Quantifying sediment-associated metal dispersal using Pb isotopes: Application of binary and multivariate mixing models at the catchment-scale

In this study Pb isotope signatures were used to identify the provenance of contaminant metals and establish patterns of downstream sediment dispersal within the River Maritsa catchment, which is impacted by the mining of polymetallic ores. A two-fold modelling approach was undertaken to quantify sediment-associated metal delivery to the Maritsa catchment; employing binary mixing models in tributary systems and a composite fingerprinting and mixing model approach in the wider Maritsa catchment. Composite fingerprints were determined using Pb isotopic and multi-element geochemical data to characterize sediments delivered from tributary catchments. Application of a mixing model allowed a quantification of the percentage contribution of tributary catchments to the sediment load of the River Maritsa. Sediment delivery from tributaries directly affected by mining activity contributes 42-63% to the sediment load of the River Maritsa, with best-fit regression relationships indicating that sediments originating from mining-affected tributaries are being dispersed over 200 km downstream.     

Risk models for wildfowl diseases

The purpose of this paper is to explore the use of computer models, including artificial intelligence systems, in the context of risk assessment and management for wildfowl diseases. In particular, the paper focuses on avian cholera and botulism in U.S. wildfowl, which are a source of continuing concern to the U.S. Fish and Wildlife Service (USFWS). Severe outbreaks occur frequently, and some have been estimated to claim the lives of as many as 300 000 waterfowl. A potentially valuable support to the USFWS would be a set of models that assist in recognizing situations with high risk of an outbreak, assessing the anticipated severity of an outbreak, and advising on possible preventive measures. The USFWS has already initiated development of several potentially useful models. This paper reviews these as well as other related efforts, within the overall context of risk management for avian botulism and cholera.     

AN EXPERIMENT IN DETERMINISTIC WATERSHED MODELING1

An experimental three-dimensional finite-difference watershed model in the form of a Fortran IV program was constructed. The model was an oversimplified one which divided the watershed volume into layers of cells which represented the overland flow, the vadose, and the phreatic zones. Water budget equations which utilized such formulas as Darcy's law and Manning's equation were applied to each interior cell. The resulting set of simultaneous equations was solved for heads at the end of successive time increments. This information was transformed to streamflow and other hydrologic output. Input was weather data, which effected appropriate adjustments in the cells representing the surface-water and vadose zones. After testing the model, it was concluded that this type of model is undesirably sensitive to cell size and length of time increment. In spite of the deficiencies of this primitive model, this general kind of approach to modeling seems promising, but it may be necessary to devise new transport equations which apply to more natural divisions of watersheds.     

EFFECT OF RAINFALL EXCESS CALCULATIONS ON MODELED HYDROGRAPH ACCURACY AND UNIT-HYDROGRAPH PARAMETERS1

ABSTRACT: Two methods of computing rainfall excess in the U.S. Army Corps of Engineers’flood hydrograph package (HEC-1), the Initial and Uniform method and the Exponential method, are compared to evaluate the effects on modeled hydrograph accuracy. Two computed unit-hydrograph parameters, time of concentration and storage coefficient, were also compared. Rainfall and runoff data from 209 storms in 32 gaged basins in Illinois were used to calibrate the HEC-1 model. Three hydrograph characteristics - sum of incremental flows, peak discharge, and time of peak discharge - were used to evaluate modeled hydrograph accuracy. Mean percent error for each basin and hydrograph characteristic was computed. An evaluation of the mean errors indicates that, although some bias in modeled hydrograph accuracy is evident, rainfall excess computed using either method results in a computed hydrograph accuracy that is within generally accepted limits. Application of a linear-regression model shows no significant differences in computed values of unit-hydrograph parameters.     

PREDICTING BASEFLOW ALKALINITY AS AN INDEX TO EPISODIC STREAM ACIDIFICATION AND FISH PRESENCE1

ABSTRACT: Regression models to predict baseflow alkalinity from basin hydrogeology were developed and verified for headwater streams on the Laurel Hill anticline in southwestern Pennsylvania. Predicted baseflow alkalinities were then used to estimate sensitivity to acidification and presence of trout (Salvelinus fontinalis) populations for 61 headwater streams. Sensitivity classifications were verified by surveying trout populations. Geologic variables relating to the carbonate rock burial depth, extent of carbonate rock recharge areas, and length of stream channel flowing through effluent carbonate rock outcrops were much more useful in predicting baseflow alkalinity than areal extent of carbonate rocks. Baseflow alkalinity was not well related to status of trout populations on these anticlinal basins, especially on noneffluent basins where bedrock dip exceeded surface slope.     

PREDICTING THE SUMMER PEAK BIOMASS OF FOUR SPECIES OF BLUE-GREEN ALGAE (CYANOPHYTA/CYANOBACTERIA) IN SWEDISH LAKES1

ABSTRACT: Stepwise multiple regression analysis was used to develop models predicting the summer peak biomass of Aphanizomenon flos-aquae, Anabaena flos-aquae, Oscillatoria agardhii, and Microcystis aeruginosa in four Swedish lakes. These analyses suggest that while epilimnetic total phosphorus concentration is the principal predictor of their peak biomass, other factors such as station mean depth, water temperature, total nitrogen, and total CO₂ concentration are also important.     

CONTEMPORANEOUS AUTOREGRESSIVE-MOVING AVERAGE (CARMA) MODELING IN WATER RESOURCES1

ABSTRACT: The Contemporaneous Autoregressive-Moving Average (CARMA) model is a simple and efficient model that can be used to fit many multivariate hydrological time series. For certain types of multistation river flow systems, the CARMA model is naturally obtained when the physical restrictions of the system or the characteristics of the data are taken in consideration during the formulation of the model. It is shown how the CARMA model can optimally be used to handle multiple time series where the number of observations in each series may be different. Adequate model building techniques, as well as computational and statistical efficient algorithms to estimate the parameters of the model, are given. The methodologies and applications of the CARMA model are illustrated with three examples. It is also shown how the full multivariate ARMA model may lead to losses in efficient of the estimators when the CARMA model is adequate.     

NUMERICAL TECHNIQUES APPLIED TO PARTICLE DEPOSITION DURING SLOT FLOW1

ABSTRACT A mathematical model is presented of the process of particle sedimentation from a fluid-solid slurry while flowing through a vertical slot. The differential equations describing the process consist of 1st order, non-linear, partial differential equation and a 1st order, ordinary differential equation. These two equations have been solved using a forward difference technique. Results for typical sets of system parameters are presented and discussed. The model finds practical application to solid-waste disposal processes and to petroleum reservoir stimulation processes.     

MODERNIZATION OF NATIONAL WEATHER SERVICE RIVER FORECASTING TECHNIQUES1

The National Weather Service is nearing the conclusion of a five year period of transition from index type catchment modelling to the use of conceptual hydrologic models. The decision to make this technological change was based on an extensive research project in which various catchment models were tested in a wide variety of basins and their strong and weak points ascertained. This project is described. Some of the problems involved in the changeover, which are discussed, are practical parameter optimization methods, computer requirements for the more complex technology, data requirements, fitting of the catchment model to major river systems, training of personnel and staffing problems.     

FLEXIBLE PRICING IN WATER SUPPLY PLANNING–FOR FLEXIBLE ENGINEERS1

ABSTRACT. Preliminary results from a digital simulation model designed to test time-varying water pricing policies are presented. Stochastic inflows feeding a water supply reservoir are assumed for a hypothetical community with defined demand functions. Prices are allowed to vary as a function of reservoir level, generally rising as reservoir levels fall. Increasing, decreasing and constant rates are tested. It is concluded that varying the price to reflect the increased value of scarce supplies can greatly reduce the risk of water supply shortages. It is also concluded that varying incremental (conservational) pricing policies not only reduces the risk of shortages, but also lowers the average price to the community while rewarding the low consumption user with lower average rates.