APPROACHES TO MULTIVARIATE MODELING OF WATER RESOURCES TIME SERIES1

ABSTRACT: Alternative approaches suggested for modeling multiseries of water resources systems are reviewed and compared. Most approaches fall within the general framework of multivariate ARMA models. Formal modeling procedures suggest a three-stage iterative process, namely: model identification, parameter estimation and diagnostic checks. Although a number of statistical tools are already available to follow such modeling process, in general, it is not an easy task, especially if high order vector ARMA models are used. However, simpler ARMA models such as the contemporaneous and the transfer-function models may be sufficient for most applications in water resources. Two examples of modeling bivariate and trivariate streamflow series are included. Alternative modeling procedures are used and compared by using data generation techniques. The results obtained suggest that low order models, as well as contemporaneous ARMA models, reproduce quite well the main statistical characteristics of the time series analyzed. It is assumed that the same conclusions apply for most water resources time series.     

TREND ASSESSMENT OF WATER QUALITY TIME SERIES1

ABSTRACT A general methodology is described for identifying and statistically modeling trends which may be contained in a water quality time series. A range of useful exploratory data analysis tools are suggested for discovering important patterns and statistical characteristics of the data such as trends caused by external interventions. To estimate the entries in an evenly spaced time series when data are available at irregular time intervals, a new procedure based upon seasonal adjustment is described. Intervention analysis is employed at the confirmatory data analysis stage to rigorously model changes in the mean levels of a series which are identified using exploratory data analysis techniques. Furthermore, intervention analysis can be utilized for estimating missing observations when they are not too numerous. The effects of cutting down a forest upon various water quality variables and also the consequences of acid rain upon the alkalinity in a stream provide illustrative applications which demonstrate the effectiveness of the methodology.     

Predicting River Floodplain and Lateral Channel Migration for Salmon Habitat Conservation1

Abstract: In this article, we describe a method for predicting floodplain locations and potential lateral channel migration across 82,900 km (491 km² by bankfull area) of streams in the Columbia River basin. Predictions are based on channel confinement, channel slope, bankfull width, and bankfull depth derived from digital elevation and precipitation data. Half of the 367 km² (47,900 km by length) of low‐gradient channels (≤ 4% channel slope) were classified as floodplain channels with a high likelihood of lateral channel migration (182 km², 50%). Classification agreement between modeled and field‐measured floodplain confinement was 85% (κ = 0.46, p < 0.001) with the largest source of error being the misclassification of unconfined channels as confined (55% omission error). Classification agreement between predicted channel migration and lateral migration determined from aerial photographs was 76% (κ = 0.53, p < 0.001) with the largest source of error being the misclassification of laterally migrating channels as non‐migrating (35% omission error). On average, more salmon populations were associated with laterally migrating channels and floodplains than with confined or nonmigrating channels. These data are useful for many river basin planning applications, including identification of land use impacts to floodplain habitats and locations with restoration potential for listed salmonids or other species of concern.     

Hydrologic Model Framework for Water Resources Planning in the Santa Cruz River,Southern Arizona1

Abstract: The authors develop a model framework that includes a set of hydrologic modules as a water resources management and planning tool for the upper Santa Cruz River near the Mexican border, Southern Arizona. The modules consist of: (1) stochastic generation of hourly precipitation scenarios that maintain the characteristics and variability of a 45‐year hourly precipitation record from a nearby rain gauge; (2) conceptual transformation of generated precipitation into daily streamflow using varied infiltration rates and estimates of the basin antecedent moisture conditions; and (3) surface‐water to ground‐water interaction for four downstream microbasins that accounts for alluvial ground‐water recharge, and ET and pumping losses. To maintain the large inter‐annual variability of streamflow as prevails in Southern Arizona, the model framework is constructed to produce three types of seasonal winter and summer categories of streamflow (i.e., wet, medium, or dry). Long‐term (i.e., 100 years) realizations (ensembles) are generated by the above described model framework that reflects two different regimes of inter annual variability. The first regime is that of the historic streamflow gauge record. The second regime is that of the tree ring reconstructed precipitation, which was derived for the study location. Generated flow ensembles for these two regimes are used to evaluate the risk that the regional four ground‐water microbasins decline below a preset storage threshold under different operational water utilization scenarios.     

Estimating the Relative Efficiency of Brazilian Publicly and Privately Owned Water Utilities: A Stochastic Cost Frontier Approach1

Abstract: This paper assesses cost efficiencies of Brazilian public and private companies of water supply. To measure the efficiency, we used a stochastic frontier model derived from the translog family – a specification similar to a Cobb‐Douglas including a quadratic term in log output. The model parameters are estimated by maximum likelihood using Brazilian data for the year 2002. Statistical inference leads to the conclusion that there is no evidence that private firms and public firms are significantly different in terms of efficiency measurements.     

Enhancing Hyrdological Simulation Program – FORTRAN Model Channel Hydraulic Representation1

Abstract: The hydrological simulation program – FORTRAN (HSPF) is a comprehensive watershed model that employs depth‐area‐volume‐flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross‐sections and reservoirs. An accurate FTABLE determination for a stream cross‐section site requires an accurate determination of mean flow depth, mean flow width, roughness coefficient, longitudinal bed slope, and length of stream reach. A method that uses regional regression equations to estimate mean flow depth, mean flow width, and roughness coefficient is presented herein. FTABLES generated by the proposed method (Alternative Method) and FTABLES generated by Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) were compared. As a result, the Alternative Method was judged to be an enhancement over the BASINS method. First, the Alternative Method employs a spatially variable roughness coefficient, whereas BASINS employs an arbitrarily selected spatially uniform roughness coefficient. Second, the Alternative Method uses mean flow width and mean flow depth estimated from regional regression equations whereas BASINS uses mean flow width and depth extracted from the National Hydrography Dataset (NHD). Third, the Alternative Method offers an option to use separate roughness coefficients for the in‐channel and floodplain sections of compound channels. Fourth, the Alternative Method has higher resolution in the sense that area, volume, and flow data are calculated at smaller depth intervals than the BASINS method. To test whether the Alternative Method enhances channel hydraulic representation over the BASINS method, comparisons of observed and simulated streamflow, flow velocity, and suspended sediment were made for four test watersheds. These comparisons revealed that the method used to estimate the FTABLE has little influence on hydrologic calibration, but greatly influences hydraulic and suspended sediment calibration. The hydrologic calibration results showed that observed versus simulated daily streamflow comparisons had Nash‐Sutcliffe efficiencies ranging from 0.50 to 0.61 and monthly comparisons had efficiencies ranging from 0.61 to 0.84. Comparisons of observed and simulated suspended sediments concentrations had model efficiencies ranging from 0.48 to 0.56 for the daily, and 0.28 to 0.70 for the monthly comparisons. The overall results of the hydrological, hydraulic, and suspended sediment concentration comparisons show that the Alternative Method yielded a relatively more accurate FTABLE than the BASINS method. This study concludes that hydraulic calibration enhances suspended sediment simulation performance, but even greater improvement in suspended sediment calibration can be achieved when hydrological simulation performance is improved. Any improvements in hydrological simulation performance are subject to improvements in the temporal and spatial representation of the precipitation data.     

CUMULATIVE EFFECTIVE STREAM POWER AND BANK EROSION ON THE SACRAMENTO RIVER,CALIFORNIA, USA1

ABSTRACT: Bank erosion along a river channel determines the pattern of channel migration. Lateral channel migration in large alluvial rivers creates new floodplain land that is essential for riparian vegetation to get established. Migration also erodes existing riparian, agricultural, and urban lands, sometimes damaging human infrastructure (e.g., scouring bridge foundations and endangering pumping facilities) in the process. Understanding what controls the rate of bank erosion and associated point bar deposition is necessary to manage large alluvial rivers effectively. In this study, bank erosion was proportionally related to the magnitude of stream power. Linear regressions were used to correlate the cumulative stream power, above a lower flow threshold, with rates of bank erosion at 13 sites on the middle Sacramento River in California. Two forms of data were used: aerial photography and field data. Each analysis showed that bank erosion and cumulative effective stream power were significantly correlated and that a lower flow threshold improves the statistical relationship in this system. These correlations demonstrate that land managers and others can relate rates of bank erosion to the daily flow rates of a river. Such relationships can provide information concerning ecological restoration of floodplains related to channel migration rates as well as planning that requires knowledge of the relationship between flow rates and bank erosion rates.     

MODELING THE LONG TERM IMPACTS OF USING RIGID STRUCTURES IN STREAM CHANNEL RESTORATION1

Abstract: Natural channel designs often incorporate rigid instream structures to protect channel banks, provide grade control, promote flow deflection, or otherwise improve channel stability. The long term impact of rigid structures on natural stream processes is relatively unknown. The objective of this study was to use long term alluvial channel modeling to evaluate the effect of rigid structures on channel processes and assess current and future stream channel stability. The study was conducted on Oliver Run, a small stream in Pennsylvania relocated due to highway construction. Field data were collected for one year along the 107 m reach to characterize the stream and provide model input, calibration, and verification data. FLUVIAL-12 was used to evaluate the long term impacts of rigid structures on natural channel adjustment, overall channel stability, and changing form and processes. Based on a consideration of model limitations and results, it was concluded that the presence of rigid structures reduced channel width-to-depth ratios, minimized bed elevation changes due to long term aggradation and degradation, limited lateral channel migration, and increased the mean bed material particle size throughout the reach. Results also showed how alluvial channel modeling can be used to improve the stream restoration design effort.     

Wet bench reactive hazards of cleaning stages in semiconductor manufacturing processes

According to the research from FM Global (Factory Mutual Insurance Company), most of the incidents that have occurred in semiconductor plants in the past two decades were reported as “Fire Cases”. They claim that the fires in wet chemical cleaning processes were mainly caused by heater failure. However, depending on the process conditions, electrical heaters are designed to turn off automatically when the temperature reaches a set point. Therefore, a thorough study of the situations related to possible fires in wet chemical cleaning processes is necessary.

This study focused on the incompatible behaviors of cleaning materials used in the wet bench stage. These results can be applied to determine the causes of fires in the wet bench stage from using reactive chemicals for cleaning purposes.

Another purpose of this study was to investigate the potential hazards of widely used chemicals (hydrogen peroxide, concentrated sulfuric acid, hydrochloric acid and isopropyl alcohol) within similar processes in semiconductor plants. Experimental data were also verified in order to establish a concentration triangular diagram, which could be used to identify a combustion, deflagration or even detonation zone. Finally, this study can provide basic design data for an inherently safer process to avoid potential hazards caused by dangerous mixtures, which may result in large property loss in semiconductor plants.     

Monitoring Ecosystems in the Sierra Nevada: The Conceptual Model Foundation

Monitoring at large geographic scales requires a framework for understanding relationships between components and processes of an ecosystem and the human activities that affect them. We created a conceptual model that is centered on ecosystem processes, considers humans as part of ecosystems, and serves as a framework for selecting attributes for monitoring ecosystems in the Sierra Nevada. The model has three levels: 1) an ecosystem model that identifies five spheres (Atmosphere, Biosphere, Hydrosphere, Lithosphere, Sociocultural), 2) sphere models that identify key ecosystem processes (e.g., photosynthesis), and 3) key process models that identify the "essential elements"that are required for the process to operate (e.g., solar radiation), the human activities ("affectors") that have negative and positive effects on the elements (e.g., air pollution), and the "consequences"of affectors acting on essential elements (e.g., change in primary productivity). We discuss use of the model to select attributes that best reflect the operation and integrity of the ecosystem processes. Model details can be viewed on the web at http://www.r5.fs.fed.us/sncf/spam_report/index.htm(Appendix section).