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.     

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.     

Evolution of extreme-mating behaviour: patterns of extrapair paternity in a species with forced extrapair copulation

Sexual conflict can result in the evolution of extreme mating strategies, including forced copulation. Forced extrapair copulation (FEPC) is generally rare among birds, but is common in re-introduced populations of the hihi (Notiomystis cincta), a socially monogamous, New Zealand endemic, endangered passerine. The aim of this study was to understand the patterns of extrapair paternity in a population where the majority of EPC is forced and to examine the factors, in particular female-specific, influencing the proportion of offspring fathered by extrapair males (EPP—extrapair paternity) and the number of males siring extrapair offspring within a brood (EPM) in this species. Using 8 years of comprehensive paternity, life-history and demographic information for 485 breeding attempts, we show that the frequency of EPP is dependent on (1) social male and female age, (2) the month the female fledged, (3) breeding density and (4) whether it was their first or second reproductive event of the season. In addition, we show that both EPP and EPM are negatively associated with breeding synchrony and clutch size is the most important predictor of EPM. Understanding the drivers of EPP and EPM in species with FECP is important because these are strong determinants of variance in reproductive success and the maintenance of extreme mating behaviour.     

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 %.     

A statistical comparison of naphthenic acids characterized by gas chromatography-mass spectrometry

Naphthenic acids are complex mixtures of alkyl-substituted acyclic and cycloaliphatic carboxylic acids, with the general chemical formula C_nH_2n+zO₂, where n is the carbon number and Z specifies a homologous family. These acids have a variety of commercial uses, including being used as wood preservatives. They are found in conventional and heavy oils, and in the oil sands of northeastern Alberta, Canada. Naphthenic acids are major contributors to the toxicity of tailings waters that result from the oil sands extraction process. Eight naphthenic acids preparations (four from commercial sources and four from the oil sands operations) were derivatized and analyzed by gas chromatography–mass spectrometry. The composition of each mixture was summarized as a three-dimensional plot of the abundance of specific ions (corresponding to naphthenic acids) versus carbon number (ranging from 5 to 33) and Z family (ranging from 0 to −12). The data in these plots were divided into three groups according to carbon number (group 1 contained carbon numbers 5–14, group 2 contained carbon numbers 15–21, and group 3 contained carbon numbers 22–33). A t-test, using arcsine-transformed data, was applied to compare corresponding groups in samples from various sources. Results of the statistical analyses showed differences between various commercial naphthenic acids preparations, and between naphthenic acids from different oil sands ores and tailings ponds. This statistical approach can be applied to data collected by other mass spectrometry methods.     

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.