Can global rainfall estimates (satellite and reanalysis) aid landslide hindcasting?

Predicting rainfall-induced landslides hinges on the quality of the rainfall product. Satellite rainfall estimates or rainfall reanalyses aid in studying landslide occurrences especially in ungauged areas, or in the absence of ground-based rainfall radars. Quality of these rainfall estimates is critical; hence, they are commonly crosschecked with their ground-based counterparts. Beyond their temporal precision compared to ground-based observations, we investigate whether these rainfall estimates are adequate for hindcasting landslides, which particularly requires accurate representation of spatial variability of rainfall. We developed a logistic regression model to hindcast rainfall-induced landslides in two sites in Japan. The model contains only a few topographic and geologic predictors to leave room for different rainfall products to improve the model as additional predictors. By changing the input rainfall product, we compared GPM IMERG and ERA5 rainfall estimates with ground radar–based rainfall data. Our findings emphasize that there is a lot of room for improvement of spatiotemporal prediction of landslides, as shown by a strong performance increase of the models with the benchmark radar data attaining 95% diagnostic performance accuracy. Yet, this improvement is not met by global rainfall products which still face challenges in reliably capturing spatiotemporal patterns of precipitation events.

     

Adequacy of satellite derived rainfall data for stream flow modeling

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. G. Artan, J. L. Smith and K. Asante – work performed under USGS contract 03CRCN0001.     

基于深度特征的双极化SAR遥感图像岩性自动分类

基于像元基元、极化合成孔径雷达（Synthetic Aperture Radar,SAR）数据和传统机器学习算法的岩性分类方法,易受SAR图像固有斑点噪声影响,精度不高.为了降低噪声的影响,本研究以大尺度像元邻域为基元,用于表征地表地质体的遥感图像特征和岩性语义信息;采用高分三号双极化SAR数据进行极化分解构建3通道假彩色合成影像;然后采用深度卷积神经网络（Deep Convolutional Neural Network,DCNN）迁移学习的方法,提取有效的深度特征表示,分别实现5 m和15 m两种空间分辨率下岩性遥感自动分类.结果表明:基于不同分辨率数据和不同DCNN算法,岩性遥感自动分类的总精度均大于80%,最高精度达到91%.基于大尺度像元邻域和DCNN迁移学习方法,能够实现基于SAR数据的高精度岩性分类.      

Dual polarization radar Lagrangian parameters: a statistics-based probabilistic nowcasting model

The aim of this study is to present a statistics-based Lagrangian nowcasting model to predict intense rainfall convective events based on dual polarization radar parameters. The data employed in this study are from X-band radar collected during the CHUVA-Vale campaign from November 2011 to March 2012 in southeast Brazil. The model was designed to catch the important physical characteristics of storms, such as the presence of supercooled water above 0 °C isotherm, vertical ice crystals in high levels, graupel development in the mixed-phase layer and storm vertical growth, using polarimetric radar in the mixed-phase layer. These parameters are based on different polarimetric radar quantities in the mixed phase, such as negative differential reflectivity (Z _DR) and specific differential phase (K _DP), low correlation coefficient (ρ _hv) and high reflectivity Z _h values. Storms were tracked to allow the Lagrangian temporal derivation. The model is based on the estimation of the proportion of radar echo volume in the mixed phase that is likely to be associated with intense storm hydrometeors. Thirteen parameters are used in this probabilistic nowcasting model, which is able to predict the potential for future storm development. The model distinguishes two different categories of storms, intense and non-intense rain cell events by determining how many parameters reach the “intense” storm threshold.     

Potentials and constraints of different types of soil moisture observations for flood simulations in headwater catchments

Flood generation in mountainous headwater catchments is governed by rainfall intensities, by the spatial distribution of rainfall and by the state of the catchment prior to the rainfall, e.g. by the spatial pattern of the soil moisture, groundwater conditions and possibly snow. The work presented here explores the limits and potentials of measuring soil moisture with different methods and in different scales and their potential use for flood simulation. These measurements were obtained in 2007 and 2008 within a comprehensive multi-scale experiment in the Weisseritz headwater catchment in the Ore-Mountains, Germany. The following technologies have been applied jointly thermogravimetric method, frequency domain reflectometry (FDR) sensors, spatial time domain reflectometry (STDR) cluster, ground-penetrating radar (GPR), airborne polarimetric synthetic aperture radar (polarimetric SAR) and advanced synthetic aperture radar (ASAR) based on the satellite Envisat. We present exemplary soil measurement results, with spatial scales ranging from point scale, via hillslope and field scale, to the catchment scale. Only the spatial TDR cluster was able to record continuous data. The other methods are limited to the date of over-flights (airplane and satellite) or measurement campaigns on the ground. For possible use in flood simulation, the observation of soil moisture at multiple scales has to be combined with suitable hydrological modelling, using the hydrological model WaSiM-ETH. Therefore, several simulation experiments have been conducted in order to test both the usability of the recorded soil moisture data and the suitability of a distributed hydrological model to make use of this information. The measurement results show that airborne-based and satellite-based systems in particular provide information on the near-surface spatial distribution. However, there are still a variety of limitations, such as the need for parallel ground measurements (Envisat ASAR), uncertainties in polarimetric decomposition techniques (polarimetric SAR), very limited information from remote sensing methods about vegetated surfaces and the non-availability of continuous measurements. The model experiments showed the importance of soil moisture as an initial condition for physically based flood modelling. However, the observed moisture data reflect the surface or near-surface soil moisture only. Hence, only saturated overland flow might be related to these data. Other flood generation processes influenced by catchment wetness in the subsurface such as subsurface storm flow or quick groundwater drainage cannot be assessed by these data. One has to acknowledge that, in spite of innovative measuring techniques on all spatial scales, soil moisture data for entire vegetated catchments are still today not operationally available. Therefore, observations of soil moisture should primarily be used to improve the quality of continuous, distributed hydrological catchment models that simulate the spatial distribution of moisture internally. Thus, when and where soil moisture data are available, they should be compared with their simulated equivalents in order to improve the parameter estimates and possibly the structure of the hydrological model.     

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.     

机载多普勒天气雷达及应用研究进展

机载多普勒天气雷达由于其灵活机动性,在台风、暴雨等灾害性天气系统中尺度三维精细结构研究中发挥着重要作用.对机载多普勒天气雷达技术及其资料应用进行了概要性综述,主要从机载多普勒天气雷达发展历程、4种主要机载多普勒雷达技术特点、雷达天线扫描策略、单多普勒雷达风场反演技术、双多普勒雷达风场反演技术、雷达资料同化以及目标观测等方面进行阐述和分析;着重讨论了应用中需要解决的问题.最后,指出发展具有快速扫描和双偏振功能的机载相控阵多普勒雷达是机载天气雷达的发展方向,它可以获取高时空分辨率的探测数据,能够对云和降水系统的三维精细动力结构、热力结构以及微物理结构等进行综合研究.     

基于水文模型的雷达监测降雨量误差传递研究

基于多普勒雷达和相应的雨量计资料,利用卡尔曼滤波校准法对分组Z~I关系估算的雷达降雨进行同化,结合新安江模型,提出采用增长模繁殖法对雷达监测降雨量资料进行扰动,定量分析了模型输入误差对径流模拟的影响。经过湖北省白莲河流域的实际应用研究表明,卡尔曼滤波校准法估算降水量的精度比Z~I关系法有了明显的提高,其相应的洪水预报效果也都优于Z~I关系;提出的增长模繁殖法对雷达监测降雨量资料产生的扰动输入误差在经过模型的传递后有增大的趋势。     

宁镇地区地质灾害预报模型——以镇江润州区为例

宁镇地区是长江中下游地质灾害最严重的地区之一。镇江润州区虽然仅是宁镇地区的一个局部区域,但其气候和地质环境特征具有典型意义,所提出的地质灾害气象预警预报模型同样适用于整个宁镇地区,对长江中下游地区亦有借鉴作用。气候环境、降雨尤其是连续降雨或强降雨是诱发地质灾害的重要因素。润州区地质灾害主要与梅雨期总降雨量有关,其次与台汛期台风带来的降雨量有关,而与台汛期总降雨量无关。地质灾害预测预警方程应针对不同时期采用不同的预警模型：非梅雨期的预警方程采用预报日降雨量结合前5日降水之和的综合模型,梅雨期的预警方程采用梅雨期降雨总量模型。提出地质灾害气象预报预警等级应根据《国家突发公共事件总体应急预案》将等级统一划分为4级。该模型可作为完善我国现有地质灾害气象预警预报系统的参考。     

CondMerg: an open source implementation in R language of conditional merging for weather radars and rain gauges observations

Monitoring of extreme events requires accurate measurement of rainfall intensities and merging weather radar data with ground information is a very common technique used to obtain the required precision. In order to do this, several methods exist but very few open source implementations are available. CondMerg is the first open source software developed in R language implementing the conditional merging method and some other experimental variants based on it. It is a cross-platform software, easily adaptable to different needs, optimized for batch processing of multiple events but also usable in near real time applications. For its execution it requires two inputs: a CSV file with rain gauges measurements and a geo-referred TIF file with weather radar quantitative precipitation estimations; main outputs are TIF files with merged observations although the code also returns information about cross-validation, with scatter plots and indexes. All TIF files are ready to be managed by common GIS software for easy visualization and analysis. Use of the program is very simple: execution can be interactive or non-interactive and, in both cases, it just requires to set some parameters at the beginning of the program and run it. The code has been tested on different extreme rain events occurred in the Piedmont region (northwestern Italy) showing improved accuracy of reconstructed rainfall fields.     

基于分布式水文模拟的三峡区间洪水预报(Ⅰ)——模型构建及验证

长江三峡区间因暴雨形成的洪水峰高量大,对三峡水库的防洪安全和运行调度的影响很大.本论文依据三峡地区的地形地貌特征,采用基于GIS的机理性分布式水文模型,来模拟三峡区间入库洪水,以尽量减少洪水预报中的不确定性.利用近期建成的78个自动雨量站网监测的小时降雨信息作为模型的输入,对模型参数进行了率定和验证,结果表明:大多数洪水过程的模拟精度较好,但也有的模拟结果较差,其中降雨信息缺失是洪水预报不确定性的主要来源.     

Satellite-based rainfall estimation and discharge measurement of Middle Indus River,Pakistan

The impacts of floods and droughts are intensified by climate change, lack of preparedness, and coordination. The average rainfall in study area is ranging from 200 to 400 mm per year. Rain gauge generally provides very accurate measurement of point rain rates and the amounts of rainfall but due to scarcity of the gauge locations provides very general information of the area on regional scale. Recognizing these practical limitations, it is essential to use remote sensing techniques for measuring the quantity of rainfall in the Middle Indus. In this research, Tropical Rainfall Measuring Mission (TRMM) estimation can be used as a proxy for the magnitude of rainfall estimates from classical methods (rain gauge), quantity, and its spatial distribution for Middle Indus river basin. In order to use TRMM satellite data for discharge measurement, its accuracy is determined by statistically comparing it with in situ gauged data on daily and monthly bases. The daily R ² value (0.42) is significantly lower than monthly R ² value (0.82), probably due to the time of summation of TRMM 3-hourly precipitation data into daily estimates. Daily TRMM data from 2003 to 2012 was used as input forcing in Soil and Water Assessment Tool (SWAT) hydrological model along with other input parameters. The calibration and validation results of SWAT model give R ² = 0.72 and 0.73 and Nash-Sutcliffe coefficient of efficiency = 0.69 and 0.65, respectively. Daily and monthly comparison graphs are generated on the basis of model discharge output and observed data.     

中国大陆流域分区TRMM降水质量评价

根据中国境内2 257个气象站点1998-2013年逐日降水资料,结合流域分区,采用探测准确性、相关系数以及相对误差等指标,对热带降水测量（TRMM）降水精度和一致性进行系统评价。结果表明:① TRMM日降水准确性从东南沿海向西北内陆递减;② 气象站点年均降水日数显著大于TRMM年均降水日数;③ 西北片区以外气象站点降水量和TRMM降水量在月尺度和年尺度上均具有较好的相关关系;④ 各流域年均TRMM面降水量均高于气象站点面降水量,且TRMM面降水量相对误差雨季较小,枯季较大;⑤ 各流域TRMM面降水量与气象站点面降水量演变趋势基本一致,南方各流域年降水量均呈减少趋势,北方各流域年降水量均呈增加趋势,全国尺度上年降水量呈微弱的减少趋势。     

Advances in Measurement Techniques and Statistics Features

Rain Drop Size Distribution (DSD) is one of the key parameters to micro physical process and macro dynamical structure of precipitation. It provides useful information for understanding the mechanisms of precipitation formation and development. Conventional measurement techniques include momentum method, flour method, filtering paper, raindrop camera and immersion method. In general, the techniques havelarge measurement error, heavy workload, and low efficiency. Innovation of disdrometer is a remarkable progress in DSD observation. To date, the major techniques are classified into impacting, optical and acoustic disdrometers, which are automated and more convenient and accurate. The impacting disdrometer transforms the momentum of raindrops into electric impulse, which are easy to operate and quality assured but with large errors for extremely large or small raindrops. The optical disdrometer measures rainfall diameter and its velocity in the same time, but cannot distinguish the particles passing through sampling area simultaneously. The acoustic disdrometer determines DSD from the raindrop impacts on water body with a high temporal resolution but easily affected by wind. In addition, the Doppler can provide DSD with polarimetric techniques for large area while it is affected by updrafts, downdrafts and horizontal winds.DSD has meteorological features, which can be described with the Marshall Palmer (M-P), the Gamma, the lognormal or the normalized models. The M P model is suitable for steady rainfall, usually used for weak and moderate rainfall. The gamma model is proposed for DSD at high rain rate. The lognormal model is widely applied for cloud droplet analysis, but not appropriate for DSD with a broad spectrum. The normalized model is free of assumptions about the shape of the DSD. For practical application, statistical comparison is necessary for selection of a most suitable model. Meteorologically, convective rain has a relatively narrow and smooth DSD spectrum usually described by the M P model. Stratiform rain has a broad DSD spectrum described with the Gamma model. Stratocumulus mixed rain has relatively large drop diameter but small mean size usually described by the Gamma model. The continent rainfall is altitude dependent and it differs from the maritime cloud rainfalls in terms of rain rate and drop diameter. Overall, the meteorological features are useful to improve our understanding of precipitation formation but also important to development of precipitation retrieval techniques with a high accuracy.     

An operational flood warning system for poorly gauged basins: demonstration in the Guadalhorce basin (Spain)

This paper deals with the presentation of a flood warning system (GFWS) developed for the specific characteristics of the Guadalhorce basin (3,200 km², SE of Spain), which is poorly gauged and often affected by flash and plain floods. Its complementarity with the European flood alert system (EFAS) has also been studied. At a lower resolution, EFAS is able to provide a flood forecast several days in advance. The GFWS is adapted to the use of distributed rainfall maps (such as radar rainfall estimates), and discharge forecasts are computed using a distributed rainfall–runoff model. Due to the lack of flow measurements, the model parameters calibrated on a small watershed have been transferred in most of the basin area. The system is oriented to provide distributed warnings and fulfills the requirements of ungauged basins. This work reports on the performance of the system on two recent rainfall events that caused several inundations. These results show how the GFWS performed well and was able to forecast the location and timing of flooding. It demonstrates that despite its limitations, a simple rainfall–runoff model and a relatively simple calibration could be useful for event risk management. Moreover, with low resolution and long anticipation, EFAS appears as a good complement tool to improve flood forecasting and compensate for the short lead times of the GFWS.     

用GMS卫星资料反演复杂地形下的降水率

强降水主要由生命史短的中小尺度天气系统造成,对此类天气系统的预报,目前只有依靠卫星和雷达的实时监测并结合中系统的概念模式外推来完成。由于中国西北地区地形极为复杂,造成雷达盲区,影响其估算降水率。因此采用GMS-4卫星的红外和可见光展宽云图资料,经处理并转换后,再加入相应网格点上的数字化地形高度资料作为因子之一,用多级逐步判别模式估算逐时雨强等级,最后形成一套可在微机上对雨强场进行图像显示及处理的软件系统,满足了现时预报的需要。结果表明,小雨以上的降雨区域不论面积、形状均与实况基本一致。     

相位激发极化法应用研究

相位激发极化法是一种频率域激发极化方法,可直接测量电场电压与供电电流之间的绝对相位差。由于该方法对仪器精度要求较高,因而国内有关实际应用方面的资料相对较少。在金属矿产勘查中,目前国内大多采用时间域激发极化方法,测量岩矿石的极化率或充电率。虽然频率域激发极化法也有应用,但主要采用双频或多频测量,利用视频散率参数进行解释,野外测量工作量较大,测量精度相对较低。近几年,利用相位激发极化法在科研、生产中做了一些工作,这里介绍相位激发极化法模型试验及数据反演结果,岩矿石标本时间域(充电率)和频率域(相位)测试对比结果,以及实际应用实例及数据反演结果。应用结果表明,用相位激发极化法在矿产勘查中可以取得较好的勘察效果,并能在今后的工作中发挥更大的作用。     

基于信息量法的地质灾害气象风险预警模型:以甘肃省陇南地区为例

地质灾害气象风险预警是目前地质灾害防治研究领域的难点和热点。陇南地区是中国地质灾害造成人员财产损失和受灾害威胁最严重的区域之一,为精细化和准确化预报陇南地区地质灾害风险,在ArcGIS平台将研究区划分为250 m×250 m的栅格单元,使用信息量法选取9个影响因素进行地质环境敏感性评价,结合有效降雨量构建地质灾害气象风险预警模型;该模型通过6次历史降雨事件引发的156起地质灾害验证,预报准确率为83.42%,提高了研究区内地质灾害风险预警精度。该研究基于信息量法的地质环境敏感性分区客观合理,综合考虑下垫面和气象要素的第二代预警模型在类似地区的应用,有较高的准确性和适用性。     

Rainfall thresholds for the forecasting of landslide occurrence at regional scale

This paper concerns a regional scale warning system for landslides that relies on a decisional algorithm based on the comparison between rainfall recordings and statistically defined thresholds. The latter were based on the total amount of rainfall, which was cumulated considering different time intervals: 1-, 2- and 3-day cumulates took into account the critical rainfall influencing shallow movements, whilst a variable time interval cumulate (up to 240 days) was used to consider the triggering of deep-seated landslides in low permeability terrains. A prototypal version of the model was initially set up to define statistical thresholds. Then, thresholds were calibrated using a database of past georegistered and dated landslides. A validation procedure showed that the calibration highly improves the results and therefore the model was integrated in the regional warning system of Emilia Romagna (Italy) for civil protection purposes. The proposed methodology could be easily implemented in other similar regions and countries where a sufficiently organised meteorological network is present.     

基于物理模型的被动微波遥感反演土壤水分

利用土壤水分和海洋盐度(SMOS)卫星进行土壤水分反演的算法中,对地表发射率的描述仍采用半经验Q/H模型,该模型描述地表粗糙度对有效发射率在V和H极化下影响相同.基于微波散射理论模型-高级积分方程模型(AIEM)建立了一个针对SMOS传感器的参数配置,包含各种地表粗糙度和介电特性的裸露地表辐射模拟数据库,发展了L波段多角度地表辐射参数化模型.在此基础上,利用SMOS多角度双极化特点,建立了土壤水分反演算法.该算法可以消除粗糙度对土壤水分反演的影响,同时最小化反演过程中辅助信息引入带来影响.反演算法通过美国农业部提供的L波段多角度地基辐射计数据(BARC)进行验证,在20°~50°入射角,土壤水分反演精度在4%左右.