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.     

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.     

CHARACTERIZATION OF HYDROLOGIC CONDITIONS TO SUPPORT PLATTE RIVER SPECIES RECOVERY EFFORTS1

ABSTRACT: Efforts are under way to recover habitat for several threatened and endangered species in and along the Platte River in central Nebraska. A proposed recovery program for these species requires a means of characterizing “wet” versus “normal” versus “dry” hydrologic conditions in order to set corresponding Platte River instream flow targets. Methods of characterizing hydrologic conditions in real time were investigated for this purpose. Initially, 10 watershed variables were identified as potentially valuable indicators of hydrologic conditions. Ultimately, six multiple linear regression equations were developed for six periods of the year using a subset of these variables expressed as frequencies of nonexceedence. The adequacy of these equations for characterizing conditions was assessed by evaluating their historic correlation to subsequent flow in the central Platte River (1947–1994). These equations explained 54 to 82 percent of variability in the observed flow exceedences in the validation datasets, depending upon the period of year evaluated. These equations will provide initial criteria for setting applicable flow targets to determine, in real time, whether water regulation projects associated with the species recovery effort can divert or store flows without conflicting with recovery objectives.     

河冰对桥墩作用的冰荷载计算方法(Ⅰ)——河冰的力学性能试验

通过对松花江河冰的物理力学性能试验和松花江公路大桥桥墩的流冰动压力测量、桥面的脉动测量 ,依据国内外对冰 -结构相互作用的分析 ,提出了适合我国黑龙江冰情特点的春季流冰冰荷载的计算方法。     

Dynamics of Bacterial Abundance,Biomass, Activity,and Community Composition in the Oligotrophic Traunsee and the Traun River (Austria)

The holomictic Traunsee is the deepest and second largest lakein Austria. The special characteristic of this ecosystem isthe fact that local salt and soda industries presumably alterthe lake by the discharge of waste materials. Since thebeginning of the 20th century salt and soda works areannually releasing up to 50,000 tons of solid wastes and up to150,000 tons of chloride into Traunsee. To assess potentialeffects of these anthropogenic impacts on the bacterioplanktonthree sampling sites, influenced as well as not influenced bythe industrial discharge, were chosen for comparison andsampled monthly from November 1997 to October 1998. Bacterialabundance ranged between 0.4 to 3.0 × 10⁶ cells ml^-1 with decreasing numbers along the depth profile. Theproportion of actively respiring bacteria, i.e. INT [2-(4-iodophenyl)-3-(4-nitrophenyl)-5-phenyltetrazolium chloride]reducing cells, never exceeded 10% of DAPI (4',6'-diamidino-2-phenylindole) stained cells. Fluorescence in situ hybridization (FISH) was used to examine the seasonal and spatial distribution of dominant phylogenetic groups of thebacterioplankton. Up to 84% of bacteria detected with DAPIcould be detected via FISH applying the universal bacterialprobe EUB338. Percentages of alpha- and beta-Proteobacteriaand members of the Cytophaga-Flavobacterium cluster did notexceed 60% of DAPI-stained cells.Beta-Proteobacteriaappeared to be the most abundant group, not only in Traunsee butalso in two reference lakes, Attersee and Hallstättersee. No significant differences in any of the bacterial parameters couldbe detected between the three sampling sites and all measurementswere found in the range reported for oligotrophic lakes. The highdischarge of the Traun River, resulting in a lake water renewaltime of only one year, may diminish possible effects of industrial waste discharge in the pelagic zone.     

MULTISCALE RIVER ENVIRONMENT CLASSIFICATION FOR WATER RESOURCES MANAGEMENT1

ABSTRACT: River Environment Classification (REC) is a new system for classifying river environments that is based on climate, topography, geology, and land cover factors that control spatial patterns in river ecosystems. REC builds on existing principles for environmental regionalization and introduces three specific additions to the “ecoregion” approach. First, the REC assumes that ecological patterns are dependent on a range of factors and associated landscape scale processes, some of which may show significant variation within an ecoregion. REC arranges the controlling factors in a hierarchy with each level defining the cause of ecological variation at a given characteristic scale. Second, REC assumes that ecological characteristics of rivers are responses to fluvial (i.e., hydrological and hydraulic) processes. Thus, REC uses a network of channels and associated watersheds to classify specific sections of river. When mapped, REC has the form of a linear mosaic in which classes change in the downstream direction as the integrated characteristics of the watershed change, producing longitudinal spatial patterns that are typical of river ecosystems. Third, REC assigns individual river sections to a class independently and objectively according to criteria that result in a geographically independent framework in which classes may show wide geographic dispersion rather than the geographically dependent schemes that result from the ecoregion approach. REC has been developed to provide a multiscale spatial framework for river management and has been used to map the rivers of New Zealand at a 1:50,000 mapping scale.     

ACCURACY AND RELIABILITY OF NUMERICAL RIVER MODELS1

ABSTRACT: Over the last 20 years, our possibilities to model river flows numerically have increased enormously. In this paper, the question is addressed whether a more sophisticated model is always better than a simpler one. Increased detail, both in finer resolution and in physical processes taken into account, has its price in more computer time, higher data need, and perhaps more unknown coefficients to be calibrated. Moreover, uncertainty in actual physical conditions (e.g., bottom roughness), inflow and parameters remains, which may dominate the uncertainty of the results. Also, the questions asked by a decision maker may not always be very precise. For a schematic but relevant example, we show that a better model does not necessarily give more reliable results because some of the basic uncertainties remain. It is concluded that we should use the simplest model that will answer the question as to the accuracy needed, taking into account uncertainties in the data