Assessment of flood adaptive capacity of urban areas in Thailand

Urban floods have a significant impact on the economy, livelihoods, and daily activities. Despite extensive research on flood adaptation, there is a lack of consensus on ways to assess flood adaptive capacity. This research thus proposes an assessment framework of flood adaptive capacity of urban residents in flood-prone areas. The indicators are based on six components: economic resources, social capital, awareness and training, technology, infrastructure, and institutions and policies. The relevancy of the indicators was evaluated by experts in related fields, and a questionnaire was developed to collect data from a random sample of 230 households in 10 flood-prone municipalities in Thailand. Statistical analysis and structural equation modeling were subsequently performed to validate the components and indicators, and a flood-adaptability questionnaire was constructed. As a trial implementation, the questionnaire was applied to a target flood-prone municipality, Phetchaburi, to assess its adaptive capacity to flooding, expressed as flood adaptive capacity index. The adaptive capacity of Phetchaburi municipality to flooding was found to be high indicating the improvement in economic resources and infrastructure components. These findings reveal that the proposed framework is suitable for assessing the flood adaptive capacity of urban residents and useful for integrated flood risk assessment and management.     

The return periods and risk assessment of severe dust storms in Inner Mongolia with consideration of the main contributing factors

This study presents a methodology for return period analysis and risk assessment of severe dust storm disaster. Meteorological observation data, soil moisture data, and remote sensing data from 30 meteorological stations in Inner Mongolia (western China) from 1985 to 2006 were used for the study. A composite index of severe dust storm disaster (Index I (SDS)) based on the influence mechanisms of the main contributing factors was developed by using the analytic hierarchy process and the weighted comprehensive method, and the hazard risk curves (i.e., the transcendental probability curves of I (SDS)) for the 30 stations were established using the parameter estimation method. We then analyzed the risk of the occurrence of severe dust storm under different scenarios of 5-, 10-, 20-, and 50-year return periods. The results show that the risk decreased from west to east across Inner Mongolia, and there are four severe dust storm occurrence peak value centers, including Guaizihu, Jilantai, Hailisu, and Zhurihe-Erenhot. The severity of dust storms in seven places will be intolerable in the 50-year return period scenario and in three places in the 20-year return period scenario. These results indicate that these locations should concentrate forces on disaster prevention, monitoring, and early warning. The I (SDS) was developed as an easily understandable tool useful for the assessment and comparison of the relative risk of severe dust storm disasters in different areas. The risk assessment was specifically intended to support local and national government agencies in their management of severe dust storm disasters in their efforts to (1) make resource allocation decisions, (2) make high-level planning decisions, and (3) raise public awareness of severe dust storm risk.     

Assessing alpine plant vulnerability to climate change: a modeling perspective

The potential ecological impact of ongoing climate change has been much discussed. High mountain ecosystems were identified early on as potentially very sensitive areas. Scenarios of upward species movement and vegetation shift are commonly discussed in the literature. Mountains being characteristically conic in shape, impact scenarios usually assume that a smaller surface area will be available as species move up. However, as the frequency distribution of additional physiographic factors (e.g., slope angle) changes with increasing elevation (e.g., with few gentle slopes available at higher elevation), species migrating upslope may encounter increasingly unsuitable conditions. As a result, many species could suffer severe reduction of their habitat surface, which could in turn affect patterns of biodiversity. In this paper, results from static plant distribution modeling are used to derive climate change impact scenarios in a high mountain environment. Models are adjusted with presence/absence of species. Environmental predictors used are: annual mean air temperature, slope, indices of topographic position, geology, rock cover, modeled permafrost and several indices of solar radiation and snow cover duration. Potential Habitat Distribution maps were drawn for 62 higher plant species, from which three separate climate change impact scenarios were derived. These scenarios show a great range of response, depending on the species and the degree of warming. Alpine species would be at greatest risk of local extinction, whereas species with a large elevation range would run the lowest risk. Limitations of the models and scenarios are further discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Mapping and quantifying habitat fragmentation in small coastal areas: a case study of three protected wetlands in Apulia (Italy)

In the Mediterranean Region, habitat loss and fragmentation severely affect coastal wetlands, due to the rapid expansion of anthropogenic activities that has occurred in the last decades. Landscape metrics are commonly used to define landscape patterns and to evaluate fragmentation processes. This investigation focuses on the performance of a set of landscape pattern indices within landscapes characterized by coastal environments and extent below 1,000 ha. The aim is to assess the degree of habitat fragmentation for the monitoring of protected areas and to learn whether values of landscape metrics can characterize fine-resolution landscape patterns. The study areas are three coastal wetlands belonging to the Natura 2000 network and sited on the Adriatic side of Apulia (Southern Italy). The Habitat Maps were derived from the Vegetation Maps generated integrating phytosociological relevés and Earth Observation data. In the three sites, a total of 16 habitat types were detected. A selected set of landscape metrics was applied in order to investigate their performance in assessing fragmentation and spatial patterns of habitats. The final results showed that the most significant landscape patterns are related to highly specialized habitat types closely linked to coastal environments. In interpreting the landscape patterns of these highly specialized habitats, some specific ecological factors were taken into account. The shape indices were the most useful in assessing the degree of fragmentation of habitat types that usually have elongated morphology along the shoreline or the coastal lagoons. In all the cases, to be meaningful, data obtained from the application of the selected indices were jointly assessed, especially at the class level.     

Assessment of risk factors in forest road design and construction activities with fuzzy analytic hierarchy process approach in Turkey

Forest road design and construction are time-consuming and complicated because various risk factors can be encountered during the process. The aim of this study is to comprehensively assess the risk factors in forest road design and construction using the fuzzy analytic hierarchy process (AHP) method in Turkey, thus contributing to the proper performance of these activities. Within the scope of the study, six main risk factors and 22 sub-risk factors were identified based on literature review. In order to determine the weights of the relevant risk factors, the opinions of three different groups [(group 1: academicians), (group 2: forest engineers (private sector employees + public sector employees)), (group 3: group 1 + group 2)] about the risk factors were obtained. Relevant risk factor weights were determined using the fuzzy AHP method. According to group 3, the most important main risk factors are technical risks and environmental risks. In addition, the most important sub-risk factors for each relevant main risk factor were incorrect road alignment, inadequate work safety in the field, insufficient capital, legal problems on the road alignment, landslide risk during road construction, and illegal logging. Differences were observed between groups 1 and 2 in the weight rankings of relevant risk factor. The results demonstrate that the fuzzy AHP method can be used effectively to assess the risks of forest road design and construction.     

Assessing dam implementation impact on threatened carnivores: the case of Alqueva in SE Portugal

Large dam construction in water deficient areas is a management decision often controversial. Besides providing water storage, economical benefits, and a source of renewable energy, the construction and flooding caused by large dams cause disruptions in natural systems. We monitored the pre- and post-Alqueva dam impacts on the threatened carnivore species (polecat, otter, wildcat and Iberian lynx) populations in SE Portugal, and assessed which factors mostly contribute to post-dam distribution. Major short term impacts of large dams are: (1) increase in accessibility and human presence; (2) movement of heavy machinery and dam-workers; (3) deforestation with habitat loss and fragmentation; (4) change from lotic to lentic system; (5) lower prey availability and harsher capture; and (6) changes in land use adjacent to the reservoir. Thus, the response to those impacts can be predicted as a decline of polecat, wildcat and lynx distribution ranges, and a recovery of the otter from the severe short term impacts. Our results corroborate this hypothesis for all the species, especially during deforestation/early flooding. Otter's distribution range increased in the phase of greater impact, with a subsequent decrease with flooding. Our results suggest carnivores used "escape" areas with favourable habitat and prey conditions, however, the areas with higher probability of species presence decreased by two fold showing a drastic range reduction. To ensure populations' survival of these charismatic threatened carnivore populations of Mediterranean landscapes of south-east Portugal, we propose continuing the monitoring program and the development of a conservation program for the subsisting areas of optimal and suboptimal habitats.     

Land use change and landslide characteristics analysis for community-based disaster mitigation

On August 8, 2009, Typhoon Morakot brought heavy rain to Taiwan, causing numerous landslides and debris flows in the Taihe village area of Meishan Township, Chiayi County, in south-central Taiwan. In the Taihe land is primary used for agriculture and land use management may be a factor in the area’s landslides. This study explores Typhoon Morakot-induced landslides and land use changes between 1999 and 2009 using GIS with the aid of field investigation. Spot 5 satellite images with a resolution of 2.5 m are used for landslide interpretation and manually digitalized in GIS. A statistical analysis for landslide frequency–area distribution was used to identify the landslide characteristics associated with different types of land use. There were 243 landslides with a total area of 2.75 km² in the study area. The area is located in intrinsically fragile combinations of sandstone and shale. Typhoon Morakot-induced landslides show a power–law distribution in the study area. Landslides were mainly located in steep slope areas containing natural forest and in areas planted with bamboo, tea, and betel nut. Land covered with natural forest shows the highest landslide ratio, followed by bamboo, betel nut, and tea. Landslides thus show a higher ratio in areas planted with shallow root vegetation such as bamboo, betel nut, and tea. Furthermore, the degree of basin development is proportional to the landslide ratio. The results show that a change in vegetation cover results in a modified landslide area and frequency and changed land use areas have higher landslide ratios than non-changed. Land use management and community-based disaster prevention are needed in mountainous areas of Taiwan for hazard mitigation.     

A simple method to identify areas of environmental risk due to manure application

The management of swine manure is becoming an important environmental issue in Chile. One option for the final disposal of manure is to use it as a biofertilizer, but this practice could impact the surrounding environment. To assess the potential environmental impacts of the use of swine manure as a biofertilizer, we propose a method to identify zones of environmental risk through indices. The method considers two processes: nutrient runoff and solute leaching, and uses available information about soils, crops and management practices (irrigation, fertilization, and rotation). We applied the method to qualitatively assess the environmental risk associated with the use of swine manure as a biofertilizer in an 8,000-pig farm located in Central Chile. Results showed that the farm has a moderate environmental risk, but some specific locations have high environmental risks, especially those associated with impacts on areas surrounding water resources. This information could assist the definition of better farm-level management practices, as well as the preservation of riparian vegetation acting as buffer strips. The main advantage of our approach is that it combines qualitative and quantitative information, including particular situations or field features based on expert knowledge. The method is flexible, simple, and can be easily extended or adapted to other processes.     

三江源畜牧业示范区土壤重金属含量特征及评价

为了明确三江源智慧生态畜牧业示范区内土壤重金属元素含量特征及潜在风险,2015年7月在三江源智慧生态畜牧业示范区11个示范村镇进行土壤样品采集,带回实验室分析Pb、Cd、Hg、Cr、Cu、Zn、Ni含量。对数据进行统计分析并采用内梅罗综合污染指数和生态危害指数进行风险等级评价。结果显示:部分采样点重金属元素含量高于青海省背景值;Pb、Cr、Cu、Zn、Ni主要受土壤母质的影响,Cd受自然和人为因素的双重影响,Hg主要受人为因素影响;内梅罗综合污染指数显示11个点位的指数都小于1,该地未出现污染状况;生态危害指数显示除GMY点位处于轻微风险等级,其余采样点为中等风险等级。总体上示范区内土壤未出现强污染和面源污染状况,但需要加强点源污染的风险防范。     

A GIS-based approach for the long-term prediction of human health risks at contaminated sites

A Health Index/Risk Evaluation Tool (HIRET) has been developed for the integration of risk assessment and spatial planning using GIS capabilities. The method is meant to assist decision makers and site owners in the evaluation of potential human health risk with respect to land use. Human health risk defined as the potential adverse effects on human life or health is generally accepted as the most important aspect for site assessment and planning of remediation strategies. It concerns polluted sites that endanger human health on one hand and derelict land that does not cause the immediate risk on the other hand. In current state-of-the-art risk-assessment, long-term spatial and temporal changes of risks, in relation to changes in contamination patterns and land use functions, are not taken into account. The aim of this paper is to demonstrate the methodology developed for human health risk assessment in aspect of spatial and temporal domain. HIRET was developed as an extension for ESRI software ArcView 3.2 and allows performing dynamic human health risk assessment in long-term period, which is relevant for land use planning. The paper illustrates how such methodology can assist in environmental decision-making to enhance the efficiency of contaminated land management. A case study of contaminated site is given showing how data can be used within a GIS framework to produce maps indicating areas of potential human health risk.     

江苏省沿江城市饮用水系统适应能力评估

在对饮用水系统适应能力界定的基础上,基于水源地、供水、用水、排污处理和技术5个子系统的适应性要素构建沿江城市饮用水系统适应能力评价指标体系和评价模型,采用分指数与综合指数法评估系统的适应能力水平、存在问题,并据此对江苏省沿江地区城市饮用水系统适应能力分异特征、类型及影响因素进行深入探讨。结果表明,南部环太湖地区城市饮用水系统适应能力高于中部滨江地区,北部地区适应能力最低;从各子系统适应能力得分情况来看,需加大对沿江地区水源地的保护力度,合理规划港口、码头等的布设;加快北部地区供排基础设施的建设,提高风险应急防范能力;南部环湖地区重点开展节水型企业与生态工业园区创建。     

Using NOAA AVHRR data to assess flood damage in China

The article used two NOAA-14 Advanced Very High ResolutionRadiometer (AVHRR) datasets to assess flood damage in the middleand lower reaches of China's Changjiang River (Yangtze River) in 1998. As the AVHRR is an optical sensor, it cannot penetratethe clouds that frequently cover the land during the flood season, and this technology is greatly limited in flood monitoring. However the widely used normalized difference vegetation index (NDVI) can be used to monitor flooding, sincewater has a much lower NDVI value than other surface features.Though many factors other than flooding (e.g. atmospheric conditions, different sun-target-satellite angles, and cloud) can change NDVI values, inundated areas can be distinguished fromother types of ground cover by changes in the NDVI value beforeand after the flood after eliminating the effects of other factors on NDVI. AVHRR data from 26 May and 22 August, 1998 wereselected to represent the ground conditions before and after flooding. After accurate geometric correction by collecting GCPs,and atmospheric and angular corrections by using the 6S code, NDVI values for both days and their differences were calculatedfor cloud-free pixels. The difference in the NDVI values betweenthese two times, together with the NDVI values and a land-use map, were used to identify inundated areas and to assess the arealost to the flood. The results show a total of 358 867 ha, with 207 556 ha of cultivated fields (paddy and non-irrigated field) inundated during the flood of 1998 in the middle and lower reaches of the Changjiang River Catchment; comparing with the reported total of 321 000 and 197 000 ha, respectively. The discrimination accuracy of this method was tested by comparing the results from two nearly simultaneous sets of remote-sensingdata (NOAA's AVHRR data from 10 September, 1998, and JERS-1 synthetic aperture radar (SAR) data from 11 September, 1998, with a lag of about 18.5 hr) over a representative flooded regionin the study area. The results showed that 67.26% of the total area identified as inundated using the NOAA data was also identified as inundated using the SAR data.     

Behavioural determinants of an individual's intention to adapt to climate change: Both internal and external perspectives

Climate change has had a significant negative impact on socio-economic factors and the earth's ecology. To cope with climate change, many countries have employed various policies and measures to reduce damage due to climate change. For individual residents, adaptation behaviour is vital for reducing individual welfare losses. This research analysed how psychological determinants and other external factors influence residents' intention to adapt to climate change. We proposed an extended protection motivation theory (PMT) model, developed a reliable scale and conducted a nationwide field survey. We interviewed 1402 residents in 29 provinces, and 874 valid questionnaires were collected, providing data that were used in a structural equation model. The results show that our model can serve as a reliable framework for analysing the determinants of residents' intention to adapt to climate change. Policy is the most important factor for stimulating the formation of residents' adaptation intention. Risk appraisals and adaptation appraisals have positive and significant impacts on the intention of residents to adopt climate change adaptation behaviour. Information and climate perception do not directly influence residents' behavioural intentions but indirectly affect their intentions through the process of risk appraisal and adaptation appraisal. Corresponding policy suggestions are made that may be helpful for the formulation of adaptation policies.     

Well-being,life satisfaction and capabilities of flood disaster victims

The individual well-being of flood disaster victims is examined making use of two concepts: life satisfaction and perceived capabilities in life. These concepts are compared in two samples: a representative sample of Flemish respondents and a specific sample of people that have been the victim of a pluvial flood. Well-being as life satisfaction is found not to be related to past or expected future flooding, whereas well-being as capabilities in life is negatively related to both past and expected future flooding.     

乌鲁木齐河流域浅层地下水防污性能评价

地下水防污性能的评价是确定地下水资源保护措施是否可行的关键。本文根据乌鲁木齐河流域浅层地下水水文地质状况,采用DRASTIC模型,选取包气带岩性、厚度与结构、地形作为评价因子,在乌鲁木齐河流域地下水污染现状评价的基础上,用模糊综合评判法评价了地下水防污性能,从而为乌鲁木齐河流域地下水污染防治提供了依据。     

Classification of alluvial soils according to their potential environmental risk: a case study for Belgian catchments

Alluvial soils may represent important sinks of contaminants as a result of the deposition of contaminated sediments along the river by overbank flooding or after dredging. Because of the erosion of alluvial deposits or the release of contaminants from sediments, alluvial soils can also be a source of contamination. In this paper, a risk assessment for contaminated (alluvial) soils is presented. The approach, mainly based on physico-chemical soil characteristics, single extractions and leaching tests, is illustrated by means of a case study from four Belgian catchments. The extractions and leaching tests that were used have been validated by European testing programs and can provide valuable information for classifying the potential environmental risks of soils. Irrespective of the location, pH, organic carbon content and 'mobilisable' metal concentrations were the most important factors explaining 'mobile' metal concentrations in the alluvial soils. Additionally, the data of the physico-chemical soil characterization, extractions and leaching tests were combined with local and regional factors to classify the alluvial soils in different categories according to their actual and potential risk for the environment.     

Regression Analysis Model Applied to Biomonitoring Studies

A regression model is proposed for studying the relationship between trace metals concentrations and weights of individuals of Monodonta turbinata (Born), a gastropod mollusc used as a trace metal biomonitor of marine coastal areas. The model herein presented was developed including sites as reference factors and showed very good correlations. The prevision model of contamination gave good results for this kind of pollutants, and it can be used as a tool for monitoring programmes.     

Finding threatened forest areas in the central volcanic mountain range conservation area in Costa Rica

The degree at which tropical forests are exposed to human pressure is spatially dependent. Population density, proximity to roads, terrain slope, logging activities and land distribution projects are well known factors inducing deforestation and forest degradation in Latin America. Using expert knowledge to weight these threat factors and a Geographical Information System for spatial modeling, a multi-criteria analysis procedure is presented, that allows stratifying a study region in categories of deforestation threat. The procedure was implemented in the Central Volcanic Mountain Range Conservation Area (CVMRCA) in Costa Rica with the purpose of finding areas with a combination of physical and socioeconomic characteristics that is particularly predisposing to a high probability of deforestation. To validate the map, the CVMRCA was stratified in categories of deforestation risk, and the result was superposed to historical deforestation data of the period 1986–1996. The good correlation between risk category and historical deforestation (r = 0.91, p < 0.001) indicates that the map can be used as a decision support tool for defining priority areas for conservation action.     

Statistical apportionment and risk assessment of selected metals in sediments from Rawal Lake (Pakistan)

The present study was carried out in order to evaluate the statistical apportionment and risk assessment of selected metals (Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Pb, Sr, and Zn) in freshly deposited sediments in Rawal Lake, Pakistan. Composite sediment samples were collected, oven-dried, grounded, homogenized, and processed to assess the water-soluble and acid extractable concentrations of the metals in the water extract and acid extract of the sediments using flame atomic absorption spectrophotometer. Statistical methods were used to identify the possible sources of the metals. Sediment quality guidelines and potential acute toxicity were used to evaluate the ecotoxicological sense of selected metals. Non-carcinogenic health risk assessment was also carried out to determine the potential adverse health risks to the inhabitants. Relatively higher concentration was noted for Ca, Fe, Mg, Na, K, Mn, and Sr in the sediment samples. Principal component analysis and cluster analysis revealed anthropogenic contributions of Cd, Pb, Cr, Mn, Fe, and Li in the sediments. Enrichment factors of the metals in sediments showed severe to moderate enrichment of Cd, Pb, Ca, Fe, Li, Mn, and Sr. Geoaccumulation indices and contamination factors evidenced significant contamination by Cd and Pb, although, on the whole, low degree of contamination was noted. The levels of some metals exceeded the sediment quality guidelines, which revealed frequently adverse biological effects to the dwelling biota in the aquatic ecosystem. The sediments were found to be significantly contaminated by Cd, Pb, Cr, Mn, Fe, and Li.     

Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China

Soil erosion is a serious environmental problem in Guizhou Province, which is located in the centre of the karst areas of southwestern China. Unfortunately, Guizhou Province suffers from a lack of financial resources to research, monitor and model soil erosion at large watershed. In order to assess the soil erosion risk, soil erosion modeling at the watershed scale are urgently needed to be undertaken. This study integrated the Revised Universal Soil Loss Equation (RUSLE) with a Geographic Information System (GIS) to estimate soil loss and identify the risk erosion areas in the Maotiao River watershed, which is a typical rural watershed in Guizhou Province. All factors used in the RUSLE were calculated for the watershed using local data. It was classified into five categories ranging from minimal risk to extreme erosion risk depending on the calculated soil erosion amount. The soil erosion map was linked to land use, elevation and slope maps to explore the relationship between soil erosion and environmental factors and identify the areas of soil erosion risk. The results can be used to advice the local government in prioritizing the areas of immediate erosion mitigation. The integrated approach allows for relatively easy, fast, and cost-effective estimation of spatially distributed soil erosion. It thus indicates that RUSLE-GIS model is a useful and efficient tool for evaluating and mapping soil erosion risk at a large watershed scale in Guizhou Province.