AN INTEGRATED ONE‐DIMENSIONAL AND TWO‐DIMENSIONAL URBAN STORMWATER FLOOD SIMULATION MODEL1

ABSTRACT: Flash flooding is the rapid flooding of low lying areas caused by the stormwater of intense rainfall associated with thunderstorms. Flash flooding occurs in many urban areas with relatively flat terrain and can result in severe property damage as well as the loss of lives. In this paper, an integrated one‐dimensional (1‐D) and two‐dimensional (2‐D) hydraulic simulation model has been established to simulate stormwater flooding processes in urban areas. With rainfall input, the model simulates 2‐D overland flow and 1‐D flow in underground stormwater pipes and drainage channels. Drainage channels are treated as special flow paths and arranged along one or more sides of a 2‐D computational grid. By using irregular computation grids, the model simulates unsteady flooding and drying processes over urban areas with complex drainage systems. The model results can provide spatial flood risk information (e.g., water depth, inundation time and flow velocity during flooding). The model was applied to the City of Beaumont, Texas, and validated with the recorded rainfall and runoff data from Tropical Storm Allison with good agreement.     

INVESTIGATION OF TURBIDITY MAXIMUM IN A MESOTIDAL ESTUARY,TAIWAN1

ABSTRACT: To comprehend the distributions of salinity, temperature, and suspended sediment in the Danshuei River estuary in Taiwan, monthly field surveys were conducted in 2003. These included several high and low slackwater surveys and intensive surveys. The results show that the Danshuei River estuary is predominately a partially mixed estuary. The highest concentration of suspended sediment is typically observed at the Chung‐Hsin Bridge, the most upstream sampling station. The suspended sediment concentration exhibits a general decreasing trend in the downstream direction. It may be concluded that the sediments mostly come from the upstream reach. A locally high concentration of suspended sediment is found at the Kuan‐Du station because of the local deep channel bathymetry and two‐layered estuarine circulation. A vertical two‐dimensional hydrodynamic and sediment transport model is applied to investigate the tidally averaged salinity distribution, residual circulation, and suspended sediment concentration. The modeling results reveal that, under the Q₇₅ flow condition (i.e., low flow), a turbidity maximum occurs at the Kuan‐Du station due to the strong estuarine circulation. The model simulation with a much higher river flow condition results in a weaker residual circulation and weaker turbidity maximum.     

WEST AFRICA: VOLTA DISCHARGE DATA QUALITY ASSESSMENT AND USE1

ABSTRACT: Water resource management in West Africa is often a complicated process due to inadequate resources, climatic extremes, and insufficient hydrological information. Insufficient data hinder sustainable watershed management practices, one of the top priorities in the Volta River Basin. This research properly fills in missing data by modeling the hydrological distribution in the Volta River Basin. On average, discharge gages across the basin are missing 20 percent of their monthly data over 20 years. Two methods were used to supplement missing data: a statistically linear model and a conceptual hydrological model. A linear equation, developed from the regression of precipitation and runoff, was used to evaluate the quality of existing data. The hydrological model separates the system into root and groundwater zones. Measured values were used to calibrate the hydrological model and to validate the statistical model. The quality of existing data was analyzed and organized for usability. Accuracy of the hydrological model was also evaluated for its effectiveness using R² and standard error. It was found that the hydrological model was an improvement from the linear model on a monthly basis; R² values improved by as much as 0.5 and monthly error decreased. Monthly predictions of the hydrological model were used to fill gaps of measured data sets.     

HYDROLOGIC MODELING OF A BIOINFILTRATION BEST MANAGEMENT PRACTICE1

ABSTRACT: The goal of this research was to develop a methodology for modeling a bioinfiltration best management practice (BMP) built in a dormitory area on the campus of Villanova University in Pennsylvania. The objectives were to quantify the behavior of the BMP through the different seasons and rainfall events; better understand the physical processes governing the system's behavior; and develop design criteria. The BMP was constructed in 2001 by excavating within an existing traffic island, backfilling with a sand/soil mixture, and planting with salt tolerant grasses and shrubs native to the Atlantic shore. It receives runoff from the asphalt (0.26 hectare) and turf (0.27 hectare) surfaces of the watershed. Monitoring supported by the hydrologic model shows that the facility infiltrates a significant fraction of the annual precipitation, substantially reducing the delivery of nonpoint source pollution and erosive surges downstream. A hydrologic model was developed using HEC‐HMS to represent the site and the BMP using Green‐Ampt and kinematic wave methods. Instruments allow comparison of the modeled and measured water budget parameters. The model, incorporating seasonally variable parameters, predicts the volumes infiltrated and bypassed by the BMP, confirming the applicability of the selected methods for the analysis of bioinfiltration BMPs.     

Trip-Based Explanatory Variables For Estimating Vehicle Fuel Consumption and Emission Rates

The current state-of-practice in the US for estimatingvehicle emissions is based on a single traffic-relatedexplanatory variable, namely average speed. Research,however, has demonstrated that the use of average speed asa single traffic-related variable is insufficient for theestimation of vehicle emissions. For example, although theEnvironmental Protection Agency (EPA) MOBILE5 model wouldindicate that a slowing of traffic typically increasesemissions, empirical research indicates the opposite inmany cases.The objective of this paper is to identify criticalaggregate trip variables as potential explanatory variablesfor the estimation of a vehicle's fuel consumption andemissions. Subsequently, statistical models for estimatingfuel consumption and emissions of hydrocarbon (HC), carbonmonoxide (CO), and oxides of nitrogen (NO_x) aredeveloped using these critical variables that include theaverage speed, speed variability, the level ofdeceleration, and the level of acceleration. The proposedmodels are demonstrated to be consistent with microscopicenergy and emission model estimates that are based on thevehicle's instantaneous speed and acceleration levels(coefficient of determination ranges from 0.88 to 0.96).     

基于神经网络的温度预测

室内温度与诸多影响因素之间的非线性、复杂性等关系 ,给建模、预测带来了难度 ,引入了人工神经网络 ;利用人工神经网络的非线性、并行计算和自学习特性进行建模 ,实现了对温度模拟     

WATER QUALITY MODELING OF ALTERNATIVE AGRICULTURAL SCENARIOS IN THE U.S. CORN BELT1

ABSTRACT: Simulated water quality resulting from three alternative future land‐use scenarios for two agricultural watersheds in central Iowa was compared to water quality under current and historic land use/land cover to explore both the potential water quality impact of perpetuating current trends and potential benefits of major changes in agricultural practices in the U.S. Corn Belt. The Soil Water Assessment Tool (SWAT) was applied to evaluate the effect of management practices on surface water discharge and annual loads of sediment and nitrate in these watersheds. The agricultural practices comprising Scenario 1, which assumes perpetuation of current trends (conversion to conservation tillage, increase in farm size and land in production, use of currently‐employed Best Management Practices (BMPs)) result in simulated increased export of nitrate and decreased export of sediment relative to the present. However, simulations indicate that the substantial changes in agricultural practices envisioned in Scenarios 2 and 3 (conversion to conservation tillage, strip intercropping, rotational grazing, conservation set‐asides and greatly extended use of best management practices (BMPs) such as riparian buffers, engineered wetlands, grassed waterways, filter strips and field borders) could potentially reduce current loadings of sediment by 37 to 67 percent and nutrients by 54 to 75 percent. Results from the study indicate that major improvements in water quality in these agricultural watersheds could be achieved if such environmentally‐targeted agricultural practices were employed. Traditional approaches to water quality improvement through application of traditional BMPs will result in little or no change in nutrient export and minor decreases in sediment export from Corn Belt watersheds.     

APPLICATION OF AN ENVIRONMENTAL AND ECONOMIC MODELING SYSTEM FOR WATERSHED ASSESSMENTS1

ABSTRACT: A National Pilot Project (NPP) on Livestock and the Environment was initiated in 1992 to help provide solutions to environmental problems associated with livestock production. A major development of the NPP was the Comprehensive Economic and Environmental Optimization Tool‐Livestock and Poultry (CEEOT‐LP), an integrated modeling system designed to produce economic and environmental indicators for alternative policy scenarios applied to intensive livestock production watersheds. The system consists of a farm‐level economic model (FEM) and two environmental models: the field‐scale APEX model and the watershed‐level SWAT model. To date, CEEOT‐LP has been applied to two watersheds in Texas and one in Iowa. Predicted reductions in P losses for two P‐based manure application rate scenarios, relative to baseline conditions, ranged from ?4 to ?54 percent across the three watersheds; however, N loss impacts ranged from a decrease of 34 percent to an increase of 79 percent. For five other alternative scenarios that were simulated for only one watershed, N and P loss impacts ranged between a reduction of 78 percent to an increase of 20 percent. Aggregate watershed‐level economic impacts of the seven scenarios spanned a spectrum of a 27 percent decrease to a 25 percent increase in profit, relative to the baseline.     

CONSTRUCTING A PROBLEM SOLVING ENVIRONMENT TOOL FOR HYDROLOGIC ASSESSMENT OF LAND USE CHANGE1

ABSTRACT: This paper describes the integration of a comprehensive hydrological model known as the Hydrological Simulation Program Fortran (HSPF) into a problem solving environment (PSE) for watershed management. The original PSE concept was a structure providing web‐based access to a suite of models, including HSPF and other models of in‐stream hydrodynamics, biological impacts and economic effects, for the watershed‐wide assessment of alternative land use scenarios. The present paper describes only the HSPF integration into the PSE program. Example applications to the 148 square kilometer (57 square mile) Back Creek subwatershed in the upper Roanoke River system (1,479 square kilometers or 571 square miles) in southwest Virginia are used to illustrate important concepts and linkages between land development and hydrological change using hypothetical' what if'scenarios. The features of HSPF and its limitations in this context are discussed. The paper as such is a proof‐of‐concept paper and not a completion report. It is intended to describe the PSE tool building process rather than analysis of the many possible simulation outcomes. However, the dominance of raw imperviousness as a contributor to hydrograph response is apparent in all the PSE simulations described in this paper.     

SUBWATERSHED SPATIAL ANALYSIS TOOL: DISCRETIZATION OF A DISTRIBUTED HYDROLOGIC MODEL BY STATISTICAL CRITERIA1

ABSTRACT: Complex hydrologic models, designed for simulating larger watersheds, require a huge amount of input data. Most of these models use spatially distributed data as inputs. Spatial data can be aggregated or disaggregated for use as input to a model, which can impact model outputs. Although, it is efficient to minimize data redundancy by aggregating the spatial data, upscaling reduces the detail/resolution of input information and increases model uncertainty. On the other hand, a large number of model inputs with high degrees of disaggregation take more computer time and space to process. Hence, a balance between striving for a maximum level of aggregation and a minimum level of information loss has to be achieved. This study presents a definition of an appropriate level of discretization, derived by establishing a relationship between a model's efficiency and the number of subwater‐sheds modeled. An entropy based statistical approach/tool called Subwatershed Spatial Analysis Tool (SUSAT) was developed to find an objective choice of an appropriate level of discretization. The new approach/tool was applied to three watersheds, each representing different hydrologic conditions, using a hydrologic model. Coefficients of efficiency and entropy estimated at different levels of discretization were used to validate the success of the new approach.