EFFICIENCY OF HYDROLOGIC DATA COLLECTION SYSTEMS ROLE OF TYPE I AND II ERRORS1

ABSTRACT The efficiency of hydrologic data collection systems is relevant to solution of environmental problems, scientific understanding of hydrologic processes, model-building and management of water resources. Because these goals may be overlapping and non-commensurate, design of data networks is not simple. Identified are four elements of error or risk in such networks: (a) choice of variables and mathematical model for the same process, (b) accuracy of model parameter estimates, (c) acceptance of wrong hypothesis or rejection of correct hypothesis and (d) economic losses associated with error. Of these four, the classical hypothesis testing problem is specifically evaluated in terms of costs of type I and II errors for simple and composite hypotheses; mathematical models for these economic analyses also include costs of sample data and costs of waiting while new data is obtained. An illustrative computational example focuses on the hypothesis that natural recharge might be augmented by a system of pumping wells along an ephemeral channel. The relationship of the hypothesis testing problem to Bayesian decision theory is discussed; it is felt that the latter theory offers a more comprehensive framework for design and use of hydrologic data networks.     

Limitations of applying life cycle assessment to complex co-product systems: The case of an integrated precious metals smelter-refinery

Integrated smelter-refineries play an important role in the recovery of multiple metals from complex primary and secondary materials, and hence in closing metals cycles. Processes in these facilities are strongly interconnected, dynamic, and multifunctional, which challenges a typical representation in life cycle assessment (LCA). This is especially true when LCA is applied to calculate the environmental profile of single metals products.This study examines methodological requirements for assessing complex co-product systems using attributional LCA through a static, gate-to-gate inventory model that quantifies the environmental impacts of each of the metal products of an integrated precious metals smelter-refinery. The model is based on a large number of subprocesses and is formulated using detailed industry data, which allows quantification of the sensitivity of the results with respect to allocation rationales and the data collection period.The results within one impact category vary strongly among metals (up to four orders of magnitude for copper compared to rhodium). Moving from mass- to value-based allocation changes the result for a given metal by up to two orders of magnitude. If value-based allocation is used, the selected reference year for metals prices influences the results by up to a factor of two.Allocation rationales are critically analyzed, and it is shown that none reflect the business model or other system drivers. While the model is focused on quantifying environmental impacts of metal outputs, the actual process is economically driven to efficiently treat a continuously changing feed mix. The complexity of a smelter-refinery cannot be captured by static, attributional inventory models, which is why the choice of allocation rationale remains arbitrary. Instead, marginal, parameterized models are needed; however, such models are substantially more time and data intensive and require disclosure of more detailed, process specific data.     

MULTIRESERVOIR ANALYSIS TECHNIQUES IN WATER QUANTITY STUDIES1

ABSTRACT. This paper deals with the subject of applying different types of systems analysis tools to water quantity studies of multireservoir networks of increasing degrees of complexity. The object is to show how each tool can be used, modified and combined with other tools to solve specific problems and to indicate the degrees of complexity at which more sophisticated tools should be applied. Firstly, several applications and limitations of linear programming and dynamic programming are discussed. Secondly, it is shown that mass curve analysis is useful, can be extended to serve in computing reservoir rules for conventional multireservoir simulation models, and can be applied in conjunction with either historic or generated sequences of hydrologic input data. Thirdly, extended and limiting features of conventional time-interval-by-time-interval multireservoir simulation models are analyzed. And fourthly, a two-model series for problems which defy analysis by more basic tools is described in detail, the first model using network analysis (Out-of-Kilter Algorithm) for all space and time arcs simultaneously and providing data for the second general-purpose model using network analysis each time interval. The importance of efficient computer procedures is stressed. The background for the paper includes systems analysis of water availability and hydro-thermal power studies carried out during the past six years in that part of Canada lying between the Great Lakes and the Rocky Mountain Divide.     

SENSITWITY ANALYSIS OF SIMULATED CONTAMINATED SEDIMENT TRANSPORT1

ABSTRACT: A simulation analysis of contaminated sediment transport involves model selection, data collection, model calibration and verification, and evaluation of uncertainty in the results. Sensitivity analyses provide information to address these issues at several stages of the investigation. A sensitivity analysis of simulated contaminated sediment transport is used to identify the most sensitive output variables and the parameters most responsible for the output variable sensitivity. The output variables included are streamflow and the flux of sediment and Cs¹³⁷. The sensitivities of these variables are measured at the field and intermediate scales, for flood and normal flow conditions, using the HSPF computer model. A sensitivity index was used to summarize and compare the results of a large number of output variables and parameters. An extensive database was developed to calibrate the model and conduct the sensitivity analysis on a 6.2 mi² catchment in eastern Tennessee. The fluxes of sediment and Cs¹³⁷ were more sensitive than streamflow to changes in parameters for both flood and normal flow conditions. The relative significance of specific parameters on output variable sensitivity varied according to the type of flow condition and the location in the catchment. An implications section illustrates how sensitivity analysis results can help with model selection, planning data collection, calibration, and uncertainty analysis.     

TIME SERIES ANALYSIS IN PERSPECTIVE1

ABSTRACT: By employing a set of criteria for classifying the capabilities of time series models, recent developments in time series analysis are assessed and put into proper perspective. In particular, the inherent attributes of a wide variety of time series models and modeling procedures presented by the authors of the 18 papers contained in this volume are clearly pointed out. Additionally, it is explained how these models can address many of the time series problems encountered when modeling hydrologic, water quality and other kinds of time series. For instance, families of time series models are now available for modeling series which may contain nonlinearities or may follow nonGaussian distributions. Based upon a sound physical understanding of a problem and results from exploratory data analyses, the most appropriate model to fit to a data set can be found during confirmatory data analyses by following the identification, estimation and diagnostic check stages of model construction. Promising future research projects for developing flexible classes of time series models for use in water resources applications are suggested.     

PREDICTION OF LOCAL SCOUR AROUND BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS1

This paper describes a method for predicting local scour around bridge piers using an artificial neural network (ANN). Methods for selecting input variables, calibrations of network control parameters, learning process, and verifications are also discussed. The ANN model trained by laboratory data is applied to both laboratory and field measurements. The results illustrate that the ANN model can be used to predict local scour in the laboratories and in the field better than other empirical relationships that are currently in use. A parameter study is also carried out to investigate the importance of each input variable as reflected in data.     

Predicting Debris Yield From Burned Watersheds: Comparison of Statistical and Artificial Neural Network Models1

Abstract: Alluvial fans in southern California are continuously being developed for residential, industrial, commercial, and agricultural purposes. Development and alteration of alluvial fans often require consideration of mud and debris flows from burned mountain watersheds. Accurate prediction of sediment (hyper‐concentrated sediment or debris) yield is essential for the design, operation, and maintenance of debris basins to safeguard properly the general population. This paper presents results based on a statistical model and Artificial Neural Network (ANN) models. The models predict sediment yield caused by storms following wildfire events in burned mountainous watersheds. Both sediment yield prediction models have been developed for use in relatively small watersheds (50‐800 ha) in the greater Los Angeles area. The statistical model was developed using multiple regression analysis on sediment yield data collected from 1938 to 1983. Following the multiple regression analysis, a method for multi‐sequence sediment yield prediction under burned watershed conditions was developed. The statistical model was then calibrated based on 17 years of sediment yield, fire, and precipitation data collected between 1984 and 2000. The present study also evaluated ANN models created to predict the sediment yields. The training of the ANN models utilized single storm event data generated for the 17‐year period between 1984 and 2000 as the training input data. Training patterns and neural network architectures were varied to further study the ANN performance. Results from these models were compared with the available field data obtained from several debris basins within Los Angeles County. Both predictive models were then applied for hind‐casting the sediment prediction of several post 2000 events. Both the statistical and ANN models yield remarkably consistent results when compared with the measured field data. The results show that these models are very useful tools for predicting sediment yield sequences. The results can be used for scheduling cleanout operation of debris basins. It can be of great help in the planning of emergency response for burned areas to minimize the damage to properties and lives.     

Influence of environmental street characteristics on walking route choice of elderly people

Walking is an important source of outdoor physical activity among elderly people. In order to devise measures aimed at encouraging walking among the elderly it is important to understand how the local environment influences the walking behaviour of elderly people. Here, a model describing the influence of environmental street characteristics on the walking route choice of elderly people is presented. Techniques adapted from the field of transportation research were employed within the model. Data concerning the walking route choice to specific destinations reported by 364 independently living elderly residents (55–80 years) from three Dutch urban districts were collected. Route choice was modelled within a ‘Geographic Information System’ (GIS) database by using ‘resistance factors’ to describe the resistance to walking of street sections (i.e. links) within the street network. These factors were optimized by minimizing the difference between the estimated and the reported number of trips along each link. This is, to the authors' knowledge the first time that this technique has been applied within this context. The influence of link characteristics on link resistance was investigated by multivariate linear regression. The first results of the route choice model and the influence of street characteristics on route choice are reported and discussed.     

PROCESS-ORIENTED ESTIMATION OF SUSPENDED SEDIMENT CONCENTRATION1

ABSTRACT: Least squares regression and ARIMA models were developed from suspended sediment data for the Ausable River, Southern Ontario, Canada. A poor correlation between discharge and suspended sediment concentration results from the dynamics of the physical system, including seasonality, antecedent conditions, and hysteresis. Regression model results were significantly improved by the division of the data set into seasons and the addition of simple. but physically meaningful variables. Misleading improvements obtained from the regression of sediment load and discharge are discussed. ARIMA models provided accurate forecasts of sediment concentration on a real-time basis, but the rigorous data requirements limit their use in modeling suspended sediment concentrations in Canadian rivers.     

MASS BALANCE MODEL ESTIMATION OF PHOSPHORUS CONCENTRATIONS IN RESERVOIRS1

ABSTRACT: Mass balance models have been common tools in lake quality management for some years. However, verification for use on reservoirs, especially in the Western United States, has been seriously lacking, In this study, such a verification is attempted using data from the U.S EPA National Eutrophication Survey. Several models from the literature are compared for accuracy in application to the western reservoir data. Model standard error and correlation between estimated and observed reservoir phosphorus concentrations are the Criteria used for comparison. Standard errors am further used to calculate uncertainty of trophic state classification based on estimated phosphorus concentration. The model proposed by Dillon and Rigler (1974) proved most accurate, with a correlation coefficient of 0.86 and standard error of 0.2, based on logarithmic transformed values. Deficiencies in the other models appear to & from coefficients fit to lake data and from inappropriate model formulation.     

Sustainable consumption profile differences among Brazilian regions

Brazil is a vast country and there are several scientific studies reporting sustainable behavior in its different regions. Since methodologies used in these studies differ from one another, it is hard to compare them. This paper aims to identify whether differences in sustainable behavior occur in different Brazilian regions and what differences can be identified. Through a web survey, we analyzed data from 1,489 participants, from four different regions. We identified two factors (behavior and search for information), and analyzed the differences through multivariate analysis of variance. The Northeast region had a higher score for “search for information”, while Southern regions performed better on “behavior.” The Midwest region had the worst performance for both factors. The reasons for such differences may be greatly influenced by the social/cultural context of each region. The results also show that consumers still do not use their power of choice to pressure companies to become more sustainable.     

TREATING WATER INSTITUTIONS AS ENDOGENOUS VARIABLES: DEMONSTRATION OF A CONCEPTUAL MODEL1

ABSTRACT: Institutional innovation is central to many water resource problems. (In this context “institutions” refers to the laws and regulations governing water allocation and use.) Yet, typically, economic analyses treat institutions as exogenous and fixed. Unfortunately, this conventional assumption does not allow economists to address many modern problems. This paper develops an economic framework in which institutions are treated as endogenous. The model accounts for (1) factors that stimulate calls for formal institutional change, (2) the role of interest groups in policymaking, and (3) actual institutional change as it impacts choice domains and thus economic performance. The model is compared to a specific case of change in Colorado's water institutions, namely, instream water rights legislation in the 1970's. The empirical evidence is generally consistent with model hypotheses. The model promises to be useful to scholars and policymakers interested in institutional innovation.     

Comparative Evaluation of Three River Water Quality Models1

Abstract: Selection of a biochemical oxygen demand (BOD) reaction model to incorporate into dissolved oxygen (DO) water quality models is an overlooked choice available to river water quality modelers. Data from rivers can serve in screening methods to discriminate between competing water quality models. In this study, 15 published BOD and DO datasets based on a 7 year long study of the Bormida River in Italy are used to calibrate three‐multiorder BOD models: first‐order, three‐halves order, and second‐order, which are then included in three corresponding DO models which incorporate these BOD models. The adequacy of the first‐order, three‐halves order and second‐order BOD models was evaluated by calculating the root mean square error between a model and data. A similar procedure was followed to evaluate three DO models, each of which incorporated one of the three BOD models. The first‐order BOD model most frequently fit the river data best, followed by the three‐halves order and the second‐order BOD models. The DO model incorporating a first‐order BOD model most frequently fit the data best, followed by the DO order incorporating second‐order BOD and the DO model incorporating three‐halves order BOD.     

Comparison of Morphodynamic Models for the Lower Yellow River1

Xia, Junqiang, Zhengbing Wang, Yanping Wang, and Xin Yu, 2012. Comparison of Morphodynamic Models for the Lower Yellow River. Journal of the American Water Resources Association (JAWRA) 1‐18. DOI: 10.1111/jawr.12002 Abstract: Significant channel adjustments often occur during flood seasons in the Lower Yellow River (LYR), and it is a challenging work to accurately simulate the morphodynamic processes in the LYR using numerical models. A comparison of two morphodynamic models (Delft3D and 2DLLCDM) for the LYR is presented herein to identify critical improvements for these models. The concepts of these models are first compared with each other. The models were then used to simulate the processes of flood routing, sediment transport, and morphological changes occurring in a braided reach of the LYR. The differences were investigated between the simulated results from these models and corresponding field measurements, and the results indicate that: (1) the hydrodynamic processes calculated by both models agree closely with the measurements if an appropriate Manning’s roughness coefficient is used; (2) the concentrations of suspended load at the downstream boundary calculated by the models agree reasonably with the observed data; and (3) the predicted cross‐sectional profiles obtained from these models do not correspond well with the measurements. Based on these findings, the weak aspects of the models are clarified, and three critical improvements are recommended, including: (1) the development of roughness predictor; (2) the refinement of graded sediment transport capacity formulation; and (3) the consideration of bank erosion module. These improvements need to be implemented in the future.     

SPATIALLY EXPLICIT HYDROLOGIC MODELING OF LAND USE CHANGE1

ABSTRACT: Using a Geographic Information System (GIS), a method is presented to develop a spatially explicit time series of land use in an urbanizing watershed. The method is prefaced on the existence of independent observations of land use at different times and data that describes the spatial‐temporal land use transition characteristics of the watershed between these two points in time. A method is then presented to generalize the TR‐55 graphical method, a common lumped hydrologic model for estimating peak discharge, for use in a spatially explicit scheme. This scheme predicts peak discharge throughout a watershed, rather than at a single selected watershed outlet. Coupling these two methods allows the engineer to model both the temporal and spatial evolution of peak discharge for the watershed. An illustrative watershed in a suburban area of Washington, DC is selected to demonstrate the methods. The model results from these analyses are presented graphically to highlight the complex features in peak discharge behavior that exist both spatially, as a function of position within the watershed drainage network, and temporally, as the watershed undergoes urbanization. These features are not commonly noted in most hydrologic analyses but are captured in these analyses because of the high spatial and temporal resolution of the methods presented. The physical implications of the modeled results are discussed in the context of the information content of a stream gauge located at the overall outlet of the illustrative watershed. This work shows that the common practice of transposition of gauge information to locations internal to the watershed would neglect internal variability in peak discharge behavior, and could potentially lead to the determination of inappropriate design discharges.     

滇池沉积物重金属污染状况评估

本文通过多年滇池底泥的采样监测数据,采用地积累指数法和对数衰减模型评估滇池的底泥质量状况,希望摸清底泥中重金属污染状况,并分析评价其对水生生物的风险,为底泥疏浚、截污护岸的滇池治理工程提供一定的科学依据。研究表明:以地积累指数法评价,(1)滇池监测断面底泥质量呈现轻度污染,镉出现一定程度富集,汞在个别监测断面也出现富集情况;(2)6种重金属污染排序为镉>汞>铅>铜>铬>砷;(3)从监测断面来看,海口西污染程度较重,滇池南底泥质量较好。采用对数衰减模型评价,(1)滇池监测断面沉积物重金属污染存在潜在生物风险,应引起重视;(2)从产生可以观察到毒性效果的可能性大小看,6种重金属潜在危害可能性排序为砷>铅>铜>铬>镉>汞;(3)从监测断面来看,白鱼口和观音山中潜在危害可能性大。从富集污染程度分析,海口西监测断面的底泥污染最重,可考虑在海口西监测断面附近进行一定的底泥疏浚工程。从而达到治标治本的目的。滇池监测断面沉积物重金属污染存在潜在生物风险,应引起重视,但在可控范围。     

Estimating the benefits and costs to mountain bikers of changes in trail characteristics,access fees,and site closures: choice experiments and benefits transfer

Mountain biking is an increasingly popular leisure pursuit. Consequences are trail degradation and conflicts with hikers and other users. Resource managers often attempt to resolve these problems by closing trails to mountain biking. In order to estimate the impact of these developments, a model has been devised that predicts the effects of changes in trail characteristics and introduction of access fees, and correlates these with biker preference on trail selection. It estimates each individual's per-ride consumer's surplus associated with implementing different policies. The surplus varies significantly as a function of each individual's gender, budget, and interest in mountain biking. Estimation uses stated preference data, specifically choice experiments. Hypothetical mountain bike trails were created and each surveyed biker was asked to make five pair-wise choices. A benefit-transfer simulation is used to show how the model and parameter estimates can be transferred to estimate the benefits and costs to mountain bikers in a specific area.     

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.     

Valuing river characteristics using combined site choice and participation travel cost models

This paper presents new welfare measures for marginal changes in river quality in selected English rivers. The river quality indicators used include chemical, biological and habitat-level attributes. Economic values for recreational use of three types of river-upland, lowland and chalk-are presented. A survey of anglers was carried out and using these data, two travel cost models were estimated, one to predict the numbers of trips and the other to predict angling site choice. These models were then linked to estimate the welfare associated with marginal changes in river quality using the participation levels as estimated in the trip prediction model. The model results showed that higher flow rates, biological quality and nutrient pollution levels affect site choice and influence the likelihood of a fishing trip. Consumer surplus values per trip for a 10% change in river attributes range from pound 0.04 to pound 3.93 ( pound 2001) depending on the attribute.     

Superfund,Hedonics, and the Scales of Environmental Justice

Environmental justice (EJ) is prominent in environmental policy, yet EJ research is plagued by debates over methodological procedures. A well-established economic approach, the hedonic price method, can offer guidance on one contentious aspect of EJ research: the choice of the spatial unit of analysis. Environmental managers charged with preventing or remedying inequities grapple with these framing problems. This article reviews the theoretical and empirical literature on unit choice in EJ, as well as research employing hedonic pricing to assess the spatial extent of hazardous waste site impacts. The insights from hedonics are demonstrated in a series of EJ analyses for a national inventory of Superfund sites. First, as evidence of injustice exhibits substantial sensitivity to the choice of spatial unit, hedonics suggests some units conform better to Superfund impacts than others. Second, hedonic estimates for a particular site can inform the design of appropriate tests of environmental inequity for that site. Implications for policymakers and practitioners of EJ analyses are discussed.