Multiple time scales in rainfall variability

Monthly rainfall data averaged over a selected number of stations in peninsular Malaysia with a long record was subjected to singular spectrum analysis to determine the different modes of fluctuations in the rainfall. The analysis highlights the presence of fluctuations in the QBO time scale to a very long term time scale of 18–5 years which is possibly linked to lunar tidal forcing. There is also evidence of the Malaysian rainfall responding to El-Nino Southern Oscillation. An oscillation with a 7 to 10 year cycle is also evident. The annual cycle as a regular periodic oscillation is well established by the SSA.     

Decomposition of wind speed fluctuations at different time scales

Understanding the inherent features of wind speed (variability on different time scales) has become critical for assured wind power availability, grid stability, and effective power management. The study utilizes the wavelet, autocorrelation, and FFT (fast Fourier transform) techniques to analyze and assimilate the fluctuating nature of wind speed data collected over a period of 29–42 years at different locations in the Kingdom of Saudi Arabia. The analyses extracted the intrinsic features of wind speed, including the long-term mean wind speed and fluctuations at different time scales (periods), which is critical for meteorological purposes including wind power resource assessment and weather forecasting. The long-term mean wind speed varied between 1.45 m/s at Mecca station and 3.73 m/s at Taif. The annual variation is the largest (±0.97 m/s) at Taif and the smallest (±0.25 m/s) at Mecca. Similarly, the wind speed fluctuation with different periods was also discussed in detail. The spectral characteristics obtained using FFT reveal that Al-Baha, Najran, Taif and Wadi-Al-Dawasser having a sharp peak at a frequency f = 0.00269 (1/day) retain a more regular annual repetition of wind speed than Bisha, Khamis-Mushait, Madinah, Mecca, and Sharourah. Based on the autocorrelation analysis and FFT results, the stations are divided into three groups: (i) having strong annual modulations (Al-Baha, Najran, Taif and Wadi-Al-Dawasser), (ii) having comparable annual and half-yearly modulations (Bisha, Khamis-Mushait, and Mecca) and (iii) having annual modulation moderately prominent (Madinah and Sharourah).     

Calibrating a rainfall erosivity assessment model at regional scale in Mediterranean area

A simplified regression model is here calibrated on the basis of rainfall data records of Sicily (southern Italy), in order to show the model reliability in assessing the R-factor of the Universal Soil Loss Equation and its revised version (RUSLE) and to provide an estimate of long-term rainfall erosivity at medium-regional scale. The proposed model is a rearrangement of a former simplified model, formulated for the Italian environment, grouping three easily available rainfall variables on various time scales, which has been shown to be more successful than others in reproducing the rainfall erosive power over different locations of Italy. A geostatistical interpolation procedure is then applied for generating the regional long-term erosivity map with associated standard error. Areas with severe erosive rainfalls (from 2,000 up to more than 6,000 MJ mm ha⁻¹ h⁻¹) are pointed out which will correspond to areas suffering from severe soil erosion. Solving the problem of calculating the R-factor value in the RUSLE equation by means of such a simplified model here formulated will allow to predict the related soil loss. Moreover, given the availability of long time-series of concerned rainfall data, it will be possible to analyse the variability of rainfall erosivity within the last 50 years, and to investigate the application of RUSLE or similar soil erosion models with forecasting purposes of soil erosion risk.     

A comparison of Indian and African monsoon variability at different time scales

A review is given of the summer monsoon systems in Africa and India, and of their comparison at different time scales. Features of the circulation are described first, including the main respective meteorological centres of action controlling the annual cycle of the rain bands over these two regions. The main elements of the atmospheric intraseasonal variability are then presented, which controls in particular the onset of these two monsoon systems. Then the sensitivity of these two monsoon systems to oceanic and continental surface conditions in the context of interannual variability is discussed and compared. Consequences in term of predictability are commented. Finally, the Intergovernmental Panel on Climate Change (IPCC4) scenarios of the future climate over these two regions are presented.     

地质灾害与不同尺度降雨时空分布关系

降雨是地质灾害最重要的诱发因素之一,开展地质灾害与不同尺度降雨的时空分布研究,分析降雨诱发地质灾害的特点规律,对于提升地质灾害区域预警水平和防灾减灾实践具有重要意义。本文以2006～2007年汛期地质灾害的实际发生情况为例,通过统计分析方法,对区域地质灾害与年降雨量、月降雨量、月暴雨日数、典型降雨过程之间的时空分布关系开展系统分析,研究表明:降雨是群发型地质灾害发生的重要诱发因素,地质灾害的发育密度与年均雨量成正比,地质灾害发育密度最大的区域,其年均雨量最大;地质灾害分布与月降雨量、月暴雨日数的分布总体上具备一定的对应关系,但并不是完全对应的,主要受到典型强降雨过程的落区控制;在地质灾害多发区出现典型强降雨过程时,地质灾害群发。     

The comparison analysis of Chinese public perception of earthquakes on different time scales

China has suffered from severe earthquake disasters in recent years. In order to explore the impact of severe earthquakes on public risk perception on different time scales, four surveys were conducted twice each after the severe Wenchuan and Yushu earthquakes. t tests were performed between two consecutive surveys to explore the change of public risk attitudes. The results demonstrated that after the two severe earthquakes, the public seismic risk acceptance has increased over time, and the comparison between pre- and post-Yushu earthquake illustrated that the severe disaster had more impact on vulnerable population such as females, children and low-income people. Moreover, linear regression models were employed to find the determining factors of public acceptance towards earthquake risks. It was discovered that the public perceived earthquake effect had significant negative relationship with seismic risk acceptance, and public trust towards local government had positive relationship with the risk acceptance. This study could help government to gain better understanding of public mental status and take more effective disaster preparedness measures when preventing and responding to a severe earthquake.     

Impact of the hydrological cycle on past climate changes: three illustrations at different time scales

We investigate in the paper the impact of the hydrologic cycle on climate at different periods. The aim is to illustrate how the changes in moisture transport, precipitation pattern, and weathering may alter, at regional or global scales, the CO₂ and climate equilibriums. We choose three climate periods to pinpoint intricate relationships between water cycle and climate. The illustrations are the following. (i) The onset of ice-sheet build-up, 115 kyr BP. We show that the increased thermal meridian gradient of SST allows large moisture advection over the North American continent and provides appropriate conditions for perennial snow on the Canadian Archipelago. (ii) The onset of Indian Monsoon at the end of the Tertiary. We demonstrate that superimposed to the Tibetan Plateau, the shrinkage of the Tethys, since Oligocene, plays a major role to explain changes in the geographical pattern of the southeastern Asian Monsoon. (iii) The onset of Global Glaciation (750 Ma). We show that the break-up of Rodinia occurring at low latitudes is an important feature to explain how the important precipitation increase leads to weathering and carbon burial, which contribute to decrease atmospheric CO₂ enough to produce a snows ball Earth. All these periods have been simulated with a hierarchy of models appropriate to quantify the water cycle impact on climate. To cite this article: G. Ramstein et al., C. R. Geoscience 337 (2005).     

On different time scales of suspended matter dynamics in the Weser estuary

Long-term observations in the Weser estuary (Germany) between 1983 and 1997 provide insight into the response of the estuarine turbidity maximum (ETM) under a wide range of conditions. In this estuary the turbidity zone is closely tied to the mixing zone, and the positions of the ETM and the mixing zone vary with runoff. The intratidal suspended particulate matter (SPM) concentrations vary due to deposition during slack water periods, subsequent resubsequent and depletion of temporarily-formed and spatially-limited deposits during the following ebb or flood, and subsequent transport by tidal currents. The corresponding time history of SPM concentrations is remarkably constant over the years. Spring tide SPM concentrations can be twice the neap tide concentrations or even larger. A hysteresis in SPM levels between the falling and rising spring-neap cycle is attributed to enhanced resuspension by the stronger spring tidal currents. There is evidence that the ETM is pushed up-estuary during times of higher mean water levels due to storms. During river floods the ETM is flushed towards the outer estuary. If river floods and their decreasing parts occur during times of relatively high mean water levels, the ETM seems to be maintained in the outer estuary. If river floods and their decreasing parts occur during times of relatively low mean water levels, the ETM seems to loose inventory and may need up to half a year of non-event conditions to gain its former magnitude. During this time seasonal effects may be involved. Analyses of storm events and river floods have revealed that the conditions in the seaward boundary region play an equally important role for the SPM dynamics as those arising from the river.     

Key pluvial parameters in assessing rainfall erosivity in the south-west development region,Romania

Located in the south-western part of Romania, the south-west development region overlaps the main relief forms: the Carpathians mountains, the Getic Subcarpathians, the Getic piedmont, the Romanian plain and the Danube valley. The study aims at providing an overview on the main pluvial parameters and their role in assessing rainfall erosivity in the study area. The authors assessed the occurrence, frequency and magnitude of some of the most significant pluvial parameters and their impact on the climatic aggressiveness in the study area. Thus, the monthly and annual mean and extreme climatic values for different rainfall related parameters (e.g., maximum amounts of precipitation/24 hr, heavy rainfall), as well as relevant indices and indicators for pluvial aggressiveness (Fournier, Fournier Modified, Angot) were calculated. The rainfall erosivity was assessed in order to provide both the spatial distribution of the triggering extreme weather phenomena and the resulted intensity classes for the analysed indices and indicators. The authors used long-term precipitation records (1961–2010) for the selected relevant meteorological stations distributed throughout all analysed relief units.     

Spatial variability of rainfall trends in Iran

The main objective of this paper is to analyze the spatial variability of rainfall trends using the spatial variability methods of rainfall trend patterns in Iran. The study represents a method on the effectiveness of spatial variability for predicting rainfall trend patterns variations. In rainfall trend analysis and spatial variability methods, seven techniques were used: Mann–Kendall test, Sen’s slope method, geostatistical tools as a global polynomial interpolation and the spatial autocorrelation (Global Moran’s I), high/low clustering (Getis-Ord General G), precipitation concentration index, generate spatial weights matrix tool, and activation functions of semiliner, sigmoid, bipolar sigmoid, and hyperbolic tangent in the artificial neural network technique .For the spatial variability of monthly rainfall trends, trend tests were used in 140 stations of spatial variability of rainfall trends in the 1975–2014 period. We analyzed the long and short scale spatial variability of rainfall series in Iran. Spatial variability distribution of rainfall series was depicted using geostatistical methods (ordinary kriging). Relative nugget effect (RNE) predicted from variograms which showed weak, moderate, and strong spatial variability for seasonal and annual rainfall series. Moreover, the rainfall trends at each station were examined using the trend tests at a significance level of 0.05. The results show that temporal and spatial trend patterns are different in Iran and the monthly rainfall had a downward (decreasing) trend in most stations, and the trend was statistically significant for most of the series (73.5% of the stations demonstrated a decreasing trend with 0.5 significance level). Rainfall downward trends are generally temporal-spatial patterns in Iran. The monthly variations of rainfall decreased significantly throughout eastern and central Iran, but they increased in the west and north of Iran during the studied interval. The variability patterns of monthly rainfall were statistically significant and spatially random. Activation functions in the artificial neural network models, in annual time scale, had spatially dispersed distribution with other clustering patterns. The results of this study confirm that variability of rainfall revealing diverse patterns over Iran should be controlled mainly by trend patterns in the west and north parts and by random and dispersed patterns in the central, southern, and eastern parts.     

Identifying flood-prone landfills at different spatial scales

Landfills are mainly located in lowland areas close to settlements inducing flood risk of potential environmental contamination and adverse health effects. During recent flood events, numerous landfill sites were reportedly exposed to inundations, leading to erosion of landfilled material and release of pollutants threatening humans and the environment. Although emissions from landfills under regular operating conditions are well investigated, the behaviour and associated emissions in case of flooding are widely unknown. To enable environmental risk management, flood-prone landfills must be identified to establish priorities for subsequent protection and mitigation measures. This paper presents two flood risk assessment approaches at different spatial scales: a macro-scale assessment approach (MaSA) and a micro-scale assessment approach (MiSA). Both methodologies aim to determine the proportion of landfills endangered by flooding, and evaluate the impacts. The latter are expressed by means of risk categories (minor to serious) of impacts that flooded sites might have on humans and the environment. The evaluation of 1,064 landfills in Austria based on MaSA yields roughly 30 % of landfills located within or close to flood risk zones. Material inventories of 147 sites exposed to flooding are established, and potential emissions during a flood event are estimated. Three representative case study areas are selected and investigated in detail by applying the MiSA approach based on 2D hydrodynamic models to calculate flow depths and shear stress and by developing emission scenarios to validate the macro-scale screening approach (MaSA). The applications of MiSA and MaSA outlines that hazardous emissions due to flooding can lead to significant impacts on the environment. Uncertainty associated with related processes and data sources is considerably high. Nevertheless, both MiSA and MaSA provide a decision support tool to identify landfills with imminent risk for humans and the environment. Therefore, the described methodologies provide toolsets to enable environmental risk reduction by applying a priority-ranked flood risk management.     

Long term variation in rainfall erosivity in Uruguay: a preliminary Fournier approach

In order to explore the consequences of precipitation increase on soil erosion in Uruguay, the monthly Fournier Index (FI) and the annual Modified Fournier Index (MFI) were developed as a preliminary approach, covering consecutive decadal periods from 1931 to 2000. Rainfall data were used from 13 stations distributed all over the country. MFI shows a decrease in the 1940s, an increase during the 1950s, then a little decrease during the 1960s and 1970s and an increase in the 1980s, remaining near these last values during the 1990s. FI behavior in July and October in the last two decades shows a decrease in the Northeast region of the country—the region with highest annual precipitation—and a slight increase over the Southeast—the region with the lowest annual precipitation and the only region with a winter rainfall maximum. For the core months of winter and early spring there is a decline in erosivity in the Northeast, but an increase in the Southeast. January shows erosivity decreasing in the South during the last two decades. In April there is a peak in precipitation variability all across the country. FI shows an early increase during the 1940s in the Northwest, and generally very low values during the 1970s, with the return of high values in the 1990s, especially in the Northern corner. Results pose a challenge in order to improve research on the erosion problem, since the main source of freshwater nationwide remains surface river flow, which is prone to higher turbidity problems in areas of high soil erosion.     

Geostatistical analysis of soil moisture measurements and remotely sensed data at different spatial scales

The European remote sensing satellite (ERS-2) synthetic aperture radar (SAR) data was used for temporal monitoring of soil moisture at Sukhothai, Thailand. Higher correlations were found between the observed soil moisture and the radar backscattering coefficient. The soil moisture distribution shows great variation in space and time due to its stochastic nature. In order to obtain a better understanding of the nature and causes of spatial variation of soil moisture, the extensive soil moisture measurements observed in Thailand and also remotely sensed ERS-2 SAR data were used for geostatistical analysis. The observed soil moisture shows seasonal variations with mean varying from 3.33 %v/v (dry season) to 33.44 %v/v (wet season). The spatial geostatistical structure also shows clear seasonal variations in the geostatistical characteristics such as range and sill. The sills vary from 1.00 (%v/v)² for the driest day to 107.57 (%v/v)² for one of the wet days. The range or the correlation lengths varies between 46.5 and 149.8 m for the wettest and driest periods. The nugget effect does not show strong seasonal pattern or trend but the dry periods usually have a smaller nugget effect than the wet periods. The spherical variogram model fits the sample variograms very well in the case of soil moisture observations while the exponential model fits those of the remotely sensed data. The ranges observed from the observed soil moisture data and remotely sensed data at the same resolution are very similar. Resolution degradation affects the geostatistical structure of the data by reducing the sills, and increasing the ranges.     

Field examples of variations in fault patterns at different scales

Three field examples are presented which show changes in fault patterns at different scales. Normal faults in Jurassic limestones in Somerset consist of zones of sub-parallel segments at the exposure-scale, but contain complex zones of brecciation at the decimetre-scale. Normal faults in chalk at Flamborough Head consist of a complex network of small faults which accommodate strain between a set of large faults. The different-sized faults at Flamborough Head have different geometries and histories, with the larger faults showing a phase of reverse reactivation. The faulting in the Sydney Basin, Australia, can be explained in terms of the evolution and reactivation of transfer zones between overstepping faults. These transfer zones can cause the deformation to appear to be more complex as the analysis becomes more detailed.
Much recent work on the scaling relationslups of faults assumes that self-similar fault patterns occur over a wide range of scales. The data presented in this paper, however, suggest that there are problems in using the deformation pattern at one scale to infer deformation at other scales. Ideally, any analysis should involve the study of a wide range of scales to overcome these problems.     

开合构造在不同时空尺度下的地学表现

开合构造是研究地球开合运动及其构造特征,分析开合构造体系的形成机制,探索地球成因和演化的一种新假说。不同时空尺度的开合构造在地学上存在不同的表现,需要从不同角度开展研究。以亚欧非邻区巨型开合构造区、地中海大型开合构造区、东大别中型开合构造区为例,研究了开合构造理论在大地构造分区、地震活动以及现代大地测量结果解释等方面的应用。研究表明:(1)依据开合构造观点可将亚欧非邻区巨型开合构造划分为俄罗斯构造集群、非洲构造集群、北亚构造集群、中亚构造集群、南亚构造集群及东亚构造集群;(2)亚欧非邻区的强地震活动与构造集群间的新生代开合构造转换带关系密切;(3)地中海大型开合构造区内的地震剖面及震源机制揭示了地中海—土耳其—伊朗—阿富汗构造转换带现今构造运动主要以合为主;(4)东大别中型开合构造周边的狮子山、黄梅、麻城等台站的地倾斜和地应变、周边GNSS和流动重力观测结果揭示了该区周边存在时间尺度较短、量级较弱的由“合”向“开”的趋势转变,开合运动是近期诸多观测数据趋势出现准同步性变化的共同机理。     

Evaluation of rainfall erosivity and its temporal variation in the Yanhe River catchment of the Chinese Loess Plateau

The potential of rain to generate soil erosion is known as the rainfall erosivity (R), and its estimation is fundamental for a better understanding of the erosive ability of certain rainfall events. In this paper, we investigated the temporal variations of rainfall erosivity using common daily rainfall data from four meteorological stations during 1956 to 1989 and 2008 to 2010 periods in the Yanhe River catchment of the Chinese Loess Plateau. The adaptability of several simplified calculation models for R was evaluated and compared with the results of previous studies. An exponential model based on the modified Fournier index (MFI) was considered as the optimum for our study area. By considering the monthly distribution and coefficient of variation of annual precipitation, equations based on two indices, the MFI and its modification F _F , produced a higher calculation accuracy than mean annual precipitation. The rainfall erosivity in the Yanhe River catchment has a remarkable interannual difference, with a seasonality index ranging from 0.69 to 1.05 and a precipitation concentration index from 14.51 to 27.46. In addition to the annual rainfall amounts, the extreme wave of monthly rainfall distribution also has an effect on the magnitude and temporal variation of rainfall erosivity, especially interannual variation. For long time series of rainfall erosivity, a trend coefficient r of ?0.07 indicated a slight decline in erosivity in the Yanhe River catchment from 1956 to 2010.     

A composite index for drought hazard assessment using CPC rainfall time series data

Hazard analysis is the first step in any disaster management activity. Drought is a serious environmental hazard strongly limiting the agricultural production in the tropical countries like India. A comprehensive drought hazard map is useful for multiple perspectives such as agriculture, environment and hydrology. In this study, daily rainfall data of the Climate Prediction Centre during the south-west monsoon season (June–September) of 12 years, over India was analysed. Based on rainfall and rainy days, six indicators of drought were generated which were then synthesized into a composite index of drought hazard for every 10 × 10 km pixel. The weights for the composite index were generated through variance approach. The index has effectively captured the spatial variations in meteorological drought across India by showing a typical pattern with increasing hazardous area from east to west. The drought hazard map also shows considerable agreement with the climate classification map and the drought proneness map reported by other studies. Thus, the current study presents a simple and novel approach for drought hazard analysis, using the routinely available geospatial rainfall data products. The methodology can be extended to other geographies and disasters too. Use of time series data of longer period would improve the reliability of the composite drought hazard index.     

Trend analysis and ARIMA modelling of pre-monsoon rainfall data for western India

Spatial and temporal variability of rainfall over different seasons influence physical, social and economic parameters. Pre-monsoon (March, April and May – MAM) rainfall over the country is highly variable. Since heat lows and convective rainfall in MAM have an impact on the intensity of the ensuing monsoons, hence the pre-monsoon period was chosen for the study. The pre-whitened Mann Kendall test was used to explore presence of rainfall trend during MAM. The results indicate presence of significant (at 10% level) increasing trend in two stations (Ajmer, Bikaner). The practical significance of the change in rainfall was also explored as percentage changes over long term mean, using Theil and Sen's median slope estimator. Forecast using univariate ARIMA model for pre-monsoon months indicates that there is a significant rise in the pre-monsoon rainfall over the northwest part of the country.     

Temporal dynamics of soil erosion and rainfall erosivity as geoindicators of land degradation in Northwestern Argentina

The subtropical region of Northwestern Argentina displays severe environmental deterioration due to a combination of factors, including seasonally contrasting weather, highly erodable loessic soils, a topography with varied slopes, and natural vegetation coverage restricted by deforestation and agricultural advance, in addition to exploitation of natural resources by people. The aim of the present research was to determine the landscape degradation, using as geoindicators the increase in erosion by water and the pluviometric gradient variations through time.Two regions were chosen as sample areas in the province of Tucumán: the eastern foothills and plain of the Southeastern Ranges (Western Chaco); and the intermountain valley of Tafí. Erosion increase was quantified by measuring the length of gullies and ravines; and the sedimentation in the artificial lake (La Angostura) located in the center of the valley of Tafí. Climate changes were analyzed by means of the rainfall erosivity variations in both sample areas during the last 30 years.The lineal increase in erosion is closely related to the pluvial dynamics. Nevertheless, this erosive intensification is also dependent on the interaction of environmental factors and human activities (deforestation, land use changes, unrestricted agriculture).