PREDICTIVE MODELS FOR GREAT LAKES HYDROLOGY1

ABSTRACT: The individual hydrologic components are assumed to be normally distributed for each month and linear regression equations are estimated for predicting the value of the individual monthly hydrologic components. It is shown that some of the hydrologic components for downwind (in this case downstream) lakes are dependent upon hydrologic events for the upwind lakes. This is particularly so for precipitation in the downwind lake basins which appears to be dependent upon evaporation values for upwind lakes.     

A REEVALUATION OF THE GROUND WATER BUDGET FOR LAS VEGAS VALLEY,NEVADA, WITH EMPHASIS ON GROUND WATER DISCHARGE1

ABSTRACT: An essential component to the ground water budget for the Las Vegas Valley (LVV) in southern Nevada is discharge from the ground water system. Discharge for the LW has been based on estimates made more than 50 years ago of 35,524,224 m3 per year as evapotranspiration (ET) and 0 m³ per year as subsurface outflow. Newly published values for recharge based on a more robust data set (70,308,360 m³) indicate a large imbalance associated with the earlier discharge estimates, providing the basis for the reevaluation conducted in this study. ET estimates in this study, as opposed to previous studies, were assigned a range in values that included an approach that assigned higher weight to the unique soil, plant, water, and climatic conditions that existed in predevelopment (1905) LW. The earlier discharge estimates also assumed that the basin was hydrologically closed; however, based on our evaluation, a range in yearly discharge by subsurface outflow from 1,480,176 m³ to 19,735,680 m³ could be assigned. Likewise, a range in yearly ET from 20,475,768 m³ to 78,819,372 m³ could be assigned. Based on newly published recharge values, closure can only occur if higher values are assigned to both the subsurface outflow and/or ET components of ground water discharge. We cannot provide a complete water balance closure with our ground water discharge estimate of 64,140,960 m³. However our reevaluation gives support to the higher recharge estimates and provides the rationale for future studies to be conducted based on a more rigorous scientific assessment.     

International mining taxation issues and comparisons

This paper presents the quantitative results of recent research on Canada's minerals and metals industry, and its international competitiveness for mineral investment. The information and analysis presented are derived from the work of a Canadian government-industry task force that was created in 1991, under the auspices of the Intergovernmental Working Group on the Mineral Industry (IGWG). Much of this work deals with mining taxation in several Canadian provinces. More importantly, an attempt is made to evaluate the total tax burden that the mining industry must bear, on a project basis, at all levels from exploration through refining operations in many important competitor countries. While the focus of the paper is on an international comparison of mining taxation, some non-tax issues relating to Canada's competitiveness for mineral investment are addressed .     

Support vector machine based prediction of photovoltaic module and power station parameters

ABSTRACT

The uncertainty in the output power of the photovoltaic (PV) power generation station due to variation in meteorological parameters is of serious concern. An accurate output power prediction of a PV system helps in better design and planning. The present study is carried out for the prediction of output power of PV generating station by using Support Vector Machines. Two cases are considered in the present study for prediction. Case-I deals with the prediction of PV module parameters such as V_oc, I_sh, R_s, R_sh, I_max, V_max, P_max, and case-II deals with the prediction of power generation parameters such as P_DC, P_AC, and system efficiency. Historical data of PV power station with an installed capacity of 10 MW and weather information are used as input to develop four different seasons-based SVM models for all parameters. The performance results of the models are presented in terms of Mean Relative Error (MRE) and Root Mean Square Error (RMSE). Additionally, the performance results obtained with polynomial and Radial Based Function kernel are also compared to show that which kernel has better prediction accuracy, and practicability. The result shows that the minimum average RMSE and MRE for case-I with Radial Based Function kernel are 0.034%, 0.055%, 0.002%, 1.726%, 0.044%, 0.047%, 2.342%, and 0.005%, 0.014%, 0.079%, 0.885%, 0.005%, 0.007%, 0.013%, and for case-II with poly kernel are 0.014%, 0.016%, 0.149% and 0.011%, 0.0175, 1.03%, respectively. The present study will be helpful to provide technical guidance to the prediction of the PV power System.     

A High‐Resolution National‐Scale Hydrologic Forecast System from a Global Ensemble Land Surface Model

Warning systems with the ability to predict floods several days in advance have the potential to benefit tens of millions of people. Accordingly, large‐scale streamflow prediction systems such as the Advanced Hydrologic Prediction Service or the Global Flood Awareness System are limited to coarse resolutions. This article presents a method for routing global runoff ensemble forecasts and global historical runoff generated by the European Centre for Medium‐Range Weather Forecasts model using the Routing Application for Parallel computatIon of Discharge to produce high spatial resolution 15‐day stream forecasts, approximate recurrence intervals, and warning points at locations where streamflow is predicted to exceed the recurrence interval thresholds. The processing method involves distributing the computations using computer clusters to facilitate processing of large watersheds with high‐density stream networks. In addition, the Streamflow Prediction Tool web application was developed for visualizing analyzed results at both the regional level and at the reach level of high‐density stream networks. The application formed part of the base hydrologic forecasting service available to the National Flood Interoperability Experiment and can potentially transform the nation's forecast ability by incorporating ensemble predictions at the nearly 2.7 million reaches of the National Hydrography Plus Version 2 Dataset into the national forecasting system.     

Results of Community Deliberation About Social Impacts of Ecological Restoration: Comparing Public Input of Self-Selected Versus Actively Engaged Community Members

Participatory processes for obtaining residents' input about community impacts of proposed environmental management actions have long raised concerns about who participates in public involvement efforts and whose interests they represent. This study explored methods of broad-based involvement and the role of deliberation in social impact assessment. Interactive community forums were conducted in 27 communities to solicit public input on proposed alternatives for recovering wild salmon in the Pacific Northwest US. Individuals identified by fellow residents as most active and involved in community affairs ("AE residents") were invited to participate in deliberations about likely social impacts of proposed engineering and ecological actions such as dam removal. Judgments of these AE participants about community impacts were compared with the judgments of residents motivated to attend a forum out of personal interest, who were designated as self-selected ("SS") participants. While the magnitude of impacts rated by SS participants across all communities differed significantly from AE participants' ratings, in-depth analysis of results from two community case studies found that both AE and SS participants identified a large and diverse set of unique impacts, as well as many of the same kinds of impacts. Thus, inclusion of both kinds of residents resulted in a greater range of impacts for consideration in the environmental impact study. The case study results also found that the extent to which similar kinds of impacts are specified by AE and SS group members can differ by type of community. Study results caution against simplistic conclusions drawn from this approach to community-wide public participation. Nonetheless, the results affirm that deliberative methods for community-based impact assessment involving both AE and SS residents can provide a more complete picture of perceived impacts of proposed restoration activities.     

High prevalence of infections and pathological changes in burbot (Lota lota) from a polluted lake (Lake Mjøsa,Norway)

The aim of the present study was to investigate whether exposure to high levels of persistent organic pollutants (POPs) affected a fish population in Lake Mjøsa. Lake Mjøsa is known to be contaminated by polybrominated diphenyl ethers (PBDEs), a subgroup of brominated flame retardants from local industrial activities. Fish from Lake Losna, a less contaminated lake located close to Lake Mjøsa, was used as reference (control).The sampling of burbot (Lota lota) was carried out between 2005 and 2008. Hepatic levels of POPs were analysed in burbot from the two lakes, and the fish were examined for bacterial- and parasite infection and histopathological changes. The levels of polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethanes (DDTs), and PBDEs were about 10, 15 and 300 times higher in fish from Lake Mjøsa compared to fish from Lake Losna. Mycobacterium salmoniphilum was present in 7% and 35% of the fish from Lake Losna and Lake Mjøsa respectively. Significantly higher number of external and visceral macroscopic lesions, histopathological diffuse changes and granulomas were seen in fish from Lake Mjøsa compared to Lake Losna. Furthermore the parasite infection was higher and the hepatic lipid content was significantly lower in burbot from Lake Mjøsa. The results of the present study suggest that the high level of contamination in Lake Mjøsa could have a negative impact on the health status of wild fish inhabiting the lake.     

Atmospheric Aerosol Composition and Concentration as a Function of Particle Size and of Time

As a step toward better understanding the reactive Los Angeles air basin atmosphere, a study was undertaken at the University of California—Riverside Campus, to determine the composition and concentration of atmospheric particulate matter as a function of particle size and time. The study involved developing a method for obtaining size-classified, time-fractionated aerosol samples amenable to chemical and physical (including microscopic) analysis. During a 15-day period, samples were obtained over 4-hr periods and subsequently analyzed for nitrate, sulfate, iron, and lead. Concentration of six gaseous pollutantsj total aerosol light-scattering, and several meteorological measurements were simultaneously recorded and averaged over the 4-hr intervals. This data was presented graphically to show the diurnal variation in and relationship between gaseous, particulate, and meteorological measurements. A strong relationship between gaseous peroxyacetyl nitrate, particulate nitrate, and aerosol light-scattering was found. High concentrations of ammonium nitrate particles, mainly in the 0.5-2μ, diameter size range, were found in the atmospheric particulate samples collected on days of very high smog (very limited visibility).     

The Mass Distribution of Large Atmospheric Particles

This paper describes the results of a study to determine the total mass and the mass distribution of atmospheric aerosols, especially that mass associated with particles greater than 10 μm diameter. This study also determined what fraction of the total aerosol mass a standard high-volume air sampler collects and what fraction and size interval settle out on a dust fall plate. A special aerosol sampling system was designed for this study to obtain representative samples of large airborne particles. A suburban sampling site was selected because no local point sources of aerosols existed nearby. Samples were collected under various conditions of wind velocity and direction to obtain measurements on different types of aerosols.

Study measurements show that atmospheric particulate matter has a bimodal mass distribution. Mass associated with large particles mainly ranged from 5 to 100 μm in size, while mass associated with small particles ranged from an estimated 0.03 to 5 μm in size. Combined, these two distributions produced a bimodal mass distribution with a minimum around 5 μm diameter. The high-volume air sampler was found to collect most of the total aerosol mass, not just that fraction normally considered suspended particulate. Dust fall plates did not provide a good or very useful measure of total aerosol mass. The two fundamental processes of aerosol formation, condensation and dispersion appear to account for the formation of a bimodal mass distribution in both natural and anthropogenic aerosols. Particle size distribution measurements frequently are in error because representative samples of large airborne particles are not obtained. Considering this descrepancy, air pollution regulations should specify or be based upon an upper particle size limit.