographic index as an indicator of the likely spatial distribution of rainfall excess generation in the catchment. The topographic index values within the catchment are determined using the digital terrain analysis procedures in conjunction with digital elevation model (DEM) data. Select parameters in TOPMODEL are calibrated using an iterative procedure to obtain the best‐fit runoff hydrograph. The calibrated parameters are the surface transmissivity, T_O, the transmissivity decay parameter, m, and the initial moisture deficit in the root zone, S_r0. These parameters are calibrated using three storm events and verified using three additional storm events. Overall, the calibration results obtained in this study are in general agreement with the results documented from previous studies using TOPMODEL. However, the parameter values did not perform well during the verification phase of this study.     

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.     

Effect of Rainfall Regime and Slope on Runoff in a Gullied Loess Region on the Loess Plateau in China

Runoff was measured from seven plots with different slopes nested in Tuanshangou catchment on the Loess Plateau to study effect of slopes on runoff in relation to rainfall regimes. Based on nine years of field observation and K-mean clusters, 84 rainfall events were grouped into three rainfall regimes. Rainfall regime A is the group of events with strong rainfall intensity, high frequency, and short duration. Rainfall regime C consists of events with low intensity, long duration, and infrequent occurrence. Rainfall regime B is the aggregation of events of medium intensity and medium duration, and less frequent occurrence. The following results were found: (1) Different from traditional studies, runoff coefficient neither decreased nor increased, but presented peak value on the slope surfaces; (2) For individual plot, runoff coefficients induced by rainfall regime A were the highest, and those induced by rainfall regime C were the lowest; Downslope, the runoff coefficients induced by three rainfall regimes presented the same changing trend, although the peak value induced by regime A occurred on a shorter slope length compared to those by regime B and C; (3) Scale effect on runoff induced by rainfall regime A was the least, and that induced by rainfall regime C was the largest. These results can be explained by the interactions of crusting, soil moisture content, slope length and gradient, and erosion units, etc., in the context of different rainfall regimes.     

Estimating Potential E. coli Sources in a Watershed Using Spatially Explicit Modeling Techniques1

Riebschleager, K.J., R. Karthikeyan, R. Srinivasan, and K. McKee, 2012. Estimating Potential E. coli Sources in a Watershed Using Spatially Explicit Modeling Techniques. Journal of the American Water Resources Association (JAWRA) 48(4): 745‐761. DOI: 10.1111/j.1752‐1688.2012.00649.x Abstract: The Spatially Explicit Load Enrichment Calculation Tool (SELECT) was automated to characterize waste and the associated pathogens from various sources within a mixed land use watershed. Potential Escherichia coli loads in Lake Granbury watershed were estimated using spatially variable governing factors, such as land use, soil condition, and distance to streams. A new approach for characterizing E. coli loads resulting from malfunctioning on‐site wastewater treatment systems (OWTSs) was incorporated into SELECT along with the Pollutant Connectivity Factor (PCF) module. The PCF component was applied to identify areas contributing E. coli loads during runoff events by incorporating the influence of potential E. coli loading, runoff potential, and travel distance to waterbodies. Simulation results indicated livestock and wildlife are potential E. coli contributing sources in the watershed. The areas in which these sources are potentially contributing are not currently monitored for E. coli. The bacterial water quality violations seen around Lake Granbury are most likely the result of malfunctioning OWTSs and pet wastes. SELECT results demonstrate the need to evaluate each contributing source separately to effectively allocate site specific best management practices (BMPs) utilizing stakeholder inputs. It also serves as a powerful screening tool for determining areas where detailed investigation is merited.     

Effects of Watershed Impervious Cover on Dissolved Silica Loading in Storm Flow1

Abstract: Dissolved silica (DSi) availability is a factor that affects the composition of algal populations in aquatic ecosystems. DSi cycling is tightly linked to the hydrological cycle, which is affected by human alterations of the landscape. Development activities that increase impervious cover change watershed hydrology and may increase the discharge of DSi‐poor rainwater and decrease the discharge of DSi‐rich ground water into aquatic ecosystems, possibly shifting algal community composition toward less desirable assemblages. In this study, DSi loadings from two adjacent coastal watersheds with different percent impervious cover were compared during four rain and five nonrain events. Loadings in the more impervious watershed contained a significantly larger proportion of surface runoff than base flow (ground‐water discharge) and had lower [DSi] water during rain events than the less impervious watershed. Application of the Soil Conservation Service Curve Number (CN) method showed that the minimum rainfall height necessary to yield runoff was significantly lower for the more impervious watershed, implying that runoff volumes increase with impervious cover as well as the frequency of runoff‐yielding events. Empirical data collected during this study and estimates derived from the CN method suggest that impervious cover may be responsible for both short‐term DSi limitation during rain events as well as long‐term reduction of DSi inputs into aquatic ecosystems.     

The Ability of Urban Residential Lawns to Disconnect Impervious Area from Municipal Sewer Systems1

Abstract: Runoff from urban catchments depends largely on the amount of impervious surface and the connectivity of these surfaces to the storm sewer drainage system. In residential areas, pervious lawns can be used to help manage stormwater runoff by intercepting and infiltrating runoff from impervious surfaces. The goal of this research was to develop and evaluate a simple method for estimating the reduction in stormwater runoff that results when runoff from an impervious surface (e.g., rooftop) is directed onto a pervious surface (e.g., lawn). Fifty‐two stormwater runoff reduction tests were conducted on six residential lawns in Madison, Wisconsin during the summer of 2004. An infiltration‐loss model that requires inputs of steady‐state infiltration rate, abstraction (defined here as surface storage, vegetation interception and cumulative total infiltration minus steady‐state infiltration during the period prior to steady‐state), and inundated area was evaluated using experimental data. The most accurate results were obtained using the observed steady‐state infiltration rates and inundated areas for each test, combined with a constant abstraction for all tests [root mean squared (RMS) difference = 1.0 cm]. A second case utilized lawn‐averaged steady‐state infiltration rates, a regression estimate of inundated area based on flow‐path length, and lawn‐specific abstractions based on infiltration rate (RMS difference = 2.2 cm). In practice, infiltration rates will likely be determined using double‐ring infiltration measurements (RMS difference = 3.1 cm) or soil texture (RMS difference = 5.7 cm). A generalized form of the model is presented and used to estimate annual stormwater runoff volume reductions for Madison. Results indicate the usefulness of urban lawns as a stormwater management practice and could be used to improve urban runoff models that incorporate indirectly connected impervious areas.     

WATERSHED WEIGHTING OF EXPORT COEFFICIENTS TO MAP CRITICAL PHOSPHOROUS LOADING AREAS1

ABSTRACT: The Export Coefficient model (ECM) is capable of generating reasonable estimates of annual phosphorous loading simply from a watershed's land cover data and export coefficient values (ECVs). In its current form, the ECM assumes that ECVs are homogeneous within each land cover type, yet basic nutrient runoff and hydrological theory suggests that runoff rates have spatial patterns controlled by loading and filtering along the flow paths from the upslope contributing area and downslope dispersal area. Using a geographic information system (GIS) raster, or pixel, modeling format, these contributing area and dispersal area (CADA) controls were derived from the perspective of each individual watershed pixel to weight the otherwise homogeneous ECVs for phosphorous. Although the CADA‐ECM predicts export coefficient spatial variation for a single land use type, the lumped basin load is unaffected by weighting. After CADA weighting, a map of the new ECVs addressed the three fundamental criteria for targeting critical pollutant loading areas: (1) the presence of the pollutant, (2) the likelihood for runoff to carry the pollutant offsite, and (3) the likelihood that buffers will trap nutrients prior to their runoff into the receiving water body. These spatially distributed maps of the most important pollutant management areas were used within New York's West Branch Delaware River watershed to demonstrate how the CADA‐ECM could be applied in targeting phosphorous critical loading areas.     

EFFECTS OF A NORTH CENTRAL WASHINGTON WILDFIRE ON RUNOFF AND SEDIMENT PRODUCTION1

ABSTRACT: Runoff was measured from a 564-ha catchment located on the Entiat Experimental Forest for nine years before a severe wild-fire in 1970 destroyed the mixed conifer vegetation. Runoff records from the Chelan River (2 393 km²) were used as control data for determining changes in water yield during the seven years following the fire. The first post-fire year was a period of transition in which the soil profile retained more water than in previous years and measured runoff was 8.9 cm greater than the predicted value based on pre-fire conditions. Runoff from the burned catchment during subsequent years was much greater than measured values before the fire. Measured minus predicted runoff, based on the pre-fire calibration equation, varied from 10.7 cm during the dry year of 1977 to 47.2 cm during the abnormally wet year of 1972. Flow duration curves indicated that runoff at each percent value after the fire was at least double the comparable pre-fire value. Sediment production increased dramatically after the fire because of increased flow rates, increased overland flow caused by reduced infiltration capacity, and mass soil movement. Sediment yield is beginning to decrease as stream channels become stabilized and vegetation on upper slopes improves infiltration capacity.