Rainfall induced debris flows in pyroclastic deposits, Campania (southern Italy)

A combination of empirical and physically based hydrological models has been used to analyze historical data on rainfall and debris-flow occurrence in western Campania, to examine the correlation between rainfall and debris-flow events.

Rainfall data from major storms recorded in recent decades in western Campania were compiled, including daily series from several rain gauges located inside landslide areas, supplemented by hourly rainfall data from some of the principal storms.

A two-phase approach is proposed. During phase 1, soil moisture levels have been modelled as the hydrological balance between precipitation and evapotranspiration, on a daily scale, using the method of Thornthwaite [Geograph. Rev. 38 (1948) 55].

Phase 2 is related to the accumulation of surplus moisture from intense rainfall, leading to the development of positive pore pressures. These interactions take place on an hourly time scale by the “leaky barrel” (LB) model described by Wilson and Wiezoreck [Env. Eng. Geoscience, 1 (1995) 11]. In combination with hourly rainfall records, the LB model has been used to compare hydrological effects of different storms. The critical level of retained rain water has been fixed by the timing of debris-flow activity, related to recorded storm events.

New rainfall intensity–duration thresholds for debris-flow initiation in western Campania are proposed. These thresholds are related to individual rain gauge and assume a previously satisfied field capacity condition. The new thresholds are somewhat higher than those plotted by previous authors, but are thought to be more accurate and thus need less conservatism.     

Comparison of logistic regressions and snowfall intensity–duration threshold as forecasting tools for direct-action snow avalanches in the Presidential Range,New Hampshire,USA

Built environment, which includes some major investments in Oman, has been designed based on historical data and do not incorporate the climate change effects. This study estimates potential variations of the hourly annual maximum rainfall (AMR) in the future in Salalah, Oman. Of the five climate models, two were selected based on their ability to simulate local rainfall characteristics. A two-stage downscaling–disaggregation approach was applied. In the first stage, daily rainfall projections in 2040–2059 and 2080–2099 periods from MRI-CGCM3 and CNRM-CM5 models based on two Representative Concentration Pathways (RCP8.5 and RCP4.5) were downscaled to the local daily scale using a stochastic downscaling software (LARS-WG5.5). In the second stage, the stochastically downscaled daily rainfall time series were disaggregated using K-nearest neighbour technique into hourly series. The AMRs, extracted from 20 years of projections for four scenarios and two future periods were then fitted with the generalized extreme value distribution to obtain the rainfall intensity–frequency relationship. These results were compared with a similar relationship developed for the AMRs in baseline period. The results show that the reduction in number of wet days and increases in total rainfall will collectively intensify the future rainfall regime. A marked difference between future and historical intensity–frequency relationships was found with greater changes estimated for higher return periods. Furthermore, intensification of rainfall regime was projected to be stronger towards the end of the twenty-first century.     

Modeling landslide recurrence in Seattle, Washington, USA

To manage the hazard associated with shallow landslides, decision makers need an understanding of where and when landslides may occur. A variety of approaches have been used to estimate the hazard from shallow, rainfall-triggered landslides, such as empirical rainfall threshold methods or probabilistic methods based on historical records. The wide availability of Geographic Information Systems (GIS) and digital topographic data has led to the development of analytic methods for landslide hazard estimation that couple steady-state hydrological models with slope stability calculations. Because these methods typically neglect the transient effects of infiltration on slope stability, results cannot be linked with historical or forecasted rainfall sequences. Estimates of the frequency of conditions likely to cause landslides are critical for quantitative risk and hazard assessments. We present results to demonstrate how a transient infiltration model coupled with an infinite slope stability calculation may be used to assess shallow landslide frequency in the City of Seattle, Washington, USA. A module called CRF (Critical RainFall) for estimating deterministic rainfall thresholds has been integrated in the TRIGRS (Transient Rainfall Infiltration and Grid-based Slope-Stability) model that combines a transient, one-dimensional analytic solution for pore-pressure response to rainfall infiltration with an infinite slope stability calculation. Input data for the extended model include topographic slope, colluvial thickness, initial water-table depth, material properties, and rainfall durations. This approach is combined with a statistical treatment of rainfall using a GEV (General Extreme Value) probabilistic distribution to produce maps showing the shallow landslide recurrence induced, on a spatially distributed basis, as a function of rainfall duration and hillslope characteristics.     

Rainfall flood hazard at nuclear power plants in India

Flood hazard evaluation is an important input for Nuclear Power Plants external events safety studies. In the present study, flood hazard at various nuclear sites in India due to rainfall has been evaluated. Hazard estimation is a statistical procedure by which rainfall intensity versus occurrence frequency is estimated from historical records of rainfall data and extrapolated with asymptotic extreme value distribution. Rainfall data needed for flood hazard assessment are daily annual maximum rainfall (24?h data). The observed data points have been fitted using Gumbel, power law and exponential distribution, and return period has been estimated. To study the stationarity of rainfall data, a moving window estimate of the parameters has been performed. The rainfall pattern is stationary in both coastal and inland regions over the period of observation. The coastal regions show intense rainfall and higher variability than inland regions. Based on the plant layout, catchment area and drainage capacity, the prototype fast breeder reactor (PFBR) site is unlikely to be flooded.     

基于位移比模型的三峡库区云阳县域内蠕变型滑坡降雨预警

建立高效合理的区域滑坡灾害降雨预警模型对滑坡防治具有重要意义.然而以往的研究多侧重于临滑预警,对蠕变型滑坡在强降雨工况下的短暂加速变形的预警研究还有待深入.以三峡库区云阳县域内滑坡为例,首先根据滑坡地表位移监测数据的特点对统计样本进行合理筛选.再通过降雨因子与滑坡发生的相关性分析以及对滑坡在降雨条件下位移变化情况的数值模拟,确定了适用于不同时间阶段的降雨统计变量.然后将考虑了滑坡规模特征的滑坡位移比（累计位移与滑坡纵长之比）作为变形指标,分时段统计滑坡地表位移监测数据与历史降雨信息,建立了日降雨数据与月位移数据的对应关系,得到了可用于确定降雨量阈值的位移比模型,并获得了云阳县蠕变型滑坡的五级预警分区.最后分别选用研究区滑坡险情实例、长年位移监测数据及极端降雨事件对模型预警效果进行检验.结果显示基于专业监测数据的位移比模型的滑坡降雨预警结果与实际情况相符,可为蠕变型滑坡的预警预报提供依据.      

Storms Generator Method That Preserves Their Historical Statistical Characteristics. Application To Mexico City Basin Daily Rainfall Fields

A first procedure to generate synthetic storms, which preserves the statistical characteristics of the historical daily precipitation events registered in 49 stations located within the basin of Mexico City is presented. This procedure (a variation of the Svanidze method) implicitly supposes that the correlation between the maximum rainfall and its spatial distribution is meaningless. However, the obtained results did not validate that hypothesis. For this reason a second procedure was developed, which allows to consider the correlation between maximum rainfall and spatial distribution. This second procedure allowed reproducing the statistical characteristics of the daily rainfall for each station and also its spatial distribution, as shown in this work.     

Rainfall duration and debris-flow initiated studies for real-time monitoring

A rainfall-induced debris flow warning is implemented employing real-time rain gauge data. The pre-warning for the time of landslide triggering derives the threshold or critical rainfall from historical events involving regional rainfall patterns and geological conditions. In cases of debris flow, the time taken cumulative runoff, to yield abundant water for debris triggering, is an important index that needs monitoring. In gathered historical cases, rainfall time history data from the nearest rain gauge stations to debris-flow sites connected to debris flow are used to define relationships between the rainfall intensity and duration. The effects by which the regional rainfall patterns (antecedent rainfall, duration, intensity, cumulative rainfall) and geological settings combine together to trigger a debris-flow are analyzed for real-time monitoring. The analyses focused on 61 historical hazard events with the timing of debris flow initiation and rainfall duration to burst debris-flow characteristics recorded. A combination of averaged rainfall intensity and duration is a more practical index for debris-flow monitoring than critical or threshold rainfall intensity. Because, the outburst timing of debris flows correlates closely to the peak hourly rainfall and the forecasting of peak hourly rainfall reached in a meteorological event could be a valuable index for real-time debris-flow warning.     

ECMWF再分析日降雨量与CMAP候降雨量在中国境内的数据整合

将中国境内1980～1993年ECMWF再分析日降雨量和美国环境预报中心CMAP候降雨量按16种方案整合后,再与实测资料做相关分析得出粗略的质量评估;并应用旋转主成分分析结合复变量莫莱特小波变换分析方法就其在东亚季风区的空间模态和不同频率下变化的时间序列得出具体的质量评估。结果表明:由最好的整合资料算出的6个旋转空间模态与实测资料比较除顺序有所改变外二者惊人地相似,不仅其14 a日均降雨量和标准偏差借助遥感候降雨量较再分析数据大有改进(尤其在四川盆地),而且还保留了再分析日降雨量再现不同时间尺度下实测降雨量波动的能力。除周内波动有所不同外,与夏季风爆发和洪涝灾害关系密切的周际以上波动与实测资料大致相符或基本吻合。     

Intermittent reservoir daily-inflow prediction using lumped and distributed data multi-linear regression models

In this study, multi-linear regression (MLR) approach is used to construct intermittent reservoir daily inflow forecasting system. To illustrate the applicability and effect of using lumped and distributed input data in MLR approach, Koyna river watershed in Maharashtra, India is chosen as a case study. The results are also compared with autoregressive integrated moving average (ARIMA) models. MLR attempts to model the relationship between two or more independent variables over a dependent variable by fitting a linear regression equation. The main aim of the present study is to see the consequences of development and applicability of simple models, when sufficient data length is available. Out of 47 years of daily historical rainfall and reservoir inflow data, 33 years of data is used for building the model and 14 years of data is used for validating the model. Based on the observed daily rainfall and reservoir inflow, various types of time-series, cause-effect and combined models are developed using lumped and distributed input data. Model performance was evaluated using various performance criteria and it was found that as in the present case, of well correlated input data, both lumped and distributed MLR models perform equally well. For the present case study considered, both MLR and ARIMA models performed equally sound due to availability of large dataset.     

Rainfall patterns for shallow landsliding in perialpine Slovenia

This paper presents two types of analysis: an antecedent rainfall analysis based on daily rainfall and an intensity-duration analysis of rainfall events based on hourly data in perialpine Slovenia in the ?kofjelo?ko Cerkljansko hills. For this purpose, eight rainfall events that are known to have caused landslides in the period from 1990 to 2010 were studied. Over the observed period, approximately 400 records of landslides were collected. Rainfall data were obtained from three rain gauges. The daily rainfall from the 30 days before landslide events was investigated based on the type of landslides and their geo-environmental setting, the dates of confirmed landslide activity and different consecutive rainfall periods. The analysis revealed that the rainfall events triggering slope failure can be divided into two groups according to the different antecedent periods. The first group of landslides typically occurred after short-duration rainstorms with high intensity, when the daily rainfall exceeded the antecedent rainfall. The second group comprises the rainfall events with a longer antecedent period of at least 7 days. A comparison of the plotted peak and mean intensities indicates that the rainfall patterns that govern slope failure are similar but do not necessarily reflect the rainfall intensity at the time of shallow landslides in the Dav?a or Poljane areas, where the majority of the landslides occurred. Because of several limitations, the suggested threshold cannot be compared and evaluated with other thresholds.     

中国日降雨空间变化对雨水径流源头总量控制的影响

为研究中国不同区域的降雨特征对径流总量控制效果的影响,利用186个气象站近30年的日降雨量资料,通过空间分析与统计计算,得到不同年径流总量控制率所对应的设计降雨量以及年均控制降雨量;结合年径流总量控制率与年均控制降雨量的关系将中国区域分为9种类型。结果表明:中国设计降雨量地域变化明显,广东、四川、广西、河北和河南等省的标准差为全国平均水平的1.5~3倍,且随年径流总量控制率的提升而增加,源头径流控制效果差异明显;南部地区径流控制效果多为"高量低率";"低量低率"区位于甘肃、宁夏等地,面积占比为9.44%,其降雨特征不适合发挥源头控制设施的效果;而最适宜发挥源头控制作用的"高量高率"区位于西南部分地区,面积占比为3.80%。     

Rainfall erosivity and erosivity density in Eastern Ghats Highland of east India

The rainfall erosivity (R-factor in USLE) is the long-term average of the sum of the product of rainfall kinetic energy and its maximum 30-min intensity. Therefore, at most 30-min time intervals pluviograph records are required to calculate R-factor. But, such high-resolution data are scarce in many parts of the world and require lengthy processing period. In this study, R-factor was correlated with daily, monthly and annual rainfall, and its spatial variability in Eastern Ghats Highland of east India was mapped. The result showed that power regression models predicted satisfactorily the daily, monthly and annual R-factor, of which annual R-factor model performed best (model efficiency 0.93). Mean monsoon season R-factor was 15.6 and 10.0 times higher than the pre- and post-monsoon season R-factor, and thus remained highly critical with respect to erosion. Annual R-factor values ranged from 3040 to 10,127 MJ mm ha^?1 h^?1 year^?1, with standard deviation of 1981 MJ mm ha^?1 h^?1 year^?1. Rainfall intensity was positively correlated with erosivity density, and numerical value of rainfall intensity was almost double of the erosivity density value. The combination of rainfall and erosivity density was used to identify flood, erosion and landslide-prone areas. The developed iso-erosivity, erosivity density and risk maps can be opted as a tool for policy makers to take suitable measures against natural hazards in Eastern Ghats Highland of east India and elsewhere with similar rainfall characteristics.

     

The role of rainfall in the landslide hazard: the case of the Avigliano urban area (Southern Apennines, Italy)

Mass movements varying in type and size, some of which are periodically reactivated, affect the urban area of Avigliano. The disturbed and remoulded masses consist of sandy–silty or silty–clayey plastic material interbedded with stone fragments and conglomerate blocks. Five landslides that were markedly liable to rainfall-associated instability phenomena were selected.

The relationships between landslides and rainfall were investigated using a hydrological and statistical model based on long-term series of daily rainfall data. The model was used to determine the return period of cumulative daily rainfall over 1–180 days. The resulting hydrological and statistical findings are discussed with the aim of identifying the rainfall duration most critical to landslides.

The concept of a precipitation threshold was generalized by defining some probability classes of cumulative rainfall. These classes indicate the thresholds beyond which reactivation is likely to occur. The probability classes are defined according to the return period of the cumulative rainfall concomitant with landslide reactivation.     

Quantitative precipitation forecasting over Narmada Catchment

Quantitative precipitation forecasting (QPF) has been attempted over the Narmada Catchment following a statistical approach. The catchment has been divided into five sub-regions for the development of QPF models with a maximum lead-time of 24 hours. For this purpose the data of daily rainfall from 56 raingauge stations, twice daily observations on different surface meteorological parameters from 28 meteorological observatories and upper air data from 11 aerological stations for the nine monsoon seasons of 1972–1980 have been utilized. The horizontal divergence, relative vorticity, vertical velocity and moisture divergence are computed using the kinematic method at different pressure levels and used as independent variables along with the rainfall and surface meteorological parameters. Multiple linear regression equations have been developed using the stepwise procedure separately with actual and square root and log-transformed rainfall using 8-year data (1972–1979). When these equations were verified with an independent data for the monsoon season of 1980, it was found that the transformed rainfall equations fared much better compared to the actual rainfall equations. The performance of the forecasts of QPF model compared to the climatological and persistence forecasts has been assessed by computing the verification scores using the forecasts for the monsoon season of 1980.     

北京清代“晴雨录”降水记录的再研究——应用多因子回归方法重建北京(1724～1904年)降水量序列

本文对早期发表的《北京250年降水》资料进行复算,并讨论其复原方法。在此基础上进一步探讨清代“晴雨录”降水资料复原方法的改进问题。试作了两种多因子回归复原方案,经对比这些方案及其试算结果,认为以8因子的逐步回归方案效果最佳。将此结果与《北京250年降水》1)及同期的器测降水量记录等进行比较,给出新的北京1724～2000年降水量复原序列。     

用经验模型判断能力验证统计分析结果的合理性

能力验证是检测实验室识别与同行差异的一种途径,但中国合格评定国家认可委员会( CNAS)在组织能力验证时发现由于种种原因,有些实验室并不能秉承诚信的原则参加能力验证活动,导致统计分析结果“失真”.如何甄别这种情况,确保所有参加CNAS能力验证活动的实验室都获得公平的评价,这是CNAS亟待解决的问题.本文在用国内文献数据对经验模型进行修正的基础上,提出用上报数据目标标准偏差(或稳健标准偏差,sR)与基于经验模型的计算值之比(H值)是否小于0.5作为判据来审核上报数据统计分析结果的合理性.对13套能力验证数据分析表明:其中10套上报数据sR正常,3套数据存在问题.当目标标准偏差偏小,H＜0.5时,建议采用同样是稳健统计方法的迭代法代替四分位法来计算目标标准偏差(sR),或用经验模型计算结果代替实验值计算Z值.通过验证表明,借助Horwitz经验模型可以判断能力验证数据统计分析结果的合理性,并能有效地识别并防止由于某种原因导致对能力验证结果评价失效的情况.     

Assessment of climate change impacts on rainfall using large scale climate variables and downscaling models – A case study

Many of the applied techniques in water resources management can be directly or indirectly influenced by hydro-climatology predictions. In recent decades, utilizing the large scale climate variables as predictors of hydrological phenomena and downscaling numerical weather ensemble forecasts has revolutionized the long-lead predictions. In this study, two types of rainfall prediction models are developed to predict the rainfall of the Zayandehrood dam basin located in the central part of Iran. The first seasonal model is based on large scale climate signals data around the world. In order to determine the inputs of the seasonal rainfall prediction model, the correlation coefficient analysis and the new Gamma Test (GT) method are utilized. Comparison of modelling results shows that the Gamma test method improves the Nash–Sutcliffe efficiency coefficient of modelling performance as 8% and 10% for dry and wet seasons, respectively. In this study, Support Vector Machine (SVM) model for predicting rainfall in the region has been used and its results are compared with the benchmark models such as K-nearest neighbours (KNN) and Artificial Neural Network (ANN). The results show better performance of the SVM model at testing stage. In the second model, statistical downscaling model (SDSM) as a popular downscaling tool has been used. In this model, using the outputs from GCM, the rainfall of Zayandehrood dam is projected under two climate change scenarios. Most effective variables have been identified among 26 predictor variables. Comparison of the results of the two models shows that the developed SVM model has lesser errors in monthly rainfall estimation. The results show that the rainfall in the future wet periods are more than historical values and it is lower than historical values in the dry periods. The highest monthly uncertainty of future rainfall occurs in March and the lowest in July.     

江西省吉安县地质灾害气象预警研究

暴雨型地质灾害具有突发性强的特点,降雨是地质灾害的触发因素,根据降雨量进行地质灾害预警预报可以较大减少地质灾害损失。文章在吉安县崩塌、滑坡、泥石流地质灾害易发程度分区的基础上,采用显式统计模型,通过分析历史地质灾害和日降雨量资料之间的关系,研究吉安县地质灾害气象预警模型。研究表明:当日降雨量达到50 mm、70 mm、110 mm、160 mm时,不同等级崩塌、滑坡、泥石流地质灾害易发区进入相应地质灾害气象预警状态。吉安县地质灾害气象预警区划成果填补了吉安县县域地质灾害气象预警的空白,为地质灾害预警决策提供了量化指标。     

降雨型滑坡失稳概率计算方法

为了解决滑坡风险评价中的滑坡失稳概率计算问题,利用前人在降雨阈值的研究成果,结合气象学中降雨概率分布理论,以云南省盐津县庙坝滑坡为例进行计算,建立降雨型滑坡失稳概率计算模型。结果表明,盐津县降雨型滑坡的降雨阈值类型为累积降雨量-历时关系阈值,即为单日降雨阈值,降雨阈值为29.7 mm;盐津县在当日降雨量达到或超过阈值水平时可能诱发滑坡,对滑坡影响的滞后天数最大为5天;庙坝滑坡在8月20—25日6天内单日降雨达到或超过29.7 mm的降雨概率为46.49%;庙坝滑坡在8月25日因前5天或当天单日降雨量超过29.7 mm而失稳的概率为0.2853%。     

An integrated flood risk assessment model for property insurance industry in Taiwan

Taiwan is located in an area affected by Northwest Pacific typhoons, which are also one of the most important sources of rainfall to the island. Unfortunately, the abundant rainfall brought by typhoons frequently produces hazards. In recent years, typhoons and floods have caused serious damage, especially Typhoon Morakot in 2009. In this study, a probabilistic model is developed based on historical events which can be used to assess flood risk in Taiwan. There are 4 separate modules in this model, including a rainfall event module, a hydraulic module, a vulnerability module, and a financial loss module. Local data obtained from the Taiwan government are used to construct this model. Historical rainfall data for typhoon and flood events that have occurred since 1960, obtained from the Central Weather Bureau, are used for computing the maximum daily rainfall for each basin. In addition, the latest flood maps from the Water Resources Agency are collected to assess the probable inundation depth. A case study using the local data is carried out. Assessment is made to predict possible economic loss from different financial perspectives such as the total loss, insured loss, and loss exceeding probabilities. The assessment results can be used as a reference for making effective flood risk management strategies in Taiwan.