SUSPENDED SEDIMENT AND METALS REMOVAL FROM URBAN RUNOFF BY A SMALL LAKE1

ABSTRACT: A small lake in the Chicago Metropolitan Area was from 91 to 95 percent efficient in removing suspended sediment and from 76 to 94 percent efficient in removing copper, iron, lead, and zinc from urban runoff. Sediments accumulated in the lake in the form of an organic-rich mud at an average rate of 20 millimeters per year; this reduced lake storage and covered potential habitat for aquatic organisms. Copper, lead, and zinc concentrations were closely associated with suspended-sediment concentrations and with silt- and clay-sized fractions of lake sediment. Although concentrations of mercury and cadmium were near detection limits in runoff, measurable concentrations of these metals accumulated in the lake sediments.     

MANAGEMENT OF INSTREAM FLOWS THROUGH RUNOFF DETENTION AND RETENTION1

ABSTRACT: The use of reservoirs and land treatments to manage streamflow for the maintenance or enhancement of instream flow values is a valid concept. Historically, large reservoirs have been used for flood control and water-supply regulation. Smaller structures have enjoyed widespread use for soil and water conservation in headwater areas. Where reservoir releases can be controlled, it is technically feasible to regulate flows for the enhancement of instream values. However, institutional and political obstacles may preclude the operation of some reservoirs for this purpose. Retention and detention structures and land treatments, implemented for soil and water conservation purposes, have often had favorable effects on the streamflow hydrograph. Decreases in peak flows and increases in low flows have been documented. Design concepts for runoff-control structures are discussed in relation to instream flow management objectives. Hydro-logic simulation is offered as a potential tool for project design and feasibility analysis.     

RUNOFF PREDICTION USING REMOTE SENSING IMAGERY1

ABSTRACT: Percent imperviousness is an important parameter in modeling the urban rainfall-runoff process and is usually determined using manual methods such as random sampling or conventional accounting methods. In this study two computerized methods are used for estimating the percent imperviousness of urban watersheds using high altitude remote sensing imagery. These methods include the Laser Image Processing Scanner and the Video-Tape Camera system. Imperviousness is directly estimated in the former method while in the latter it is estimated as a function of the statistics of the responses on emulsions of the imagery. The percent imperviousness computed by utilizing remote sensing imagery was used with the conceptual models of rainfall-runoff models. The models were applied to four urban watersheds and the runoff prediction results indicate that imperviousness determined by using remote sensing imagery was as accurate as that obtained by the manual methods, and that the use of remote sensing imagery requires significantly less time and money.     

SHORT-TERM FORECASTING OF SNOWMELT RUNOFF USING ARMAX MODELS1

ABSTRACT: Time series models of the ARMAX class were investigated for use in forecasting daily riverflow resulting from combined snowmelt/rainfall. The Snowmelt Runoff Model (Martinec-Rango Model) is shown to have a form similar to the ARMAX model. The advantage of the ARMAX approach is that analytical model identification and parameter estimation techniques are available. In addition, previous forecast errors can be included to improve forecasts and confidence limits can be estimated for the forecasts. Diagnostic checks are available to determine if the model is performing properly. Finally, Kalman filtering can be used to allow the model parameters to vary continuously to reflect changing basin runoff conditions. The above advantages result in improved flow forecasts with fewer model parameters.     

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.     

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.     

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.