FACTORS INVOLVED IN EVALUATING GROUND WATER IMPACTS OF DEEP COAL MINE DRAINAGE1

ABSTRACT: The determination of probable ground water impacts of proposed deep coal mining is required as part of permit applications. Impact prediction generally involves well production test analysis and modeling of ground water systems associated with coal seams. Well production tests are often complicated due to the relatively low permeabilities of sandstones and shales of ground water systems. The effects of the release of water stored within finite diameter production wells must be considered. Well storage capacity appreciably affects early well production test time drawdown or time recovery data. Low pumping rates, limited cones of depression, and length of required pumping periods ate important well production test design factors. Coal seam ground water system models are usually multilayered and leaky artesian. Mine drafts partially penetrate the ground water system. Simulation of coal mine drainage often involves the horizontal permeability and storage coefficient of the coal seam zone, vertical permeabilities of sandstones and shales (aquitard) above and below the coal seam zone, and the hydrologic properties of the source bed above the aqultard overlying the coal seam zone. Ground water level declines in both the coal seam zone and source bed near land surface are necessary factors in impact analysis. An example of evaluation studies in southwest Indiana will illustrate factors involved in deep coal mine drainage modeling efforts.     

INFORMATION TECHNOLOGY IN WATERSHED MANAGEMENT DECISION MAKING1

ABSTRACT: Watershed management decision making is a complex process. Cooperation and communication among federal, state, and local stakeholders is required while balancing biophysical and socioeconomic concerns. The public is taking part in environmental decisions, and the need for technology transfer from public agencies to stakeholders is increasing. Information technology has had a profound influence on watershed management over the past decade. Advances in data acquisition through remote sensing, data utilization through geographic information systems (GIS), and data sharing through the Internet have provided watershed managers access to more information for management decisions. In the future, applications incorporating hydrologic simulation models, GIS, and decision support systems will be deployed through the Internet. In addition to challenges in making complex modeling technology available to diverse audiences, new information technology issues, such as interoperability, Internet access, and security, are introduced when GIS, simulation models, and decision support systems are integrated in an Internet environment. This paper presents a review of current use of information technology in watershed management decision making and a discussion of issues created when developing Internet based, integrated watershed management decision support systems. A prototype spatial decision support system (SDSS) for rangeland watershed management was developed using web services, which are components that communicate using text based messages, thus eliminating proprietary protocols. This new framework provides an extensible, accessible, and interoperable approach for SDSS.     

Monitoring and management of streambank erosion and natural revegetation on the lower Gordon River,Tasmanian Wilderness World Heritage Area,Australia

The wash from high-speed tourist cruise launches causes erosion of the formerly stable banks of the lower Gordon River within the Tasmanian Wilderness World Heritage Area. Speed and access restrictions on the operation of commercial cruise vessels have considerably slowed, but not halted erosion, which continues on the now destabilized banks. To assess the effectiveness of restrictions, bank erosion and natural revegetation are monitored at 48 sites using erosion pins, survey transects, and vegetation quadrats. The subjectively chosen sites are grouped on the basis of geomorphology and bank materials. The mean measured rate of erosion of estuarine banks slowed from 210 to 19 mm/year with the introduction of a 9 knot speed limit. In areas where cruise vessels continue to operate, alluvial banks were eroded at a mean rate of 11 mm/yr during the three-year period of the current management regime. Very similar alluvial banks no longer subject to commercial cruise boat traffic eroded at the slower mean rate of 3 mm/yr. Sandy levee banks have retreated an estimated maximum 10 m during the last 10–15 years. The mean rate of bank retreat slowed from 112 to 13 mm/yr with the exclusion of cruise vessels from the leveed section of the river. Revegetation of the eroded banks is proceeding slowly; however, since the major bank colonizers are very slow growing tree species, it is likely to be decades until revegetation can contribute substantially to bank stability.     

Daily Updating of Operational Statistical Seasonal Water Supply Forecasts for the western U.S.1

Abstract: Official seasonal water supply outlooks for the western United States are typically produced once per month from January through June. The Natural Resources Conservation Service has developed a new outlook product that allows the automated production and delivery of this type of forecast year‐round and with a daily update frequency. Daily snow water equivalent and water year‐to‐date precipitation data from multiple SNOTEL stations are combined using a statistical forecasting technique (“Z‐Score Regression”) to predict seasonal streamflow volume. The skill of these forecasts vs. lead‐time is comparable to the official published outlooks. The new product matches the intra‐monthly trends in the official forecasts until the target period is partly in the past, when the official forecasts begin to use information about observed streamflows to date. Geographically, the patterns of skill also match the official outlooks, with highest skill in Idaho and southern Colorado and lowest skill in the Colorado Front Range, eastern New Mexico, and eastern Montana. The direct and frequent delivery of objective guidance to users is a significant new development in the operational hydrologic seasonal forecasting community.     

Assessment of the functionality of a pilot-scale reactor and its potential for electrochemical degradation of calmagite, a sulfonated azo-dye

Electrochemical degradation (ECD) is a promising technology for in situ remediation of diversely contaminated environmental matrices by application of a low level electric potential gradient. This investigation, prompted by successful bench-scale ECD of trichloroethylene, involved development, parametric characterization and evaluation of a pilot-scale electrochemical reactor for degradation of calmagite, a sulfonated azo-dye used as a model contaminant. The reactor has two chambers filled with granulated graphite for electrodes. The system has electrical potential, current, conductivity, pH, temperature, water-level and flow sensors for automated monitoring. The reactor supports outdoor and fail-safe venting, argon purging, temperature regulation and auto-shutdown for safety. Treatment involves recirculating the contaminated solution through the electrode beds at small flow velocities mimicking low fluid-flux in groundwater and submarine sediments. The first phase of the investigation involved testing of the reactor components, its parametric probes and the automated data acquisition system for performance as designed. The results showed hydraulic stability, consistent pH behavior, marginal temperature rise (<5 degrees C) and overall safe and predictable performance under diverse conditions. Near complete removal of calmagite was seen at 3-10V of applied voltage in 8-10h. The effects of voltage and strength of electrolyte on degradation kinetics have been presented. Further, it was observed from the absorption spectra that as calmagite degrades over time, new peaks appear. These peaks were associated with degradation products identified using electrospray ionization mass spectrometry. A reaction mechanism for ECD of calmagite has also been proposed.     

Comparison of fine-scale acoustic monitoring systems using home range size of a demersal fish

We compared the results from fixed acoustic transmitters and transmitters implanted in lingcod Ophiodon elongatus provided by two fine-scale passive acoustic monitoring systems: the older Vemco^? Radio Acoustic Positioning (VRAP) system and the newer VR2W Positioning System (VPS) with either three or four receivers. The four-receiver VPS method calculated five times more positions of lingcod than VRAP and more than twice as many as the three-receiver VPS. Calculated positions of fixed transmitters were less precise with VRAP than either VPS approach. Measurements of home range for lingcod were similar between the four-receiver VPS and VRAP, which were both greater than the three-receiver VPS. Comparisons varied when lingcod were in/near complex habitats. As new technology develops, it is important to understand how new methods compare to previous methods. This may be important when describing patterns of movement or habitat use in the context of changes in habitat or management efforts.     

Measuring the environmental performance of IPPC industry: I. Devising a quantitative science-based and policy-weighted Environmental Emissions Index

This paper describes the derivation of an Environmental Emissions Index (EEI) intended to quantify the environmental performance of Integrated Pollution Prevention and Control (IPPC) installations and sectors. Characterisation and normalisation methods used in lifecycle analyses were applied to 20 routinely reported emissions parameters, pertaining to six environmental impact categories. Distance to policy targets for relevant emissions were used to weight impact categories, and link the EEI to policy priorities. Ireland and the EU15 were considered as scales of context. The European Pollutant Emission Register was a convenient source of normalisation data, but restricted the context of the EEI to industrial emissions, and distorted outputs. Using national and EU15 total loading estimates for normalisation resulted in an EEI that better reflected the relative contribution of reported emissions towards overall environmental pressures. Using Ireland's pharmaceutical sector as a case study indicated that weighting factors, and the toxicity range of NMVOC emissions, were the largest sources of EEI uncertainty. Through the integration of inventory data, scientific characterisation, and policy targets, the EEI translates reported emissions data from IPPC installations and sectors into a benchmark of environmental performance. It may be regarded as an evolving tool of potential utility to regulators and policy makers.     

Environmental emergency decision support system based on Artificial Neural Network

We present a general methodology for developing environmental emergency decision support systems (EEDSS) based on an Artificial Neural Network (ANN). We highlight the method for developing the system using an illustrative example of an unexpected atmospheric accident with an ANN prototype system for a district in Shanghai. The network architecture of the ANN is introduced. Then the development process and key technologies are addressed. The procedures for matching the environmental emergency decision support characteristics are as follows: (1) digitization (coding) of case information and emergency measures, in which the information of cases are divided into the input attributes and decision-making information, and standardized and digitized through the Feature Evaluation (FE) method and the Intensity Hierarchical (IH) method, respectively; (2) construction of environmental emergency ANN, in which Gradient Descent with Momentum and Adaptive Learning Rate (GDMALR) method (traingdx function), a modified back-propagation algorithm, is employed to do training; and (3) translation (decoding) of decision-making information, in which output data of ANN is interpreted into practical contingency measures with Translation Based on Conventional Import Ratios (TBCIR) method. The training features, time, errors, accuracy, and input attribute weights of the prototype system are analyzed. The usage of the prototype system is demonstrated through a hypothetical case. This article encounters the challenge of ANN’s own lack of training samples. We discuss to the concept of integrating Case-Based Reasoning (CBR), Genetic Algorithm (GA), and ANN to overcome this difficulty and form a technology system for generating useful decision support information for environmental emergency response.