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.     

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.     

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.     

Transport of fecal bacteria by boots and vehicle tires in a rural Alaskan community

People living without piped water and sewer can be at increased risk for diseases transmitted via the fecal-oral route. One rural Alaskan community that relies on hauling water into homes and sewage from homes was studied to determine the pathways of fecal contamination of drinking water and the human environment so that barriers can be established to protect health. Samples were tested for the fecal indicator, Escherichia coli, and the less specific indicator group, total coliforms. Shoes transported fecal contamination from outside to floor material inside buildings. Contamination in puddles on the road, in conjunction with contamination found on all-terrain vehicle (ATV) tires, supports vehicle traffic as a mechanism for transporting contamination from the dumpsite or other source areas to the rest of the community. The abundance of fecal bacteria transported around the community on shoes and ATV tires suggests that centralized measures for waste disposal as well as shoe removal in buildings could improve sanitation and health in the community.     

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.     

Incorporating Uncertainty Into the Ranking of SPARROW Model Nutrient Yields From Mississippi/Atchafalaya River Basin Watersheds1

Abstract: Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient‐reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight‐digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.     

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.     

Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation1

Young, Charles A., Marisa I. Escobar‐Arias, Martha Fernandes, Brian Joyce, Michael Kiparsky, Jeffrey F. Mount, Vishal K. Mehta, David Purkey, Joshua H. Viers, and David Yates, 2009. Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation. Journal of the American Water Resources Association (JAWRA) 45(6):1409‐1423. Abstract: The rainfall‐runoff model presented in this study represents the hydrology of 15 major watersheds of the Sierra Nevada in California as the backbone of a planning tool for water resources analysis including climate change studies. Our model implementation documents potential changes in hydrologic metrics such as snowpack and the initiation of snowmelt at a finer resolution than previous studies, in accordance with the needs of watershed‐level planning decisions. Calibration was performed with a sequence of steps focusing sequentially on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. An assessment of the calibrated streamflows using goodness of fit statistics indicate that the model robustly represents major features of weekly average flows of the historical 1980‐2001 time series. Runs of the model for climate warming scenarios with fixed increases of 2°C, 4°C, and 6°C for the spatial domain were used to analyze changes in snow accumulation and runoff timing. The results indicated a reduction in snowmelt volume that was largest in the 1,750‐2,750 m elevation range. In addition, the runoff center of mass shifted to earlier dates and this shift was non‐uniformly distributed throughout the Sierra Nevada. Because the hydrologic model presented here is nested within a water resources planning system, future research can focus on the management and adaptation of the water resources system in the context of climate change.