Against the Trend-An tentative Data Analysis Method using Classical Regression against Machine Learning Approach

The machine learning approach is a new hot topic in recent years that are widely used in different sections, including industries, economy, disaster prediction and politics. After decades’ of development, the available machine learning algorithms are numerous and diverse. Traditional methods such as regression, classical statistical methods, are unfortunately laid aside as non-mainstream. This paper tries to compare the classical regression with machine learning algorithm as classifier. Typical machine learning algorithm support vector machine (SVM) is compared with the classical regression. The classical regression is modified to tailor as classifier. Confidence interval and credibility of prediction from regression is developed to evaluate the prediction uncertainty. Benchmark data from public database is used to demonstrate the performance. The results showed that regression exhibits an efficient computational cost with comparative accuracy

Quantifying the effects of watershed subdivision scale and spatial density of weather inputs on hydrological simulations in a Norwegian Arctic watershed

The effects of watershed subdivisions on hydrological simulations have not been evaluated in Arctic conditions yet. This study applied the Soil and Water Assessment Tool and the threshold drainage area (TDA) technique to evaluate the impacts of watershed subdivision on hydrological simulations at a 5,913-km2 Arctic watershed, Målselv. The watershed was discretized according to four TDA scheme scales including 200, 2,000, 5,000, and 10,000 ha. The impacts of different TDA schemes on hydrological simulations in water balance components, snowmelt runoff, and streamflow were investigated. The study revealed that the complexity of terrain and topographic attributes altered significantly in the coarse discretizations: (1) total stream length (−47.2 to −74.6%); (2) average stream slope (−68 to −83%); and (3) drainage density (−24.2 to −51.5%). The spatial density of weather grid integration reduced from −5 to −33.33% in the coarse schemes. The annual mean potential evapotranspiration, evapotranspiration, and lateral flow slightly decreased, while areal rainfall, surface runoff, and water yield slightly increased with the increases of TDAs. It was concluded that the fine TDAs produced finer and higher ranges of snowmelt runoff volume across the watershed. All TDAs had similar capacities to replicate the observed tendency of monthly mean streamflow hydrograph, except overestimated/underestimated peak flows. Spatial variation of streamflow was well analyzed in the fine schemes with high density of stream networks, while the coarse schemes simplified this. Watershed subdivisions affected model performances, in the way of decreasing the accuracy of monthly streamflow simulation, at 60% of investigated hydro-gauging stations (3/5 stations) and in the upstream. Furthermore, watershed subdivisions strongly affected the calibration process regarding the changes in sensitivity ranking of 18 calibrated model parameters and time it took to calibrate

A Review of Hydrological Models Applied in the Permafrost-Dominated Arctic Region

The Arctic region is the most sensitive region to climate change. Hydrological models are fundamental tools for climate change impact assessment. However, due to the extreme weather conditions, specific hydrological process, and data acquisition challenges in the Arctic, it is crucial to select suitable hydrological model(s) for this region. In this paper, a comprehensive review and comparison of different models is conducted based on recently available studies. The functionality, limitations, and suitability of the potential hydrological models for the Arctic hydrological process are analyzed, including: (1) The surface hydrological models Topoflow, DMHS (deterministic modeling hydrological system), HBV (Hydrologiska Byråns Vattenbalansavdelning), SWAT (soil and water assessment tool), WaSiM (water balance simulation model), ECOMAG (ecological model for applied geophysics), and CRHM (cold regions hydrological model); and (2) the cryo-hydrogeological models ATS (arctic terrestrial simulator), CryoGrid 3, GEOtop, SUTRA-ICE (ice variant of the existing saturated/unsaturated transport model), and PFLOTRAN-ICE (ice variant of the existing massively parallel subsurface flow and reactive transport model). The review finds that Topoflow, HBV, SWAT, ECOMAG, and CRHM are suitable for studying surface hydrology rather than other processes in permafrost environments, whereas DMHS, WaSiM, and the cryo-hydrogeological models have higher capacities for subsurface hydrology, since they take into account the three phase changes of water in the near-surface soil. Of the cryo-hydrogeological models reviewed here, GEOtop, SUTRA-ICE, and PFLOTRAN-ICE are found to be suitable for small-scale catchments, whereas ATS and CryoGrid 3 are potentially suitable for large-scale catchments. Especially, ATS and GEOtop are the first tools that couple surface/subsurface permafrost thermal hydrology. If the accuracy of simulating the active layer dynamics is targeted, DMHS, ATS, GEOtop, and PFLOTRAN-ICE are potential tools compared to the other models. Further, data acquisition is a challenging task for cryo-hydrogeological models due to the complex boundary conditions when compared to the surface hydrological models HBV, SWAT, and CRHM, and the cryo-hydrogeological models are more difficult for non-expert users and more expensive to run compared to other models

Effect of temperature on the leaching of heavy metals from nickel mine tailings in the arctic area, Norway

The leaching of heavy metals from tailings deposit due to the oxidation of sulphidic tailings and formation of acidic leachate is considered a high risk to the surrounding environment. Temperature plays an important role in the leaching of heavy metals from tailings in changing acid-based environment, especially in the Arctic area. To investigate how the temperature variation affected metal release from tailings in the Arctic area, a series of column leaching experiments was conducted under four temperature situations (5°C, 10°C, 14°C and 18°C). Physicochemical properties, Fe, Zn, Ni and Mn concentrations of leachates at each cycle were measured, and multivariate statistical analysis was applied to research the effect of temperature on heavy metals leaching from tailings in the Arctic area. The results showed that higher temperatures encouraged tailings to oxidation and sulfuration of and promoted heavy metal release from the tailings through precipitation and erosion. Ni, Zn and Mn have similar releasing resources from tailings and positive correlation in the leaching activity. Rising temperature accelerated Fe leaching; Fe leaching promoted leaching of the other metals, especially of Mn. Appropriately increase temperature will accelerate oxidization and sulfidization of the tailings, promote acid generation and increase TDS and, finally, promote the release of heavy metals. Climate change, with rising temperatures increasing the risk of heavy metals leaching from the tailings, should be given greater attention. Keeping tailings away from the appropriate temperature and in a higher alkalinity is a good method to control the leaching of heavy metals from tailings

Assessment of the impacts of landscape patterns on water quality in Trondheim rivers and Fjord, Norway

Due to the impacts of hydrological and ecological processes on water quality, discharges from upstream catchments have induced significant pollution to the recipients. This study aims to investigate the possible pollution sources from catchments with different types of land use and landscape patterns and develop the relationships between water quality and the catchment hydro-geological and environmental variables. Data from 10 monitoring sites in Trondheim formulated the basis of the case study. Thermotolerant coliform bacteria (TCB) and total phosphorus (TP) were applied as main indicators to represent the water quality in the recipient rivers, streams and in Trondheim Fjord. Based on the GIS-oriented spatial analysis, 15 hydro-geographical and landscape parameters were selected as explanatory variables. Multiple linear regression (MLR) models were developed at catchment and river reach scales to study correlations between the explanatory variables and the response variables, TCB and TP, in rain and snow seasons. The study showed that the spatial landscape patterns resulted in differences in the concentrations of TCB and TP in the recipients. The agricultural land was shown to be the main pollution source, leading to a higher concentration of TP in streams. Buildings, roads, and other impervious areas have induced an increase in both TCB and TP. In contrast, the forest areas, lakes, river density and steep river slopes were shown to have capacity to filter incoming P-rich runoff, thus prevent pollutant conveyance and accumulation in recipients

Modelling the transport of oil after a proposed oil spill accident in Barents Sea and its environmental impact on Alke species

OA Green publisher. Can archive pre-print and post-print or publisher's version/PDF. Link to publisher's version: http://doi.org/10.1088/1755-1315/82/1/012010Accidental oil spills can have significant effect on the coastal and marine environment. As the oil extraction and exploration activities increase in the Barents Sea, it is of increasingly importance to investigate the potential oil spill incidents associated with these activities. In this study, the transport and fate of oil after a proposed oil spill incident in Barents Sea was modelled by oil spill contingency and response model OSCAR. The possibility that the spilled oil reach the open sea and the strand area was calculated respectively. The influence area of the incident was calculated by combining the results from 200 simulations. The possibility that the spilled oil reach Alke species, a vulnerable species and on the National Red List of birds in Barents Sea, was analyzed by combining oil spill modelling results and the Alke species distribution data. The results showed that oil is dominated with a probability of 70-100% in the open sea to reach an area in a radius of 20km from the release location after 14 days of release. The probability reduces with the increasing distances from the release location. It is higher possibility that the spilled oil will reach the Alke species in the strand area than in the open sea in the summer. The total influence area of the release is 11 429 km2 for the surface water and 1528 km2 for the coastal area

Climatic Signals in Wood Property Variables of Picea Crassifolia

Little attention has been given to climatic signals in wood properties. In this study, ring width(RW), annual average microfibril angle (MFA), annual average tracheid radial diameter (TRD), andannual average density (DEN), as the annual and intra-annual wood property variables, were measured at high resolution by SilviScan-3 on dated Picea crassifolia trees. Dendroclimatological methods were used to analyze climatic signals registered in wood property variables. RW, MFA, and TRD negatively correlated with temperature and positively correlated with precipitation in the growing season, whereas the reverse was true for DEN. Climatic signals recorded in the earlywood were similar to those measured for the full width of the annual rings. Climatic signals recorded in latewood were very weak except for latewood MFA. This study showed that wood property variables could be extensive resources for learning more about the influences of climate on tree growth and how trees adapt to ongoing climate change

Spatiotemporal patterns of particulate matter (PM) and associations between PM and mortality in Shenzhen, China

DOI: 10.1186/s12889-016-2725-6Background: Most studies on air pollution exposure and its associations with human health in China have focused on the heavily polluted industrial areas and/or mega-cities, and studies on cities with comparatively low air pollutant concentrations are still rare. Only a few studies have attempted to analyse particulate matter (PM) for the vibrant economic centre Shenzhen in the Pearl River Delta. So far no systematic investigation of PM spatiotemporal patterns in Shenzhen has been undertaken and the understanding of pollution exposure in urban agglomerations with comparatively low pollution is still limited. Methods: We analyze daily and hourly particulate matter concentrations and all-cause mortality during 2013 in Shenzhen, China. Temporal patterns of PM (PM2.5 and PM10) with aerodynamic diameters of 2.5 (10) μm or less (or less (including particles with a diameter that equals to 2.5 (10) μm) are studied, along with the ratio of PM2.5 to PM10. Spatial distributions of PM10 and PM2.5 are addressed and associations of PM10 or PM2.5 and all-cause mortality are analyzed. Results: Annual average PM10 and PM2.5 concentrations were 61.3 and 39.6 μg/m3 in 2013. PM2.5 failed to meet the Class 2 annual limit of the National Ambient Air Quality Standard. PM2.5 was the primary air pollutant, with 8.8 % of days having heavy PM2.5 pollution. The daily PM2.5/PM10 ratios were high. Hourly PM2.5 concentrations in the tourist area were lower than downtown throughout the day. PM10 and PM2.5 concentrations were higher in western parts of Shenzhen than in eastern parts. Excess risks in the number of all-cause mortality with a 10 μg/m3 increase of PM were 0.61 % (95 % confidence interval [CI]: 0.50–0.72) for PM10, and 0.69 % (95 % CI: 0.55–0.83) for PM2.5, respectively. The greatest ERs of PM10 and PM2.5 were in 2-day cumulative measures for the all-cause mortality, 2-day lag for females and the young (0–65 years), and L02 for males and the elder (>65 years). PM2.5 had higher risks on all-cause mortality than PM10. Effects of high PM pollution on mortality were stronger in the elder and male. Conclusions: Our findings provide additional relevant information on air quality monitoring and associations of PM and human health, valuable data for further scientific research in Shenzhen and for the on-going discourse on improving environmental policie

A Two-Year Surveillance of 2009 Pandemic Influenza A (H1N1) in Guangzhou, China: From Pandemic to Seasonal Influenza?

In this two-years surveillance of 2009 pandemic influenza A (H1N1) (pH1N1) in Guangzhou, China, we reported here that the scale and duration of pH1N1 outbreaks, severe disease and fatality rates of pH1N1 patients were significantly lower or shorter in the second epidemic year (May 2010-April 2011) than those in the first epidemic year (May 2009-April 2010) (P<0.05), but similar to those of seasonal influenza (P>0.05). Similar to seasonal influenza, pre-existing chronic pulmonary diseases was a risk factor associated with fatal cases of pH1N1 influenza. Different from seasonal influenza, which occurred in spring/summer seasons annually, pH1N1 influenza mainly occurred in autumn/winter seasons in the first epidemic year, but prolonged to winter/spring season in the second epidemic year. The information suggests a tendency that the epidemics of pH1N1 influenza may probably further shift to spring/summer seasons and become a predominant subtype of seasonal influenza in coming years in Guangzhou, China