Investigation of Spatial Risk Factors for RVF Disease Occurrence Using Remote Sensing &GIS—A Case Study: Sinnar State, Sudan

Rift Valley Fever (RVF) is an emerging, mosquito-borne disease with serious economical and negative implications on human and animal health. This study was conducted to verify the factors which influenced the spatial pattern of Rift Valley Fever occurrence and identified the high risk areas for the occurrence of the disease at Sinner State, Sudan. The normalized difference vegetation index (NDVI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite and rainfall data in addition to the point data of RVF clinical cases in humans were used in this study. In order to identify the RVF high risk areas, remote sensing data and rainfall data were integrated in a GIS with other information including, soil type, water body, DEM (Digital Elevation Model), and animal routes and analyzed using Spatial Analysis tools. The information on clinical cases was used for verification. The Normalized Difference Vegetation Index (NDVI) was used to describe vegetation patterns of the study area by calculating the mean NDVI. The results of the study showed that, RVF risk increased with the increase in vegetation cover (high NDVI values), and increase in rainfall, which both provided suitable conditions for disease vectors breeding and a good indicator for RVF epizootics. The study concluded that, identification of high risk area for RVF disease improved the understanding of the spatial distribution of the disease and helped in locating the areas where disease was likely to be endemic and therefore preparedness measures should be taken. The identification represents the first step of prospective predictions of RVF outbreaks and provides a baseline for improved early warning, control, response planning, and mitigation. Further detailed studies are recommended in this domain.

Urban Spatial Risk Assessment of Fire from Fueling Stations on Buildings Case Study: Lubaga Division, Kampala City, Uganda

The discovery of oil and gas in Uganda has attracted many investors, leading to increase in fuel/gas distributing companies and fueling stations creating rapid demand for land to locate the stations compared to available open urban land. Because of the explosive and combustion characteristics of fuel stored and dispensed at stations, several studies have been conducted on different fires at fueling stations such as static fire, jet fire, vapor cloud explosions, open fires, etc. but there was need to assess spatially the risk of fire from stations, its consequences and sovereignty on buildings surrounding them. This was done basing on seven parameters—proximity of buildings to stations, building materials, distance between buildings, wind speed, temperature, slope and vegetation. Analytical hierarchy process and pairwise comparison were used to weight the parameters based on their relative importance. Weighted sum tool was applied to generate the fire risk maps for the quarters—December to February, March to May, June to August, and September to November from 2008 to 2013. The parameters were overlaid with the buildings in each risk zone for all the four quarters and their influences determined. The highest contributors were proximity of the buildings to stations, building materials and separation between buildings. Most of the affected buildings were made of rusted corrugated iron sheets and wood;the separation distance from one building to another ranged from 0 - 4 m. Most of buildings located within 100 m from stations were at moderate risk level and within 50 m were at highest risk level. The period of December to February and June to August had the highest risk. The findings can be used to guide planners and policy makers on building location vs. material vs. separation. It can also guide developers on where, when and how to carry out their developments.

Spatial distribution,sources and ecological risk assessment of heavy metals in Shenjia River watershed of the Three Gorges Reservoir Area

Surface soil/sediment samples were collected from the Water-Level Fluctuation Zone(WLFZ), cultivated land and forest land at 50 different grid points from Shenjia watershed, the Three Gorges Reservoir area in August 2013. The spatial distribution, sources and ecological risk assessment for Arsenic(As), Cadmium(Cd),Chromium(Cr), Copper(Cu), Nickel(Ni), Lead(Pb)and Zinc(Zn) were analyzed in this study. The results showed all tested metals had similar distribution patterns except Ni and Cr, with areas of high concentrations distributed in the southwest(WLFZ and watershed outlet) of the study area. Ni and Cr,which were highly positively correlated and present in high concentrations, were primarily distributed in the south and middle zones of the study area. Lower concentration areas of all metals were uniformly distributed west of the high-elevation zones and forest land. Factor analysis(FA) and factor analysismultiple linear regression(FA-MLR) showed that the major sources of Cd were fertilizer and traffic sources,which together accounted for 87% of Cd. As, Zn and Cu levels were primarily supplied by industrial and domestic sources, accounting for 76% of As, 75% of Cu and 67% of Zn. Surface soils/sediments of the study watershed contaminated by Cd represent a high ecological risk, whereas other metals represent low ecological risks. The potential ecological risk index(PERI) analysis indicated that it had a low(widerange) ecological risk and a moderate(small-range)ecological risk primarily distributed in the outlet of the study watershed. Fertilizers and traffic are the primary sources of Cd pollution, which should be more closely controlled for the purposes of water quality and ecological conservation.

THE TEMPORAL AND SPATIAL PATTERNS OF ENVIRONMENTAL RISK EVENTS IN THE PAST 30 YEARS IN SHENYANG CITY

The index of Risk Frequency (RF) and other relative indices are used to analyze the temporal and spatial patterns of environmental riskevents in the past 30 years in Shenyang city. The results show that thereexists significant difference of the RFs between periods of 1966-1977 and1978-1991 (t=7.353**, t0.01=2.807). During the past 30 years, there areno significant changes of the spatial patterns of the environmental risk,while the proportions of environmental risk among the districts are extremely different. In Shenyang city, there exists a series of high riskenterprises, and the chemical industry is the one with highest risk.

Spatial Distribution and Risk Assessment of Heavy Metals in Paddy Soils of Yongshuyu Irrigation Area from Songhua River Basin,Northeast China

There is an increasing concern for potentially hazardous metals pollution, which can threaten crops production and human health. In this study, the spatial distribution and environmental risks of eight heavy metals in surface soil samples collected from the paddy fields in Yongshuyu irrigation area, Northeast China were investigated. The mean concentrations of Pb, Cr, Cu, Ni, Zn, Cd, Hg and As were 34.6 ± 4.67, 82.8 ± 9.51, 17.3 ± 4.09, 21.2 ± 12.0, 88.6 ± 17.9, 0.18 ± 0.15, 0.22 ± 0.07 and 8.77 ± 2.47 mg/kg, respectively, which were slightly higher than their corresponding background values of Jilin Province, indicating enrichment of these metals in the paddy soils, especially for Ni, Cd and Hg. The spatial distribution of heavy metals was closely correlated with local anthropogenic activities, such as agricultural production, mining and transportation. The hot-spot areas of As and Cd were mainly concentrated in the up-midstream where were associated with agricultural activities. Cr and Cu showed similar spatial distributions with hot-spot areas distributed the whole irrigation area uniformly. Ni was mainly distributed in the downstream where Ni quarries concentrated, while the spatial distribution patterns of Hg was mainly located in the upstream and downstream where the soil was significantly influenced by irrigation and coal mining emission. The spatial distributions of Pb and Zn were mainly concentrated along the highway side. The pollution levels of Yongshuyu irrigation area were estimated through index of geo-accumulation(Igeo), Nemerow integrated pollution index(NIPI) and potential ecological risk index(PERI). The results showed that Cd and Hg were the main pollutants in the study area. Health risk assessment results indicated that children were in higher non-carcinogenic and carcinogenic risks than adults with the carcinogenic metal of As. Ingestion was the main exposure pathway to non-carcinogenic and carcinogenic risk for both adults and children. Principal component analysis(PCA) indicated that Cr and Cu were mainly from parent materials, while Cd and As were mainly affected by agricultural activities. Pb and Zn were controlled by traffic activities, and the accumulations of Ni and Hg were associated with mining activities. This study would be valuable for preventing heavy metals inputs and safety in rice production of the Songhua river basin.

Spatial Analysis of Risks and Vulnerabilities to Major Hazards in Madagascar Using the Multi-Criteria Method Based on the Analytical Hierarchy Process (AHP)

Natural disasters are not negligible factors that have significant impacts on a country’s development. Madagascar cannot escape cyclones, floods and drought due to its geographical situation. The objective in this work is to assess the risks and vulnerability to these hazards in order to strengthen the resilience of the Malagasy population. Our approach is based on multi-criteria spatial analysis using the Analytical Hierarchy Process (AHP). The results form decision spatial information that can be used at the strategic level of natural risk and disaster management. This work focuses on the degree of vulnerability and it was found in this study that the Androy and Atsimo-Atsinanana regions are the most vulnerable to major hazards in Madagascar not only because of their exposure to risk but also because of their very low socio-economic status.

Systematized Literature Review on Spatial Analysis of Environmental Risk Factors of Malaria Transmission

Malaria is still the major parasitic disease in the world, with approximately 438,000 deaths in 2015. Environmental risk factors (ERF) have been widely studied, however, there are discrepancies in the results about their influence on malaria transmission. Recently, papers have been published about geospatial analysis of ERF of malaria to explain why malaria varies from place to place. Our primary objective was to identify the environmental variables most used in the geospatial analysis of malaria transmission. The secondary objective was to identify the geo-analytic methods and techniques, as well as geo-analytic statistics commonly related to ERF and malaria. We conducted a systematized review of articles published from January 2004 to March 2015, within Web of Science, Pubmed and LILACS databases. Initially 676 articles were found, after inclusion and exclusion criteria, 29 manuscripts were selected. Temperature, land use and land cover, surface moisture and vector breeding site were the most frequent included variables. As for geo-analytic methods, geostatistical models with Bayesian framework were the most applied. Kriging interpolations, Geographical Weighted Regression as well as Kulldorff’s spatial scan were the techniques more widely used. The main objective of many of these studies was to use these methods and techniques to create malaria risk maps. Spatial analysis performed with satellite images and georeferenced data are increasing in relevance due to the use of remote sensing and Geographic Information System. The combination of these new technologies identifies ERF more accurately, and the use of Bayesian geostatistical models allows a wide diffusion of malaria risk maps. It is known that temperature, humidity vegetation and vector breeding site play a critical role in malaria transmission;however, other environmental risk factors have also been identified. Risk maps have a tremendous potential to enhance the effectiveness of malaria-control programs.

三江源国家公园人兽冲突风险评价

人兽冲突风险图揭示了风险的空间格局,有助于确定减轻野生动物肇事风险的优先区域。以三江源国家公园所涉4县为研究区域,以乡镇为研究单元,基于区域灾害系统理论,从致灾因子危险性、孕灾环境敏感性、承灾体脆弱性和防灾减灾能力4个方面构建人兽冲突风险评价模型并对研究区的人兽冲突空间风险和总体风险进行综合评价。结果表明:人兽冲突风险影响因素包括兽类密度、肇事次数、归一化植被指数(normalized difference vegetation index,NDVI)、人口密度、野生猎物密度、距河流距离、距居民点距离和牲畜密度。三江源国家公园人兽冲突风险具有明显的空间分异规律。风险评价结果总体上中部高于东部和南部,高风险区域主要分布在长江源园区治多县、曲麻莱县的乡镇,较高风险以上区域占比达97.07%,表明三江源国家公园人兽冲突风险总体较高。研究结果为确定人兽冲突风险影响因素和精准防控野生动物肇事提供科学依据。

典型钢铁冶炼场地重金属污染空间分布特征及风险评价

以上海某关停钢铁冶炼厂为研究对象,结合专业判断布点法与系统布点法布设83个土壤点位,采集表、中、深层共249个土壤样品,分析As、Pb、Cd、Ni、Hg、Cu这6种重金属的分布特征、污染状况、潜在生态风险及健康风险。结果表明,As、Pb出现部分样品超标,Cd、Pb为强变异,其他重金属变异程度中等;重金属平均含量在垂向上呈现自上而下逐渐降低的趋势,且最高值均分布在表层,累积区域主要为扒渣厂房、钢渣处理区和废钢配料间;地累积指数评价结果显示,Cd和Pb的污染相对较为严重,重污染及以上的样品比例分别为8.43%、3.61%。潜在生态风险评价结果显示,场地整体的生态风险较高,Cd为主要贡献因子,较强风险及以上的样品占比高达51.81%;人体健康风险评价结果显示,Pb、As和Cd可能对人体产生一定的健康风险,因此有必要开展土壤的风险管控或修复以保证场地的再开发利用。

车辆轨迹数据驱动的急弯路段追尾冲突风险时空演化规律

为有效揭示急弯路段上车辆间追尾冲突风险的形成与变化态势,选取典型事故多发急弯路段使用无人机航拍等方式采集交通流数据,利用Tracker软件提取车辆轨迹信息,构建急弯路段追尾冲突后侵入时间PET判别指标,结合冲突先导车LV与跟随车FV的速度、加速度变化划分追尾冲突模式,进而界定临界冲突点、冲突风险范围及PET变化率指标DPET,运用回归分析量化LV与FV的速度、加速度、速度差及加速度差对DPET的影响,阐明临界冲突点及主要追尾冲突模式的微观变化特性及时空演化规律。结果表明:车辆追尾冲突存在空间集聚性,主要集中在入弯缓和曲线上游、曲中标志断面下游及出弯缓和曲线下游;在潜在追尾冲突的九大类别中发生频率最高的四大类冲突数量占比高达83.24%;PET在冲突临界点和冲突风险范围内均下降,导致DPET均为负值,在冲突临界点PET快速下降,其下降程度显著大于冲突风险范围;FV速度、加速度及LV、FV间速度差、加速度差四个指标显著影响追尾冲突临界点的DPET变化;T10模式(LV减速、FV加速)冲突过程中的DPET均值最小,PET序列下降最为剧烈,危险性显著高于其他冲突模式。

2014—2020年全国沿海溢油风险情势变化

为研究大规模海上油品运输溢油风险的时空分布特征,采用地理空间分析、大数据分析、数理统计等方法,建立海上溢油风险空间分析模型,应用全国沿海船舶AIS数据、溢油历史事故、生态环境敏感目标等数据分析2014—2020年溢油风险情势的变化情况。结果表明:与2014年相比,2020年溢油事故风险指数均值、最大值分别增加27.8%和26.8%,溢油事故风险指数变化为−0.46~0.40,其中风险增加的海域主要分布在南北大通道、成山头、长江口、台湾海峡、珠江口海域,减少区域主要分布在近岸海域。全国沿海溢油事故高风险集中区主要分布在渤海—北黄海、长江口、台湾海峡、珠江口等海域;相较于2014年,2020年高风险集中区内有局部调整变化,但是高风险集中区的分布格局未发生变化。研究成果可为溢油风险管控和应急装备配备提供支撑。

黄河流域氨氮水生生物生态风险时空分异特征

分析揭示黄河流域氨氮水生生物生态风险时空分异特征,对黄河流域氨氮风险管控和水生态环境保护工作的开展以及氨氮水环境质量标准的细化和修订具有重要意义.本文基于生态环境部颁布的《淡水水生生物水质基准-氨氮》国家生态环境基准,应用统计学方法和风险商法,研究了2022年黄河流域氨氮风险的时空分布特征并识别出重点关注时段和区域.同时,通过变异系数建立了对比氨氮风险时空差异性的方法,并采用Spearman相关性分析识别出黄河流域氨氮风险主要影响因素.结果表明:(1)黄河流域氨氮长期毒性基准和风险商的空间差异性分别为时间差异性的3.3和2.1倍.(2)时间上,冬季氨氮浓度和风险商显著升高,有风险的断面由春季的2.3%增至13.6%,冬季情况亟需额外关注.(3)空间上,黄河流域91%的断面无氨氮风险或风险较低,但渭河、汾河等黄河支流部分断面,特别是汇流河段氨氮长期毒性风险问题较为突出.(4)黄河流域氨氮风险除氨氮浓度外,主要受水体pH影响,水温对氨氮风险影响较小.研究显示,制定区域性氨氮水质标准和排放标准比季节差异化标准更为重要,需要重点关注支流和干支流汇流河段并建立水质监控和预警机制.除控制氨氮污染物的排放外,还应重点关注pH较高的水体.

基于便携式X射线荧光光谱速测的设施菜地土壤重金属污染诊断与评价

土壤重金属污染快速诊断与评价是污染防控与风险管理的前提。以广东省典型设施蔬菜产地土壤为研究对象,采用便携式X射线荧光光谱法(portable X-ray fluorescence spectroscopy,PXRF)原位快速获取土壤重金属(镉(Cd)、铜(Cu)、铬(Cr)、铅(Pb)、锌(Zn)、砷(As)、镍(Ni)及汞(Hg))含量,在传统实验室方法验证PXRF的准确性和稳定性的基础上,对广东省设施菜地表层土壤重金属的污染状况进行快速诊断,并对土壤重金属污染风险进行评价。结果表明:(1)异位PXRF法对土壤Cd、Cu、Cr、Pb、Zn、As及Ni的测定值与传统实验室方法测定值极显著相关(P<0.01),土壤Pb和As含量的PXRF原位测定值与传统实验室方法测定值极显著相关(P<0.01);(2)土壤含水量为150 g·kg^(-1)~200 g·kg^(-1)时,Cr、Pb、Zn和As的PXRF原位测定值与实验室测定值的相关性达到了极显著水平(P<0.01);(3)土壤Cd和Cu的超标现象较为突出,其点位超标率分别为20.9%和10.0%。设施菜地土壤Cd的平均含量为0.21 mg·kg^(-1),约为露天农田土壤的1.2倍。珠江三角洲地区设施土壤中各重金属的含量整体较其他地区高;(4)土壤Cd、Cu、Cr、Pb、Zn、As、Ni及Hg的单项污染指数均小于1,由高到低依次为Cd>Cu>Pb>Zn>Cr>As>Ni>Hg,内梅罗综合污染指数的均值为0.69。就整体平均值而言,土壤重金属污染程度处于清洁水平。PXRF实现了广东省设施菜地土壤重金属污染的快速诊断,并快速识别出Cd和Cu为设施菜地污染风险较高的潜在污染元素,研究结果可为设施农业土壤重金属污染快速诊断与评价提供方法和数据支撑。

浙西南典型耕地土壤重金属空间分布及污染评价

【目的】采集分析丽水市莲都区某乡土壤样品,了解全乡农田重金属污染情况,为后续开展土壤安全管理和污染综合治理提供科学依据。【方法】采用主成分分析法进行来源解析,运用单项污染指数法、内梅罗指数法、地积累指数法、潜在生态风险指数法及生态风险预警指数进行土壤重金属污染评价。【结果】土壤镉(Cd)和铅(Pb)超标率(风险筛选值)分别为60.71%和39.29%,但均低于农用地土壤污染风险管控值。土壤Cd污染指数(Pi)为1.31,属于轻微污染,其余重金属小于1,无污染;内梅罗指数(P综合)为1.10,属于轻度污染。土壤Cd和Pb的地积累指数(Igeo)分别为1.74和0.79,属中度污染和无污染-中度污染;其余重金属均处于清洁水平。5种重金属的潜在生态危害系数(E i r)均值小于40,处于轻微水平风险;生态风险指数(IR)为48.87,属于轻微风险。土壤生态风险预警指数(IER)处于轻度预警级别。汞(Hg)和铬(Cr)受到人为和自然双重因素影响,Cd、Pb和砷(As)主要受矿山开发过程中污染物排放和畜禽粪便施用等人类活动影响。【结论】研究区土壤总体为轻微污染,Cd和Pb是研究区农田土壤最重要的生态环境因子,后续应加强治理和动态检测,保障农产品安全。

基于最大熵模型的城市内涝风险预测:以北京市主城区为例

随着全球气候变化和城市化发展,城市内涝频发且严重影响城市发展,研究内涝影响因素,进行内涝风险评估对防灾减灾具有重要意义。以北京市主城区为研究区域,获取内涝空间数据和影响因子数据,采用MaxEnt模型进行探究,识别内涝潜在风险区和分析影响因子与内涝风险的关系,结果表明:影响内涝风险的主导因子为与立交桥的距离、建筑密度、不透水面比例、人口密度、暴雨持续时间、归一化植被指数(normalized difference vegetation index,NDVI);研究区内超过24.6%区域范围都处于内涝风险区,高风险区总面积约为40.17 km^(2),中风险区的总面积约为298.09 km^(2);较低风险与低风险区面积分别为423.75 km^(2)和30.53 km^(2)。各区内涝点分布数量大小关系为丰台区>海淀区>朝阳区>石景山区>西城区、东城区;历史内涝点在空间分布上具有“南密北疏,西密东疏”的分布格局与“多核中心,次中心团带连接”的特征。对风险评估结果进行空间自相关分析发现风险概率在丰台区中部,海淀区东北部、南部,石景山区东部地区呈高-高聚集,表明该区域在未来可能会受到周围区域的影响而发生内涝灾害,要高度关注该区域实现精准防控。相关成果为城市进行基础设施完善改造、潜在内涝积水点防治、制定应急减灾预案和应对措施等方面提供一定参考。

柴达木盆地可鲁克湖夏季表层沉积物重金属分布特征、来源和潜在生态风险

为了辨识青藏高原地区湖泊沉积物重金属的污染状况,丰富环境敏感脆弱区高原重金属的相关研究,因地制宜地保护特殊地域单元的生态环境,以青藏高原地区典型淡水湖为例,于2021年5月对可鲁克湖及附近部分湿地表层沉积物中10种广泛存在且对环境影响显著的重金属(Al、Cr、Mn、Fe、Ni、Cu、Zn、As、Cd、Pb)含量、沉积物pH和有机质等理化特征进行分析。通过主成分分析法初步解析其可能来源,并运用地累积指数法和潜在生态风险指数法进行生态风险评价。结果表明:除pH外,可鲁克湖表层沉积物的理化特征空间不均匀;有机质的含量及分布特征是影响Cr、Mn、Ni等重金属空间分布的主要原因;沉积物重金属浓度的平均值由高到低依次为:Fe>Al>Mn>Zn>Ni>Cu>Pb>Cr>As>Cd,均低于青海省土壤背景值;重金属地累积指数平均值均小于0,潜在重金属生态风险为轻微,仅Cd具有中等程度的生态风险,表明Cd是造成夏季可鲁克湖表层沉积物重金属生态风险的主要影响元素。相关性以及主成分分析结果显示,Cr、Ni、Cu、As、Cd、Pb具有相似的污染来源,表层沉积物中的重金属来源可能主要为自然源,受到内源沉积及岩石风化等自然作用的影响。本研究将为揭示高敏感地区表层沉积物的重金属迁移转化规律提供理论依据。

湖南省极端气候时空特征分析及风险评估

为探究湖南省极端气候的时空变化特征及风险发生概率,基于湖南省32个气象站点1961—2017年逐日气象观测资料,选取12个极端降水指数和16个极端气温指数,利用线性倾向法、M-K趋势检验法、克里金插值等方法,对湖南省极端气候的时空变化特征进行探究,并采用信息扩散模型对湖南省极端气候风险进行评估,研究表明:近57年来湖南省极端降水指数总体变化趋势较为平缓,大多数极端降水指数在空间上呈东高西低、南高北低的分布。极端气温指数总体变化趋势呈显著变暖趋势,表征高温的指数在空间上呈东南向西北递减的趋势。对湖南省极端降水的风险评估显示,湘西北发生极端降水的风险更大,而湘东南的降水总量更多。对湖南省极端气温的风险评估显示,湘西北为持续高温的高风险地区,常德市发生极端高温的风险概率较大,为2~3 a一遇。

基于景观格局的石林彝族自治县景观生态风险评价

基于石林彝族自治县2000—2020年遥感影像,利用ENVI、ArcGIS以及Fragstats4景观分析软件对研究区景观结构的组成及转变进行量化处理,建立石林县生态风险评价体系。结果表明:1)耕地占石林县总面积的50%以上,2000—2020年耕地面积减少27.51 km^(2),不透水面面积增加41.60 km^(2),林地、草地面积变化不活跃,但在2010—2020年呈下降趋势。2)20年间石林县综合生态风险变化较为剧烈,风险指数在2010年达到峰值(0.3129),其中水体景观作为高危风险景观,其指数在2010年高达2.3793;耕地作为石林县对景观生态影响最大的因子,其贡献权重高达52%。3)由于强烈的人类活动,研究区以高生态风险区为主,占研究区总面积的66.5%。总之,整个研究期间,石林彝族自治县的生态环境呈现局部改善和部分退化并存的状态,景观生态安全呈现较好的趋势,建议从调节当地产业结构入手,针对不同风险区制定相应措施,妥善处理生态保护与经济建设之间的关系。

高原富营养化湖泊杞麓湖微囊藻毒素分布特征、相关因子及其健康风险分析

杞麓湖作为典型的富营养化高原湖泊,其藻华暴发引发的微囊藻毒素(microcystins,MCs)污染问题会危害水生态安全并造成人体健康风险。为了评估杞麓湖流域MCs的秋冬季节污染现状以及健康风险情况,对湖内和7条主要入湖河流入湖口的表层水进行采样检测,分析MCs主要异构体的时空分布特征,研究MCs与水质和浮游植物等环境因子的关系,并通过人体非致癌健康风险评价MCs的风险等级。结果发现,MCs浓度自秋季到冬季呈下降趋势,秋季湖内胞内MCs(IMCs)占比超过99%,冬季IMCs与胞外MCs(EMCs)浓度接近。MC-RR和MC-LR是主要的MCs异构体类型,其中MC-RR在秋季浓度占比高于MC-LR和MC-YR,而冬季MC-LR最高。MCs与微囊藻密度等生物因子呈极显著正相关关系,与TN、TP和NH_(3)-N营养盐呈显著负相关关系。杞麓湖EMCs污染的风险指数范围为0.004~0.110,处于极低或低风险,冬季风险略高于秋季,因南岸入湖EMCs污染以及湖内IMCs释放带来的风险需要进一步关注。

基于空间逻辑回归模型的滑坡易发性评价

滑坡是山地丘陵地区发生最频繁、危害性最强的地质灾害之一。进行滑坡易发性评价对于人们进行土地灾害评估和减轻滑坡相关损失是十分必要的。在过去的几十年里,已经开发了许多种模型用于滑坡评估和易发性分级,但这些模型大多数并未考虑数据的空间结构信息,预测精度还有待提高。研究使用随机森林模型筛选风险因子后对四川雅安芦山地区震后滑坡使用贝叶斯空间逻辑回归进行建模,并与普通未考虑空间结构信息的逻辑回归建模结果进行比较。贝叶斯空间逻辑回归的AUC值为0.931,在传统逻辑回归的基础上提升了近14%,为滑坡易发性评价带来了新的思路。