APPLICATION OF THE U.S.G.S. DIFFUSION HYDRODYNAMIC MODEL FOR URBAN FLOODPLAIN ANAYSIS1

ABSTRACT: The two-dimensional Diffusion Hydrodynamic Model, DHM, is applied to the evaluation of floodplain depths resulting from an overflow of a leveed river. The environmental concerns of flood protection and high flow velocities can be better studied with the help of the two-dimensional DHM flow model than by use of the one-dimensional modeling techniques. In the test case, some of the predicted flood depth differences between the DHM and the one-dimensional approach (i.e., HEC-2) are found to be significant. Although the DHM generates considerable information, it is easy to use and does not require expertise beyond that required for use of the one-dimensional approaches.     

PRELIMINARY ESTIMATION OF COLD WATER AVAILABILITY IN LAKES FOR FISH HATCHERIES1

ABSTRACT: Fish hatcheiies for cold water species (e.g., salmonids) require water below a certain specified optimum temperature. Deep lakes and reservoirs, which are thermally stratified, will have cold water below the thermocline suitable for fish hatchery supplies. Proper management will require withdrawal of water at different depths and a mixture of correct proportions can yield water at desired temperatures and quality. For preliminary studies, a mathematical model can be used to show by a comparatively simple computation the effect of different withdrawal rates of cold water and to check if the situation is critical. A critical situation may warrant the application of sophisticated computer models and/or the use of chilling at the hatchery. The method is illustrated by a case study for a small lake in the Province of Nova Scotia.     

Evaluating Sediment Stability at Sites with Historic Contamination

The stability of cohesive sediment deposits during a rare storm is a critical component in the evaluation of remedial options at a contaminated sediment site. Estimating scour depths during a rare storm, and the resulting contaminant concentrations in the surficial layer of the bed, is necessary for comparing the efficacy of various remedial alternatives. Evaluation of sediment stability is accomplished using sediment transport analyses that employ quantitative procedures. Qualitative analyses or conceptual models can be useful for developing and validating quantitative analysis tools; however, qualitative techniques alone generally are insufficient for conducting defensible remedial alternative evaluations. The level of analysis used for a specific site depends on data availability, required level of accuracy, and time and budget constraints. A tier 1 analysis involves the use of approximate equations to produce order-of-magnitude estimates of scour depths during a rare storm. The second tier of this analysis scheme employs the development and application of a sediment transport model to evaluate bed stability. State-of-the-science sediment transport models have been effectively used as management tools for evaluating remedial options at several contaminated sediment sites. It should not be presumed that rare storm events cause catastrophic impacts at the site under review. Two case studies demonstrate that a rare storm is not necessarily catastrophic; significant increases in surficial bed concentrations caused by reexposure of elevated concentrations buried at depth in the bed will not necessarily occur during a rare storm. However, it is important to note that sediment stability is site-specific.     

IDENTIFICATION OF AQUIFER DISPERSIVITIES: METHODS OF ANALYSIS AND PARAMETER UNCERTAINTY1

ABSTRACT: This paper presents a method for estimating aquifer dispersivities in solute transport models. Sensitivity equations are derived for the calculation of sensitivity coefficients. A modified Gauss-Newton algorithm is used to perform the least-squares minimization. A statistical procedure is outlined to assess reliability of the estimated parameters. The solute transport model is solved by the upstream weighted, multiple cell balance method which combines the concepts of local mass balance and finite element approximations. A one-dimensional solute transport problem in a vertical column system is first used to illustrate the inverse technique. A second example considers the parameter identification problem for three-dimensional solute transport with a unidirectional steady and uniform flow field. The third example solves the parameter identification problem in a three-dimensional, stream-aquifer, solute transport system with steady state flow. Numerical experiments are conducted to study data requirements for parameter identification.     

Modeling the Fate and Transport of Plunging Inflows to Onondaga Lake

The transport and fate of two plunging tributaries, Onondaga and Ninemile Creeks, in Onondaga Lake, New York, are quantified based on application of hydrodynamic/transport models. Short‐term transport is simulated with a three‐dimensional Estuary Lake and Coastal Ocean Model (ELCOM), while the longer term fate is represented by a previously validated one‐dimensional model (UFILS4). The validation of ELCOM for the vertical distribution of tributary inflow into the lake's water column is demonstrated for four dye tracer experiments. The models are applied for three years to represent the dynamics of transport and fate for the two tributaries, with ELCOM predictions serving as input for UFILS4. The models together quantify the distribution of these inflows between the upper mixed layer (UML) and stratified depths, and the subsequent transport from stratified depths to the UML by vertical mixing. Substantial short‐term variations are predicted for both tributaries in response to variability in hydrology and weather. Increased inflow to the UML is predicted for high runoff periods. The fraction of Ninemile Creek's inflow directly entering the UML is predicted to be 50% greater than for Onondaga Creek due to Ninemile's lower negative buoyancy. The plunging phenomenon has important water quality implications, by reducing the effective loading to the UML, particularly for constituents with large rates of loss/transformation relative to the rate of vertical transport from stratified depths.     

A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models1

Abstract: Water resources planning and management efficacy is subject to capturing inherent uncertainties stemming from climatic and hydrological inputs and models. Streamflow forecasts, critical in reservoir operation and water allocation decision making, fundamentally contain uncertainties arising from assumed initial conditions, model structure, and modeled processes. Accounting for these propagating uncertainties remains a formidable challenge. Recent enhancements in climate forecasting skill and hydrological modeling serve as an impetus for further pursuing models and model combinations capable of delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The framework presented here proposes integration and offline coupling of global climate models (GCMs), multiple regional climate models, and numerous water balance models to improve streamflow forecasting through generation of ensemble forecasts. For demonstration purposes, the framework is imposed on the Jaguaribe basin in northeastern Brazil for a hindcast of 1974‐1996 monthly streamflow. The ECHAM 4.5 and the NCEP/MRF9 GCMs and regional models, including dynamical and statistical models, are integrated with the ABCD and Soil Moisture Accounting Procedure water balance models. Precipitation hindcasts from the GCMs are downscaled via the regional models and fed into the water balance models, producing streamflow hindcasts. Multi‐model ensemble combination techniques include pooling, linear regression weighting, and a kernel density estimator to evaluate streamflow hindcasts; the latter technique exhibits superior skill compared with any single coupled model ensemble hindcast.     

Linking Riparian Dynamics and Groundwater: An Ecohydrologic Approach to Modeling Groundwater and Riparian Vegetation

The growing use of global freshwater supplies is increasing the need for improved modeling of the linkage between groundwater and riparian vegetation. Traditional groundwater models such as MODFLOW have been used to predict changes in regional groundwater levels, and thus riparian vegetation potential attributable to anthropogenic water use. This article describes an approach that improves on these modeling techniques through several innovations. First, evapotranspiration from riparian/wetland systems is modeled in a manner that more realistically reflects plant ecophysiology and vegetation complexity. In the authors’ model programs (RIP-ET and PRE-RIP-ET), the single, monotonically increasing evapotranspiration flux curve in traditional groundwater models is replaced with a set of ecophysiologically based curves, one for each plant functional group present. For each group, the curve simulates transpiration declines that occur both as water levels decline below rooting depths and as waters rise to levels that produce anoxic soil conditions. Accuracy is further improved by more effective spatial handling of vegetation distribution, which allows modeling of surface elevation and depth to water for multiple vegetation types within each large model cell. The use of RIP-ET in groundwater models can improve the accuracy of basin scale estimates of riparian evapotranspiration rates, riparian vegetation water requirements, and water budgets. Two case studies are used to demonstrate that RIP-ET produces significantly different evapotranspiration estimates than the traditional method. When combined with vegetation mapping and a supporting program (RIP-GIS), RIP-ET also enables predictions of riparian vegetation response to water use and development scenarios. The RIP-GIS program links the head distribution from MODFLOW with surface digital elevation models, producing moderate- to high-resolution depth-to-groundwater maps. Together with information on plant rooting depths, these can be used to predict vegetation response to water allocation decisions. The different evapotranspiration outcomes produced by traditional and RIP-ET approaches affect resulting interpretations of hydro-vegetation dynamics, including the effects of groundwater pumping stress on existing habitats, and thus affect subsequent policy decisions.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

Variations in pesticide leaching related to land use, pesticide properties, and unsaturated zone thickness

Pesticide leaching through variably thick soils beneath agricultural fields in Morgan Creek, Maryland was simulated for water years 1995 to 2004 using LEACHM (Leaching Estimation and Chemistry Model). Fifteen individual models were constructed to simulate five depths and three crop rotations with associated pesticide applications. Unsaturated zone thickness averaged 4.7 m but reached a maximum of 18.7 m. Average annual recharge to ground water decreased from 15.9 to 11.1 cm as the unsaturated zone increased in thickness from 1 to 10 m. These point estimates of recharge are at the lower end of previously published values, which used methods that integrate over larger areas capturing focused recharge in the numerous detention ponds in the watershed. The total amount of applied and leached masses for five parent pesticide compounds and seven metabolites were estimated for the 32-km2 Morgan Creek watershed by associating each hectare to the closest one-dimensional model analog of model depth and crop rotation scenario as determined from land-use surveys. LEACHM parameters were set such that branched, serial, first-order decay of pesticides and metabolites was realistically simulated. Leaching is predicted to be greatest for shallow soils and for persistent compounds with low sorptivity. Based on simulation results, percent parent compounds leached within the watershed can be described by a regression model of the form e(-depth) (a ln t1/2-b ln K OC) where t1/2 is the degradation half-life in aerobic soils, K OC is the organic carbon normalized sorption coefficient, and a and b are fitted coefficients (R2 = 0.86, p value = 7 x 10(-9)).     

The effects of environmental change on individuals and groups: Some neglected issues in stress research

Homeostatic models of the effects of environmental change often entail certain assumptions that may not be warranted. It is widely assumed that the effects of negative environmental change or stress are necessarily adverse and have relatively short-term effects. It is further assumed that these effects are linear, that is, the greater the stress, the more negative the outcome. In contrast, from an ecological and developmental perspective, environmental change is seen as having possible paradoxical (i.e., positive) outcomes as well, depending upon the type and timing of the outcome assessed, and situational and individual factors. Non-linear models are reviewed for their applicability to a broader conceptualization of environmental change. This approach includes both multiple determinants and outcomes of stress, and is sensitive to ecological and developmental concerns, such as the timing and context of the stressor and possible long-term outcomes.     

ARTIFICIAL NEURAL NETWORKS FOR SUBSURFACE DRAINAGE AND SUBIRRIGATION SYSTEMS IN ONTARIO,CANADA1

ABSTRACT: Artificial neural network (ANN) models were developed to simulate fluctuations in midspan water table depths (WTD) given rainfall, potential evapotranspiration, and irrigation inputs on a Brookston clay loam in Woodslee, Ontario, having a dual‐purpose subsurface drainage/subirrigation setup. Water table depths and meteorologic data collected at this site from 1992 to 1994 and from 1996 to 1997 were used to train the ANNs. The ANNs were then used for real‐time control and time series simulations. The lowest root mean squared errors (RMSE) for the various ANNs were 60.6 mm for real‐time control simulation, and 88.4 mm for time‐series simulation of water table depths. It was possible to simulate WTD for the different modes of water table management in one network by incorporating an indicator for switching from one to the other. The ANN simulations were quite good even though the training data sets had irregular measurement intervals. With fewer input parameters and small network structures, ANNs still provided accurate results and required little time for training and execution. ANNs are therefore easier and faster to develop and run than conventional models and can contribute to the proper management of subsurface drainage and subirrigation systems.     

DETERMINING CRITICAL WATER QUALITY CONDITIONS FOR INORGANIC NITROGEN IN DRY,SEMI‐URBANIZED WATERSHEDS1

ABSTRACT: Traditional approaches to establishing critical water quality conditions, based on statistical analysis of low flow conditions and expressed as a recurrence interval for low flow conditions (e.g., 7Q10), may be inappropriate for drier watersheds. The use of 7Q10 as a standard design flow assumes year‐round flow, but in these watersheds, 7Q10 is zero or very small. In addition, the increasing use of multiple year dynamic water quality models at daily time steps can supercede the use of steady state approaches. Many of these watersheds are also under increasing urbanization pressure, which accentuates the flashiness of runoff and the episodic nature of critical water quality conditions. To illustrate, the conditions in the Santa Clara River, California, are considered. A statistical analysis indicates that higher inorganic nitrogen concentrations correlate strongly with low flow. However, peaks in concentrations can occur during the first storms, particularly where nonpoint source contribution is significant. Critical conditions can thus occur at different flow regimes depending on the relative magnitude of flow and pollutant contributions from various sources. The use of steady state models for these dry semi‐urbanized watersheds based on 7Q10 flows is thus unlikely to accurately simulate the potential for exceeding water quality objectives. Dynamic simulation of water quality is necessary, and as the recent intense storm event sampling data indicate, the models should be formulated to consider even smaller time steps. This places increasing demand on computational resources and datasets to accurately calibrate the models at this temporal resolution.     

INTERFACING GIS WITH WATER RESOURCE MODELS: A STATE‐OF‐THE‐ART REVIEW1

Two distinctive, independently developed technologies, geographic information systems (GIS) and predictive water resource models, are being interfaced with varying degrees of sophistication in efforts to simultaneously examine spatial and temporal phenomena. Neither technology was initially developed to interact with the other, and as a result, multiple approaches to interface GIS with water resource models exist. Additionally, continued model enhancements and the development of graphical user interfaces (GUIs) have encouraged the development of application “suites” for evaluation and visualization of engineering problems. Currently, disparities in spatial scales, data accessibility, modeling software preferences, and computer resources availability prevent application of a universal interfacing approach. This paper provides a state‐of‐the‐art critical review of current trends in interfacing GIS with predictive water resource models. Emphasis is placed on discussing limitations to efficient interfacing and potential future directions, including recommendations for overcoming many current challenges.     

美国环保署农药地下水风险评估模型

在介绍美国农药环境风险评估的概念、分级、地下水农药监测情况及水资源的立法保护等基础上,重点阐述了美国环保署在农药登记管理过程中使用的2个地下水风险评估模型,即SCI-GROW和PRZM-GW模型。SCI-GROW是以好氧条件土壤半衰期和土壤有机碳分配系数为自变量的经验线性回归模型,而PRZM-GW则是描述农药在土壤中运动的一维、有限差分模型。本文通过对美国环保署这2个特点鲜明的模型的介绍,希望能为我国的农药地下水风险评估及模型的开发提供一个新视角。     

Water–energy–greenhouse gas nexus of urban water systems: Review of concepts,state-of-art and methods

Water supply and wastewater services incur a large amount of energy and GHG emissions. It is therefore imperative to understand the link between water and energy as their availability and demand are closely interrelated. This paper presents a literature review and assessment of knowledge gaps related to water–energy–greenhouse gas (GHG) nexus studies in an urban context from an ‘energy for water’ perspective. The review comprehensively surveyed various studies undertaken in various regions of the world and focusing on individual or multiple subsystems of an urban water system. The paper also analyses the energy intensity of decentralized water systems and various water end-uses together with the major tools and models used. A major gap identified from this review is the lack of a holistic and systematic framework to capture the dynamics of multiple water–energy–GHG linkages in an integrated urban water system where centralized and decentralized water systems are combined to meet increased water demand. Other knowledge gaps identified are the absence of studies, peer reviewed papers, data and information on water–energy interactions while adopting a ‘fit for purpose water strategy’ for water supply. Finally, based on this review, we propose a water–energy nexus framework to investigate ‘fit-for-purpose’ water strategy.     

CHEMICAL REACTIONS SIMULATED BY GROUND-WATER-QUALITY MODELS1

ABSTRACT: Recent literature concerning the modeling of chemical reactions during transport in ground water is examined with emphasis on sorption reactions. The theory of transport and reactions in porous media has been well documented. Numerous equations have been developed from this theory, to provide both continuous and sequential or multistep models, with the water phase considered for both mobile and immobile phases. Chemical reactions can be either equilibrium or non-equilibrium, and can be quantified in linear or non-linear mathematical forms. Non-equilibrium reactions can be separated into kinetic and diffusional rate-limiting mechanisms. Solutions to the equations are available by either analytical expressions or numerical techniques. Saturated and unsaturated batch, column, and field studies are discussed with one-dimensional, laboratory-column experiments predominating. A summary t able is presented that references the various kinds of models studied and their applications in predicting chemical concentrations in ground waters.     

Random forest models to estimate bankfull and low flow channel widths and depths across the conterminous United States

Channel dimensions (width and depth) at varying flows influence a host of instream ecological processes, as well as habitat and biotic features; they are a major consideration in stream habitat restoration and instream flow assessments. Models of widths and depths are often used to assess climate change vulnerability, develop endangered species recovery plans, and model water quality. However, development and application of such models require specific skillsets and resources. To facilitate acquisition of such estimates, we created a dataset of modeled channel dimensions for perennial stream segments across the conterminous United States. We used random forest models to predict wetted width, thalweg depth, bankfull width, and bankfull depth from several thousand field measurements of the National Rivers and Streams Assessment. Observed channel widths varied from <5 to >2000 m and depths varied from <2 to >125 m. Metrics of watershed area, runoff, slope, land use, and more were used as model predictors. The models had high pseudo R² values (0.70–0.91) and median absolute errors within ±6% to ±21% of the interquartile range of measured values across 10 stream orders. Predicted channel dimensions can be joined to 1.1 million stream segments of the 1:100 K resolution National Hydrography Dataset Plus (version 2.1). These predictions, combined with a rapidly growing body of nationally available data, will further enhance our ability to study and protect aquatic resources.     

A national critical loads framework for atmospheric deposition effects assessment: I. Method summary

The United States Environmental Protection Agency (EPA), with the assistance of the US Department of Energy (DOE) and the National Oceanographic and Atmospheric Administration (NOAA) is examining the utility of a critical loads approach for evaluating atmospheric pollutant effects on sensitive ecosystems. A critical load has been defined as, “a quantitative estimate of an exposure to one or more pollutants below which significant harmful effects on specified sensitive elements of the environment do not occur according to present knowledge.” Working in cooperation with the United Nations Economic Community for Europe’s (UN-ECE) Long Range Transboundary Air Pollution (LRTAP) Convention, the EPA has developed a flexible, six-step approach for setting critical loads for a range of ecosystem types. The framework is based on regional population characteristics of the ecosystem(s) of concern. The six steps of the approach are: (1) selection of ecosystem components, indicators, and characterization of the resource; (2) definition of functional subregions; (3) characterization of deposition within each of the subregions; (4) definition of an assessment end point; (5) selection and application of models; and (6) mapping projected ecosystem responses. The approach allows for variable ecosystem characteristics and data availability. Specific recognition of data and model uncertainties is an integral part of the process, and the use of multiple models to obtain ranges of critical loads estimates for each ecosystem component in a region is encouraged. Through this intercomparison process uncertainties in critical loads projections can be estimated. The research described in this article has been funded by the US Environmental Protection Agency. This document has been prepared at the EPA Environmental Research Laboratory in Corvallis, Oregon, through contract #68-C8-0006 with Man Tech Environmental Technology, Inc. It has been subjected to the agency’s peer and administrative review and approved for publication. Mention of trade names or commercial products does not constitute endorse ment or recommendation for use.     

Effects of initial solute distribution on contaminant availability, desorption modeling, and subsurface remediation

Low permeability regions in which solute movement is governed by diffusion reduce the availability of pollutants for remediation and can function as long-term sources of groundwater contamination. The inherent difficulty in understanding mass transfer from these regions of sequestered contamination is further complicated by unknown solute distributions within the low-permeability regions (sequestering regions). When models are calibrated to reproduce temporal histories of solute release from a sequestering region (desorption), the fitted parameter values are used to infer the physical or chemical characteristics of the media; however, the calibrated parameters also reflect the case-specific initial conditions (i.e., the solute distribution within the sequestering region domain at the onset of desorption). This phenomenon is demonstrated using model simulations of solute diffusion from hypothetical solids with characteristics similar to those of the well studied Borden, Ontario aquifer system. Solute release from the solids is simulated using a batch diffusion model under different initial solute distributions within the solids. The results of these model simulations are used to calibrate parameters of a multiple first-order rate desorption model (MRM) to illustrate how the fitted MRM parameters increase or decrease depending on the initial "aging" of the solids. Further numerical simulations are conducted for a one-dimensional flow system under steady-state and variable-rate hydraulic flushing. These simulations show that although aging reduces desorptive mass flux during early stages of flushing, aged sites have greater desorptive mass flux (greater solute availability) than "freshly" contaminated media during the later stages of remediation. Overall, the results demonstrate why the physicochemical meaning of observed desorption rates cannot be accurately deduced without first understanding the initial solute distribution within the media.     

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.