RELATIONSHIP BETWEEN ANNUAL RUNOFF AND WATERSHED AREA FOR THE EASTERN UNITED STATES1

ABSTRACT: As part of the U.S. Environmental Protection Agency's effort to determine the long-term effects of acidic deposition on surface water chemistry, annual runoff was estimated for about 1000 ungaged sites in the eastern U.S. using runoff contour maps. One concern in using contour maps was that a bias may be introduced in the runoff estimates due to the size of the 1000 ungaged sites relative to the size of the watersheds used in developing the maps. To determine if a bias was present the relationship between the annual runoff (expressed as depth) and the watershed area for the Northeast (NE) and Southern Blue Ridge Province (SBRP) was tested using five regional data bases. One short-term data base (1984 Water Year, n = 531) and two long-term data bases (1940–57, n = 134 and 1951–80, n = 342) were used in the NE. In the SBRP one short-term database (1984 Water Year, n = 531) and one long-term data base (1951–80, n = 60) were used. For the NE and the SBRP, runoff was not directly correlated with watershed area using the five regional databases. Also, runoff normalized by precipitation was not related to watershed area.     

Large-scale constructed wetlands for nutrient removal from stormwater runoff: An everglades restoration project

The South Florida Water Management District (SFWMD) constructed a wetland south of Lake Okeechobee to begin the process of removing nutrients (especially phosphorus) from agricultural stormwater runoff entering the Everglades. The project, called the Everglades Nutrient Removal (ENR) project, is a prototype for larger, similarly constructed wetlands that the SFWMD will build as part of the Everglades restoration program. This innovative project is believed to be one of the largest agricultural stormwater cleanup projects in the United States, if not in the world. This publication describes the ENR project's design, construction, and proposed operation, as well as the proposed research program to be implemented over the next few years.     

THE EFFECTS OF A MOVING RAINSTORM ON DIRECT RUNOFF PROPERTIES1

ABSTRACT: The effects of a moving rainstorm on flood runoff characteristics were investigated. A flood hydrograph simulation model called “FH-Model” and a natural watershed were used. A hypothetical rainstorm of 50 years recurrence interval, 75 mm depth, and 4 hours duration was used to show the effects of velocity and direction of the moving rainstorm on the runoff characteristics. Compared with an equivalent stationary rainstorm (ESRS), the peak flow caused by a rainstorm moving in a downstream direction with a speed equal to channel velocity, V, was 27.5 percent higher and the peak flow caused by the same rainstorm moving in an upstream direction was 21.7 percent smaller. These percentages reduced to 10.5 percent and 8.6 percent for storms moving downstream and upstream, respectively, at three times the channel velocity, 3V. There were negligible differences in the time of peak, T_p between runoff caused by storms moving downstream and runoff produced by ESRS. However, T_p for a storm moving upstream at V velocity was 82 percent higher than that produced by ESRS, but was reduced to 27 percent higher when the storm velocity was 3V.     

CONTRIBUTION OF PRECIPITATION TO QUALITY OF URBAN STORM RUNOFF1

Precipitation and runoff samples were collected for 13 storms in a nonindustrial urban area in Central Pennsylvania between July 1980 and June 1981. Runoff was collected from tree surfaces, a residential roof and street, a shopping mall parking lot, a downtown business district alley, and a heavily traveled street. Analysis of the water samples showed 10 to 25 percent of the nitrogen, 25 percent of the sulfate, and less than 5 percent of the phosphorus, potassium, and calcium in water below a tree was deposited by the precipitation. The residential roof caused insignificant changes in water chemistry. The results for the four paved areas showed that all the nitrogen, and from 16 to 40 percent of the sulfate and 13, 4, and 2 percent of the phosphorus, potassium, and calcium, respectively, in runoff was deposited by the precipitation. Precipitation can also be an important source of sulfate and phosphorus in runoff. All of the surfaces raised the pH of the runoff, with the largest increases, from a pH of 4 to about 7, occurring in runoff from the paved areas. Precipitation and runoff chemistry was not related to antecedent conditions such as the length of the preceding dry period.     

SUBALPINE,COLD CLIMATE,STORMWATER TREATMENT WITH A CONSTRUCTED SURFACE FLOW WETLAND1

The Tahoe City Wetland Treatment System (TCWTS) was constructed in 1997 to treat stormwater runoff from 23 ha of commercial, highway, and residential land use in the Lake Tahoe Basin. This subalpine, constructed, surface flow wetland treatment system consists of two cells in series, with a design water surface area of about 0.6 ha. Water quality monitoring from October 2002 through September 2003 was conducted with autosamplers at the inflow and outflow sites during 24 sampling events, with a median duration of 53 hours, representing 42 percent of total inflow to this wetland during the year. Monitoring data indicate an improvement of 49 percent or greater in effluent concentrations of dissolved phosphorus, nitrate, orthophosphorus, and total suspended solids. On average, event mean concentrations of total phosphorus were reduced from a median 279 μg/l at the inflow to 94 μg/l at the outflow. Event mean concentrations of total nitrogen were reduced from a median 1,599 μg/l at the inflow to 810 μg/l at the outflow. Net nutrient retention for the sampling period was estimated at 3 g phosphorus (P)/m²/y and 13 g nitrogen (N)/m²/y. Almost 4,000 kg of suspended sediment was captured by this wetland system during the year.     

ASSESSING FLOOD MITIGATION ALTERNATIVES IN SHIJR AREA IN METROPOLITAN TAIPEI1

The Keelung River Basin in northern Taiwan lies immediately upstream of the Taipei metropolitan area. The Shijr area is in the lower basin and is subject to frequent flooding. This work applies micromanagement and source control, including widely distributed infiltration and detention/ retention runoff retarding measures, in the Wudu watershed above Shijr. A method is also developed that combines a genetic algorithm and a rainfall runoff model to optimize the spatial distribution of runoff retarding facilities. Downstream of Wudu in the Shijr area, five dredging schemes are considered. If 10‐year flood flows cannot be confined in the channel, then a levee embankment that corresponds to the respective runoff retarding scheme will be required. The minimum total cost is considered in the rule to select from the regional flood mitigation alternatives. The results of this study reveal that runoff retarding facilities installed in the upper and middle parts of the watershed are most effective in reducing the flood peak. Moreover, as the cost of acquiring land for the levee embankment increases, installing runoff retarding measures in the upper portion of the watershed becomes more economical.     

APPLICATION OF GREY MODEL AND ARTIFICIAL NEURAL NETWORKS TO FLOOD FORECASTING1

The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km² watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

EFFECTS OF INITIAL ABSTRACTION AND URBANIZATION ON ESTIMATED RUNOFF USING CN TECHNOLOGY1

ABSTRACT: Few studies have been conducted to explore the effects of initial abstraction on estimated direct runoff despite the widespread use of the curve number (CN) method in many hydrologic models to estimate direct runoff. In this study, use of a 5 percent ratio of initial abstraction (I_a) to storage (S) to estimate daily direct runoff with modified CN values for a 5 percent I_a/S value was investigated using the Long‐Term Hydrologic Impact Assessment (L‐THIA) geographic information system (GIS). In addition, the effects on estimated runoff of altering the hydrologic soil group due to urbanization were investigated. The L‐THIA model was applied to the Indiana Little Eagle Creek watershed with 5 percent and 20 percent I_a/S values, considering hydrologic soil group alteration due to urbanization. The results indicate that uses of a 5 percent l_a/S and modified CN values and Hydrologic Soil Group D for urbanized areas in model runs can improve long term direct runoff prediction.     

ASSESSMENT OF POSSIBLE IMPACTS OF CLIMATE CHANGE IN AN URBAN CATCHMENT1

ABSTRACT: Stationarity of rainfall statistical parameters is a fundamental assumption in hydraulic infrastructure design that may not be valid in an era of changing climate. This study develops a framework for examining the potential impacts of future increases in short duration rainfall intensity on urban infrastructure and natural ecosystems of small watersheds and demonstrates this approach for the Mission/Wagg Creek watershed in British Columbia, Canada. Nonstationarities in rainfall records are first analyzed with linear regression analysis, and the detected trends are extrapolated to build potential future rainfall scenarios. The Storm Water Management Model (SWMM) is used to analyze the effects of increased rainfall intensity on design peak flows and to assess future drainage infrastructure capacity according to the derived scenarios. While the framework provided herein may be modified for cases in which more complex distributions for rainfall intensity are needed and more sophisticated stormwater management models are available, linear regressions and SWMM are commonly used in practice and are applicable for the Mission/Wagg Creek watershed. Potential future impacts on stream health are assessed using methods based on equivalent total impervious area. In terms of impacts on the drainage infrastructure, the results of this study indicate that increases in short duration rainfall intensity may be expected in the future but that they would not create severe impacts in the Mission/Wagg Creek system. The equivalent levels of imperviousness, however, suggest that the impacts on stream health could be far more damaging.