Hydraulic management of a soil moisture controlled SDI wastewater dispersal system in an Alabama Black Belt soil

Rural areas represent approximately 95% of the 14000 km(2) Alabama Black Belt, an area of widespread Vertisols dominated by clayey, smectitic, shrink-swell soils. These soils are unsuitable for conventional onsite wastewater treatment systems (OWTS) which are nevertheless widely used in this region. In order to provide an alternative wastewater dosing system, an experimental field moisture controlled subsurface drip irrigation (SDI) system was designed and installed as a field trial. The experimental system that integrates a seasonal cropping system was evaluated for two years on a 500-m(2) Houston clay site in west central Alabama from August 2006 to June 2008. The SDI system was designed to start hydraulic dosing only when field moisture was below field capacity. Hydraulic dosing rates fluctuated as expected with higher dosing rates during warm seasons with near zero or zero dosing rates during cold seasons. Lower hydraulic dosing in winter creates the need for at least a two-month waste storage structure which is an insurmountable challenge for rural homeowners. An estimated 30% of dosed water percolated below 45-cm depth during the first summer which included a 30-year historic drought. This massive volume of percolation was presumably the result of preferential flow stimulated by dry weather clay soil cracking. Although water percolation is necessary for OWTS, this massive water percolation loss indicated that this experimental system is not able to effective control soil moisture within its monitoring zone as designed. Overall findings of this study indicated that soil moisture controlled SDI wastewater dosing is not suitable as a standalone system in these Vertisols. However, the experimental soil moisture control system functioned as designed, demonstrating that soil moisture controlled SDI wastewater dosing may find application as a supplement to other wastewater disposal methods that can function during cold seasons.     

Passive and active adaptive management: approaches and an example

Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. Yet there remains considerable confusion about what adaptive management entails, and how to actually make resource decisions adaptively. A key but somewhat ambiguous distinction in adaptive management is between active and passive forms of adaptive decision making. The objective of this paper is to illustrate some approaches to active and passive adaptive management with a simple example involving the drawdown of water impoundments on a wildlife refuge. The approaches are illustrated for the drawdown example, and contrasted in terms of objectives, costs, and potential learning rates. Some key challenges to the actual practice of AM are discussed, and tradeoffs between implementation costs and long-term benefits are highlighted.     

Adaptive management of natural resources--framework and issues

Adaptive management, an approach for simultaneously managing and learning about natural resources, has been around for several decades. Interest in adaptive decision making has grown steadily over that time, and by now many in natural resources conservation claim that adaptive management is the approach they use in meeting their resource management responsibilities. Yet there remains considerable ambiguity about what adaptive management actually is, and how it is to be implemented by practitioners. The objective of this paper is to present a framework and conditions for adaptive decision making, and discuss some important challenges in its application. Adaptive management is described as a two-phase process of deliberative and iterative phases, which are implemented sequentially over the timeframe of an application. Key elements, processes, and issues in adaptive decision making are highlighted in terms of this framework. Special emphasis is given to the question of geographic scale, the difficulties presented by non-stationarity, and organizational challenges in implementing adaptive management.     

Learning about knowledge management for improving environmental impact assessment in a government agency: the Western Australian experience

How does knowledge management (KM) by a government agency responsible for environmental impact assessment (EIA) potentially contribute to better environmental assessment and management practice? Staff members at government agencies in charge of the EIA process are knowledge workers who perform judgement-oriented tasks highly reliant on individual expertise, but also grounded on the agency’s knowledge accumulated over the years. Part of an agency’s knowledge can be codified and stored in an organizational memory, but is subject to decay or loss if not properly managed. The EIA agency operating in Western Australia was used as a case study. Its KM initiatives were reviewed, knowledge repositories were identified and staff surveyed to gauge the utilisation and effectiveness of such repositories in enabling them to perform EIA tasks.     

Adaptive management in the U.S. National Wildlife Refuge System: science-management partnerships for conservation delivery

Adaptive management is an approach to recurrent decision making in which uncertainty about the decision is reduced over time through comparison of outcomes predicted by competing models against observed values of those outcomes. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service is a large land management program charged with making natural resource management decisions, which often are made under considerable uncertainty, severe operational constraints, and conditions that limit ability to precisely carry out actions as intended. The NWRS presents outstanding opportunities for the application of adaptive management, but also difficult challenges. We describe two cooperative programs between the Fish and Wildlife Service and the U.S. Geological Survey to implement adaptive management at scales ranging from small, single refuge applications to large, multi-refuge, multi-region projects. Our experience to date suggests three important attributes common to successful implementation: a vigorous multi-partner collaboration, practical and informative decision framework components, and a sustained commitment to the process. Administrators in both agencies should consider these attributes when developing programs to promote the use and acceptance of adaptive management in the NWRS.     

Priority screening of toxic chemicals and industry sectors in the U.S. toxics release inventory: a comparison of the life cycle impact-based and risk-based assessment tools developed by U.S. EPA

Life Cycle Impact Assessment (LCIA) and Risk Assessment (RA) employ different approaches to evaluate toxic impact potential for their own general applications. LCIA is often used to evaluate toxicity potentials for corporate environmental management and RA is often used to evaluate a risk score for environmental policy in government. This study evaluates the cancer, non-cancer, and ecotoxicity potentials and risk scores of chemicals and industry sectors in the United States on the basis of the LCIA- and RA-based tools developed by U.S. EPA, and compares the priority screening of toxic chemicals and industry sectors identified with each method to examine whether the LCIA- and RA-based results lead to the same prioritization schemes. The Tool for the Reduction and Assessment of Chemical and other environmental Impacts (TRACI) is applied as an LCIA-based screening approach with a focus on air and water emissions, and the Risk-Screening Environmental Indicator (RSEI) is applied in equivalent fashion as an RA-based screening approach. The U.S. Toxic Release Inventory is used as the dataset for this analysis, because of its general applicability to a comprehensive list of chemical substances and industry sectors. Overall, the TRACI and RSEI results do not agree with each other in part due to the unavailability of characterization factors and toxic scores for select substances, but primarily because of their different evaluation approaches. Therefore, TRACI and RSEI should be used together both to support a more comprehensive and robust approach to screening of chemicals for environmental management and policy and to highlight substances that are found to be of concern from both perspectives.     

Adaptive management for a turbulent future

The challenges that face humanity today differ from the past because as the scale of human influence has increased, our biggest challenges have become global in nature, and formerly local problems that could be addressed by shifting populations or switching resources, now aggregate (i.e., "scale up") limiting potential management options. Adaptive management is an approach to natural resource management that emphasizes learning through management based on the philosophy that knowledge is incomplete and much of what we think we know is actually wrong. Adaptive management has explicit structure, including careful elucidation of goals, identification of alternative management objectives and hypotheses of causation, and procedures for the collection of data followed by evaluation and reiteration. It is evident that adaptive management has matured, but it has also reached a crossroads. Practitioners and scientists have developed adaptive management and structured decision making techniques, and mathematicians have developed methods to reduce the uncertainties encountered in resource management, yet there continues to be misapplication of the method and misunderstanding of its purpose. Ironically, the confusion over the term "adaptive management" may stem from the flexibility inherent in the approach, which has resulted in multiple interpretations of "adaptive management" that fall along a continuum of complexity and a priori design. Adaptive management is not a panacea for the navigation of 'wicked problems' as it does not produce easy answers, and is only appropriate in a subset of natural resource management problems where both uncertainty and controllability are high. Nonetheless, the conceptual underpinnings of adaptive management are simple; there will always be inherent uncertainty and unpredictability in the dynamics and behavior of complex social-ecological systems, but management decisions must still be made, and whenever possible, we should incorporate learning into management.     

Solid waste management in European countries: a review of systems analysis techniques

In the past few decades, solid waste management systems in Europe have involved complex and multi-faceted trade-offs among a plethora of technological alternatives, economic instruments, and regulatory frameworks. These changes resulted in various environmental, economic, social, and regulatory impacts in waste management practices which not only complicate regional policy analysis, but also reshape the paradigm of global sustainable development. Systems analysis, a discipline that harmonizes these integrated solid waste management strategies, has been uniquely providing interdisciplinary support for decision making in this area. Systems engineering models and system assessment tools, both of which enrich the analytical framework of waste management, were designed specifically to handle particular types of problems. Though how to smooth out the barriers toward achieving appropriate systems synthesis and integration of these models and tools to aid in the solid waste management schemes prevalent in European countries still remains somewhat uncertain. This paper conducts a thorough literature review of models and tools illuminating possible overlapped boundaries in waste management practices in European countries and encompassing the pros and cons of waste management practices in each member state of the European Union. Whereas the Southern European Union (EU) countries need to develop further measures to implement more integrated solid waste management and reach EU directives, the Central EU countries need models and tools with which to rationalize their technological choices and management strategies. Nevertheless, considering systems analysis models and tools in a synergistic way would certainly provide opportunities to develop better solid waste management strategies leading to conformity with current standards and foster future perspectives for both the waste management industry and government agencies in European Union.     

Exploring trends, sources, and causes of environmental funding: a study of Florida counties

Florida is one of the largest spenders on the environment in the U.S. Employing a database from Florida counties, this study examines two distinct environmental funding areas in government: funding to protect the environment, and funding to develop the environment. These two types of funding serve different purposes, support different activities and operations, and draw from different revenue sources. The results show that environmental funding in government is a response to the environmental pressure generated by economic activities and population growth. Counties with a higher level of manufacturing and farming activity spend more to protect the environment, while counties with higher population densities spend more to develop the environment. Moreover, counties with more funding for public safety and economic development activities spend less on the environment, indicating that environmental funding is influenced by the political processes in public budgeting in which diversified interests compete for resources. These results show that environmental spending in government is the result of combined forces arising from environmental pressure and budgetary politics.