This study reports the spatio-temporal changes in water quality of Nullah Aik, tributary of the Chenab River, Pakistan. Stream water samples were collected at seven sampling sites on seasonal basis from September 2004 to April 2006 and were analyzed for 24 water quality parameters. Most significant parameters which contributed in spatio-temporal variations were assessed by statistical techniques such as Hierarchical Agglomerative Cluster Analysis (HACA), Factor Analysis/Principal Components Analysis (FA/PCA), and Discriminant Function Analysis (DFA). HACA identified three different classes of sites: Relatively Unimpaired, Impaired and Less Impaired Regions on the basis of similarity among different physicochemical characteristics and pollutant level between the sampling sites. DFA produced the best results for identification of main variables for temporal and spatial analysis and separated eight parameters (DO, hardness, sulphides, K, Fe, Pb, Cr and Zn) that accounted 89.7% of total variations of spatial analysis. Temporal analysis using DFA separated six parameters (E.C., TDS, salinity, hardness, chlorides and Pb) that showed more than 84.6% of total temporal variation. FA/PCA identified six significant factors (sources) which were responsible for major variations in water quality dataset of Nullah Aik. The results signify that parameters identified by statistical analyses were responsible for water quality change and suggest the possibility of industrial, municipal and agricultural runoff, parent rock material contamination. The results suggest dire need for proper management measures to restore the water quality of this tributary for a healthy and promising aquatic ecosystem and also highlights its importance for objective ecological policy and decision making process.

11A new land-surface parameterization scheme, namely the Soil, Vegetation, and Snow 12 (SVS) scheme, has recently been developed at Environment and Climate Change Canada to 13 replace the operationally used ISBA (Interactions between Soil, Biosphere, and Atmosphere) 14 scheme. The new scheme is designed to address a number of weaknesses and limitations of 15 ISBA that have been identified over the last decade. Unlike ISBA, which calculates a single 16 energy budget for the different land-surface components, SVS introduces a new tiling approach 17 that includes separate energy budgets for bare ground, vegetation, and two different snow packs 18 (over bare ground and low vegetation, and under high vegetation). The inclusion of a 19 photosynthesis module as an option to determine the surface stomatal resistance is another 20 significant addition in SVS. The representation of vertical water transport through soil has also 21 been substantially improved in SVS with the introduction of multiple soil layers. Overall, offline 22 simulations conducted in the present study demonstrated clear improvements in warm season 23 Manuscript (non-LaTeX) Click here to download Manuscript (non-LaTeX) Husain_et_al_20160331-TEXT-and-FIGURES.docx 2 meteorological predictions with SVS compared to the ISBA scheme. The results also revealed 1 considerable reduction of standard error in the SVS-predicted L-band brightness temperature. 2This demonstrates the scheme's ability for better hydrological prediction and its potential for 3 providing more accurate soil moisture analysis. The impact of the photosynthesis module within 4 the current implementation of SVS is, however, found to be negligible on near-surface 5 meteorological prediction and slightly negative for brightness temperature. 6 7

Numerical weather prediction is moving toward the representation of finescale processes such as the interactions between the sea-breeze flow and urban processes. This study investigates the ability and necessity of using kilometer-to subkilometer-scale numerical simulations with the Canadian urban modeling system over the complex urban coastal area of Vancouver, British Columbia, Canada, during a sea-breeze event.Observations over the densely urbanized areas, collected from the Environmental Prediction in Canadian Cities (EPiCC) network and from satellite imagery, are used to evaluate several aspects of the urban boundary layer features simulated in three model configurations with different grid spacings (2.5 km, 1 km, and 250 m). In agreement with the observations, results from the numerical experiments with 1-km and 250-m grid spacings suggest that two sea-breeze flows converge over the residential areas of Vancouver. The resulting convergence line oscillates around the hill ridge, depending on thermal contrast and flow strength. This propagation mode impacts the growing urban boundary layer, with the presence of subsidence and entrainment events. Urban-induced circulation is superimposed with the sea-breeze circulation and realistically slows down the propagation of the sea-breeze front to the south. A clear improvement is obtained for numerical experiments with 1-km instead of 2.5-km grid spacing. The use of subkilometer grid spacing provides a more detailed representation of the surface thermal forcing and of local circulations, with results more sensitive to the airflow variability and, thus, to the location of measurement sites. Joint analyses of kilometer-and subkilometerscale numerical experiments are thus recommended for different environmental applications.

A new land surface scheme has been developed at Environment and Climate Change Canada (ECCC) to provide surface fluxes of momentum, heat, and moisture for the Global Environmental Multiscale (GEM) atmospheric model. In this study, the performance of the Soil, Vegetation, and Snow (SVS) scheme in estimating the surface and root-zone soil moisture is evaluated against the Interactions between Soil, Biosphere, and Atmosphere (ISBA) scheme currently used operationally at ECCC within GEM for numerical weather prediction. In addition, the sensitivity of SVS soil moisture results to soil texture and vegetation data sources (type and fractional coverage) has been explored. The performance of SVS and ISBA was assessed against a large set of in situ observations as well as the brightness temperature data from the Soil Moisture Ocean Salinity (SMOS) satellite over North America. The results indicate that SVS estimates the time evolution of soil moisture more accurately, and compared to ISBA, results in higher correlations with observations and reduced errors. The sensitivity tests carried out during this study revealed that the SVS soil moisture results are not affected significantly by the soil texture data from different sources. The vegetation data source, however, has a major impact on the soil moisture results predicted by SVS, and accurate specification of vegetation characteristics is therefore crucial for accurate soil moisture prediction.

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Inconsistencies may arise in numerical weather prediction models—that are based on semi-Lagrangian advection—when the governing dynamical and the kinematic trajectory equations are discretized in a dissimilar manner. This study presents consistent trajectory calculation approaches, both in the presence and absence of off-centering in the discretized dynamical equations. Both uniform and differential off-centering in the discretized dynamical equations have been considered. The proposed consistent trajectory calculations are evaluated using numerical experiments involving a nonhydrostatic two-dimensional theoretical mountain case and hydrostatic global forecasts. The experiments are carried out using the Global Environmental Multiscale model. Both the choice of the averaging method for approximating the velocity integral in the discretized trajectory equations and the interpolation scheme for calculating the departure positions are found to be important for consistent trajectory calculations. Results from the numerical experiments confirm that the proposed consistent trajectory calculation approaches not only improve numerical consistency, but also improve forecast accuracy.

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