Addressing Uncertainty in TMDLS: Short Course at Arkansas Water Resources Center 2001 Annual Conference

Management of a critical natural resource like water requires information on the status of that resource. The US Environmental Protection Agency (EPA) reported in the 1998 National Water Quality Inventory that more than 291,000 miles of assessed rivers and streams and 5 million acres of lakes do not meet State water quality standards. This inventory represents a compilation of State assessments of 840,000 miles of rivers and 17.4 million acres of lakes; a 22 percent increase in river miles and 4 percent increase in lake acres over their 1996 reports. Siltation, bacteria, nutrients and metals were the leading pollutants of impaired waters, according to EPA. The sources of these pollutants were presumed to be runoff from agricultural lands and urban areas. EPA suggests that the majority of Americans-over 218 million-live within ten miles of a polluted waterbody. This seems to contradict the recent proclamations of the success of the Clean Water Act, the Nation\u27s water pollution control law. EPA also claims that, while water quality is still threatened in the US, the amount of water safe for fishing and swimming has doubled since 1972, and that the number of people served by sewage treatment plants has more than doubled

Assessment of the potential impacts of plant traits across environments by combining global sensitivity analysis and dynamic modeling in wheat

A crop can be viewed as a complex system with outputs (e.g. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information. Application of numerical methods for model exploration assist in evaluating the major most influential inputs, providing the simulation model is a credible description of the biological system. A sensitivity analysis was used to assess the simulated impact on yield of a suite of traits involved in major processes of crop growth and development, and to evaluate how the simulated value of such traits varies across environments and in relation to other traits (which can be interpreted as a virtual change in genetic background). The study focused on wheat in Australia, with an emphasis on adaptation to low rainfall conditions. A large set of traits (90) was evaluated in a wide target population of environments (4 sites x 125 years), management practices (3 sowing dates x 2 N fertilization) and $CO_2$ (2 levels). The Morris sensitivity analysis method was used to sample the parameter space and reduce computational requirements, while maintaining a realistic representation of the targeted trait x environment x management landscape ($\sim$ 82 million individual simulations in total). The patterns of parameter x environment x management interactions were investigated for the most influential parameters, considering a potential genetic range of +/- 20% compared to a reference. Main (i.e. linear) and interaction (i.e. non-linear and interaction) sensitivity indices calculated for most of APSIM-Wheat parameters allowed the identifcation of 42 parameters substantially impacting yield in most target environments. Among these, a subset of parameters related to phenology, resource acquisition, resource use efficiency and biomass allocation were identified as potential candidates for crop (and model) improvement.Comment: 22 pages, 8 figures. This work has been submitted to PLoS On

Future Projections of Urban Waste Flows aand their Impacts in African Metropolises Cities

This paper presents future trends of urban wastes and their impacts on the environment of African cities using plausible mitigation scenarios. To accomplish this, an integrated dynamic model for urban waste flows was developed, tested, calibrated and validated. Its parameter sensitivity was analyzed. Using population projection up to 2052 with different levels of technological implementation, policy enforcement and awareness raising, four runs were executed. The “business as usual” run showed that with no additional mitigation measures, the environmental quality in Kampala and Dar es salaam Cities deteriorates. The “more enforcement” and “more collection” scenarios showed good reduction in environmental loads but they perform less well in resource recovery. The “proper management” scenario that combines enhanced technological implementation, awareness raising and policy enforcement, produced the smallest environmental loads, and recovered the largest amount of resources. Thus, the city authorities, general public, community based organisations and Non-governmental organizations would have to increase their efforts in finances and commitment to improve the urban environmental quality and increase resource recovery

Steering in computational science: mesoscale modelling and simulation

This paper outlines the benefits of computational steering for high performance computing applications. Lattice-Boltzmann mesoscale fluid simulations of binary and ternary amphiphilic fluids in two and three dimensions are used to illustrate the substantial improvements which computational steering offers in terms of resource efficiency and time to discover new physics. We discuss details of our current steering implementations and describe their future outlook with the advent of computational grids.Comment: 40 pages, 11 figures. Accepted for publication in Contemporary Physic

Factory Eco-Efficiency Modelling: Framework Development and Testing

Eco-efficiency is becoming an increasingly important organisational performance measure. Its indicators are regularly used alongside productivity, cost, quality, health and safety in operations and corporate social responsibility reporting. The purpose of this paper is to show an eco-efficiency modelling framework, and its application in the case of an automotive manufacturer. The framework composes, models and analyses resource and production data. Focus on energy, water distributions and material transformations in manufacturing, utility and facility assets are used to analyse eco-efficiency. Resources are examined in respect to three data granularity factors: subdivision, pulse, and magnitude. Models are linked with performance indicators to assess asset eco-efficiency. This work contributes to industrial sustainability literature by introducing a modelling framework that links with data granularity and eco-efficiency indicators