Snow model sensitivity analysis to understand spatial and temporal snow dynamics in a high‐elevation catchment

In this paper, we addressed a sensitivity analysis of the snow module of the GEOtop2.0 model at point and catchment scale in a small high‐elevation catchment in the Eastern Italian Alps (catchment size: 61 km²). Simulated snow depth and snow water equivalent at the point scale were compared with measured data at four locations from 2009 to 2013. At the catchment scale, simulated snow‐covered area (SCA) was compared with binary snow cover maps derived from moderate‐resolution imaging spectroradiometer (MODIS) and Landsat satellite imagery. Sensitivity analyses were used to assess the effect of different model parameterizations on model performance at both scales and the effect of different thresholds of simulated snow depth on the agreement with MODIS data. Our results at point scale indicated that modifying only the “snow correction factor” resulted in substantial improvements of the snow model and effectively compensated inaccurate winter precipitation by enhancing snow accumulation. SCA inaccuracies at catchment scale during accumulation and melt period were affected little by different snow depth thresholds when using calibrated winter precipitation from point scale. However, inaccuracies were strongly controlled by topographic characteristics and model parameterizations driving snow albedo (“snow ageing coefficient” and “extinction of snow albedo”) during accumulation and melt period. Although highest accuracies (overall accuracy = 1 in 86% of the catchment area) were observed during winter, lower accuracies (overall accuracy < 0.7) occurred during the early accumulation and melt period (in 29% and 23%, respectively), mostly present in areas with grassland and forest, slopes of 20–40°, areas exposed NW or areas with a topographic roughness index of ?0.25 to 0 m. These findings may give recommendations for defining more effective model parameterization strategies and guide future work, in which simulated and MODIS SCA may be combined to generate improved products for SCA monitoring in Alpine catchments.     

Modelling atmospheric and hydrologic processes for assessment of meadow restoration impact on flow and sediment in a sparsely gauged California watershed

The restoration of meadowland using the pond and plug technique of gully elimination was performed in a 9‐mile segment along Last Chance Creek, Feather River Basin, California, in order to rehabilitate floodplain functions such as mitigating floods, retaining groundwater, and reducing sediment yield associated with bank erosion and to significantly alter the hydrologic regime. However, because the atmospheric and hydrological conditions have evolved over the restoration period, it was difficult to obtain a comprehensible evaluation of the impact of restoration activities by means of field measurements. In this paper, a new use of physically based models for environmental assessment is described. The atmospheric conditions over the sparsely gauged Last Chance Creek watershed (which does not have any precipitation or weather stations) during the combined historical critical dry and wet period (1982–1993) were reconstructed over the whole watershed using the atmospheric fifth‐generation mesoscale model driven with the US National Center for Atmospheric Research and US National Center for Environmental Prediction reanalysis data. Using the downscaled atmospheric data as its input, the watershed environmental hydrology (WEHY) model was applied to this watershed. All physical parameters of the WEHY model were derived from the existing geographic information system and satellite‐driven data sets. By comparing the prerestoration and postrestoration simulation results under the identical atmospheric conditions, a more complete environmental assessment of the restoration project was made. Model results indicate that the flood peak may be reduced by 10–20% during the wet year and the baseflow may be enhanced by 10–20% during the following dry seasons (summer to fall) in the postrestoration condition. The model results also showed that the hydrologic impact of the land management associated with the restoration mitigates bank erosion and sediment discharge during winter storm events. Copyright © 2013 John Wiley & Sons, Ltd.     

基于决策树分类的大屯矿区地物信息提取及矿区污染分析

本文在对国内外遥感图像分类方法充分研究分析的基础上,选择决策树分类法对大屯矿区的Landsat 8遥感图像进行分类研究。选取样本提取并分析研究区典型地类光谱特征曲线,依据光谱曲线特征和归一化植被指数建立了土地利用分类决策树模型,通过反复试验和修正,筛选出适宜大屯矿区地物分类的决策树最优阈值,对研究区进行分类和精度评价,最后通过分类结果对研究区的水体污染状况进行简要分析。     

雅安芦山4.20震后县级单元生态系统风险评价

区域生态风险评价是对各种生态风险及环境问题进行评价和管理的重要手段。针对雅安地震灾区特殊的自然地理及生态环境特征,选取芦山县为研究对象,采用遥感、GIS及SPSS统计分析的方法,通过风险源、风险受体、暴露和易损性分析,建立生态风险综合评价模型,划分生态风险区类型,进而提出生态风险管理对策。结果表明:1)微度和低度生态风险区集中分布在高海拔的森林及草地生态系统,该区生物多样性丰富,抗干扰能力较强,地质灾害及人类活动影响较小;2)中度和高度生态风险区具有沿农田及建设用地生态系统集聚分布的特征,该区地质灾害频繁,地壳活动性较强,生态系统抵抗灾害的能力较差。研究结果可为地震灾区防御、规避风险及安全选址提供科学依据。     

基于线要素动态化简的匹配算法比较与评价

矢量线要素数据来源多样,细节层次不一,限制了已有匹配算法正确率的提高,同时也给算法评价带来困难。化简可以减少线要素细节层次,提取其主要形态,据此提出一种基于线要素动态化简的匹配算法评价新方法。对不同匹配算法采用相同数据,在相同化简算法支撑下进行匹配,从而实现对不同匹配算法的评价。首先,阐述动态化简方法提取线要素主要形态的过程;其次,利用动态化简分别辅助4种已有匹配算法,获取每个匹配算法的最优匹配正确率;最后,将4种匹配算法的原始匹配结果与加入动态化简后的匹配结果进行对比,分析化简对匹配结果的影响,并把该影响运用到匹配算法的比较和评价中来。其中,1通过匹配正确率变化、误匹配等分析了匹配算法的数据适用性;2通过化简比例系数K变化时新增匹配数量的统计,评价了匹配算法对线要素局部细节的敏感程度并提出该指标的量化方法;3结合匹配算法采用的匹配相似度指标对其作出评价。     

山东半岛典型海岸带多环芳烃分布特征、来源解析及风险评价

山东半岛海岸带面临着各类复杂的环境问题,尤其是受到了多环芳烃(PAHs)等持久性有机物的污染,本文研究了整个山东半岛典型海岸带62个站点表层沉积物中PAHs的含量及其分布特征,并对其来源和潜在风险进行解析与评价。研究表明,该地区表层沉积物中16种PAHs总含量为0.06~3191.40 ng/g(平均值262.08 ng/g),与国内外海岸带相比,山东半岛海岸带表层沉积物中PAHs整体污染状况处于较低水平,但个别站点的PAHs含量偏高。运用特征比值法、相关性分析及主成分分析法解析研究区PAHs主要来源为木柴、煤炭、油类的燃烧以及油类泄露的联合作用。采用效应区间低值法(ERL)和中值法(ERM)对PAHs进行生态风险评价,结果表明莱州湾周边所有站点及威海、青岛周边个别站点苊、芴浓度位于ERL值与ERM值之间,但多数站点对生态环境潜在负面效应很小。山东半岛典型海岸带中PAHs对生物的毒副作用尚在安全可控范围内,极少对生态环境产生负面效应。     

Modelling complex systems of heterogeneous agents to better design sustainability transitions policy

This article proposes a fundamental methodological shift in the modelling of policy interventions for sustainability transitions in order to account for complexity (e.g. self-reinforcing mechanisms, such as technology lock-ins, arising from multi-agent interactions) and agent heterogeneity (e.g. differences in consumer and investment behaviour arising from income stratification). We first characterise the uncertainty faced by climate policy-makers and its implications for investment decision-makers. We then identify five shortcomings in the equilibrium and optimisation-based approaches most frequently used to inform sustainability policy: (i) their normative, optimisation-based nature, (ii) their unrealistic reliance on the full-rationality of agents, (iii) their inability to account for mutual influences among agents (multi-agent interactions) and capture related self-reinforcing (positive feedback) processes, (iv) their inability to represent multiple solutions and path-dependency, and (v) their inability to properly account for agent heterogeneity. The aim of this article is to introduce an alternative modelling approach based on complexity dynamics and agent heterogeneity, and explore its use in four key areas of sustainability policy, namely (1) technology adoption and diffusion, (2) macroeconomic impacts of low-carbon policies, (3) interactions between the socio-economic system and the natural environment, and (4) the anticipation of policy outcomes. The practical relevance of the proposed methodology is subsequently discussed by reference to four specific applications relating to each of the above areas: the diffusion of transport technology, the impact of low-carbon investment on income and employment, the management of cascading uncertainties, and the cross-sectoral impact of biofuels policies. In conclusion, the article calls for a fundamental methodological shift aligning the modelling of the socio-economic system with that of the climatic system, for a combined and realistic understanding of the impact of sustainability policies.     

DSC2型称重式降水传感器测雨性能的分析

为更有效地利用降雨观测数据,充分发挥新型探测设备建设效益,文章对DS(2型称重降水传感器的测雨性能进行分析评估,选取北京市13个国家级地面气象观测站在2013年4—10月,称重式降水传感器与人工、翻斗观测降雨量的业务观测资料,分析称重与人工和翻斗观测在降雨总量、日降雨量等方面的差异。结果表明:在选取样本中,12个台站的总降雨量误差符合现行业务要求,三种测量在日降雨量等级判断方面基本一致。称重比人工观测的日降雨量平均偏小0.13 mm,日降雨量相关系数为0.9968,对应地,称重比翻斗观测的结果平均偏小0.17 mm,日降雨量相关系数为0.9983。     

基于作物模型的河南省旱稻干旱风险评估

采用作物模型与数理统计相结合的方法,利用长期历史气象资料,以作物模型和地理信息系统技术为工具,系统分析了河南地区旱稻生育期水分盈亏情况。以模型模拟的雨养条件下实际蒸散量相对于潜在条件下的蒸散量(即需水量)的亏缺率,即水分亏缺指数,以雨养条件下产量相对于潜在产量的损失率(即灾损指数)作为产量灾损强度评价指标,从受旱程度和产量损失两个角度构建干旱风险评估模型,进行干旱风险评估。结果表明:河南省旱稻生育期集中在6—9月,水分亏缺最多的阶段为出苗—穗分化阶段,水分亏缺指数变化在0.50~0.60,其次是开花—成熟阶段和穗分化—开花阶段,水分亏缺指数变化在0.11~0.43;全生育期水分亏缺指数在0.36~0.50。出苗—穗分化阶段干旱发生的风险最大,其次是开花—成熟阶段,穗分化—开花阶段的最小。河南旱稻生育期干旱风险呈现为由东南向西北逐渐升高的分布,其中三门峡、济源西部一带风险最高,洛阳南部和南阳西北部一带最低,黄河以北大部地区和豫东、豫南地区风险居中。     

应用系统分析与事故树模型的设备雷电灾害风险评估

分析目前国内雷电灾害风险评估发展现状,针对精细化雷击风险评估需求,以某大桥塔体电梯雷电灾害风险评估为例,在对雷击损坏途径进行系统分析的基础上,引入事故树(FTA)分析方法对电梯雷击损坏事件的致因关系进行了建模、分析与评价,得出电梯雷击损坏事件发生的年预计概率、导致雷击电梯损坏事件发生的关键以及最佳控制雷击电梯损坏事件发生的最有效因素。