Estimation of water quality profiles in deep lakes based on easily measurable constituents at the water surface using artificial neural networks coupled with stationary wavelet transform.

This study proposes a novel framework to accurately estimate water quality profiles in deep lakes based on parameters measured at the water surface, considering Boulder Basin of Lake Mead as a case study. Hourly-measured meteorological data were used to compute heat exchange between lake and atmosphere. Heat fluxes combined with every 6-hour measured water temperature, conductivity, and dissolved oxygen (DO) profiles, from the water surface to a depth of 100 m over a 48-month period, were used to train seven different artificial neural network-based methods for estimating water quality profiles.

Nonlinear programming technique for analyzing flocculent settling data.

The traditional graphical approach for drawing iso-concentration curves to analyze flocculent settling data and design sedimentation basins poses difficulties for computer-based design methods. Thus, researchers have developed empirical approaches to analyze settling data. In this study, the ability of five empirical approaches to fit flocculent settling test data is compared.

Needs-based sewerage prioritization: alternative to conventional cost-benefit analysis.

This paper presents an empirical approach to select and prioritize sewerage projects within set budgetary limitations. The methodology includes a model which quantifies benefits of a sewerage project as an index or dimensionless number. The index considers need and urgency of sewerage and other project goals.

Pressure-assisted ozonation of PCB and PAH contaminated sediments.

Sediment contamination by recalcitrant organics such as polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs) is prevalent and of a great concern. Remediation efforts are hampered by the hydrophobic nature of the contaminants that limits their availability as well as by the sediment matrix that limits their exposure to treatment agents. Using contaminated sediment samples from the Passaic River, St.

Simulation of resuspended sediments resulting from dredging operations by a numerical flocculent transport model.

Environmental remediations such as dredging operations cause contaminated sediments from the bottom of water bodies to become suspended into the water column. These resuspended particles are significant water quality concerns and cause adverse effects to aquatic organisms. In this paper, we present a vertically integrated two-dimensional flocculent sediment transport model to better model concentration changes of resuspended bottom sediments.

Development of a two-dimensional analytical model for predicting toxic sediment plumes due to environmental dredging operations.

A two-dimensional analytical transport model is developed to predict the dredge induced plume concentration in the horizontal plane under steady-state for simple hydraulic conditions. The derivation of the analytical solution is based on the solution to the advection-diffusion equation. The application of this analytical model is limited to mechanical dredge operations, bucket dredge, which has continuous point source in the water column.