Potential Risk Areas Research Articles

Areas under high ozone and nitrogen loads are spatially disjunct in Czech forests

It is widely accepted that excessive loads of nitrogen (N) deposition and ambient ozone (O3) endanger natural ecosystems and the environment. Despite substantial reductions in emissions since the early 1990s both in the Czech Republic and in neighbouring countries, neither O3 exposures nor N deposition have yet decreased to acceptable levels relative to the recommended thresholds. Based on long-term monitoring and high-quality data, we have indicated the areas of special risk due to high N deposition and O3 exposures in Czech forests in 2000–2015. The areas of potential risk denote those forests under the highest loads of N deposition and O3 exposure on a regular basis. The underlying classification approach is relativistic, i.e. based ultimately on quartiles of pollution intensities and not derived from critical limits or loads. The forest areas under the highest O3 exposures and N deposition are spatially disjunct. The highest O3 exposures are in the southern and the highest N deposition is in the northern Czech Republic. In contrast to our assumption, only 1322 km2, i.e. 4.6% of the total forested area (28,782 km2) are overlapping areas with a potential risk due both to high O3 exposures and to N deposition. Our results provide valuable input information for a more detailed environmental analysis, anticipated in the future, addressing to what extent the indicated areas at potential risk are associated with the actual negative impacts on forests.

A study on antimony migration in soils using an artificial neural network model and a convection-dispersion diffusion model

We conducted a small soil column penetration test and lysimeter experiment in four soils (Isohumosol, Ferrosol, Primosol, and Sandy soil), to generate a migration model for antimony (Sb) in soil based on the convection-diffusion equation. Variation of the Sb concentration was also simulated by the Artificial neural networks model (ANN) model. The convection-dispersion model will provide a reference for the transfer of Sb in the environment. The results agreed with the laboratory measurements with an R2 of 0.79–0.98 in the Isohumosol, Ferrosol, and Primosol. It was found that the convection-dispersion model could be used to explain the migration of Sb in soil. The areas of high potential ecological risk for the Ferrosol, Isohumosol, and Primosol soils were at the soil surface, and there was a low to moderate potential ecological risk for the deep soil profile. Artificial neural network model fitting results showed that Sb migration was rapid in Sandy soil because these soils have a weak Sb-adsorption capacity. The Sb concentration in the surface soil was much higher than at other soil depths. Little variation was observed in the Sandy soil and Isohumosol, indicating a weak Sb-adsorption capacity for these soils. The Sb migration model will help us to describe and predict Sb pollution in the soil environment, providing the basis for managing Sb-contaminated soil.

Identifying and forecasting potential biophysical risk areas within a tropical mangrove ecosystem using multi-sensor data

Mangroves are one of the most productive ecosystems known for provisioning of various ecosystem goods and services. They help in sequestering large amounts of carbon, protecting coastline against erosion, and reducing impacts of natural disasters such as hurricanes. Bhitarkanika Wildlife Sanctuary in Odisha harbors the second largest mangrove ecosystem in India. This study used Terra, Landsat and Sentinel-1 satellite data for spatio-temporal monitoring of mangrove forest within Bhitarkanika Wildlife Sanctuary between 2000 and 2016. Three biophysical parameters were used to assess mangrove ecosystem health: leaf chlorophyll (CHL), Leaf Area Index (LAI), and Gross Primary Productivity (GPP). A long-term analysis of meteorological data such as precipitation and temperature was performed to determine an association between these parameters and mangrove biophysical characteristics. The correlation between meteorological parameters and mangrove biophysical characteristics enabled forecasting of mangrove health and productivity for year 2050 by incorporating IPCC projected climate data. A historical analysis of land cover maps was also performed using Landsat 5 and 8 data to determine changes in mangrove area estimates in years 1995, 2004 and 2017. There was a decrease in dense mangrove extent with an increase in open mangroves and agricultural area. Despite conservation efforts, the current extent of dense mangrove is projected to decrease up to 10% by the year 2050. All three biophysical characteristics including GPP, LAI and CHL, are projected to experience a net decrease of 7.7%, 20.83% and 25.96% respectively by 2050 compared to the mean annual value in 2016. This study will help the Forest Department, Government of Odisha in managing and taking appropriate decisions for conserving and sustaining the remaining mangrove forest under the changing climate and developmental activities.

Decision‐Making and Flood Risk Uncertainty: Statistical Data Set Analysis for Flood Risk Assessment

AbstractFloods are a significant issue worldwide with over 1 billion people living in areas of potential flood risk. With climate change these risks are anticipated to increase, but there is great uncertainty associated with future projections, which poses challenges to those making decisions on flood management. Climate change projections which explicitly capture climate model parameters uncertainty are available in the United Kingdom; however, their use by practitioners, rather than researchers, has so far been limited. This paper takes an inclusive approach, working with end users, to answer practitioner relevant questions regarding future climate change influence for flood hazards. The method developed demonstrates the findings across Scotland, United Kingdom and investigates (i) the regional impacts to extreme flows and the associated uncertainty, (ii) the changes in extreme peak flows in terms of frequency, and (iii) the physical and hydroclimatic factors controlling these results. The method used industry standard statistical methods, driven by practitioner requirements, and explicitly includes the statistical uncertainty in the climate and extreme value distribution models in extreme flow estimates. Results are analyzed using hierarchical clustering and decision tree analysis, and the subsequent trends are shown to be constrained by different hydrological, climatic, and physical catchment characteristics. Results suggest that there is a high probability that low return period peak flow events would exceed the baseline extreme high return period event by the 2080s, which has significant implications for future‐proofing infrastructure design. This study provides a practical example and outputs resulting from collaboration between research and industry practices.

Pseudo-nitzschia sp. diversity and seasonality in the southern North Sea, domoic acid levels and associated phytoplankton communities

The diversity, toxicity and seasonality of Pseudo-nitzschia sp. were investigated from February to November 2012 in the southern Bight of the North Sea (SBNS) along the French coast. The identification of Pseudo-nitzschia species in this area was addressed for the first time in this study. Our results revealed a low species richness (3 distinct species) in association with moderate (102 pg mL−1) to high (263 pg mL−1) domoic acid (DA) levels in autumn and spring, respectively.Pseudo-nitzschia succession corresponded to the dominance of P. delicatissima in April–May (86% of total diatoms) as a co-occurring species of the Phaeocystis globosa bloom. Following the Phaeocystis bloom (May–September), P. pungens dominated markedly over P. fraudulenta and P. delicatissima and was the only species present in autumn, although at low abundance (<1000 cell L−1). The results of this study support the idea that Pseudo-nitzschia seasonality in the SBNS relies principally on temperature and nutrient availability (DIN and silicates), which, in turn, depend on locally fluctuating environmental conditions (rainfalls and winds). This study highlights the potential for the SBNS to be a potential risk area in regard to the possible impacts of DA on marine resources and the DA transfer through marine food webs. This is of particular concern since DA concentration in seawater was not systematically correlated to potentially toxic Pseudo-nitzschia abundance.

Spatiotemporal patterns and determinants of dengue at county level in China from 2005–2017

ObjectiveTo identify the high risk spatiotemporal clusters of dengue cases and explore the associated risk factors. MethodsMonthly indigenous dengue cases in 2005-2017 were aggregated at county level. Spatiotemporal cluster analysis was used to explore dengue distribution features using SaTScan9.4.4 and Arcgis10.3.0. In addition, the influential factors and potential high risk areas of dengue outbreaks were analyzed using ecological niche models in Maxent 3.3.1 software. ResultsWe found a heterogeneous spatial and temporal distribution pattern of dengue cases. The identified high risk region in the primary cluster covered 13 counties in Guangdong Province and in the secondary clusters included 14 counties in Yunnan Province. Additionally, there was a nonlinear association between meteorological and environmental factors and dengue outbreaks, with 8.5%–57.1%, 6.7%–38.3% and 3.2%–40.4% contribution from annual average minimum temperature, land cover and annual average precipitation, respectively. ConclusionsThe high risk areas of dengue outbreaks mainly are located in Guangdong and Yunnan Provinces, which are significantly shaped by environmental and meteorological factors, such as temperature, precipitation and land cover.

Risk assessment of desertification using GIS in upper and lower reaches of Mond basin, Iran

The present paper attempts to develop a new model by considering various indicators of different types of land degradation or desertification. These types include water erosion, soil salinity, vegetation degradation, and lowering of ground water table. The indicators can be used to find areas with higher rates of degradation which are called Potential Risk Areas (risky zones) in this paper, and can also be used to estimate the probability that degradation will increase in these areas. The Mond river basin, located in the southern part of Iran, has been selected as a test area to assess the risk and kind of desertification. For this purpose two sub basins of the Khormuj and Khane-Zenian & Siakh-Darengun have been chosen for detailed study as these two provide enough variation in climatic conditions like rainfall and topography. The different kinds of data gathered from records and published reports of the different governmental offices of Iran have been used for this purpose. The thresholds for the severity classes of indicators have been established and then the hazard map for each indicator of types of desertification has been prepared in a GIS. The risk maps of water erosion, soil salinization, lowering of water table, and vegetation degradation have been produced for both sub basins. Areas on the maps are assigned to risk classes on the basis of risk scores derived by considering the cumulative effects of all indicators overlying the area in the GIS. It was possible to distinguish the areas under ‘actual risk’ from areas under ‘potential risk’ of desertification types. Also areas under potential risk are classified to subclasses with different probability level to show a statistical picture of risk in future. The final map of risk of desertification is produced by overlaying all four maps of degradation types. Between the two basins the overall environmental condition in the Khormuj sub basin is worse. Results show that potential risk areas are much widespread than areas under actual risk in the upper reaches (of both sub basins) of Mond basin, indicating further threat of land degradation or desertification in the future. The percent of areas under actual risk are much more extensive in the lower reaches (Khormuj sub basin), indicating the higher degradation at present. It is hoped that this attempt using GIS will be found applicable for other regions of the world.

Scrub typhus in Jiangsu Province, China: epidemiologic features and spatial risk analysis

BackgroundWith the increasing incidence of scrub typhus in recent years, it is of great value to analyse the spatial and temporal distribution of scrub typhus by applying micro-geographical studies at a reasonably fine scale, and to guide the control and management.MethodsWe explored the use of maximum entropy modelling method to confirm the spatial and temporal distribution of scrub typhus according to the occurrence locations of human cases in Jiangsu Province. The risk prediction map under specific environmental factors was therefore drawn by projecting the training model across China. The area under the curve and the omission rate were used to validate the model. Meanwhile, Jackknife tests were applied to enumerate the contribution of different environmental variables, then to predict the final model. The predicted results were validated by using China’s known occurrence locations.ResultsA total of 566 occurrence locations with known 4865 scrub typhus occurrence records were used in our study. The number of female cases was higher than male cases, with a proportion of 1.17:1, and people in any age group could be infected. The number of cases presented an inverted-U relation with age. The percentage of cases aged from 60 to 69 years old was the highest, accounting for 30.50% of all cases. Ecological niche modelling results indicated that the locations of scrub typhus cases, which was of great importance in the disease transmission cycle, had a certain ecological niche with environmental elements in many dimensions. Moreover, the key environmental factors for determining scrub typhus occurrence were temperature (including temperature seasonality, min temperature of coldest month, mean diurnal range, and monthly mean temperature), precipitation of wettest month, and land cover types. The risk prediction maps indicated that mid-eastern China was the potential risk areas for scrub typhus of “autumn type”. Meanwhile, in our results, Guangdong Province was the high-risk region for “autumn type” scrub typhus, where cases were mainly reported as “summer type”.ConclusionThe combination of climatic and geographic factors with GIS methods is an appropriate option to analyse and estimate the spatial and temporal distribution of scrub typhus.

Spatial relationship between the field-measured ambient gamma dose equivalent rate and geological conditions in a granitic area, Velence Hills, Hungary: An application of digital spatial analysis methods

In order to estimate the annual dose that the public receive from natural radioactivity, the identification of the potential risk areas is required which, in turn, necessitates understanding the relationship between the spatial distribution of natural radioactivity and the geogenic risk factors (e.g., rock types, presence of dikes, faults, physical conditions of soil, etc.). A detailed spatial analysis of outdoor ambient gamma dose equivalent rate was performed in the western side of Velence Hills, the largest outcropped granitic area in Hungary. In order to assess the role of local geology in the spatial distribution of gamma dose rates, field measurements were carried out at ground level at 300 sites along a 250 m x 250 m regular grid in a total surface of 19.8 km2. Digital image processing methods were applied to identify anomalies, heterogeneities and spatial patterns in the measured gamma dose rates, including local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction, second derivative profile curvature, local variability, lineament density, 2D autocorrelation and directional variogram analyses. Statistical inference shows that different gamma dose rate levels are associated with the geological formations, with the highest level on the Carboniferous granite including outlying values. Moreover, digital image processing reveales that linear gamma dose rate spatial features are parallel to the SW-NE dike system and to the NW-SE main fractures. The results of this study underline the importance of understanding the role of geogenic risk factors influencing the ambient gamma dose equivalent rate received by public. The study also demonstrates the power of the image processing techniques for the identification of spatial pattern in field-measured geogenic radiation.

Rockburst occurrences and microseismicity in a longwall panel experiencing frequent rockbursts

A rockburst is a kind of dynamic geological hazard faced by engineers and researchers. Identification of a potential rockburst risk area (PRBRA) allows effective, targeted measures to be taken mitigate these hazards. To provide a reference for determining PRBRA in longwall panels with similar conditions, an in situ investigation that lasted for over three years was conducted on LW3401 in the Junde coal mine which experienced a total of 22 rockbursts. The investigation involves rockburst consequences (including the location, length, degree, and modes of the ensuing damage), seismic features of rockburst (including the source and seismic energy), and the relationship between rockbursts and microseismicity. Results show that damaged areas are mostly within the 18 m behind the excavation face, or up to 30 m ahead of the coalface. Lengths of damaged sections of roadways are within 95 m (and 115 m) during roadway excavation (and coalface advancing operations). The seismic energy of rockbursts ranges from 1.60 × 104 to 8.21 × 106 J. Sources of rockbursts lie mostly within 145 m of damage locations. Before a rockburst, sources of microseismic (MS) events begin to cluster around the roadway or coalface. Daily total energy and MS event counts rose, then fell, before a rockburst occurred. PRBRAs in a roadway lie within a certain distance behind the excavation face, or ahead of the coalface. When high-energy MS events are found in close proximity to a PRBRA, the rockburst risk in a given panel increases.

Analysis of ground deformation based on GPS in Sanshandao gold mine, China

Sanshandao Gold Mine is the first and largest mine operating below sea level in China. Mining has been practiced in this region for at least 25 years. In recent years, buildings above the mining area have been extensively damaged. GPS (with 315 monitoring points) was used to monitor the ground deformation since 2009. Ground deformation induced by mining is much more complex in metal mine than that in coal mines due to the well-developed joints, high tectonic stress and several intersecting faults. All of the factors are analyzed in this study. The results show that discontinuous deformation has occurred on the surface because of the sliding to F3 (name of fault), and there are two motion patterns of F3 during the mining process. Additionally, joints in rock masses with steep dip angles contribute to the vertical displacement and joints with shallow dip angles contribute to the horizontal displacement. Meanwhile, high tectonic stress dramatically enlarges the scale of ground deformation, especially with respect to the horizontal displacement. This deformation results in a striped formation of compressed and stretched regions. Additionally, high-risk and potential risk areas are identified in this study. Finally, the successive data measured since 2009 can contribute to a deeper understanding of ground deformation in metal mine.

Spatial electromagnetic field intensity modelling of global system for mobile communication base stations in the Istanbul Technical University Ayazaga campus area.

The rapid development of the global system for mobile communication services and the consequent increased electromagnetic field (EMF) exposure to the human body have generated debate on the potential danger with respect to human health. The many research studies focused on this subject have, however, not provided any certain evidence about harmful consequences due to mobile communication systems. On the other hand, there are still views suggesting such exposure might affect the human body in different ways. To reduce such effects to a minimum, the International Commission on Non-Ionizing Radiation Protection (ICNIRP) has declared boundary values for the energy released by the base stations, which are the main source of the electromagnetic fields. These values are accepted by many countries in various parts of the world. The aim of this study was to create EMF intensity maps for the area covered by Istanbul Technical University (ITU) and find areas of potential risk with regard to health considering the current situation and future trends. In this study, the field intensities of electromagnetic signals issued at the frequencies of 900 and 1800 MHz were measured in V/m at 29 pre-specified survey points using a spectrum analyzer (Spectran HF-6065). Geographic information systems and spatial interpolation techniques were used to produce EMF intensity maps. Three different spatial interpolation methods, minimum mean square error, Radial Basis and Empirical Bayesian Kriging, were compared. The results were geographically analyzed and the measurements expressed as heat maps covering the study area. Using these maps, the values measured were compared with the EMF intensity standards issued by ICNIRP. The results showed that the exposure levels to the EMF intensities were all within the ICNIRP limits at the ITU study area. However, since the EMF intensity level with respect to human health is not known, it is not possible to confirm if these levels are safe or not.

Using sequential indicator simulation method to define risk areas of soil heavy metals in farmland.

The heavy metals in soil have serious impacts on safety, ecological environment and human health due to their toxicity and accumulation. It is necessary to efficiently identify the risk area of heavy metals in farmland soil, which is of important significance for environment protection, pollution warning and farmland risk control. We collected 204 samples and analyzed the contents of seven kinds of heavy metals (Cu, Zn, Pb, Cd, Cr, As, Hg) in Zengcheng District of Guangzhou, China. In order to overcame the problems of the data, including the limitation of abnormal values and skewness distribution and the smooth effect with the traditional kriging methods, we used sequential indicator simulation method (SISIM) to define the spatial distribution of heavy metals, and combined Hakanson index method to identify potential ecological risk area of heavy metals in farmland. The results showed that: (1) Based on the similar accuracy of spatial prediction of soil heavy metals, the SISIM had a better expression of detail rebuild than ordinary kriging in small scale area. Compared to indicator kriging, the SISIM had less error rate (4.9%-17.1%) in uncertainty evaluation of heavy-metal risk identification. The SISIM had less smooth effect and was more applicable to simulate the spatial uncertainty assessment of soil heavy metals and risk identification. (2) There was no pollution in Zengcheng's farmland. Moderate potential ecological risk was found in the southern part of study area due to enterprise production, human activities, and river sediments. This study combined the sequential indicator simulation with Hakanson risk index method, and effectively overcame the outlier information loss and smooth effect of traditional kriging method. It provided a new way to identify the soil heavy metal risk area of farmland in uneven sampling.

LO05: A statistical analysis to estimate the spatial dynamics of opioid-related emergency medical services responses in the city of Calgary 2017

Introduction: Understanding the spatial distribution of opioid abuse at the local level may facilitate community intervention strategies. The purpose of this analysis was to apply spatial analytical methods to determine clustering of opioid-related emergency medical services (EMS) responses in the City of Calgary. Methods: Using opioid-related EMS responses in the City of Calgary between January 1st through October 31st, 2017, we estimated the dissemination area (DA) specific spatial randomness effects by incorporating the spatial autocorrelation using intrinsic Gaussian conditional autoregressive model and generalized linear mixed models (GLMM). Global spatial autocorrelation was evaluated by Morans I index. Both Getis-Ord Gi and the LISA function in Geoda were used to estimate the local spatial autocorrelation. Two models were applied: 1) Poisson regression with DA-specific non-spatial random effects; 2) Poisson regression with DA-specific G-side spatial random effects. A pseudolikelihood approach was used for model comparison. Two types of cluster analysis were used to identify the spatial clustering. Results: There were 1488 opioid-related EMS responses available for analysis. Of the responses, 74% of the individuals were males. The median age was 33 years ( IQR: 26-42 years) with 65% of individuals between 20 and 39 years, and 27% between 40 and 64 years. In 62% of EMS responses, poisoning/overdose was the chief complaint. The global Morans Index implied the presence of global spatial autocorrelation. Comparing the two models applied suggested that the spatial model provided a better fit for the adjusted opioid-related EMS response rate. Calgary Center and East were identified as hot spots by both types of cluster analysis. Conclusion: Spatial modeling has a better predictability to assess potential high risk areas and identify locations for community intervention strategies. The clusters identified in Calgarys Center and East may have implications for future response strategies.

STUDY ON THE DISTRIBUTION OF GEOLOGICAL HAZARDS BASED ON FRACTAL CHARACTERISTICS – A CASE STUDY OF DACHUAN DISTRICT

Abstract. It is a complicated process to analyze the cause of geological hazard. Through the analysis function of GIS software, 250 landslides were randomly selected from 395 landslide hazards in the study area, superimposed with the types of landforms, annual rainfall and vegetation coverage respectively. It used box dimension method of fractal dimension theory to study the fractal characteristics of spatial distribution of landslide disasters in Dachuan district, and analyse the statistical results. Research findings showed that the The fractal dimension of the landslides in the Dachuan area is 0.9114, the correlation coefficient is 0.9627, and it has high autocorrelation. Zoning statistics according to various natural factors, the fractal dimension between landslide hazard points and deep hill, middle hill area is strong as well as the area whose average annual rainfall is 1050 mm–1250 mm and vegetation coverage is 30 %–60 %. Superposition of the potential hazard distribution map of single influence factors to get the potential hazard zoning of landslides in the area. Verifying the potential hazard zoning map of the potential landslides with 145 remaining disaster points, among them, there are 74 landslide hazard points in high risk area, accounting for 51.03 % of the total. There are 59 landslides in the middle risk area, accounting for 40.69 % of the total, and 12 in the low risk area, accounting for 8.28 % of the total. The matching degree of the verifying result and the potential hazard zoning is high. Therefore, the fractal dimension value divided the degree of geological disaster susceptibility can be described the influence degree of each influence factor to geological disaster point more intuitively, it also can divide potential disaster risk areas and provide visual data support for effective management of geological disasters.

The spatial-temporal evolution law of microseismic activities in the failure process of deep rock masses

Under high stress and blasting disturbance, the failure of deep rock masses is a complex, dynamic evolutionary process. To reveal the relation between macroscopic failure of deep rock masses and spatial-temporal evolution law of micro-cracking within, the initiation, extension, and connection of micro-cracks under blasting disturbance and the deformation and failure mechanism of deep rock masses were studied. The investigation was carried out using the microseismic (MS) monitoring system established in the deep mining area of Ashele Copper Mine (Xinjiang Uygur Autonomous Region, China). The results showed that the failure of the deep rock masses is a dynamic process accompanied with stress release and stress adjustment. It is not only related to the blasting-based mining, but also associated with zones of stress concentration formed due to the mining. In that space, the concentrated area in the cloud chart for the distribution of MS event density before failure of the rocks shows the basically same pattern with the damaged rocks obtained through scanning of mined-out areas, which indicates that the cloud chart can be used to determine potential risk areas of rocks in the spatial domain. In the time domain, relevant parameters of MS events presented different changes before the failure of the rocks: the energy index decreased while the cumulative apparent volume gradually increased, the magnitude distribution of microseismic events decreased rapidly, and the fractal dimension decreased at first and then remained stable. This demonstrates that the different changes in relevant MS parameters allow researchers to predict the failure time of the rocks. By analysing the dynamic evolution process of the failure of the deep rock masses, areas at potential risk can be predicted spatially and temporally. The result provides guidance for those involved in the safe production and management of underground engineering and establishes a theoretical basis for the study on the stability of deep rock masses.

Using analytic hierarchy process with GIS for Dengue risk mapping in Kolkata Municipal Corporation, West Bengal, India

Detecting and mapping of Dengue risk areas is a complex, tiring, multifaceted and protracted task requiring evaluation of many criteria. It is not sure that always one single factor is liable for Dengue Fever transmission in all areas, but it differs with changing geographical location. This paper presents the application of analytic hierarchy process alongside with geospatial analysis for detecting Dengue risk areas in Kolkata Municipal Corporation by integrating environmental parameters. It employs two stage analyses synergistically to form a Spatial Decision Support System. The first stage analysis makes use of the thematic layers in Geographical Information System in combination with environmental factors leading to support the second stage analysis using the analytic hierarchy process as a tool. Moreover, weighted overlay analysis was used for detecting potential risk areas. The research result shows that the calculated weights of criteria are within the range of Consistency Ratio being > 0.1. The chosen decision criteria are consistent because the calculated Consistency Ratio is 0.0551 which is < 0.1 and considered as acceptable for decision making. The most influential factors are found the Household Density, Water Logged Areas, Land Surface Temperature, Population Density, Land Elevation and Land Use Land Cover. The present study shows that the spatial relationship can help in understanding the pattern and distribution of dengue outbreak and zonation of potential risk areas.

AVALIAÇÃO DA REDE DE HIDRANTES NA CIDADE DE SÃO CARLOS-SP EM RELAÇÃO A EXPANSÃO URBANA, DENSIDADE POPULACIONAL E AGENTES DE INCÊNDIOS

O número de ocorrências de incêndios tem aumentado ano a ano em várias cidades brasileiras e grande parte destes sinistros é destrutiva e causa mortes. Um dos principais fatores responsáveis pelos resultados negativos relacionados a incêndios é a quantidade insuficiente de hidrantes instalados nas cidades, uma vez que a expansão da malha urbana e os assentamentos da população ocorrem mais rapidamente que a instalação destes equipamentos. Este estudo avalia a distribuição da rede de hidrantes na cidade de São Carlos-SP em relação a agentes de incêndio alocados na cidade e o adensamento populacional. Analisa também a relação entre expansão da malha urbana, crescimento populacional e a presença dos hidrantes, com a finalidade de estimar o crescimento das áreas de potencial risco. Os resultados permitem concluir que a cidade de São Carlos-SP apresenta insuficiência de hidrantes em relação a quantidade indicada pela instrução técnica estadual, que a rede instalada cobre apenas um terço da malha urbana e que apenas parte da população urbana é atendida pelo raio de cobertura destes equipamentos.

Variations in abundance and diversity of phytoplankton in the surface waters of the Golden Horn Estuary (Sea of Marmara)

The abundance pattern and species diversity of phytoplankton in the surface waters of the Golden Horn Estuary were investigated between August 2011 and July 2012 in relation to environmental factors. Seventy-eight phytoplankton taxa (38 diatoms, 30 dinoflagellates and 10 phytoflagellates) belonging to eight taxonomic classes were identified in bottle and net samples. Phytoplankton abundance increased in spring and summer (from March to August) and reached its highest (10,429 × 103cells L−1) during the bloom ofHeterosigma akashiwo(Raphidophyceae) in the middle and upper estuary in late May. In general, phytoplankton abundance was higher in the middle estuary indicating more suitable conditions for phytoplankton growth, while species richness and diversity was higher in the lower estuary. The most abundant species wereSkeletonema marinoiandThalassiosirasp. among diatoms;Scrippsiella trochoideaamong dinoflagellates;Plagioselmis prolongaandHeterosigma akashiwoamong phytoflagellates. Diatoms were more abundant in the lower and middle estuary, while dinoflagellates and phytoflagellates in the upper estuary. The main factors causing the spatio-temporal variation of phytoplankton in the study area were temperature, salinity, water transparency and nutrients. Water transparency in the upper estuary is mostly influenced by organic and inorganic matter carried by two streams. As a result, this area should be considered a potential risk area for future algal blooms.

Hydrological and flood hazard assessment using a coupled modelling approach for a mountainous catchment in Portugal

Floods may lead to destruction of property, to damage to the environment and ultimately to loss of lives. Although it is not possible to avoid them, they are enhanced by human activities that increase the probability of occurrence of these natural events. Preliminary flood risk assessment and determination of areas of potential significant flood risk is mandatory according to the European Floods Directive (2007). In order to meet the established legislation, a methodology was developed that couples two modelling approaches: the Hydrological Simulation Program—FORTRAN (HSPF) and IBER. A target watershed, with complex orography and known to be vulnerable to flood hazards, is selected: the Vez River (northern Portugal). The performance of the HSPF model, driven by a climate gridded dataset, was assessed, followed by the reconstruction of the flow rate in the catchment for the period from 1950 to 2015. The results hint at an agreement between simulated and observed daily flow rates, with high coefficient of determination value and of the Nash–Sutcliffe coefficient of efficiency (> 0.7 daily timescale). A satisfactory performance was also found in reproducing flood peak events. An average deviation of 10% was found between observed and simulated flood peaks. The output of HSPF was subsequently used to drive IBER, thus determining flood hazard areas for a 10, 50 and 100-year return periods. The methodology presented here provides basic tools for decision-makers to evaluate hydrologic responses to climate data, namely the determination of flood hazard maps, but also risk assessment, water management, environmental protection and sustainability.