A gender analysis of quality of life in Saskatoon, Saskatchewan

While many community initiatives have attempted to assess the nature and determinants of their citizens’ quality of life (QOL), these initiatives have produced little about whether the key determinants of life quality differ by gender. Using both quantitative and qualitative data from a recent QOL research project in Saskatoon, Saskatchewan, Canada, this study explores whether factors that predict poor QOL are similar for women and men. The study also examines whether the nature of these gender differences varies across low, medium and high socio-economic status locales. Results showed that men and women were very similar in: (1) their QOL ratings, (2) reports of deterioration in neighborhood QOL, and (3) rating particular aspects of their neighborhood. Few gender differences were also found when analyzing data referring to place characteristics and social cohesion. Multivariate analysis revealed further similarities: (1) being divorced/widowed was a significant predictor of poor QOL, and (2) a negative view of community security issues was associated with deterioration in perceived neighborhood quality of life. For women, however, other variables were important predictors of QOL: being middle aged, being single, and having a poor opinion of the overall quality of their neighborhood. Qualitative analysis revealed that while men and women shared concern about general areas such as safety and neighborhood supports, their perceptions of the details around these issues differed. The multi-method results suggest that urban policy actions should include a gendered discussion of common QOL issues.     

Wind and water: Environmental learning in early colonial New Zealand

Abstract:  In the 19th century, pamphlets and handbooks written for intending settlers often depicted New Zealand as environmentally benign. Upon arrival, however, the newcomers experienced episodes of stormy weather and flooding. They also found greater variations across the country, between the seasons, and from year to year, than they had been led to expect. Primarily by experience, but in part guided by Māori informants, rural people learned to recognize the signs of impending storms and flooding in lowland rivers. They also came to appreciate the less predictable features of eastern South Island weather systems, and found ways to reduce their economic and environmental impact.     

Numerical method of moments for solute transport in a nonstationary flow field conditioned on hydraulic conductivity and head measurements

The unconditional stochastic studies on groundwater flow and solute transport in a nonstationary conductivity field show that the standard deviations of the hydraulic head and solute flux are very large in comparison with their mean values (Zhang et al. in Water Resour Res 36:2107–2120, 2000; Wu et al. in J Hydrol 275:208–228, 2003; Hu et al. in Adv Water Resour 26:513–531, 2003). In this study, we develop a numerical method of moments conditioning on measurements of hydraulic conductivity and head to reduce the variances of the head and the solute flux. A Lagrangian perturbation method is applied to develop the framework for solute transport in a nonstationary flow field. Since analytically derived moments equations are too complicated to solve analytically, a numerical finite difference method is implemented to obtain the solutions. Instead of using an unconditional conductivity field as an input to calculate groundwater velocity, we combine a geostatistical method and a method of moment for flow to conditionally simulate the distributions of head and velocity based on the measurements of hydraulic conductivity and head at some points. The developed theory is applied in several case studies to investigate the influences of the measurements of hydraulic conductivity and/or the hydraulic head on the variances of the predictive head and the solute flux in nonstationary flow fields. The study results show that the conditional calculation will significantly reduce the head variance. Since the hydraulic head measurement points are treated as the interior boundary (Dirichlet boundary) conditions, conditioning on both the hydraulic conductivity and the head measurements is much better than conditioning only on conductivity measurements for reduction of head variance. However, for solute flux, variance reduction by the conditional study is not so significant.     

泥质潮滩的海水-地下水交换量化研究——以莱州湾南岸为例

本文目的是利用数值模拟量化研究莱州湾南岸泥质潮滩的海水-地下水交换。选取的典型剖面长约3 800 m,坡度小于1%,沿剖面选取5个监测点,观测地下水的水头和盐度,分析其随时间的变化规律。概化水文地质条件基础上,用SEAWAT-2000建立二维数值模型,模拟水流的流动并将水头模拟值和观测值进行拟合。基于良好的拟合结果,计算出海底地下水排泄(Submarine Groundwater Discharge,SGD)量为17.46 m3/m/d,海水流入量为2.71 m~3/m/d。文章最后提出了观测和模拟过程中存在的问题,需要今后进一步解决。     

The Impact of the Herbicide Diuron on Photosynthesis in Three Species of Tropical Seagrass

The impact and recovery from exposure to the herbicide diuron [DCMU; 3-(3′,4′-dichlorophenyl)-1,1-dimethylurea] was assessed for three tropical seagrasses, maintained in outdoor aquaria over a 10-day period. Photosynthetic stress was detected using chlorophyll a fluorescence, measured with a Diving-PAM (pulse amplitude modulated fluorometer). Exposure to 10 and 100 μg l⁻¹ diuron resulted in a decline in effective quantum yield (ΔF/F_m^′) within 2 h of herbicide exposure in Cymodocea serrulata, Halophila ovalis and Zostera capricorni. Effective quantum yield also declined over the first 24 h of exposure in H. ovalis at even lower diuron concentrations (0.1 and 1.0 μg l⁻¹). Effective quantum yield in H. ovalis and Z. capricorni was significantly depressed at all diuron concentrations (0.1–100 μg l⁻¹) after 5 days exposure, whereas effective quantum yield in C. serrulata was only significantly lower in plants exposed to highest diuron concentrations (10 and 100 μg l⁻¹). Effective quantum yield depression was present 5 days after plants exposed to 10 and 100 μg l⁻¹ diuron were returned to fresh seawater. These results indicate that exposure to herbicide concentrations present in nearshore Queensland sediments present a potential risk to seagrass functioning.     

Precise orbit determination for the FORMOSAT-3/COSMIC satellite mission using GPS

The joint Taiwan–US mission FORMOSAT-3/ COSMIC (COSMIC) was launched on April 17, 2006. Each of the six satellites is equipped with two POD antennas. The orbits of the six satellites are determined from GPS data using zero-difference carrier-phase measurements by the reduced dynamic and kinematic methods. The effects of satellite center of mass (COM) variation, satellite attitude, GPS antenna phase center variation (PCV), and cable delay difference on the COSMIC orbit determination are studied. Nominal attitudes estimated from satellite state vectors deliver a better orbit accuracy when compared to observed attitude. Numerical tests show that the COSMIC COM must be precisely calibrated in order not to corrupt orbit determination. Based on the analyses of the 5 and 6-h orbit overlaps of two 30-h arcs, orbit accuracies from the reduced dynamic and kinematic solutions are nearly identical and are at the 2–3 cm level. The mean RMS difference between the orbits from this paper and those from UCAR (near real-time) and WHU (post-processed) is about 10 cm, which is largely due to different uses of GPS ephemerides, high-rate GPS clocks and force models. The kinematic orbits of COSMIC are expected to be used for recovery of temporal variations in the gravity field.     

Factors controlling seasonal groundwater and solute flux from snow‐dominated basins

Critical zone influences on hydrologic partitioning, subsurface flow paths and reactions along these flow paths dictate the timing and magnitude of groundwater and solute flux to streams. To isolate first‐order controls on seasonal streamflow generation within highly heterogeneous, snow‐dominated basins of the Colorado River, we employ a multivariate statistical approach of end‐member mixing analysis using a suite of daily chemical and isotopic observations. Mixing models are developed across 11 nested basins (0.4 to 85 km²) spanning a gradient of climatological, physical, and geological characteristics. Hydrograph separation using rain, snow, and groundwater as end‐members indicates that seasonal contributions of groundwater to streams is significant. Mean annual groundwater flux ranges from 12% to 33% whereas maximum groundwater contributions of 17% to 50% occur during baseflow. The direct relationship between snow water equivalent and groundwater flux to streams is scale dependent with a trend toward self‐similarity when basins exceed 5.5 km². We find groundwater recharge increases in basins of high relief and within the upper subalpine where maximum snow accumulation is coincident with reduced conifer cover and lower canopy densities. The mixing model developed for the furthest downstream site did not transfer to upstream basins. The resulting error in predicted stream concentrations points toward weathering reactions as a function of source rock and seasonal shifts in flow path. Additionally, the potential for microbial sulfate reduction in floodplain sediments along a low‐gradient, meandering portion of the river is sufficient to modify hillslope contributions and alter mixing ratios in the analysis. Soil flushing in response to snowmelt is not included as an end‐member but is identified as an important mechanism for release of solutes from these mountainous watersheds. End‐member mixing analysis used in combination with high‐frequency observations reveals important aspects of catchment hydrodynamics across scale.     

Lapse Rate Adjustments of Gridded Surface Temperature Normals in an Area of Complex Terrain: Atmospheric Reanalysis versus Statistical Up-Sampling

The applicability of elevation-regression based interpolation methods for long-term temperature normals, for example the Parameter-elevation Regressions on Independent Slopes Model (PRISM), becomes increasingly limited in data sparse, complex terrain such as that found in mountainous British Columbia (BC), Canada. Recent methods to improve both the resolution and accuracy of interpolation models have focused on the development of “up-sampling” algorithms based on local lapse rate adjustments to the original interpolated surfaces. Lapse rates can be derived from statistical models (e.g., elevation-based polynomial regression equations) or dynamical models (e.g., vertical temperature profiles from numerical weather prediction (NWP) models). This study compares a widely used statistical up-sampling algorithm, ClimateBC, with two NWP reanalysis products, the National Centers for Environmental Prediction/National Corporation for Atmospheric Research, Reanalysis 1 (NCEP1) and the more modern European Centre for Medium-range Weather Forecasts (ECMWF) Reanalysis Interim (ERA-Interim). Thirty-year climate normals for maximum and minimum temperatures were calculated using statistical up-sampling and NWP lapse rate adjustments to existing PRISM-based climate normals at a subset of stations in BC. Specifically, up-sampling model evaluation was performed using 1951–80 climate normals from an independent set of 54 surface stations (1 m to 2347 m) which were not included in the PRISM interpolation or assimilated into the NWP reanalysis products. All models performed similarly for minimum temperature, which showed only a slight improvement over PRISM. For maximum temperature, ClimateBC, NCEP1 and ERA-Interim all performed significantly better than PRISM, in particular during spring and summer. The ERA-Interim reanalysis outperformed NCEP1 in almost all months. The results suggest that lapse rate adjustment algorithms based on reanalysis products will have greater potential as progress continues on developing NWP components.

R ésumé ?[Traduit par la rédaction] L'application des techniques d'interpolation par régression en fonction de l'altitude pour les normales de température à long terme, comme le Parameter-elevation Regressions on Independent Slopes Model (PRISM), devient très difficile dans les régions accidentées pour lesquelles on dispose de données insuffisantes, par exemple les secteurs montagneux de la Colombie-Britannique (C.-B.) au Canada. Les toutes dernières méthodes destinées à augmenter le degré de résolution des modèles d'interpolation et leur précision reposent sur la conception d'algorithmes d’échantillonnage vertical fondés sur l'ajustement des surfaces interpolées originales au moyen du gradient vertical local. Nous pouvons établir les gradients verticaux à partir de modèles statistiques (p. ex., des équations de régression polynomiales en fonction de l'altitude) ou de modèles dynamiques (p. ex., des profils verticaux de température à partir de modèles de prévision numérique du temps (PNT)). Dans la présente étude, nous comparons un algorithme d’échantillonnage vertical statistique communément utilisé, le programme ClimateBC, à deux produits de réanalyse de PNT, celle des National Centres for Environmental Prediction/National Corporation for Atmospheric Research Reanalysis 1 (NCEP1), et la réanalyse provisoire (ERA-Interim) du Centre européen pour les prévisions météorologiques à moyen terme (ECMWF). Les normales climatiques de trente ans pour les températures maximums et minimums ont été calculées en appliquant la méthode d’échantillonnage vertical statistique et l'ajustement du gradient obtenu par PNT aux normales climatiques établies à partir du PRISM pour un sous-ensemble de stations en Colombie-Britannique. Plus particulièrement, nous avons procédé à l’évaluation du modèle d’échantillonnage vertical en nous servant des normales climatiques (1951–1980), pour un ensemble de 54 stations d'observation en surface indépendantes (1?m à 2347?m), exclues du modèle d'interpolation PRISM et des produits de réanalyse de PNT. Pour tous les modèles, nous avons obtenu des résultats comparables pour la température minimum, soit une légère amélioration seulement par rapport au PRISM. Pour la température maximum, nous avons obtenu avec ClimateBC, NCEP1 et ERA-Interim, des résultats nettement plus probants qu'avec PRISM, notamment au printemps et en été. Les réanalyses ERA-Interim ont donné de meilleurs résultats que NCEP1 pour pratiquement tous les mois. D'après ces résultats, le potentiel des algorithmes d'ajustements des gradients verticaux de température, établis à partir de produits de réanalyse se renforcera à mesure que les composantes de PNT se développeront.