A STRIP MODEL APPROACH TO PARAMETERIZE A COUPLED GREEN‐AMPT KINEMATIC WAVE MODEL1

ABSTRACT: Infiltration processes at the plot scale are often described and modeled using a single effective hydraulic conductivity (Kg) value. This can lead to errors in runoff and erosion prediction. An integrated field measurement and modeling study was conducted to evaluate: (1) the relationship among rainfall intensity, spatially variable soil and vegetation characteristics, and infiltration processes; and (2) how this relationship could be modeled using Green and Ampt and a spatially distributed hydrologic model. Experiments were conducted using a newly developed variable intensity rainfall simulator on 2 m by 6 m plots in a rangeland watershed in southeastern Arizona. Rainfall application rates varied between 50 and 200 mm/hr. Results of the rainfall simulator experiments showed that the observed hydrologic response changed with changes in rainfall intensity and that the response varied with antecedent moisture condition. A distributed process based hydrologic simulation model was used to model the plots at different levels of hydrologic complexity. The measurement and simulation model results show that the rainfall runoff relationship cannot be accurately described or modeled using a single Kg value at the plot scale. Multi‐plane model configurations with infiltration parameters based on soil and plot characteristics resulted in a significant improvement over single‐plane configurations.     

Allometric exponents do not support a universal metabolic allometry

The debate about the value of the allometric scaling exponent (b) relating metabolic rate to body mass (metabolic rate = a x mass(b)) is ongoing, with published evidence both for and against a 3/4-power scaling law continuing to accumulate. However, this debate often revolves around a dichotomous distinction between the 3/4-power exponent predicted by recent models of nutrient distribution networks and a 2/3 exponent predicted by Euclidean surface-area-to-volume considerations. Such an approach does not allow for the possibility that there is no single "true" exponent. In the present study, we conduct a meta-analysis of 127 interspecific allometric exponents to determine whether there is a universal metabolic allometry or if there are systematic differences between taxa or between metabolic states. This analysis shows that the effect size of mass on metabolic rate is significantly heterogeneous and that, on average, the effect of mass on metabolic rate is stronger for endotherms than for ectotherms. Significant differences between scaling exponents were also identified between ectotherms and endotherms, as well as between metabolic states (e.g., rest, field, and exercise), a result that applies to b values estimated by ordinary least squares, reduced major axis, and phylogenetically correct regression models. The lack of support for a single exponent model suggests that there is no universal metabolic allometry and represents a significant challenge to any model that predicts only a single value of b.     

Chemical trends in background air quality and the ionic composition of precipitation for the period 1980-2004 from samples collected at Valentia Observatory, Co. Kerry, Ireland

A major Irish study, based upon more than 8000 samples collected over the measurement period of 22 years, for sulfur dioxide (SO2-S), sulfate (SO4-S) and nitrogen dioxide (NO2-N) concentrations (microg m(-3)) within air, and the ionic composition of precipitation samples based on sodium (Na+), potassium (K+), magnesium (Mg2+), calcium (Ca2+), chloride (Cl-), sulfate (SO4-S), non-sea salt sulfate (nssSO4-S), ammonium (NH4-N), and nitrate (NO3-N) weighted mean concentrations (mg l(-1)), has been completed. For the air samples, the sulfur dioxide and sulfate concentrations decreased over the sampling period (1980-2004) by 75% and 45%, respectively, whereas no significant trend was observed for nitrogen dioxide. The highest concentrations for sulfur dioxide, sulfate and nitrogen dioxide were associated with wind originating from the easterly and northeasterly directions i.e. those influenced by Irish and European sources. The lowest concentrations were associated with the westerly directions i.e. for air masses originating in the North Atlantic region. This was further verified with the use of backward (back) trajectory analysis, which allowed tracing the movement of air parcels using the European Centre for Medium range Weather Forecasting (ECMWF) ERA-40 re-analysis data. High non-sea salt sulfate levels were being associated with air masses originating from Europe (easterlies) with lower levels from the Atlantic (westerlies). With the precipitation data, analysis of the non-sea salt sulfate concentrations showed a decrease by 47% since the measurements commenced.     

Tracking acid mine-drainage in Southeast Arizona using GIS and sediment delivery models

This study investigates the application of models traditionally used to estimate erosion and sediment deposition to assess the potential risk of water quality impairment resulting from metal-bearing materials related to mining and mineralization. An integrated watershed analysis using Geographic Information Systems (GIS) based tools was undertaken to examine erosion and sediment transport characteristics within the watersheds. Estimates of stream deposits of sediment from mine tailings were related to the chemistry of surface water to assess the effectiveness of the methodology to assess the risk of acid mine-drainage being dispersed downstream of abandoned tailings and waste rock piles. A watershed analysis was preformed in the Patagonia Mountains in southeastern Arizona which has seen substantial mining and where recent water quality samples have reported acidic surface waters. This research demonstrates an improvement of the ability to predict streams that are likely to have severely degraded water quality as a result of past mining activities.     

Designing ambient particulate matter monitoring program for source apportionment study by receptor modeling

Particulate matter (PM) receptor modeling requires specific intensive input data that is always a challenge to produce cost effectively. A well-designed monitoring program is important to collect such PM ambient data in urban areas with diverse and densely distributed sources. This paper presents a general framework for designing such a monitoring program while emphasizing appropriate quality assurance and quality control elements that are particularly applicable where limited resources are available. Topics for discussion include selection of monitoring sites, sampling and analytical techniques, and the uncertainty estimation for ambient concentration input data. The design framework is illustrated by a case study of a monitoring program for PM source apportionment in the Bangkok Metropolitan Region in which 24-h fine and coarse PM samples were collected using two collocated dichotomous samplers. Comparison between black carbon measurements by Smoke Stain reflectometry and Thermal Optical Transmittance method is highlighted.     

Spatio-temporal modelling of electric vehicle charging demand and impacts on peak household electrical load

This paper presents a composite methodology for obtaining spatial and temporal projections of charging demand and peak-shaving potential from plug-in electric vehicles (EVs), and the associated spatio-temporal impacts on peak household electrical load. The methodology comprises a suite of models of future EV uptake, travel by households, household electricity demand and recharge/discharge of EVs at their home locations. The analysis is disaggregated to hourly time-steps over a full year, and spatially to mesh blocks comprising around 250 houses per block. The modelling suite is applied to an analysis of peak household load impacts across the state of Victoria, Australia, under nine different combinations of EV uptake and charging/discharging behaviour. The projected increase in peak household electrical loads under expected penetration rates and charging demands is less than 10 % on most high-demand days, but can be up to 15 % on a handful of days and geographic locations. Peak-load impacts under off-peak charging are mostly less than 5 %. With judicious EV discharging strategies, there is potential to shave peak loads on the highest demand days by up to 5 %.     

Comparison of GC-MS and FTIR methods for quantifying naphthenic acids in water samples

The extraction of bitumen from the oil sands in Canada releases toxic naphthenic acids into the process-affected waters. The development of an ideal analytical method for quantifying naphthenic acids (general formula C(n)H(2n+Z)O(2)) has been impeded by the complexity of these mixtures and the challenges of differentiating naphthenic acids from other naturally-occurring organic acids. The oil sands industry standard FTIR method was compared with a newly-developed GC-MS method. Naphthenic acids concentrations were measured in extracts of surface and ground waters from locations within the vicinity of and away from the oil sands deposits and in extracts of process-affected waters. In all but one case, FTIR measurements of naphthenic acids concentrations were greater than those determined by GC-MS. The detection limit of the GC-MS method was 0.01 mg L(-1) compared to 1 mg L(-1) for the FTIR method. The results indicated that the GC-MS method is more selective for naphthenic acids, and that the FTIR method overestimates their concentrations.     

A model-based assessment of the environmental impact of land-use change across scales in Southern Amazonia

Regional Environmental Change - This article describes the design of a new model-based assessment framework to identify and analyse possible future trajectories of agricultural development and...     

Environmental Awareness and Public Support for Protecting and Restoring Puget Sound

In an effort to garner consensus around environmental programs, practitioners have attempted to increase awareness about environmental threats and demonstrate the need for action. Nonetheless, how beliefs about the scope and severity of different types of environmental concerns shape support for management interventions are less clear. Using data from a telephone survey of residents of the Puget Sound region of Washington, we investigate how perceptions of the severity of different coastal environmental problems, along with other social factors, affect attitudes about policy options. We find that self-assessed environmental understanding and views about the seriousness of pollution, habitat loss, and salmon declines are only weakly related. Among survey respondents, women, young people, and those who believe pollution threatens Puget Sound are more likely to support policy measures such as increased enforcement and spending on restoration. Conversely, self-identified Republicans and individuals who view current regulations as ineffective tend to oppose governmental actions aimed at protecting and restoring Puget Sound. Support for one policy measure—tax credits for environmentally-friendly business practices—is not significantly affected by political party affiliation. These findings demonstrate that environmental awareness can influence public support for environmental policy tools. However, the nature of particular management interventions and other social forces can have important mitigating effects and need to be considered by practitioners attempting to develop environment-related social indicators and generate consensus around the need for action to address environmental problems.     

River environmental decision support system development for Suzhou Creek in Shanghai

The Suzhou Creek Rehabilitation Project (SCRP) is one of the largest water-related environmental rehabilitation schemes ever undertaken in the vicinity of Shanghai, China. This paper details the development and application of a River Environmental Decision Support System (REDSS) for scientific planning and decision-making on the Suzhou Creek project, and illustrates the flexibility of the REDSS framework. We developed the following components: (1) a GIS-based analysis employing Component technology; (2) a "data mart" for multi-dimensional, multi-level, integrated, dynamic, and flexible data querying; and (3) a set of hydrodynamic and water quality models which can simulate complex tidal river networks. In addition, we detail how a water quality assessment model is embedded into the REDSS by employing an Identification Index Method. With the REDSS, all GIS and non-GIS components are integrated seamlessly and data from different sources can be queried simultaneously. This allows for various scenarios to be simulated and analyzed in advance to predict and assess the effects of proposed engineering and management measures. Generated information can thus support effective decisions. All operations of the REDSS can be implemented conveniently through user-friendly interfaces. The function of the REDSS framework is demonstrated through an application to Suzhou Creek. Because the REDSS characteristics are quite general, it may be applied in different geographic regions.