Project

Lower Mississippi River: water quality, time-of-travel, spill mitigation and analysis

Goal: The Lower Mississippi River (LMR) refers here to the reach of this North American river that borders or passes through the State of Louisiana. Hazardous spills and reduced water quality in the LMR impact drinking water for the City of New Orleans and other community and industrial water users, coastal wetlands, and fisheries. This project includes studies characterizing LMR water quality, measurement of LMR travel time and dispersion, and modeling travel time and concentration of spills.

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Project log

Michael Waldon
added a research item
The Mississippi River Early Warning Organic Compound Detection System (EWOCDS) was established in 1986 to warn Lower Mississippi River drinking water providers of chemical discharges which might adversely impact water quality. Nine sampling stations have been located between the cities of Baton Rouge and New Orleans, Louisiana. This reach receives pollutant discharges from more than seventy major chemical industries, refineries, and municipal treatment facilities. When elevated levels of one or more of the pollutants are found in a sample, downstream water intakes are warned, and downstream sampling is intensified. EWOCDS results are stored in a centralized database by the Louisiana Department of Environmental Quality. The objective of this paper is describe the temporal and spacial patterns observed in the information from the thousands of raw water samples which has been analyzed by the EWOCDS since 1986. Analysis of the data is assisted through the use of a geographical information system (GIS), comparison to SARA 313 toxics release inventory data, and time-of-travel and dispersion estimates provided by a computer model. Annual pollutant loads for the more commonly observed volatile organic compounds are estimated. Median and 90th percentile loads during periods of unusually low flow were used to characterize the typical load of contaminants present in the River. The entire period of record, available at the time of the study, was used to estimate loads of contaminants caused by spills or short-term upsets. It is observed that much of the pollutant load is associated with short term events of excessive concentration. Such events likely result from spills or upsets. These events can often be tracked as they pass successive network stations, and these data are generally consistent with the time-of-travel model projections.
Michael Waldon
added a research item
This presentation reviews studies by the authors aimed at developing methods for tracking spills and estimating loads and concentration of volatile organic compounds (VOCs) on the Mississippi River in Louisiana, USA. This work would not have been possible without the efforts and assistance of federal and state agencies including the Louisiana Department of Environmental Quality, US Army Corps of Engineers, and the US Geological Survey. This presentation first describes relevant Mississippi River monitoring and reporting systems. It next summarizes river studies done by the authors. Finally, based on past experience and our study results, we present conclusions and recommendations.
Michael Waldon
added a research item
The Lower Mississippi River supports essential uses including drinking water supply, fire protection, industrial cooling water and process water supply, agricultural water supply, fisheries, maintenance of plant and wildlife habitat, transportation, and recreation. Accidental or intentional spills threaten these uses. Considerable attention has been paid to modeling spills in the marine environment. In contrast, despite their sensitivity, much less effort has been focused on the development and testing of models applicable to spills in rivers. The River Time-of-Travel model (R-TOT) is a river spill management tool intended to support rapid decision making under real-time spill conditions on the Lower Mississippi River. As a real-time management tool, R-TOT requires limited data input and provides rapid projections of spill time of arrival, time of passage, and peak concentration at locations downstream of the spill origin. The current version 6 of R-TOT includes features that were suggested by users of the earlier R-TOT versions, and was programmed in Microsoft Visual Basic. R-TOT 6 inputs river-specific information from data files and is well suited for extension to other reaches and other rivers. Following presentation of the development and application of the R-TOT model, extensions of theories and methods of analysis of longitudinal dispersion will be discussed.
Michael Waldon
added a research item
R-TOT, the River Time-of-Travel Model, is a model for prediction of time of travel of a solute or entrained material. Version 6 of R-TOT was programmed in Microsoft Visual Basic, and is distributed as a “stand-alone” application which must be installed using the Windows Installation Wizard. The model provides a convenient user interface for input, provides a summary output screen, and easy user access to the data analysis and graphical capabilities available within spreadsheets like Excel. Although R-TOT may be applied to other streams, the distributed version applies to the Lower Mississippi River, USA. See the R-TOT Programmer’s Manual (Waldon and Gandikota, 1999) for information on applying the model to other streams. The model was designed to present a friendly and uncomplicated user interface, and to provide a straight-forward computational approach which is intended to minimize the programming effort required for incorporation of new study data or application to a new stream. Appendices of this manual include extensive lists of landmark locations and pipeline locations on the Lower Mississippi River.
Michael Waldon
added a research item
R-TOT, the River Time of Travel Model, predicts of time of travel of a solute or entrained material in a river. The current version of R-TOT is programmed in Microsoft Visual Basic 6.0. The model provides a convenient user interface for input and output using forms to display queries and results. The model also provides easy user access to various special features available through Visual Basic. The program has primarily been applied in modeling spills in the Lower Mississippi River. However, as described in this manual, the program may be applied to other rivers by editing the R-TOT model data files.
Michael Waldon
added 13 research items
The Early Warning Organic Compound Detection System (EWOCDS) was established over two years ago to warn Lower Mississippi River drinking water providers of chemical discharges which might adversely impact water quality. Sampling sites are located from Exxon at Rivermile 232 downstream to St. Bernard at Rivermile 87.9. Daily water samples are collected and analyzed at each site. When elevated levels of one or more of the priority chemical pollutants are found in a daily sample, additional hourly samples are collected. The results of the chemical analysis of the water samples are stored in a computer database. In general, the EWOCDS is effective, and has been successful in its primary mission of detecting excessive concentrations of its target compounds in the River. This success has resulted from the extensive efforts of numerous individuals, the support of the cooperating organizations, and the efforts and support of the Louisiana DEQ. The objective of this paper is to provide a preliminary description of the water sampling information which has been collected by the EWOCDS since 1986 at ten locations (eight on a daily basis) on the river. This study is based on data reported for over 4700 Mississippi River water samples. Compounds detected most frequently at the Exxon station (Rivermile 232, 355 mean daily samples) and downstream at New Orleans Carrollton water intake station (Rivermile 104.7, 696 mean daily samples) are shown in Table 1. Several conclusions are evident from our review of the EWOCDS data. First, on most days concentrations of compounds are well below numerical criteria generally applied to surface waters (USEPA, 1986). For every compound except trichloromethane (chloroform), concentrations of monitored compounds are below detection at every EWOCDS station in the majority of samples. Indeed, most of the mass of chemicals passing New Orleans appears to be segregated into relatively short term events of relatively high concentration. A second conclusion is that the EWOCDS has worked well in monitoring the occurrence of these events, however, because the duration of these events may be shorter than one day, the daily sampling period is inadequate to provide reliable early warning and sampling frequency should be increased. Automated river water sample collection might provide a cost effective alternative to frequent manual sample collection and analysis. Portable automated samplers might also be of value to the Louisiana DEQ in river monitoring for surveillance and enforcement.
Rhodamine WT tracer dye was injected into the Mississippi River at New Orleans (Rivermile 102.8) to determine the travel time of the leading edge, peak, and trailing edge of the dye cloud at two downstream locations, Belle Chasse (Rivermile 76.0) and Pointe a la Hache (Rivermile 49.0). The flow in the River, determined at Tarbert Landing (River Mile 306.3) was 300,000 cubic feet per second. Dispersion and duration of the dye cloud at downstream sites also were determined. Information from this study was used• to extend the existing time-of-travel prediction model (Baton Rouge to New Orleans) to include the reaches from New Orleans to Belle Chasse and Pointe a la Hache.
Michael Waldon
added a project goal
The Lower Mississippi River (LMR) refers here to the reach of this North American river that borders or passes through the State of Louisiana. Hazardous spills and reduced water quality in the LMR impact drinking water for the City of New Orleans and other community and industrial water users, coastal wetlands, and fisheries. This project includes studies characterizing LMR water quality, measurement of LMR travel time and dispersion, and modeling travel time and concentration of spills.