Potential Salinity and Temperature Futures for the Chesapeake Bay Using a Statistical Downscaling Spatial Disaggregation Framework

Estuaries are productive and ecologically important ecosystems, incorporating environmental drivers from watersheds, rivers, and the coastal ocean. Climate change has potential to modify the physical properties of estuaries, with impacts on resident organisms. However, projections from general circulation models (GCMs) are generally too coarse to resolve important estuarine processes. Here, we statistically downscaled near-surface air temperature and precipitation projections to the scale of the Chesapeake Bay watershed and estuary. These variables were linked to Susquehanna River streamflow using a water balance model and finally to spatially resolved Chesapeake Bay surface temperature and salinity using statistical model trees. The low computational cost of this approach allowed rapid assessment of projected changes from four GCMs spanning a range of potential futures under a high CO₂ emission scenario, for four different downscaling methods. Choice of GCM contributed strongly to the spread in projections, but choice of downscaling method was also influential in the warmest models. Models projected a ~2–5.5 °C increase in surface water temperatures in the Chesapeake Bay by the end of the century. Projections of salinity were more uncertain and spatially complex. Models showing increases in winter-spring streamflow generated freshening in the Upper Bay and tributaries, while models with decreased streamflow produced salinity increases. Changes to the Chesapeake Bay environment have implications for fish and invertebrate habitats, as well as migration, spawning phenology, recruitment, and occurrence of pathogens. Our results underline a potentially expanded role of statistical downscaling to complement dynamical approaches in assessing climate change impacts in dynamically challenging estuaries.     

Comparison of two alluvial aquifers shows the probable role of river sediments on the release of arsenic in the groundwater of district Vehari,Punjab, Pakistan

The study was done to assess the effect of the river Sutlej on arsenic (As) contamination. Sampling was done from the alluvial plain with increasing distance from the river Sutlej in district Vehari and compared with the study done in the proximity of River Sutlej. Sixty (60) groundwater samples mostly from shallow depths were collected and analyzed for As concentrations. Multivariate statistical tools (PCA and CA), saturation index, piper plots and Gibbs diagrams were used to detect evidence about the interrelationship and sources of As and other water quality variables responsible for groundwater contamination. Results revealed that As concentration ranged from below detection limit to 156 µg/L indicating that 50% samples exceeding the WHO guidelines (10 µg/L) and 17% exceeding the Pakistan National Environmental Quality Standards (NEQS) limits (50 µg/L) Sutlej. The piper plot revealed that water chemistry of the study area was Ca–HCO₃^?, Ca–Mg–Cl, type. Correlations between As and HCO₃^? (r²?=?0.433) was positive, while negative correlations were observed between As–Mn²⁺ and As–Fe²⁺ (r²?=???0.102), (r²?=?0.107) respectively. Geochemical signatures of the groundwater in the study area showed that the As could be released by oxidative dissolution to some extent and elevated evaporation in the arid environment of the study area under the stimulus of alkaline water and high pH (range 7.1–8.4). Although the concentrations are exceeding the WHO limit in 50% of the water samples but, are less than the previous study done in Mailsi near River Sutlej. Further, the concentrations decreased as the distance from the River increased which shows the probable role of sediments deposited by the River Sutlej.     

Evaluation of the effect of river style framework on water quality: application of geomorphological factors

The Tarwal River basin with an area of 6560.20 km² is located in the eastern part of Iranian Kurdistan Province. This river crosses the Qorveh and Dehgolan plains and joins the Ghezel Ozan River in Zanjan Province. The importance of this river as a source for drinking water and agricultural and industrial uses in the region necessitates the need for research in this field. The main purpose of this study is to identify the natural features of the riverbed from the perspective of river geomorphology and to investigate their impact on water quality and river self-purification capacity. To achieve this, the river style framework was employed. To investigate the effects of each style framework on the river, a total of 20 samples from the entrance and outlet of styles were obtained using Impact Assessment method and sampling standards which were later analyzed for their quality parameters including T, pH, EC, TDS, TSS, Na, Ca, Mg, K, Cl, F, NO₂, NO₃, SO₄, PO₄, DO, COD and BOD. The results indicated that the changes in the styles lead to changes in water quality and the impact of each style is greater on the physical parameters than the chemical parameters. The river self-purification capacity varied depending on the style. The maximum and the minimum self-purifications occurred in fine-grained Anabranching and low-sinuosity fine-grained styles, respectively.     

Valuation of socio-economic indicators for progressing urban sustainability under distinctive rubrics

The key objective of the study is to collect the factors which play an important role in the city's sustainability and implementation advantages for the development of cities in future. This article develops an urban sustainability assessment framework by giving GIS-based decision support tools to guide cities toward sustainability. Multicriteria analysis was used as the decision support system and provides an analytical framework for assessing differences in the level of criteria and ranking decision options. It has the capability for assessment of urban sustainability because it brings sustainability criteria from three pillars of sustainability, environmental, social, and economic, which provide an integrated approach for assessment of urban sustainability. The GIS-based multicriteria analysis serves as a sustainability support system that maps urban sustainability and the underlying environmental, social, and economic conditions. The results from the study show that the four cities - Faisalabad, Lahore, Gujranwala, and Multan - have better economic conditions while only Lahore and Faisalabad showed social progress and the remaining cities showed less suitability. For the environmental index, none of the cities attained high suitability. Lahore, Faisalabad, and Rawalpindi showed better conditions than Gujranwala and Multan. It is demonstrated that Punjab cities have made progress in economic condition and improvement in social condition but have poor environmental condition. In the study, the environmental dimension has indicators which have more impact on the urban sustainability. Environmental degradation is observed in all selected regions and not a single region showed suitability toward its environmental condition and due to this none of the cities gained suitable scores for urban sustainability. Consequently, urban sustainability is a multidimensional and dynamic process that needs regular evaluation and monitoring. Thus, this article contends that the tools help to highlight and emphasize those areas that need guidance in achieving urban sustainability.     

Using GIS to improve public health emergency response in rural areas during the COVID-19 crisis: A case study of South Carolina,US

Geographic information systems (GIS) have become essential tools in the public health domain, especially when it comes to monitoring and surveillance of disease. The purpose of this article is to describe and explore the benefits of using GIS to improve public health emergency response during a global pandemic and, in particular, how to effectively optimize the allocation of public health resources in a rural setting using a data-driven approach that considers the multifactorial demand for new COVID-19 testing sites. Herein, the authors present their interprofessional project as an example of such efforts to inform applications for practice. The team developed a GIS-based multicriteria decision analysis model for use by decision-makers and public health experts in similar future planning and response scenarios. Focus is placed on rural characteristics (e.g., accessibility), vulnerable populations, and daily changing conditions (e.g., COVID-19 daily case fluctuations) that create additional challenges for public health agencies and policymakers.     

Relationships between the AE, ap and Dst indices near solar minimum (1974) and at solar maximum (1979)

Three-hourly average values of the Dst, AE and ap geomagnetic activity indices have been studied for 1 years duration near the solar minimum (1974) and also at the solar maximum (1979). In 1979 seven intense geomagnetic storms (Dst < –100 nT) occurred, whereas in 1974 only three were reported. This study reveals: (1) the yearly average of AE is greater in 1974 than in 1979, whereas the inverse seems to be true for the yearly average of Dst, when a higher number of intense storms is present. These averages indicate the kind of activity occurring on the sun as shown in earlier work. (2) The seasonal variation of Dst is higher than that of ap and is almost negligible in AE. (3) The correlation coefficient of ap × AE is in general the highest, as the magnetometers that monitor both indices are close, and is surpassed only by the ap × Dst correlation during geomagnetic storms, when the influence of the ring current is dominant. The correlation of ap × Dst also shows a seasonal variability. (4) For the first time a study of correlation between ap and a linear combination of AE and Dst has also been made. We found higher correlation coefficients in this case as compared to those between ap × Dst and ap ×xs AE.     

Satellite-Based Assessment of the Extent and Changes in the Mangrove Ecosystem of the Niger Delta

This study was carried out with the primary aim of understanding how the mangrove ecosystem in the Niger Delta has been altered recently. Specifically, we determined the spatial extent of the mangrove forest in the Niger Delta using remotely sensed satellite data and estimated changes in the spatial extent of the forest from the mid-1980s through 2003. Overall, about 21,340 hectares of Mangrove forest was lost over the study period. Fieldwork confirmed that these losses were primarily due to urbanization, dredging activities, activities of the oil and gas industries, and the spread of Nypa Palm (Nypa frutican) plant species.     

Experimental vulnerability curves for the residential buildings of Iran

Iran is one of the most seismically active countries of the world located on the Alpine-Himalayan earthquake belt. More than 180,000 people were killed due to earthquakes in Iran during the last five decades. Considering the fact that most Iranians live in masonry and non-engineered houses, having a comprehensive program for decreasing the vulnerability of society holds considerable importance. For this reason, loss estimation should be done before an earthquake strikes to prepare proper information for designing and selection of emergency plans and the retrofitting strategies prior to occurrence of earthquake. The loss estimation process consists of two principal steps of hazard analysis and vulnerability assessment. After identifying the earthquake hazard, the first step is to evaluate the vulnerability of residential buildings and lifelines and also the social and economic impacts of the earthquake scenarios. Among these, residential buildings have specific importance, because their destruction will disturb the daily life and result in casualties. Consequently, the vulnerability assessment of the buildings in Iran is important to identify the weak points in the built environment structure. The aim of this research is to prepare vulnerability curves for the residential buildings of Iran to provide a proper base for estimating probable damage features by future earthquakes. The estimation may contribute fundamentally for better seismic performance of Iranian societies. After a brief review of the vulnerability assessment methods in Iran and other countries, through the use of the European Macroseismic method, a model for evaluating the vulnerability of the Iranian buildings is proposed. This method allows the vulnerability assessment for numerous sets of buildings by defining the vulnerability curves for each building type based on the damage observations of previous earthquakes. For defining the vulnerability curves, a building typology classification is presented in this article, which is representative of Iranian building characteristics. The hazard is described in terms of the macroseismic intensity and the EMS-98 damage grades have been considered for classifying the physical damage to the buildings. The calculated vulnerability indexes and vulnerability curves show that for engineered houses there is not any notable difference between the vulnerability of Iranian and Risk-UE building types. For the non-engineered houses, the vulnerability index of brick and steel structures is less than the corresponding values of the other unreinforced masonry buildings of Iran. The vulnerability index of unreinforced and masonry buildings of Iran are larger than the values of the similar types in Risk-UE and so the Iranian buildings are more vulnerable in this regard.