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1.
Estimation of rainfall and temperature for a desired return period is a prerequisite for planning, design and operation of various hydraulic structures and for evaluation of technical and engineering appraisal of large infrastructure projects. This can be computed through Extreme Value Analysis (EVA) by fitting probability distributions to the annual series of 1-day maximum rainfall, maximum and minimum temperature. This paper details the study on adoption of Extreme Value Type-1, Extreme Value Type-2, 2-parameter Log Normal and Log Pearson Type-3 (LP3) probability distributions in EVA of rainfall and temperature for Hissar. Based on the applicability, standard parameter estimation procedures such as method of moments, maximum likelihood method (MLM) and order statistics approach are used for determination of parameters of distributions. The adequacy on fitting of probability distributions used in EVA of rainfall and temperature is evaluated by goodness-of-fit (GoF) tests, viz. Anderson–Darling and Kolmogorov–Smirnov and diagnostic test using D-index. The GoF and diagnostic tests results suggest the LP3 (MLM) is better suited amongst four probability distributions adopted in EVA of rainfall and temperature for Hissar.  相似文献   

2.
The most direct method of design flood estimation is at-site flood frequency analysis, which relies on a relatively long period of recorded streamflow data at a given site. Selection of an appropriate probability distribution and associated parameter estimation procedure is of prime importance in at-site flood frequency analysis. The choice of the probability distribution for a given application is generally made arbitrarily as there is no sound physical basis to justify the selection. In this study, an attempt is made to investigate the suitability of as many as fifteen different probability distributions and three parameter estimation methods based on a large Australian annual maximum flood data set. A total of four goodness-of-fit tests are adopted, i.e., the Akaike information criterion, the Bayesian information criterion, Anderson–Darling test, and Kolmogorov–Smirnov test, to identify the best-fit probability distributions. Furthermore, the L-moments ratio diagram is used to make a visual assessment of the alternative distributions. It has been found that a single distribution cannot be specified as the best-fit distribution for all the Australian states as it was recommended in the Australian rainfall and runoff 1987. The log-Pearson 3, generalized extreme value, and generalized Pareto distributions have been identified as the top three best-fit distributions. It is thus recommended that these three distributions should be compared as a minimum in practical applications when making the final selection of the best-fit probability distribution in a given application in Australia.  相似文献   

3.
Uncertainty in depth–duration–frequency (DDF) curves is usually disregarded in the view of difficulties associated in assigning a value to it. In central Iran, precipitation duration is often long and characterized with low intensity leading to a considerable uncertainty in the parameters of the probabilistic distributions describing rainfall depth. In this paper, the daily rainfall depths from 4 stations in the Zayanderood basin, Iran, were analysed, and a generalized extreme value distribution was fitted to the maximum yearly rainfall for durations of 1, 2, 3, 4 and 5 days. DDF curves were described as a function of rainfall duration (D) and return period (T). Uncertainties of the rainfall depth in the DDF curves were estimated with the bootstrap sampling method and were described by a normal probability density function. Standard deviations were modeled as a function of rainfall duration and rainfall depth using 104 bootstrap samples for all the durations and return periods considered for each rainfall station.  相似文献   

4.
The aim of this study was to investigate temporal variation in seasonal and annual rainfall trend over Ranchi district of Jharkhand, India for the period (1901–2014: 113 years). Mean monthly rainfall data series were used to determine the significance and magnitude of the trend using non-parametric Mann–Kendall and Sen’s slope estimator. The analysis showed a significant decreased in rainfall during annual, winter and southwest monsoon rainfall while increased in pre-monsoon and post-monsoon rainfall over the Ranchi district. A positive trend is detected in pre-monsoon and post-monsoon rainfall data series while annual, winter and southwest monsoon rainfall showed a negative trend. The maximum decrease in rainfall was found for monsoon (? 1.348 mm year?1) and minimum (? 0.098 mm year?1) during winter rainfall. The trend of post-monsoon rainfall was found upward (0.068 mm year?1). The positive and negative trends of annual and seasonal rainfall were found statistically non-significant except monsoon rainfall at 5% level of significance. Rainfall variability pattern was calculated using coefficient of variation CV, %. Post-monsoon rainfall showed the maximum value of CV (70.80%), whereas annual rainfall exhibited the minimum value of CV (17.09%), respectively. In general, high variation of CV was found which showed that the entire region is very vulnerable to droughts and floods.  相似文献   

5.
Present study deals with the statistical analysis of long-term ground level ozone (O3) trend and the influence of meteorological variables on its variation over Delhi, India. Daily mean and maximum of O3 and meteorological data, obtained from India Meteorological Department, were arranged for the period of 9 years (1998–2006). Based on the preliminary correlation study of all the data with O3, six variables viz. daily maximum temperature, daily average relative humidity, dew point, wind speed, visibility, and total sunshine were selected. Classical additive time series decomposition technique was used to obtain seasonally adjusted long-term trend. To analyze the masking effect of meteorology, adjustment was made using Kolmogorov–Zurbenko filters followed by stepwise regression analysis to the smoothed series of O3 maximum and meteorological variables, which showed that long-term trend was independent of sunshine duration. Results indicate a significant increasing trend with annual increase of 1.13 % for O3 mean and 3 % for O3 maximum. Annual deseasonalized trend for seasonal cycle shows bimodal oscillations. About 43 % of O3 variation was explained by the selected meteorological factors and rest of variation attributed to factors like emission of precursor gases, pollutant transport, policy changes, etc. Among the three tested regression models, performance of Model 2 with variable temperature, wind speed, and visibility was found to be best that resulted in lowering of O3 trend. Large variability (23 %) was explained by the variable visibility depicted that the emission of primary pollutants not only provides the precursor gases but also control the local photochemical reactions.  相似文献   

6.
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.  相似文献   

7.
煤系岩石工程地质性质指标变异性研究   总被引：2，自引：0，他引：2  
对山东金山矿区３煤覆岩及底板工程地质性质类型的物理力学性质指标的变异性进行了研究,用Ｋ－Ｓ法进行的概率分布类型拟合检验表明,各指标基本服从正态分布;另外,还对煤系岩石物理力学性质指标的关联性及各向异性特征进行了初步分析,为煤矿工程地质可靠度研究提供了依据。  相似文献   

8.
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.  相似文献   


9.
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.  相似文献   

10.
长江流域降水极值的变化趋势   总被引：7，自引：1，他引：6       下载免费PDF全文
依据1960-2005年长江流域147个气象站逐日降水,ECHAM5/MPI-OM气候模式模拟的长江流域79个格点20世纪实验期(1941-2000年)以及未来3种排放情景(SRES-B1,A1B,A2)下21世纪前50年逐日降水数据,建立年最大强降水和汛期<1.27 mm/d的最长干旱持续天数序列。运用广义极值分布,广义帕雷托分布,广义逻辑分布与韦克比分布等4种分布函数定量拟合了长江流域降水极值的概率分布。研究表明:韦克比分布函数能够较好地拟合长江流域降水极值的概率分布。在3种排放情景下,未来降水极值的重现期呈现不同的空间分布特征。长江流域,尤其是中下游大部地区,1951-2000年间的50年一遇强降水和干旱事件,在2001-2050年间发展成为25年一遇降水极值事件。未来气候变暖条件下,降水极值重现期出现的这种变化趋势,将会对水资源趋势产生重大的影响。  相似文献   

11.
不同历时设计暴雨组合的风险率分析   总被引：1，自引：0，他引：1  
陈子燊  刘曾美 《水文》2011,(4):12-17
基于Copula理论与方法,以广州1951~2010年的日降水为例,以最大日降水量为基准,构建最大日降水量(W1)与历时3日(W3)降水量,最大日降水量(W1)与历时7日(W7)降水量两个组合的联合概率分布模式。经择优检验建立了边缘分布为广义极值和P-III型的Gumbel-Hougaard Copula两变量联合分布。随之,推算了两个组合降水的同现重现期和设计暴雨值。最后,依据条件分布计算了在大于或小于年最大日降水量特定设计暴雨条件下超过历时3日或7日降水设计值的风险率。  相似文献   

12.
In order to generate early warning for landslides, it is necessary to address the spatial and temporal aspects of slope failure. The present study deals with the temporal dimension of slope failures taking into account the most widespread and frequent triggering factor, i.e. rainfall, along the National Highway-58 from Rishikesh to Mana in the Garhwal Himalaya, India. Using the post-processed three-hourly rainfall intensity and duration values from the Tropical Rainfall Measuring Mission-based Multi-satellite Precipitation Analysis and the time-tagged landslide records along this route, an intensity–duration (I–D)-based threshold has been derived as I?=?58.7D ?1.12 for the rainfall-triggered landslides. The validation of the I–D threshold has shown 81.6 % accuracy for landslides which occurred in 2005 and 2006. From this result, it can be inferred that landslides in the study area can be initiated by continuous rainfall of over 12 h with about 4-mm/h intensity. Using the mean annual precipitation, a normalized intensity–duration relation of NI?=?0.0612D ?1.17 has also been derived. In order to account for the influence of the antecedent rainfall in slope failure initiation, the daily, 3-day cumulative, and 15- and 30-day antecedent rainfall values associated with landslides had been subjected to binary logistic regression using landslide as the dichotomous dependent variable. The logistic regression retained the daily, 3-day cumulative and 30-day antecedent rainfall values as significant predictors influencing slope failure. This model has been validated through receiver operating characteristic curve analysis using a set of samples which had not been used in the model building; an accuracy of 95.1 % has been obtained. Cross-validation of I–D-based thresholding and antecedent rainfall-based probability estimation with slope failure initiation shows 81.9 % conformity between the two in correctly predicting slope stability. Using the I–D-based threshold and the antecedent rainfall-based regression model, early warning can be generated for moderate to high landslide-susceptible areas (which can be delineated using spatial integration of preconditioning factors). Temporal predictions where both the methods converge indicate higher chances of slope failures for areas predisposed to instability due to unfavourable geo-environmental and topographic parameters and qualify for enhanced slope failure warning. This method can be verified for further rainfall seasons and can also be refined progressively with finer resolutions (spatial and temporal) of rainfall intensity and multiple rain gauge stations covering a larger spatial extent.  相似文献   

13.
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.  相似文献   

14.
Bogotá is located in the central Andean region of Colombia, which is frequently affected by landslide processes. These processes are mostly triggered during the rainy season in the city. This fact remarks the importance of determining what rain-derived parameters (e.g. intensity, antecedent rain, daily rain) are better related with the occurrence of landslides. For this purpose, the linear discriminant analysis (LDA), a technique derived from multivariate statistics, was used. The application of this type of analysis led to obtain simple mathematical functions that represent the probability of occurrence of landslides in Bogotá. The functions also allow to identify the most relevant variables derived from records of rainfall linked to the generation of landslides. A proof of concept using the proposed methodology was done using historic rainfall data from a 9-km2 area of homogenous climatology and geomorphology in the south part of Bogotá. Landslides needed to be grouped for the LDA. Each one of these grouping categories represents landslides that occurred in similar geomorphologic conditions. Another set of events with no landslides was generated synthetically. Results of the proof of concept show that rainfall parameters such as normalized rainfall intensity I MAP, normalized daily rainfall R MAP and rainy-days normal RDN have the best statistical correlation with the landslides observed in the zone of analysis.  相似文献   

15.
We consider some practical issues of the determination of the b-value of sequences of magnitudes with the bootstrap method for short series of length L and various quantization levels $\Updelta m$ of the magnitude. Preliminary Monte Carlo tests performed with $\Updelta m = 0$ demonstrate the superiority of the maximum likelihood estimator b MLE, and the inconsistency of the, yet often used, b LR estimator defined as the least-squares slope of the experimental Gutenberg?CRichter curve. The Monte Carlo tests are also applied to an estimator, b KS, which minimizes the Kolmogorov?CSmirnov distance between the cumulative distribution of magnitudes and a power-law model. Monte Carlo tests of discrete versions of the b MLE and b KS estimators are done for $\Updelta m = \{0.1, 0.2, 0.3 \}$ and used as reference to evaluate the performance of the bootstrap determination of b. We show that all estimators provide b estimates within 10?% error for L????100 and if a large number, n?=?2?×?105, of bootstrapped sample series is used. A resolution test done with $\Updelta m = 0.1$ reveals that a clear distinction between b?=?0.8, 1.0, and 1.2 is obtained if L????200.  相似文献   

16.
Flood frequency analysis is a pre-requisite for setting up and safeguarding of many hydraulic structures, such as dams, barrages, check-dams, culverts and urban drainage systems. In the flood frequency analysis, partial duration series (PDS) may be considered when dealing with values exceeding certain limits causing floods. In fact, the PDS is capable of getting more information about extreme events than the annual maximum series (AMS). Additionally, an assumption that, the magnitude of the extreme events of a PDS is best described by a generalized Pareto (GP) distribution. The present work investigates the at-site flood frequency analysis to find the average number of peaks (λ) for modelling the PDS on the basis of the PDS/GP assumption and variability in the GP parameters coupled with the quantile estimation with an increase in the value of average number of peaks (λ) each year in the Mahanadi river system, Odisha, India. Also, to verify the PDS/GP assumption we tested seven different frequency distributions (Exponential, Gumbel, logistics, generalized extreme value (GEV), Lognormal (LN), generalized logistics (GL) and Pearson Type 3). Extensive daily discharge data collected from 23 gauging sites were used for the analysis. The results indicate precision and stability of GP distribution parameters for λ?=?4 for almost all the discharge sites. The peak flood estimated for various return periods in the Mahanadi river system using GP distribution is endowed with high correlation statistics for this λ value.  相似文献   

17.
Rainfall infiltration poses a disastrous threat to the slope stability in many regions around the world. This paper proposes an extreme gradient boosting (XGBoost)-based stochastic analysis framework to estimate the rainfall-induced slope failure probability. An unsaturated slope under rainfall infiltration in spatially varying soils is selected in this study to investigate the influences of the spatial variability of soil properties (including effective cohesion c′, effective friction angle φ′ and saturated hydraulic conductivity ks), as well as rainfall intensity and rainfall pattern on the slope failure probability. Results show that the proposed framework in this study is capable of computing the failure probability with accuracy and high efficiency. The spatial variability of ks cannot be overlooked in the reliability analysis. Otherwise, the rainfall-induced slope failure probability will be underestimated. It is found that the rainfall intensity and rainfall pattern have significant effect on the probability of failure. Moreover, the failure probabilities under various rainfall intensities and patterns can be easily obtained with the aid of the proposed framework, which can provide timely guidance for the landslide emergency management departments.  相似文献   

18.
Majority of landslides in the Indian sub-continent are triggered by rainfall. Several attempts in the global scenario have been made to establish rainfall thresholds in terms of intensity-duration and antecedent rainfall models on global, regional and local scales for the occurrence of landslides. However, in the context of the Indian Himalayas, the rainfall thresholds for landslide occurrences are not yet understood fully. Neither on regional scale nor on local scale, establishing such rainfall thresholds for landslide occurrences in Indian Himalayas has yet been attempted. This paper presents an attempt towards deriving local rainfall thresholds for landslides based on daily rainfall data in and around Chamoli-Joshimath region of the Garhwal Himalayas, India. Around 128 landslides taken place in last 4 years from 2009 to 2012 have been studied to derive rainfall thresholds. Out of 128 landslides, however, rainfall events pertaining to 81 landslides were analysed to yield an empirical intensity–duration threshold for landslide occurrences. The rainfall threshold relationship fitted to the lower boundary of the landslide triggering rainfall events is I?=?1.82 D ?0.23 (I?=?rainfall intensity in millimeters per hour and D?=?duration in hours). It is revealed that for rainfall events of shorter duration (≤24 h) with a rainfall intensity of 0.87 mm/h, the risk of landslide occurrence in this part of the terrain is expected to be high. Also, the role of antecedent rainfall in causing landslides was analysed by considering daily rainfall at failure and different period cumulative rainfall prior to failure considering all 128 landslides. It is observed that a minimum 10-day antecedent rainfall of 55 mm and a 20-day antecedent rainfall of 185 mm are required for the initiation of landslides in this area. These rainfall thresholds presented in this paper may be improved with the hourly rainfall data vis-à-vis landslide occurrences and also data of later years. However, these thresholds may be used in landslide warning systems for this particular region of the Garhwal Himalayas to guide the traffic and provide safety to the tourists travelling along this pilgrim route during monsoon seasons.  相似文献   

19.
Dwarka River basin in Birbhum, West Bengal (India), is an agriculture-dominated area where groundwater plays a crucial role. The basin experiences seasonal water stress conditions with a scarcity of surface water. In the presented study, delineation of groundwater potential zones (GWPZs) is carried out using a geospatial multi-influencing factor technique. Geology, geomorphology, soil type, land use/land cover, rainfall, lineament and fault density, drainage density, slope, and elevation of the study area were considered for the delineation of GWPZs in the study area. About 9.3, 71.9 and 18.8% of the study area falls within good, moderate and poor groundwater potential zones, respectively. The potential groundwater yield data corroborate the outcome of the model, with maximum yield in the older floodplain and minimum yield in the hard-rock terrains in the western and south-western regions. Validation of the GWPZs using the yield of 148 wells shows very high accuracy of the model prediction, i.e., 89.1% on superimposition and 85.1 and 81.3% on success and prediction rates, respectively. Measurement of the seasonal water-table fluctuation with a multiplicative model of time series for predicting the short-term trend of the water table, followed by chi-square analysis between the predicted and observed water-table depth, indicates a trend of falling groundwater levels, with a 5% level of significance and a p-value of 0.233. The rainfall pattern for the last 3 years of the study shows a moderately positive correlation (R 2 = 0.308) with the average water-table depth in the study area.  相似文献   

20.
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.  相似文献   

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