EFFECTS OF A RECREATIONAL IMPOUNDMENT ON NEARBY NATURAL LAKES: A CASE STUDY1

ABSTRACT: Completion of a 1270 acre recreational impoundment (Legend Lake) in the glacial sands of Menominee County, Wisconsin, produced geochemical and hydrologic alterations in some nearby natural lakes. The impoundment was produced by the construction of three dams, one of which proved to be temporary, connecting 9 natural lakes and ponds of 383 acres with 951 acres of flooded lands. Water levels were raised 3–15 feet within the impounded area. Much of the flooded area was peat rich wetland associated with the prior drainage. Water depths are less than 15 feet in 70% of the impoundment. Three seepage lakes, located less than 1/2 mile from the impoundment, experienced shoreline flooding, shoreline and soil erosion, some tree kills, and increased turbidity. These lakes also experienced concentration increases in several chemical constituents which indicate an influx of impoundment water through a regional alternation in the groundwater flow paths. The three lakes were connected by canals, and a 2.3 cfs gravity drain with an auxiliary pumping station was built to return excess water to the outflow of the impoundment. Future projects of this type would benefit from a more extensive hydrologic and geochemical analysis prior to initiation. Had environmental assessments been required at the time of this development, as they now are in Wisconsin for similar projects, some of the problems encountered might have been alleviated.     

Life cycle assessment of sunflower and rapeseed as energy crops under Chilean conditions

An option for the agriculture and energy sectors in Chile is the cultivation of energy crops, but environmental studies are first needed in the framework of a sustainable national energy policy.In this study, we used a cradle-to-farm gate Life Cycle Assessment (LCA) to compare environmental impacts and energy and water demand of rapeseed (Brassica napus L.) and sunflower (Helianthus annuus L.) in Chile, as potential oleaginous crops for first-generation biodiesel production. National agricultural data are used for the LCA inventory and process data of international databases are adapted to local conditions. The effect of field N₂O emissions and land use change is evaluated. The results indicate that, compared to sunflower, rapeseed production has a better environmental performance in 9 out of the 11 impact categories evaluated, and lower water consumption. The energy demand of rapeseed is 4.9 GJ/t seed, 30% less than that of sunflower. Mineral fertilizers cause the highest environmental impact in both crops. The analysis of the life cycle of fertilizers indicates that extraction of raw materials and its production are key stages. Attempts to reduce the environmental impact and energy requirement of both crops should be mainly associated with the evaluation of other types of fertilization. In addition, particularly for sunflower, low impact herbicides should be evaluated, seed yield improved and cultivation practices optimized. If the crops are produced on degraded grasslands, the greenhouse gas emissions may be reduced.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Organizational change and the greening process at amoco

Implementing environmentalism in the internal operations of a firm requires a reassignment of responsibilities and functions. New job tasks are created while old ones are altered to incorporate new perspectives and responsibilities that reflect broader societal demands. In essence, what evolves is a new firm, but what exactly does this mean? After a broad analysis of the environmental transformation of American industry, four basic changes within the organizational framework of dealing with environmentalism are identified: an evolution of the environmental management function, alteration of the overall structure of the organization, expansion of the boundaries of the firm, and changes in corporate culture. The author shows how these shifts occur in sequential order as increasing uncertainty promotes the search for answers from more diverse sources. Ultimately, as environmentalism continues to evolve, it increasingly infuses itself into the corporate culture. The following article presents this model and a case study of the Amoco Corporation.