Comparison of landslide susceptibility based on a decision-tree model and actual landslide occurrence: The Akaishi Mountains, Japan

This paper proposes a statistical decision-tree model to analyze landslide susceptibility in a wide area of the Akaishi Mountains, Japan. The objectives of this study were to validate the decision-tree model by comparing landslide susceptibility and actual landslide occurrence, and to reveal the relationships among landslide occurrence, topography, and geology. Landslide susceptibility was examined through ensemble learning with a decision tree. Decision trees are advantageous in that estimation processes and order of important explanatory variables are explicitly represented by the tree structures. Topographic characteristics (elevation, slope angle, profile curvature, plan curvature, and dissection and undissection height) and geological data were used as the explanatory variables. These topographic characteristics were calculated from digital elevation models (DEMs). The objective variables were landslide occurrence and reactivation data between 1992 and 2002 that were depicted by satellite image analysis. Landslide susceptibility was validated by comparing actual data on landslides that occurred and reactivated after the model was constructed (between 2002 and 2004).This study revealed that, from 2002 to 2004, landslides tended to occur and reactivate in catchments with high landslide susceptibility. The landslide susceptibility map thus depicts the actual landslide occurrence and reactivation in the Akaishi Mountains. This result indicates that the decision-tree model has appropriate accuracy for estimating the probabilities of future landslides. The tree structure indicates that landslides occurred and reactivated frequently in the catchments that had an average slope angle exceeding ca. 29° and a mode of slope angle exceeding 33°, which agree well with previous studies. A decision tree also quantitatively expresses important explanatory variables at the higher order of the tree structure.     

Chironomids as quantitative indicators of mean July air temperature: validation by comparison with century-long meteorological records from northern Sweden

This study evaluates the potential of using chironomid assemblages to estimate past temperature changes by comparing chironomid-inferred temperatures to meteorological data for the last 87 years. This comparison is made using high-resolution (i.e., sub-decadally resolved) short cores of four lakes along a gradient of altitude (Lake Njulla, 999 m a.s.l., Lake 850, 850 m a.s.l., Lake Alanen Laanijavri, 365 m a.s.l. and Lake Vuoskkujavri, 348 m a.s.l.), vegetation (pine forest to alpine tundra vegetation) and temperature (mean July temperature of 12.4 to 8.1°C). Patterns of chironomid-inferred changes in mean July air temperature were highly comparable to changes in the meteorological data. Moreover, instrumental data were almost always within the specific errors of the quantitative estimates using chironomids. These results indicate that chironomids can be used as a powerful tool to reconstruct temperatures and that chironomids are sensitive enough to record temperature changes of low magnitude such as those recorded during the Holocene. Although this relationship between temperature and chironomid community is strong for the last 87 years, we cannot assume that other environmental factors such as organic matter, changes of lake water depth or oxygen availability were not more significant over longer temporal scales of the Holocene, or longer.     

Assessment of the prediction error in a large-scale application of a dynamic soil acidification model

 The prediction error of a relatively simple soil acidification model (SMART2) was assessed before and after calibration, focussing on the Al and NO₃ concentrations on a block scale. Although SMART2 is especially developed for application on a national to European scale, it still runs at a point support. A 5×5 km² grid was used for application on the European scale. Block characteristic values were obtained simply by taking the median value of the point support values within the corresponding grid cell. In order to increase confidence in model predictions on large spatial scales, the model was calibrated and validated for the Netherlands, using a resolution that is feasible for Europe as a whole. Because observations are available only at the point support, it was necessary to transfer them to the block support of the model results. For this purpose, about 250 point observations of soil solution concentrations in forest soils were upscaled to a 5×5 km² grid map, using multiple linear regression analysis combined with block kriging. The resulting map with upscaled observations was used for both validation and calibration. A comparison of the map with model predictions using nominal parameter values and the map with the upscaled observations showed that the model overestimated the predicted Al and NO₃ concentrations. The nominal model results were still in the 95% confidence interval of the upscaled observations, but calibration improved the model predictions and strongly reduced the model error. However, the model error after calibration remains rather large.     

Validation of Daily Amplitude of Sea Surface Temperature Evaluated with a Parametric Model Using Satellite Data

The authors have verified a regression model for the evaluation of the daily amplitude of sea surface temperature (ΔSST) proposed by Kawai and Kawamura (2002). The authors investigated the accuracy of satellite data used for the evaluation and showed that ΔSST error caused by satellite data error is less than ±0.7 K. The evaluated ΔSSTs were compared with in situ values. Its root-mean-square error is about 0.3 K or less, except for a coastal region, and it has a bias of more than +0.1 K in the tropics. This bias can be removed by considering latent heat flux. This revised version was published online in July 2006 with corrections to the Cover Date.     

Biomarkers and environmental risk assessment: guiding principles from the human health field

Although the potential use of biomarkers within environmental risk assessment (ERA) has long been recognised their routine use is less advanced compared with clinical human health risk assessment, where a number of familiar biomarkers (such as blood pressure and serum cholesterol) are in common usage. We have examined how biomarkers are incorporated into human health risk assessment and have identified several 'required elements'. These include identification of the (clinical) assessment endpoint at the outset, rational selection of the biomarker(s) (the measurement endpoint), biomarker 'validation' (e.g. QA/QC) and biomarker 'qualification' (evidence linking the measurement and assessment endpoints). We discuss these elements in detail and propose that their adoption will facilitate the routine use of biomarkers in environmental risk assessment. Furthermore, our analysis highlights the need for cooperation between those working with biomarkers within human and environmental risk assessment to exchange best practice between common disciplines for mutual advantage.     

德州70 cm高度气温与地面温度的关系初探

利用统计学和气象学原理,对德州2008年1月1日—12月31日德州70 cm高度的气温(用T₇₀表示)与地面温度（用T₀表示）中08、14时和20时及日平均资料进行分析。结果表明：冬半年08时T₇₀＞T₀（或T₇₀≈T₀）;夏半年T₇₀＜T₀,6月差值最大,为-2.6℃。14时全年都是T₇₀＜T₀,3月差值最大,为-12.1℃。20时全年基本都是T₇₀＞T₀。就日平均而言,全年都是T₇₀＜T₀。运用回归分析法建立了以T₀为基础的T₇₀预测模型,经检验表明,3—9月预测准确率较高,可以满足当地农事需要。     

2009-18年西北太平洋区域海洋再分析CORA1.0产品研制及检验

在51年(1958-2008)西北太平洋区域海洋再分析CORA1.0产品的基础上,改进了模式配置和同化方法,研制了2009-18年的CORA产品并对其进行以下检验:(1)温盐和海表高度异常均方根误差分布检验;(2)35°N处温度断面分布检验;(3)再分析流场和表漂浮标轨迹对比检验.结果显示,2009-18年的CORA产品可以再现海洋要素长时间序列,时空多尺度的变化特征,为研究特征海洋现象和过程提供背景信息.     

Human impacts and eutrophication patterns during the past ~200 years at Lago Grande di Avigliana (N. Italy)

A short sediment core from Lago Grande di Avigliana (Piedmont, Italy), the second most eutrophied lake in Italy, was analysed for pollen and diatoms to reconstruct land-use changes and to estimate baseline conditions for total phosphorus (TP) in the water column. Varve counts on sediment thin-sections and ²¹⁰Pb, ²²⁶Ra, and ¹³⁷Cs dating provided a reliable chronology for the past ~200 years. The main pollen-inferred land-use changes showed a sharp decrease of hemp retting around AD 1900, as well as a gradual change to less intensive agriculture and increasing abundance of exotic plants since AD ~1970. Diatom-inferred TP reconstructions indicated stable TP concentrations until AD ~1950, revealing baseline mesotrophic conditions (TP <25 μg l⁻¹). After AD ~1950, TP values increased distinctly and continuously, culminating in the late 1960s with concentrations of 150 μg l⁻¹. Subsequently, diatoms implied a linear decrease of TP, with an inferred value of 40 μg l⁻¹ in the surface sediment sample. Comparison with instrumental TP measurements from the water column since AD 1980 showed a rapid recovery and allowed a direct validation of the diatom TP inference. However, although the TP concentration has decreased considerably, baseline conditions have not yet been reached. When compared to the limnological effects of sewage discharges on inferred-TP concentration, our results indicated that agricultural land use played a minor role in the lake’s eutrophication.