Mapping social vulnerability to flood hazard in Norfolk,England

In this paper, we present a method to assess social vulnerability through the creation of an Open Source Vulnerability Index (OS-VI). The OS-VI provides context to environmental hazards and allows NGOs and local agencies to better tailor services and provide targeted pre-emptive vulnerability reduction and resilience-building programmes. A deductive indicator-based approach is utilised to incorporate a wide range of vulnerability indicators known to influence vulnerability. Unlike many vulnerability indices, the OS-VI incorporates flood risk as well as the loss of capabilities and the importance of key services (health facilities and food stores) through the measurement of accessibility when determining an area's level of social vulnerability. The index was developed using open-source mapping and analysis software and is composed completely of open-source data from national data sets. The OS-VI was designed at the national level, with data for all proxy indicators available across the entirety of England and Wales. For this paper, a case study is presented concerned with one English county, Norfolk.

Highlights

• We produce an open-source vulnerability index.

• Accessibility to health care found to be severely affected by flooding.

• High vulnerability areas found to be disproportionately impacted by flooding.

• Urban extent of an area found to increase its level of vulnerability.

• Flood affected areas more likely to be composed of elderly, sick and poor.

     

Application of analytical hierarchy process and geographic information systems in land-use suitability evaluation: a case study of Dümrek village (Çanakkale,Turkey)

This study used both analytical hierarchy process (AHP) and geographic information systems (GIS) to make a land-use suitability analysis for the village of Dümrek, NW Turkey. Primarily, alternative land uses for agriculture, meadow–pasture and forest were determined along with criteria for these alternatives and a hierarchical structure was produced and used to determine the weights of the criteria. Spatial data were identified by means of GIS and calculations were made using the suitability values specified and weights obtained from AHP. Suitability maps were then produced for the above land use alternatives. Subsequently, a synthesized suitability map was formed from these maps. According to the weights specified by AHP, the order of land use preferences among the alternatives for rural development of Dümrek was agriculture, forest and meadow. The synthesized suitability map showed that the areas allocated for forest and agriculture were close to the present ratios of use; however, meadow land, which does not exist at present, should be allocated as a land use to constitute 12.5% of the study area. Achieving sustainability in land use is possible by planners and administrators considering results obtained from land suitability mapping studies at the stage of allocating land uses. The method applied in this research is considered useful when taking policy decisions covering the evaluation of rural land use, particularly for subunits of the state administration.     

Relative density of finds for assessing similarity-based maps of orchid occurrence

Similarity-based mapping of the expected distribution of 10 orchid species was conducted in a study area covering 300 km² in south-eastern Estonia. The observation track and species finds were recorded during fieldwork. Absence locations were generated on the line of observation track. Both presence and absence sites having an in-between distance of at least 100 m were used as training data. Expected presence/absence of a species was calculated according to similarity between the predictable location and selected observations (examples) of presence and absence sites. For each species, the machine learning system identified the best predictive sets by selecting the most useful variables out of 136 map and remote sensing features. Similarity-based estimations were evaluated both by training fit and by independent verification data. Reliability of the predictive maps was expressed also by usefulness ratios—the densities of validation find sites (1) in the predicted presence area relative to the density of those in the predicted absence area, and (2) relative to the share of the observation track in the predicted presence area and in the predicted absence area. The predictive mapping was most efficient for Dactylorhiza incarnata, D. russowii, Epipactis palustris, and Goodyera repens. We conclude that the profound coverage of observations on any larger area is unrealistic and the reliability of similarity-based predictive maps depends on the representativity of existing records relative to the diversity of the study area. The investigation showed that the studied species are much more common in nature than the records in the national database indicate.     

Will Evolving Climate Conditions Increase the Risk of Floods of the Large U.S.‐Canada Transboundary Richelieu River Basin?

In spring 2011, an unprecedented flood hit the complex eastern United States (U.S.)–Canada transboundary Lake Champlain–Richelieu River (LCRR) Basin, destructing properties and inducing negative impacts on agriculture and fish habitats. The damages, covered by the Governments of Canada and the U.S., were estimated to C$90M. This natural disaster motivated the study of mitigation measures to prevent such disasters from reoccurring. When evaluating flood risks, long‐term evolving climate change should be taken into account to adopt mitigation measures that will remain relevant in the future. To assess the impacts of climate change on flood risks of the LCRR basin, three bias‐corrected multi‐resolution ensembles of climate projections for two greenhouse gas concentration scenarios were used to force a state‐of‐the‐art, high‐resolution, distributed hydrological model. The analysis of the hydrological simulations indicates that the 20‐year return period flood (corresponding to a medium flood) should decrease between 8% and 35% for the end of the 21st Century (2070–2099) time horizon and for the high‐emission scenario representative concentration pathway (RCP) 8.5. The reduction in flood risks is explained by a decrease in snow accumulation and an increase in evapotranspiration expected with the future warming of the region. Nevertheless, due to the large climate inter‐annual variability, short‐term flood probabilities should remain similar to those experienced in the recent past.     

Mapping loci that control lateral spike development in Tibetan barley by bulked segregant analysis (BSA)北大核心CSCD

Fertility of lateral spikelets determines the two-rowed or six-rowed spikes of barley (Hordeum vulgare L.), which results in significantly different grain yields. The change in row type from two-rowed to six-rowed shows remarkable domestication characteristics. The Qinghai-Tibet plateau has abundant resources of wild and cultivated barley, and is considered one of the centers of domestication and genetic diversity of cultivated barley. In order to obtain a primary understanding of the genetic basis of lateral spike development regulation and the domestication process in cultivated Tibetan barley, an F2 segregation population was constructed by crossing the two-rowed wild barley accession ZYM0083 with the six-rowed landraces Linzhiheiliuleng. Genetic analysis showed that the row type was controlled by a single gene. Using the specific-locus amplified fragment sequencing (SLAF-seq) technology and bulked segregant analysis (BSA), two DNA pools from 22 two-rowed spike individuals and 22 six-rowed spike individuals of the F2 population were constructed and sequenced. A total of 456 691 SLAF tags were obtained. By adopting the ED and SNP index for association analysis, three candidate regions with a 53.84-Mb interval and containing 536 genes were obtained. Four-hundred thirteen, 189, and 160 annotated genes were acquired by GO, KEGG, and COG libraries, respectively. Loci that control lateral spike development in Tibetan barley were primarily mapped by SLAF-seq, and the results presented in this study will facilitate the fine mapping and cloning of target genes. © 2018 Science Press. All rights reserved.     

Mapping cumulative impacts of mining on sediment retention ecosystem service in an Australian mining region

Mining development can potentially lead to cumulative impacts on ecosystems and their services across a range of scales. Site-specific environmental impact assessments are commonly assessed for mining projects; however, large-scale cumulative impacts of multiple mines that aggregate and interact in resources regions have had little attention in the literature and there are few examples where regional-scale mining impacts have been assessed on ecosystem services. The objective of this study is to quantify regional-scale cumulative impacts of mining on sediment retention ecosystem services. We apply the sediment delivery ratio model of Integrated Valuation of Ecosystem Services and Trade-offs to calculate and map the sediment retention and export using a synthetic catchment model and a real case study under different mining scenarios in an Australian mining region. Two impact indices were created to quantify the cumulative impacts associated with a single mine and the interactions between multiple mines. The indices clarified the magnitude of impacts and the positive/negative impacts associated with regional-scale sediment retention and export. We found cumulative impacts associated with multiple mines’ interaction occurred but the influence of these interactions was relatively weak. This research demonstrated the potential for utilising ecosystem services modelling for the quantitative assessment of the cumulative impacts. Such research provide decision-makers and planners with a tool for sustainable regional and landscape planning that balances the needs of mining and the provision of ecosystem services.     

A novel participatory and remote-sensing-based approach to mapping annual land use change on forest frontiers in Laos,Myanmar, and Madagascar

Tropical forests are under pressure from both commercial and smallholder agriculture. Forest frontiers are seeing dynamic land use changes that frequently lead to land system regime shifts, posing challenges for the sustainability of entire local social-ecological systems. Monitoring highly dynamic land use change and detecting land system regime shifts is methodologically challenging due to trade-offs between spatial and temporal data resolution. We propose an innovative approach that combines analysis of very-high-resolution satellite imagery with participatory mapping based on workshops and field walks. Applying it in Laos, Myanmar, and Madagascar, we were able to collect annual land use information over several decades. Unlike conventional land use change mapping approaches, which assess only few points in time, our approach provides information at a temporal resolution that enables detection of gradual and abrupt land system regime shifts.     

CLIMATE VARIABILITY AND FLOOD FREQUENCY ESTIMATION FOR THE UPPER MISSISSIPPI AND LOWER MISSOURI RIVERS1

ABSTRACT: This paper considers the distribution of flood flows in the Upper Mississippi, Lower Missouri, and Illinois Rivers and their relationship to climatic indices. Global climate patterns including El Niño/Southern Oscillation, the Pacific Decadal Oscillation, and the North Atlantic Oscillation explained very little of the variations in flow peaks. However, large and statistically significant upward trends were found in many gauge records along the Upper Mississippi and Missouri Rivers: at Hermann on the Missouri River above the confluence with the Mississippi (p = 2 percent), at Hannibal on the Mississippi River (p < 0.1 percent), at Meredosia on the Illinois River (p = 0.7 percent), and at St. Louis on the Mississippi below the confluence of all three rivers (p = 1 percent). This challenges the traditional assumption that flood series are independent and identically distributed random variables and suggests that flood risk changes over time.     

灾后复杂地形区域的测量测绘模型设计

灾后地形变化复杂,基于单一线性模型的测量测绘方法,测量灾区坡度陡、高差大等复杂地形时,无法有效拟合复杂地形趋势、获取高程点精度差,导致测量精确度较低。设计一种用于灾后复杂地形区域的测量测绘模型,在外部DEM辅助下精化灾区地形DEM,对灾区遥感InSAR影像进行干涉定标,实现干涉影像与外部DEM的精准对应;将多模型的线性回归策略与灾后复杂地形趋势相拟合,对解缠干涉影像图中全部影像快,通过多模型的线性回归,逐个像素精确的去除相位解缠中多余相位,过滤无价值高程点,得到有效灾区地形高程图,从中采集精确地灾后复杂地形区域高程点。实验结果表明,该模型可提高灾后复杂地形区域绘图精确度,对总体灾区地形InSAR影像测量效率高,测量的平均高程误差为±6.2cm,比单一线性模型低±3.77cm。     

基于因子强关联分析方法的滑坡易发性评价

在滑坡易发性区划制图过程中,预测模型性能的优劣很大程度上取决于众多影响因子的选择和组合,如何选择滑坡影响因子以优化滑坡预测模型的性能是区域滑坡易发性评价的关键.本文提出一种基于强关联分析的Apriori算法,通过滑坡强关联分析来从预选的15个滑坡影响因子中选择诱发灾害可能性最高的因子进行组合,进而利用随机森林构建滑坡易...