Vegetation and outdoor recess time at elementary schools: What are the connections?

Empirical and anecdotal evidence suggests that landscapes with more vegetation have a positive impact on children's focus, attention, and cognitive development. In school, children are able to regain focus, suppress impulses, and pay attention in class longer after exposure to natural settings. Because children spend much of their time in school, the amount and types of vegetation on school grounds may influence their development. Public elementary schools in the Commonwealth of Virginia (N = 988) were surveyed to examine correlations between school ground vegetation and outside recess. The number of trees on school grounds, the size of the school grounds, and the presence of sports fields were modestly correlated with greater outside recess time. These correlations support common sense because sports fields facilitate supervised play and larger school grounds provide space for sports fields and playgrounds and additional opportunities for free play. More trees on school grounds provide a welcoming environment for students and teachers, and encourage outside play. These results may help school personnel design and maintain school grounds that increase outdoor recess time.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

Effectiveness of a publicly-funded demonstration program to promote management of dryland salinity

Community and catchment-based approaches to salinity management continue to attract interest in Australia. In one such approach, Catchment Demonstration Initiative (CDI) projects were established by the Western Australian (WA) Government in 2000 for targeted investment in large-scale catchment-based demonstrations of integrated salinity management practices. The aim was to promote a process for technically-informed salinity management by landholders. This paper offers an evaluation of the effectiveness of one CDI project in the central wheatbelt of WA, covering issues including: its role in fostering adoption of salinity management options, the role of research and the technical requirements for design and implementation of on-ground works, the role of monitoring and evaluation, the identification and measurement of public and private benefits, comparison and identification of the place and value of plant-based and engineering-based options, reliance on social processes and impacts of constraints on capacity, management of governance and administration requirements and an appreciation of the value of group-based approaches.A number of factors may reduce the effectiveness of CDI-type approaches in facilitating landholder action to address salinity, many of these are socially-based. Such approaches can create considerable demands on landholders, can be expensive (because of the planning and accountability required) on the basis of dollars per hectare impacted, and can be difficult to garner ownership from all involved. An additional problem could be that few community groups would have the capacity to run such programs and disseminate the new knowledge so that the CDI-type projects can impact outside the focus catchment. In common with many publicly-funded approaches to salinity, we found that direct benefits on public assets are smaller than planned and that results from science-based requirements of monitoring and evaluation have long lead times, causing farmers to either wait for the information or act sooner and take risks based on initial results. We also found that often it is a clear outline of the process that is of most importance in decision making as opposed to the actual results. We identified limitations in regulatory processes and the capacity for local government to engage in the CDI.The opportunities that CDI-type approaches provide centre around the value of its group-based approach. We conclude that they can overcome knowledge constraints in managing salinity by fostering group-based learning, offer a structured process of trialling options so that the costs and benefits can be clearly and transparently quantified, and avoid the costly mistakes and “learning failures” of the past.     

Multi-criteria evaluation technique for SFI site identification of NORMS and oil industry waste disposal – Possibilities in Kuwait

Waste generation and accumulating quantities of oil field waste are a matter of environmental concern. This study proposes the Slurry Fracture Injection (SFI) technique as an alternative waste disposal method. The slurried solids injection waste disposal method is environmentally secure and permanent, leaving no future liabilities that must be risk-evaluated or priced. An entire waste stream comprising ground solids and waste water can be injected into deep and hydraulically secure target strata with no contamination of potable water-bearing formations or formations outside the target zone that may contain resources (gas and oil). The slurry injection method can be used to clean and reclaim landfills, oil pits and granular waste dumps. This article proposes a two-tier screening method for evaluating the feasibility of this technique and the identification of suitable target zones. A stringent environmental and process control monitoring program should complement the planning and operational period to ensure environmental protection, waste containment, and regulatory HSE compliance.     

Modeling the costs and benefits of dam construction from a multidisciplinary perspective

Although the benefits of dam construction are numerous, particularly in the context of climate change and growing global demand for electricity, recent experience has shown that many dams have serious negative environmental, human, and political consequences. Despite an extensive literature documenting the benefits and costs of dams from a single disciplinary perspective, few studies have simultaneously evaluated the distribution of biophysical, socio-economic, and geopolitical implications of dams. To meet the simultaneous demands for water, energy, and environmental protection well into the future, a broader view of dams is needed. We thus propose a new tool for evaluating the relative costs and benefits of dam construction based on multi-objective planning techniques. The Integrative Dam Assessment Modeling (IDAM) tool is designed to integrate biophysical, socio-economic, and geopolitical perspectives into a single cost/benefit analysis of dam construction. Each of 27 different impacts of dam construction is evaluated both objectively (e.g., flood protection, as measured by RYI years) and subjectively (i.e., the valuation of said flood protection) by a team of decision-makers. By providing a visual representation of the various costs and benefits associated with two or more dams, the IDAM tool allows decision-makers to evaluate alternatives and to articulate priorities associated with a dam project, making the decision process about dams more informed and more transparent. For all of these reasons, we believe that the IDAM tool represents an important evolutionary step in dam evaluation.     

Comparing the impacts of hiking, skiing and horse riding on trail and vegetation in different types of forest

Nature-based tourism in protected areas has increased and diversified dramatically during the last decades. Different recreational activities have a range of impacts on natural environments. This paper reports results from a comparison of the impacts of hiking, cross-country skiing and horse riding on trail characteristics and vegetation in northern Finland. Widths and depths of existing trails, and vegetation on trails and in the neighbouring forests were monitored in two research sites during 2001 and 2002. Trail characteristics and vegetation were clearly related to the recreational activity, research site and forest type. Horse trails were as deep as hiking trails, even though the annual number of users was 150-fold higher on the hiking trails. Simultaneously, cross-country skiing had the least effect on trails due to the protective snow cover during winter. Hiking trail plots had little or no vegetation cover, horse riding trail plots had lower vegetation cover than forest plots, while skiing had no impact on total vegetation cover. On the other hand, on horse riding trails there were more forbs and grasses, many of which did not grow naturally in the forest. These species that were limited to riding trails may change the structure of adjacent plant communities in the long run. Therefore, the type of activities undertaken and the sensitivity of habitats to these activities should be a major consideration in the planning and management of nature-based tourism. Establishment of artificial structures, such as stairs, duckboards and trail cover, or complete closure of the site, may be the only way to protect the most sensitive or deteriorated sites.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Assessment Tools for Urban Catchments: Defining Observable Biological Potential1

Abstract: Urbanization represents a strong and increasingly more prevalent impact on stream quality worldwide. One of the characteristic effects of increased urbanization is a consistent decline in biological stream condition. The characterization of this biological degradation with increasing urbanization presents a number of advantages for the study and management of urban streams and catchments. In this paper, the limitation of biological condition with urbanization, called observed biological potential, is characterized. Using an urban intensity index and a biological index developed specifically for urban systems in the Baltimore, Maryland; Cleveland, Ohio; and San Jose, California regions, two principal techniques were compared (quantile regression and bin regression) to define observed biological potential along urban gradients. Quantile regression was selected as the preferable tool for describing observed biological potential given the consistency with which it can be applied and its statistical efficiency, however, bin quantile regression performed similarly. Having identified a numeric approximation of observed biological potential, two methods for identifying factors related to distance from potential as a way of identifying critical environmental factors affecting biological condition in urban areas were explored. The results of this work can be used for identifying benchmarks for urban stream biological condition, identifying limiting catchment characteristics, and prioritizing urban stream management efforts.     

Adaptive Management of Stream Channel Maintenance at Bridge Crossings in the Northern Tier Region,Pennsylvania1

Abstract: An adaptive management framework is applied to the problem of identifying mitigation measures for sediment deposition near bridge crossings in small streams in the Northern Tier region of northern Pennsylvania. The presence of the rigid bridge infrastructure introduces a challenge for applying adaptive management practices, because the integrity of the bridge structure itself has to be maintained regardless of the mitigation practices used in the stream channel near the bridge. In an effort to overcome the unacceptable risk that field‐scale adaptive management experiments present to rigid bridge infrastructure, an adaptive management approach for laboratory‐scale experimentation of mitigation methods at bridge crossings in the Northern Tier region is presented as a way to decrease the level of uncertainty about channel response to mitigation measures and increase the rate of learning about the effectiveness of these measures. Four cycles of adaptive management experiments are discussed to demonstrate that this approach results in fast and efficient learning about channel response to mitigation methods for the given conditions. The value of monitoring and of assessment of monitored data in the overall efficiency of the adaptive management approach is highlighted. Assessment of what was learned in the adaptive management experiment cycles presented here leads to new directions to continually improve management policies and practices in stream channels at bridge crossings in the Northern Tier region. The adaptive management process, rather than continuing with a normally risk‐averse management approach, results in opportunities for learning new information about a system’s response.