Regional frequency analysis of daily rainfall extremes using L-moments approach

Daily extreme precipitation values are among environmental events with the most disastrous consequences for human society. Information on the magnitudes and frequencies of extreme precipitations is essential for sustainable water resources management, planning for weather-related emergencies, and design of hydraulic structures. In the present study, regional frequency analysis of maximum daily rainfalls was investigated for Golestan province located in the northeastern Iran. This study aimed to find appropriate regional frequency distributions for maximum daily rainfalls and predict the return values of extreme rainfall events (design rainfall depths) for the future. L-moment regionalization procedures coupled with an index rainfall method were applied to maximum rainfall records of 47 stations across the study area. Due to complex geographic and hydro-climatological characteristics of the region, an important research issue focused on breaking down the large area into homogeneous and coherent sub-regions. The study area was divided into five homogeneous regions, based on the cluster analysis of site characteristics and tests for the regional homogeneity. The goodness-of-fit results indicated that the best fitting distribution is different for individual homogeneous regions. The difference may be a result of the distinctive climatic and geographic conditions. The estimated regional quantiles and their accuracy measures produced by Monte Carlo simulations demonstrate that the estimation uncertainty as measured by the RMSE values and 90% error bounds is relatively low when return periods are less than 100 years. But, for higher return periods, rainfall estimates should be treated with caution. More station years, either from longer records or more stations in the regions, would be required for rainfall estimates above T=100 years. It was found from the analyses that, the index rainfall (at-site average maximum rainfall) can be estimated reasonably well as a function of mean annual precipitation in Golestan province. Index rainfalls combined with the regional growth curves, can be used to estimate design rainfalls at ungauged sites. Overall, it was found that cluster analysis together with the L-moments based regional frequency analysis technique could be applied successfully in deriving design rainfall estimates for northeastern Iran. The approach utilized in this study and the findings are of great scientific and practical merit, particularly for the purpose of planning for weather-related emergencies and design of hydraulic engineering structures.     

统计权重矩阵法在雷达估测降水集成中的应用

Z～R关系法和6种雷达雨量计联合法反演的区域降水量与雨量计观测得到的降水场存在较大的误差,将这7种降水估测结果作为信息源,采用统计权重矩阵法对上述7种反演结果进行集成分析,提出了一种改进雷达估测降水的方法。结果表明:在被集成资料中,Z～R关系法估测的降雨场具有明显的偏低现象,精度最差,6种雷达雨量计联合法的估测精度明显优于Z～R关系法。通过统计权重矩阵集成后,精度比集成前所有方法均有明显提高,尤其是降水场分布形势和降水中心的强度都与雨量计场非常吻合。集成得到的降水空间分布场能够较真实地反映地面的降水情况,可以在估测区域降水量中进行业务试用。     

地区线性矩法在太湖流域暴雨频率分析中的应用

介绍了基于水文气象途径的地区线性矩法的概念,通过基于次序统计量的线性矩进行参数估计与基于水文气象一致区的地区分析法相结合,以太湖流域1d时段的年极值降雨资料为例,进行暴雨频率分析。应用水文气象一致区的判别准则,将太湖流域划分为8个水文气象一致区;综合考虑三种拟合优度检测方法,选择1~8区的最优分布线型分别为:GEV、GLO、GEV、GEV、GNO、GNO、GEV、GNO;根据地区分析法原理,估算各雨量站的暴雨频率设计值。分析表明:太湖流域各重现期下的年极值降雨空间分布形态基本一致,西南山区是太湖流域的暴雨高风险区,应该在地区防洪规划中引起重视。结果表明:地区线性矩法具有很高的学术和实用价值,建议在全国范围内推广,作为防洪规划的顶层设计和基础工作,以满足工程防洪设计、地区防洪规划、山洪预警和城市防涝防洪规划等方面的需求。     

Trends and extreme value analysis of rainfall pattern over homogeneous monsoon regions of India

Trends of pre-monsoon, monsoon and post-monsoon rainfall pattern were studied on decadal basis over different homogeneous monsoon regions in India for the period 1871–2008. It is attempted to understand the relation of monsoon rainfall with the global teleconnections of El Niño and La Niña, for which the correlation analysis has been carried out with Darwin pressure and Niño 3.4 sea surface temperature (Niño 3.4 SST). The correlation analysis inferred that the significant correlations were observed when monsoon rainfall is related to ENSO indices on decadal scale than on annual ones. The study also found that the north-west region is more affected by the moderate El Niño years compared to strong El Niño years. The regions Central North-East and North-East could not make any difference among weak, moderate and strong La Niña events. The authors also have carried out the extreme value analysis over different homogeneous monsoon regions of India as well as for whole India. The results show that the return values of rainfall are increasing with the return periods for the forthcoming 10, 20, 50 and 100 years. The heterogeneity in number of threshold years that were recorded for the extreme rainfall over north-east (humid climatic type) and north-west (arid climatic type) described the climate variability. The results of the present study may be useful for the policy makers in understanding the rainfall exceedance in different return periods for planning the risk management strategies.     

Spatial variability and rainfall characteristics of Kerala

Geographical regions of covariability in precipitation over the Kerala state are exposed using factor analysis. The results suggest that Kerala can be divided into three unique rainfall regions, each region having a similar covariance structure of annual rainfall. Stations north of 10‡N (north Kerala) fall into one group and they receive more rainfall than stations south of 10‡N (south Kerala). Group I stations receive more than 65% of the annual rainfall during the south-west monsoon period, whereas stations falling in Group II receive 25–30% of annual rainfall during the pre-monsoon and the north-east monsoon periods. The meteorology of Kerala is profoundly influenced by its orographical features, however it is difficult to make out a direct relationship between elevation and rainfall. Local features of the state as reflected in the rainfall distribution are also clearly brought out by the study.     

淮北平原浅层地下水多年动态变化及监测统测评估

【研究目的】变化环境下地下水时空规律的研究有助于水资源精细化管理和区域水资源安全保障。【研究方法】本文基于淮北平原区典型气象站1953—2019年月降雨数据,采用小波分析及M-K检验法,研究多年尺度降雨周期性变化及趋势规律;结合395个国家级监测井及地下水统测数据,采用主成分分析法进行监测井优化评价。【研究结果】淮北平原多年降雨量呈现多时空尺度变化特征,南部地区主周期较北部地区偏小,但周期尺度较多,变化更为复杂;西北部的浅层地下水位持续下降,其余区域水位处于有升有降的波动状态;南部区域浅层地下水水位在1970年、2003年及2019年3个时段呈现出先降低再恢复,北部部分区域地下水水位则呈现先升高再降低的特征,研究区水位总体存在下降趋势,但2000年以来水位总体有所回升;经主成分分析优化后的277个监测井（221个水利井和56个自然资源井）能代表395个原国家监测井的总体水位变化情况。【结论】国家地下水监测工程长序列监测数据能够很好地服务于流域尺度水资源评价及管理,但省市级尺度或重点区域还需要进行优化和加密,地下水位统测可有效填补,该工作应在重要河湖两侧、淮河北岸一带、东北部山前平原等高水力梯度区域进行加密。     

福建省地质灾害气象预警有效降雨模型研究

降雨是诱发地质灾害最主要的外部因素之一,在中国东南沿海中低山丘陵区强降雨诱发的地质灾害集群发生,造成了大量人员伤亡和财产损失。以福建省为例,深入挖掘多年历史地质灾害案例的降雨实况资料,以县级行政区为统计单元,基于定量化降雨估测对诱发群发性地质灾害的典型降雨过程进行相关性研究,并基于地质环境的量化指标进行了偏相关分析验证,建立了福建省有效降雨模型并通过现场监测和预警应用进行了验证。研究表明：福建地区地质灾害的发生与灾害发生3日内降雨相关,且以0.79为折减系数逐日折减,据此建立了福建地区有效降雨模型;将福建地区有效降雨模型应用于地质灾害气象预警,可以在保证地质灾害命中率的前提下,减少预警区面积、降低预警等级、缩短预警持续时间,提高地质灾害气象预警的精准性。研究结果有助于准确把握降雨特征,可为区域地质灾害气象预警中降雨因子的合理评估提供科学依据。     

Early warning system for shallow landslides using rainfall threshold and slope stability analysis

A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerable to landslides. The 2, 3, and 5-day antecedent rainfall data versus daily rainfall was clustered to identify a cluster of critical events that could potentially trigger landslides. Further, the cluster of critical events was utilized for regression analysis to develop the threshold equations. The 5-day antecedent (x-variable) vs. daily rainfall (y-variable) provided the best fit to the data with a threshold equation of y = 80.7–0.1981x. The intercept of the equation indicates that if the 5-day antecedent rainfall is zero, the minimum daily rainfall needed to trigger the landslide in the Amboori region would be 80.7 mm. The negative coefficient of the antecedent rainfall indicates that when the cumulative antecedent rainfall increases, the amount of daily rainfall required to trigger monsoon landslide decreases. The coefficient value indicates that the contribution of the 5-day antecedent rainfall is ∼20% to the landslide trigger threshold. The slope stability analysis carried out for the area, using Probabilistic Infinite Slope Analysis Model (PISA-m), was utilized to identify the areas vulnerable to landslide in the region. The locations in the area where past landslides have occurred demonstrate lower Factors of Safety (FS) in the slope stability analysis. Thus, rainfall threshold analysis together with the FS values from slope stability can be suitable for developing a simple, cost-effective, and comprehensive early-warning system for shallow landslides in Amboori and similar regions.     

Exploiting historical rainfall and landslide data in a spatial database for the derivation of critical rainfall thresholds

Critical rainfall thresholds for landslides are powerful tools for preventing landslide hazard. The thresholds are commonly estimated empirically starting from rainfall events that triggered landslides in the past. The creation of the appropriate rainfall–landslide database is one of the main efforts in this approach. In fact, an accurate agreement between the landslide and rainfall information, in terms of location and timing, is essential in order to correctly estimate the rainfall–landslide relationships. A further issue is taking into account the average moisture conditions prior the triggering event, which reasonably may be crucial in determining the sufficient amount of precipitation. In this context, the aim of this paper is exploiting historical landslide and rainfall data in a spatial database for the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern Italy. The hourly rainfall events that caused landslides occurred in the twentieth century were specifically identified and reconstructed. A procedure was proposed to automatically convert rain guages charts recorded on paper tape into digital format and then to provide the cumulative rainfall hyetograph in digital format. This procedure is based on a segmentation followed by signal recognition techniques which allow to digitalize and to recognize the hyetograph automatically. The role of rainfall prior to the landslide events was taken into account by including in the analysis the rainfall occurred 5, 15 and 30 days before each landslide. Finally, cumulated rainfall duration thresholds for different exceedance probability levels were determined. The obtained thresholds resulted in agreement with the regional curves proposed by other authors for the same area; antecedent rainfall turned out to be particularly important in triggering landslides.     

On the impacts of ENSO and Indian Ocean dipole events on sub-regional Indian summer monsoon rainfall

The relative impacts of the ENSO and Indian Ocean dipole (IOD) events on Indian summer (June–September) monsoon rainfall at sub-regional scales have been examined in this study. GISST datasets from 1958 to 1998, along with Willmott and Matsuura gridded rainfall data, all India summer monsoon rainfall data, and homogeneous and sub-regional Indian rainfall datasets were used. The spatial distribution of partial correlations between the IOD and summer rainfall over India indicates a significant impact on rainfall along the monsoon trough regions, parts of the southwest coastal regions of India, and also over Pakistan, Afghanistan, and Iran. ENSO events have a wider impact, although opposite in nature over the monsoon trough region to that of IOD events. The ENSO (IOD) index is negatively (positively) correlated (significant at the 95% confidence level from a two-tailed Student t-test) with summer monsoon rainfall over seven (four) of the eight homogeneous rainfall zones of India. During summer, ENSO events also cause drought over northern Sri Lanka, whereas the IOD events cause surplus rainfall in its south. On monthly scales, the ENSO and IOD events have significant impacts on many parts of India. In general, the magnitude of ENSO-related correlations is greater than those related to the IOD. The monthly-stratified IOD variability during each of the months from July to September has a significant impact on Indian summer monsoon rainfall variability over different parts of India, confirming that strong IOD events indeed affect the Indian summer monsoon.

Impact of Siberian High on rainfall variability over Northern part of Indo-Pak region

Anticyclones dominate the weather over most of the eastern and the southern Asia during the winter season. This study examines the impact of Siberian High on winter rainfall variability over South Asia. In this paper, the teleconnections between the Siberian High and winter precipitation that cover the northern part of Indo-Pak region have been discussed. The objective indices of area-weighted pressure and area-weighted latitudinal and longitudinal movements high are used to find out the linkage between the winter rainfall in the mentioned region and the Siberian High. The analysis shows that rainfall pattern is significantly correlated with latitudinal displacement of the Siberian High. We have constructed a linear model of the winter rainfall using Siberian High latitude and Nino34 which explains 27 % variance of the winter precipitation for the region under study. The article also explains the physical mechanisms to establish the relationships between the Siberian High and regional rainfall.     

Rainfall analysis for Indian monsoon region using the merged rain gauge observations and satellite estimates: Evaluation of monsoon rainfall features

Objective analysis of daily rainfall at the resolution of 1° grid for the Indian monsoon region has been carried out merging dense land rainfall observations and INSAT derived precipitation estimates. This daily analysis, being based on high dense rain gauge observations was found to be very realistic and able to reproduce detailed features of Indian summer monsoon. The inter-comparison with the observations suggests that the new analysis could distinctly capture characteristic features of the summer monsoon such as north-south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough/low, over the east central parts of the country, over north-east India, along the foothills of Himalayas and over the north Bay of Bengal. When this product was used to assess the quality of other available standard climate products (CMAP and ECMWF reanalysis) at the gird resolution of 2.5°, it was found that the orographic heavy rainfall along Western Ghats of India was poorly identified by them. However, the GPCC analysis (gauge only) at the resolution of 1° grid closely discerns the new analysis. This suggests that there is a need for a higher resolution analysis with adequate rain gauge observations to retain important aspects of the summer monsoon over India. The case studies illustrated show that the daily analysis is able to capture large-scale as well as mesoscale features of monsoon precipitation systems. This study with data of two seasons (2001 and 2003) has shown sufficiently promising results for operational application, particularly for the validation of NWP models.     

四川巴中市滑坡灾害与降雨雨型关系探讨

巴中市地处四川盆地和秦岭造山带的过渡地带,地质构造以宽缓的隔档式褶皱为主,地层岩性主要为砂泥岩互层的红层岩体,红层滑坡灾害多为强降雨诱发。开展滑坡灾害与降雨雨型关系的研究,可为该地区滑坡灾害临界降雨阈值和预警服务提供参考。文章通过统计巴中市强降雨事件与滑坡发生的对应关系,初步揭示了滑坡灾害触发的降雨特征,并在分析降雨强度的基础上,结合降雨历时和降雨过程,对巴中市2007—2016年之间23场月降雨量大于200 mm的降雨事件进行了细分,共划分为单峰型、前峰型、后峰型、递增型、递减型、均匀型6类降雨雨型。对各类降雨雨型下滑坡发生数量进行统计,递增型和单峰型降雨事件下滑坡发生的比例分别为46.90%和25.02%。经稳定性计算分析,递增型和单峰型两类雨型条件下滑坡稳定性有明显降低,降雨过程对滑坡发生具有显著影响。结果表明:强降雨期间应加强降雨雨型的分析,为适时发布区域滑坡灾害预警信息、做好提前避让提供技术支撑。     

Observed daily large-scale rainfall patterns during BOBMEX-1999

A daily rainfall dataset and the corresponding rainfall maps have been produced by objective analysis of rainfall data. The satellite estimate of rainfall and the raingauge values are merged to form the final analysis. Associated with epochs of monsoon these rainfall maps are able to show the rainfall activities over India and the Bay of Bengal region during the BOBMEX period. The intra-seasonal variations of rainfall during BOBMEX are also seen using these data. This dataset over the oceanic region compares well with other available popular datasets like GPCP and CMAP. Over land this dataset brings out the features of monsoon in more detail due to the availability of more local raingauge stations.     

Multivariate geostatistical methods of mean annual and seasonal rainfall in southwest Saudi Arabia

A multivariate geostatistics (cokriging) is used for regional analysis and prediction of rainfall throughout the southwest region of Saudi Arabia. Elevation is intruded as a covariant factor in order to bring topographic influences into the methodology. Sixty-three representative weather stations are selected for a 21-year period covering different microclimate conditions. Results show that on an annual basis, there is no significant change using elevation. On the seasonal basis, the cokriging method gave more information about rainfall occurrence values, its accuracy related to the degree of correlation between elevation and rainfall by season. The prediction of spring and winter rainfall was improved owing to the importance of orographic processes, while the summer season was not affected within its monsoon climatology. In addition, fall season shows inverse and weak correlation of elevation with rainfall. Cross-validation and cokriging variances are also used for more accuracy of rainfall regional estimation. Moreover, even though the correlation is not significant, the isohyet values of cokriged estimates provided more information on rainfall changes with elevation. Finally, adding more secondary variables in addition to elevation could improve the accuracy of cokriging estimates.     

Interannual and long-term variability of Indian summer monsoon rainfall

Analysis of summer monsoon (June to September) rainfall series of 29 subdivisions based on a fixed number of raingauges (306 stations) has been made for the 108-year period 1871–1978 for interannual and long-term variability of the rainfall. Statistical tests show that the rainfall series of 29 sub-divisions are homogeneous, Gaussian-distributed and do not contain any persistence. The highest and the lowest normal rainfall of 284 and 26 cm are observed over coastal Karnataka and west Rajasthan sub-divisions respectively. The interannual variability (range) varies over different sub-divisions, the lowest being 55 and the highest 231% of the normal rainfall, for south Assam and Saurashtra and Kutch sub-divisions respectively. High spatial coherency is observed between neighbouring sub-divisions; northeast region and northern west and peninsular Indian sub-divisions show oppositic correlation tendency. Significant change in mean rainfall of six sub-divisions is noticed. Correlogram and spectrum analysis show the presence of 14-year and QBO cycles in a few sub-divisional rainfall series.     

降雨引发的兰州黄土滑坡时空规律分析和临界降雨量预测

开展降雨型黄土滑坡预警对于区域性防治滑坡具有重要意义。本研究在收集1985~2015年兰州市降雨型黄土滑坡历史数据的基础上,运用反距离权重插值(IDW)和核密度估算(KDE)方法揭示了降雨引发黄土滑坡的时空分布规律。该文基于统计学的基本原理,运用相关性和偏相关性等方法建立适合兰州市的有效降雨量模型。通过拟合有效降雨量与滑坡因子的线性回归关系,确定引发黄土滑坡的临界降雨量阈值,设定兰州市黄土滑坡的降雨量危险性预警等级。研究表明:(1)兰州市黄土滑坡灾害点沿着黄河及其支流沿岸分布,城关区滑坡点最多且呈环形分布,西固区次之,其他地区分布较少;(2)降雨是兰州市及其周边地区黄土滑坡的关键诱因,10d有效降雨量与滑坡因子均呈现显著正相关特性,其相关系数达到0.698;(3)依据10mm、20mm和40mm临界降雨量阈值将预警等级划分为低、中、高3个危险性等级。     

城市暴雨强度公式研究进展与述评

能够客观反映城市降雨特征与规律的暴雨强度公式是城市排水防涝基础设施建设、海绵城市建设过程中相关工程规划、设计的重要前提。简述了暴雨强度公式推求的过程,从暴雨强度公式型式、暴雨资料选样方法、频率曲线选择、频率曲线参数估计以及暴雨强度公式的参数求解等方面,系统梳理了国内外发展现状,深入分析、归纳了各种方法的优缺点,对暴雨强度公式编制过程中存在的两步最优与直接拟合、公式拟合的"异参同效"、公式及参数合理性分析以及编制长历时暴雨强度公式等问题进行深入剖析,认为暴雨强度公式还需在全要素误差分析、成果合理性检验、降雨空间分布、气候变化对城市未来降雨的影响等方面进行深入研究。     

Statistical-analytical methods in theoretical regional geography

In this paper the applicability of quantitative methods in theoretical regional geography is examined within Kenya. By means of statistical integration- and regionalization methods (Factor analysis, Cluster analysis, Discriminant analysis), Kenya is devided into five homogeneous regions based on information that is given by six thematical maps (mean annual rainfall, vegetation, altitude, ethnic groups, agriculture, geology). A discussion follows about the relation of these regions to the modern notion of “landscape” and generally about the utility of the newly developed terminology in theoretical regional geography.     

Trends in extreme rainfall over ecologically sensitive Western Ghats and coastal regions of Karnataka: an observational assessment

Rainfall is one of the pivotal climatic variables, which influence spatio-temporal patterns of water availability. In this study, we have attempted to understand the interannual long-term trend analysis of the daily rainfall events of ≥?2.5 mm and rainfall events of extreme threshold, over the Western Ghats and coastal region of Karnataka. High spatial resolution (0.25°?×?0.25°) daily gridded rainfall data set of Indian Meteorological Department was used for this study. Thirty-eight grid points in the study area was selected to analyze the daily precipitation for 113 years (1901–2013). Grid points were divided into two zones: low land (exposed to the sea and low elevated area/coastal region) and high land (interior from the sea and high elevated area/Western Ghats). The indices were selected from the list of climate change indices recommended by ETCCDI and are based on annual rainfall total (RR), yearly 1-day maximum rainfall, consecutive wet days (≥?2.5 mm), Simple Daily Intensity Index (SDII), annual frequency of very heavy rainfall (≥?100 mm), frequency of very heavy rainfall (≥?65–100 mm), moderate rainfall (≥?2.5–65 mm), frequency of medium rainfall (≥?40–65 mm), and frequency of low rainfall (≥?20–40 mm). Mann-Kendall test was applied to the nine rainfall indices, and Theil-Sen estimator perceived the nature and the magnitude of slope in rainfall indices. The results show contrasting trends in the extreme rainfall indices in low land and high land regions. The changes in daily rainfall events in the low land region primarily indicate statistically significant positive trends in the annual total rainfall, yearly 1-day maximum rainfall, SDII, frequency of very heavy rainfall, and heavy rainfall as well as medium rainfall events. Furthermore, the overall annual rainfall strongly correlated with all the rainfall indices in both regions, especially with indices that represent heavy rainfall events which is responsible for the total increase of rainfall.