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1.
Esmaeel Dodangeh Kaka Shahedi Jenq-Tzong Shiau Maryam MirAkbari 《Journal of Earth System Science》2017,126(6):80
Investigation on drought characteristics such as severity, duration, and frequency is crucial for water resources planning and management in a river basin. While the methodology for multivariate drought frequency analysis is well established by applying the copulas, the estimation on the associated parameters by various parameter estimation methods and the effects on the obtained results have not yet been investigated. This research aims at conducting a comparative analysis between the maximum likelihood parametric and non-parametric method of the Kendall \(\tau \) estimation method for copulas parameter estimation. The methods were employed to study joint severity–duration probability and recurrence intervals in Karkheh River basin (southwest Iran) which is facing severe water-deficit problems. Daily streamflow data at three hydrological gauging stations (Tang Sazbon, Huleilan and Polchehr) near the Karkheh dam were used to draw flow duration curves (FDC) of these three stations. The \(Q_{75}\) index extracted from the FDC were set as threshold level to abstract drought characteristics such as drought duration and severity on the basis of the run theory. Drought duration and severity were separately modeled using the univariate probabilistic distributions and gamma–GEV, LN2–exponential, and LN2–gamma were selected as the best paired drought severity–duration inputs for copulas according to the Akaike Information Criteria (AIC), Kolmogorov–Smirnov and chi-square tests. Archimedean Clayton, Frank, and extreme value Gumbel copulas were employed to construct joint cumulative distribution functions (JCDF) of droughts for each station. Frank copula at Tang Sazbon and Gumbel at Huleilan and Polchehr stations were identified as the best copulas based on the performance evaluation criteria including AIC, BIC, log-likelihood and root mean square error (RMSE) values. Based on the RMSE values, nonparametric Kendall-\(\tau \) is preferred to the parametric maximum likelihood estimation method. The results showed greater drought return periods by the parametric ML method in comparison to the nonparametric Kendall \(\tau \) estimation method. The results also showed that stations located in tributaries (Huleilan and Polchehr) have close return periods, while the station along the main river (Tang Sazbon) has the smaller return periods for the drought events with identical drought duration and severity. 相似文献
2.
研究pair-copula在干旱特性联合概率中的应用。以渭河流域咸阳站降雨资料为例,采用游程理论,选取干旱历时、干旱烈度和烈度峰值为干旱特性变量,应用Pearson线性相关系数、Spearman相关系数和Kendall秩相关系数进行相依性度量。采用4种常用的copula函数构造了12种pair-copulas,以RMSE、AIC、BIC为准则选择最优的pair-copula。运用Rosenblatt变换的Bootstrap法进行copula拟合度检验,推导3变量的联合概率分布。与3维对称、非对称阿基米德copulas和椭圆copula比较,表明pair-copula可以描述多变量水文概率分布。 相似文献
3.
基于Copulas函数的二维干旱变量联合分布 总被引：1，自引：1，他引：0
通过构建干旱变量的联合分布揭示干旱演变规律,可作为干旱分析的重要手段。基于8种单参数族的Copulas函数进行新疆乌鲁木齐和石河子气象站二维干旱变量的联合分布。经拟合优度评价:Frank Copula对干旱历时和干旱烈度、干旱历时和烈度峰值的拟合度最好;Clayton Copula对于干旱烈度和烈度峰值的拟合效果最好。二维变量联合超越概率值随单变量值的减小而增大;单变量的重现期介于二维变量联合重现期与同现重现期之间。表明Copulas函数能够描述二维干旱特征变量的联合分布。 相似文献
4.
Severity–duration–frequency (SDF) curves are very useful in the analysis of drought phenomena. Station-level information obtained from SDF curves can be interpolated to obtain severity maps for fixed return period, in order to jointly analyse the spatial variability of drought characteristics (e.g. severity, duration and frequency). This approach is limited because the severity is usually quantified through indices that use hydrological and meteorological data, depending on the type of requirements. Therefore, drought indices can only reflect hydrological conditions, but are unable to quantify economic losses associated with droughts. In other words, SDF curves do not allow effective quantification of the impact expected with a certain return period. This paper proposes the methodology drought economic risk assessment (DERA) as an approach that emphasizes the importance of the relationship between a generic drought index (which quantifies water deficit) and the economic impact of the failure to meet water demand. Using integrated SDF curves, this relationship enables drought severity and corresponding impacts to be mapped. This procedure was applied to agricultural droughts (sunflower crop) in Umbria Region (central Italy). The agricultural drought impact variable was identified by sunflower yield (Y); the economic impact variable by net benefit depletion (EL); and the drought index by Relative Severity Index (RSI), which is quantifiable by a soil–water balance model. The relationships Y = g(RSI) and EL = f(Y) were specifically determined. Using DERA, it was possible to derive curves for SDF, impact–duration–frequency, and economic losses–duration–frequency (ELDF), which were then used to map severity, impact and economic losses for the assigned return period and duration. From the ELDF curves, further information was obtained by mapping critical drought durations for the assigned return period and economic loss threshold. The case study supports the potential of the proposed approach, both in the planning and real-time management of drought effects. 相似文献
5.
Regional drought frequency analysis was carried out in the Poyang Lake basin (PLB) from 1960–2014 based on three standardized drought indices: the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI) and the standardized Palmer drought index (SPDI). Drought events and characteristics were extracted. A Gumbel–Hougaard (GH) copula was selected to construct the bivariate probability distribution of drought duration and severity, and the joint return periods (T a ) were calculated. Results showed that there were 50 (50 and 40) drought events in the past 55 years based on the SPI (SPEI and SPDI), and 9 (8 and 10) of them were severe with T a more than 10 years, occurred in the 1960s, the 1970s and the 2000s. Overall, the three drought indices could detect the onset of droughts and performed similarly with regard to drought identification. However, for the SPDI, moisture scarcity was less frequent, but it showed more severe droughts with substantially higher severity and longer duration droughts. The conditional return period (Ts|d) was calculated for the spring drought in 2011, and it was 66a and 54a, respectively, based on the SPI and SPDI, which was consistent with the record. Overall, the SPI, only considering the precipitation, can as effectively as the SPEI and SPDI identify the drought process over the PLB under the present changing climate. However, drought is affected by climate and land-cover changes; thus, it is necessary to integrate the results of drought frequency analysis based on different drought indices to improve the drought risk management. 相似文献
6.
以甘肃省陇西站月降水资料为例,应用9种3维Archimedean Copulas函数构造了干旱历时、干旱烈度和烈度峰值的联合概率分布,并进行了多变量的拟合优度评价,利用优选出的3维非对称型M12 Copula函数,计算联合分布的重现期以及不同组合下的条件概率与条件重现期。结果表明,M12Copula函数可以描述干旱历时、干旱烈度和烈度峰值间的联合分布。由于Copula函数能够用来构建不同边缘分布的联合分布,可以获得变量间不同组合下的重现期,因而能够更全面客观地反映干旱的特征,是描述干旱多变量分布的一种有效途径。 相似文献
7.
In this study, the Variable Infiltration Capacity model and Palmer Drought Severity Index (PDSI) were combined for drought identification on the Loess Plateau. The calibration method of climatic characteristic (K j ) in PDSI was improved. Land cover datasets in 1980 and 2005 were used to drive the model. The driest periods over the past four decades of the study region emerged in 1976–1982, 1997–2001 and 2003–2008. Regardless of ranking by duration, spatial extent or severity, most of the prominent droughts occurred in the detected driest periods. The drought severity and area over the upper reaches of the Yellow River were higher than other domains. A total of 53 droughts with area greater than the 25,000 km2 threshold were identified with durations longer than 3 months using clustering algorithm. Most regions of the study area exhibited spatially increasing trends in drought severity and frequency, indicating that the Loess Plateau has experienced apparent drying and warming processes between 1971 and 2010. 相似文献
8.
研究多变量干旱特性联合分布的推求方法。选择干旱历时、干旱烈度和烈度峰值为水文干旱特性变量。单变量的边际分布参数分别采用矩法、概率权重法、极大似然法和遗传算法进行计算和优化。应用检验、Kolmogorov-Smirnov等6种检验法进行单变量分布的拟合度检验。采用Pearson’s古典相关系数,Spearman秩相关系数,Kendall’s,Chi-Plots和K-Plots进行变量间的相依性度量。选择4种常用的3维Archimedean Copula函数进行干旱特性变量联合分布拟合。根据RMSE、AIC和BIC准则选择最优copula。在此基础上,采用基于Rosenblatt变换的Bootstrap法进行3维copula的拟合度检验。模型应用于渭河流域北洛河状头站径流序列,结果表明:Gumbel-Hougaard copula拟合效果最好,可以描述洛河状头站3维干旱变量的联合分布。 相似文献
9.
Azam Shahnazar Hima Nikafshan Rad Mahdi Hasanipanah M. M. Tahir Danial Jahed Armaghani Mahyar Ghoroqi 《Environmental Earth Sciences》2017,76(15):527
Ground vibration is one of the common environmental effects of blasting operation in mining industry, and it may cause damage to the nearby structures and the surrounding residents. So, precise estimation of blast-produced ground vibration is necessary to identify blast-safety area and also to minimize environmental effects. In this research, a hybrid of adaptive neuro-fuzzy inference system (ANFIS) optimized by particle swarm optimization (PSO) was proposed to predict blast-produced ground vibration in Pengerang granite quarry, Malaysia. For this goal, 81 blasting were investigated, and the values of peak particle velocity, distance from the blast-face and maximum charge per delay were precisely measured. To demonstrate the performance of the hybrid PSO–ANFIS, ANFIS, and United States Bureau of Mines empirical models were also developed. Comparison of the predictive models was demonstrated that the PSO–ANFIS model [with root-mean-square error (RMSE) 0.48 and coefficient of determination (R 2) of 0.984] performed better than the ANFIS with RMSE of?1.61 and R 2 of 0.965. The mentioned results prove the superiority of the newly developed PSO–ANFIS model in estimating blast-produced ground vibrations. 相似文献
10.
The flood characteristics, namely, peak, duration and volume provide important information for the design of hydraulic structures, water resources planning, reservoir management and flood hazard mapping. Flood is a complex phenomenon defined by strongly correlated characteristics such as peak, duration and volume. Therefore, it is necessary to study the simultaneous, multivariate, probabilistic behaviour of flood characteristics. Traditional multivariate parametric distributions have widely been applied for hydrological applications. However, this approach has some drawbacks such as the dependence structure between the variables, which depends on the marginal distributions or the flood variables that have the same type of marginal distributions. Copulas are applied to overcome the restriction of traditional bivariate frequency analysis by choosing the marginals from different families of the probability distribution for flood variables. The most important step in the modelling process using copula is the selection of copula function which is the best fit for the data sample. The choice of copula may significantly impact the bivariate quantiles. Indeed, this study indicates that there is a huge difference in the joint return period estimation using the families of extreme value copulas and no upper tail copulas (Frank, Clayton and Gaussian) if there exists asymptotic dependence in the flood characteristics. This study suggests that the copula function should be selected based on the dependence structure of the variables. From the results, it is observed that the result from tail dependence test is very useful in selecting the appropriate copula for modelling the joint dependence structure of flood variables. The extreme value copulas with upper tail dependence have proved that they are appropriate models for the dependence structure of the flood characteristics and Frank, Clayton and Gaussian copulas are the appropriate copula models in case of variables which are diagnosed as asymptotic independence. 相似文献
11.
Assessment of drought frequency, duration, and severity and its impact on pasture production in Mongolia 总被引：1，自引：1，他引：0
Drought frequency, duration, and severity and its impact on pasture productivity in the four main vegetation zones of Mongolia were analyzed using meteorological, soil moisture, and vegetation data during the growing season (April–August) of 1965–2010. Meteorological and pasture drought characteristics were explored using the Standardized Precipitation Index (SPI), the soil moisture anomalies percentile index (W p), and Palmer Drought Severity Index (PDSI) on 1-month timescale. Generally, 35–37 (15–16 %) by SPI for meteorological drought while 27–29 (12–13 %) by W p, and 16–21 (7–9 %) by PDSI for pasture drought with different durations were identified over the four vegetation zones during the study period. Most of these droughts (80 % by SPI and 50–60 % by both W p and PDSI) observed during the entire events occurred on a 1-month duration with moderate intensity. Drought frequencies were not significantly (p > 0.05) different within the four zones. The frequency of the short-term meteorological droughts was observed relatively greater than pasture droughts; however, pasture droughts were more persistent and severe than meteorological droughts. The three indices show that the frequency and severity of droughts have slightly increased over the 46 years with significant (p < 0.05) dry conditions during the last decade of 2001–2010 in the four zones (except in the high mountain). The results showed the W p was more highly significantly correlated with the precipitation anomalies (r = 0.68) and pasture production (r = 0.55) than PDSI (r = 0.51, p < 0.05 and r = 0.38, p < 0.10, respectively). A statistical model, based on pasture production and the W p, suggested that the consecutive drought months contribution during the growing season was 30 % (p < 0.05) and that pasture production was more sensitive to the occurrence of droughts during June–August (R 2 = 0.32, p < 0.05) as seen in 2000–2002 and 2007. We concluded that a greater severity and frequency of growing-season droughts, during the last decade of 2001–2010, have driven a reduction in pasture production in Mongolia. 相似文献
12.
H. Md. Azamathulla Yong Chong Cuan Aminuddin Ab. Ghani Chun Kiat Chang 《Arabian Journal of Geosciences》2013,6(9):3469-3480
This study presents gene expression programming (GEP), an extension of genetic programming, as an alternative approach to modeling the suspended sediment load relationship for the three Malaysian rivers. In this study, adaptive neuro-fuzzy inference system (ANFIS), regression model, and GEP approaches were developed to predict suspended load in three Malaysian rivers: Muda River, Langat River, and Kurau River [ANFIS (R 2?=?0.93, root mean square error (RMSE)?=?3.19, and average error (AE)?=?1.12) and regression model (R 2?=?0.63, RMSE?=?13.96, and AE?=?12.69)]. Additionally, the explicit formulations of the developed GEP models are presented (R 2?=?0.88, RMSE?=?5.19, and AE?=?6.5). The performance of the GEP model was found to be acceptable compare to ANFIS and better than the conventional models. 相似文献
13.
Roya Narimani Mahdi Erfanian Habib Nazarnejad Ahmad Mahmodzadeh 《Environmental Earth Sciences》2017,76(9):353
This study was undertaken to evaluate land use change impact and management scenarios on annual average surface runoff (SR) and sediment yield (SY) using the GeoWEPP tool in the Lighvanchai watershed (located in northwestern Iran). Following a sensitivity analysis, the WEPP model was calibrated (2005–2007) and validated (2008–2010) against monthly observed SY and SR. The coefficient of determination (R 2), Nash–Sutcliffe efficiency (NSE), mean bias error (MBE), and root-mean-square error (RMSE) were applied to quantitatively evaluate the WEPP model. The results indicate a satisfactory model performance with R 2 > 0.80 and NSE > 0.60. Therefore, the model for current land use (scenario 1) was run for a 30-year time period (1982–2011). The annual average of SR and sediment load were predicted as 93,584 m3/year and 4340 ton/year, respectively. To reduce the annual average surface runoff and sediment yield at the watershed scale, the second scenario (alfalfa cultivation with suitable tillage) and the third scenario (grassland development) as two management scenarios of land use changes were defined by identifying the critical hillslopes. The rate of SR and sediment load in the second scenario were 42,096 m3/year and 429 ton/year, respectively. For the third scenario, the model predictions were 30,239 m3/year and 226 ton/year, respectively. Compared to the first scenario, the reduction rates in annual average of sediment load were about 90 and 94%, respectively. Moreover, for the second and third management scenarios, the reduction rates in annual average of SR were about 55 and 67%, respectively. 相似文献
14.
Drought over a period threatens the water resources, agriculture, and socioeconomic activities. Therefore, it is crucial for decision makers to have a realistic anticipation of drought events to mitigate its impacts. Hence, this research aims at using the standardized precipitation index (SPI) to predict drought through time series analysis techniques. These adopted techniques are autoregressive integrating moving average (ARIMA) and feed-forward backpropagation neural network (FBNN) with different activation functions (sigmoid, bipolar sigmoid, and hyperbolic tangent). After that, the adequacy of these two techniques in predicting the drought conditions has been examined under arid ecosystems. The monthly precipitation data used in calculating the SPI time series (SPI 3, 6, 12, and 24 timescales) have been obtained from the tropical rainfall measuring mission (TRMM). The prediction of SPI was carried out and compared over six lead times from 1 to 6 using the model performance statistics (coefficient of correlation (R), mean absolute error (MAE), and root mean square error (RMSE)). The overall results prove an excellent performance of both predicting models for anticipating the drought conditions concerning model accuracy measures. Despite this, the FBNN models remain somewhat better than ARIMA models with R?≥?0.7865, MAE?≤?1.0637, and RMSE?≤?1.2466. Additionally, the FBNN based on hyperbolic tangent activation function demonstrated the best similarity between actual and predicted for SPI 24 by 98.44%. Eventually, all the activation function of FBNN models has good results respecting the SPI prediction with a small degree of variation among timescales. Therefore, any of these activation functions can be used equally even if the sigmoid and bipolar sigmoid functions are manifesting less adjusted R2 and higher errors (MAE and RMSE). In conclusion, the FBNN can be considered a promising technique for predicting the SPI as a drought monitoring index under arid ecosystems. 相似文献
15.
为应对全球范围内日益严重的干旱问题,对区域气象干旱相对完整的评估分析模式开展了探讨。提出了从区域气象干旱识别到干旱特征值计算,再到干旱特征多变量分析的3个分析评估步骤。并以渭河流域为例,对研究区域进行了矩形干旱评估单元划分,选取了RDI（Reconnaissance Drought Index）为评估指标对区域内各单元各时段的干旱状态进行了识别,结果与历史记载的干旱年份吻合较好。分别采用了分布拟合、相关系数和Copula函数等统计学方法对区域干旱的干旱特征值（干旱历时、干旱面积、干旱强度和干旱频率）进行了特征分析,得出了一系列的单变量、双变量及多变量特征分析对比结果。通过对各类分布函数的计算和绘图,得到了渭河流域干旱事件发生的条件概率和重现期,形成了一套相对完整的区域干旱评估分析模式。 相似文献
16.
Assessment of drought hazard impact on wheat cultivation using standardized precipitation index in Iran 总被引：1，自引：0，他引：1
Mohammad Reza Mansouri Daneshvar Ali Bagherzadeh Mahmood Khosravi 《Arabian Journal of Geosciences》2013,6(11):4463-4473
The assessment of drought hazard impacts on wheat cultivation as a strategic crop in Iran is essential for making mitigation plans to reduce the impact of drought. Standardized precipitation index has gained importance in recent years as a potential drought indicator and is being used more frequently for assessment of drought hazard in many countries. In the present study, the calculated standardized precipitation index for 48 stations dataset in the 30-year time scale fulfilled 30 statistical matrices. The drought hazard index map was produced by sum overlaying the spatial representations of 30 statistical matrices and categorized into four levels of low, moderate, high, and very high, which demonstrated probability of drought occurrences of 10–20 %, 20–30 %, 30–40 %, and 40–50 %, respectively. Finally, after the general division of zonal statistics in drought hazard index map of Iran, major drought hazard zones were geographically classified into five zones. The statistical analysis showed a significant correlation (R 2?=?0.701 to 0.648) between drought occurrences and wheat cultivation including surface area and total production for these drought hazard zones. 相似文献
17.
Using monitoring data of surface soil to predict whole crop-root zone soil water content with PSO-LSSVM,GRNN and WNN 总被引：1，自引：0，他引：1
Zhao Lixi Shui Pengbo Jiang Fang Qiu Hengqing Ren Shumei Li Yunkai Zhang Yu 《Earth Science Informatics》2014,7(1):59-68
Drought is a significant disaster in Beijing and it is important to find a method to assess the drought condition. First, this paper collected data of 85 soil monitoring stations in Beijing, such as soil dry bulk densities, saturated water contents, field capacities. Then, spatial variability characteristics of soil physics parameters were investigated by GIS and other three factors, 10 cm soil moisture content, organic matter and saturated water content which notably influenced soil moisture were extracted by Principal Component Analysis (PCA). Furthermore, four different nonlinear methods were put forward to predict crop-root zone soil water. 15555 single daily data from 2011 were used in parameters determination, while 15470 double daily data were used to test. The result showed that the Least Square Support Vector Machine coupling Particle Swarm Optimization Algorithm (PSO-LSSVM) (R 2?=?0. 875) did better than BP Neural Network (R 2?=?0. 840), Generalized Regression Neural Network (GRNN) (R 2?=?0. 850) and Wavelet Neural Network (WNN) (R 2?=?0. 853). As so the POS-LSSVM method was used to evaluate the drought conditions from October 2010 to March 2011 of Beijing, and the result showed that from October 2010 to January 2011, the drought conditions were getting increasingly worse while later relieved from January 2011 to March 2011. 相似文献
18.
Accurate and reliable prediction of shallow groundwater level is a critical component in water resources management. Two nonlinear models, WA–ANN method based on discrete wavelet transform (WA) and artificial neural network (ANN) and integrated time series (ITS) model, were developed to predict groundwater level fluctuations of a shallow coastal aquifer (Fujian Province, China). The two models were testified with the monitored groundwater level from 2000 to 2011. Two representative wells are selected with different locations within the study area. The error criteria were estimated using the coefficient of determination (R 2), Nash–Sutcliffe model efficiency coefficient (E), and root-mean-square error (RMSE). The best model was determined based on the RMSE of prediction using independent test data set. The WA–ANN models were found to provide more accurate monthly average groundwater level forecasts compared to the ITS models. The results of the study indicate the potential of WA–ANN models in forecasting groundwater levels. It is recommended that additional studies explore this proposed method, which can be used in turn to facilitate the development and implementation of more effective and sustainable groundwater management strategies. 相似文献
19.
M. Rezaeianzadeh A. Stein H. Tabari H. Abghari N. Jalalkamali E. Z. Hosseinipour V. P. Singh 《International Journal of Environmental Science and Technology》2013,10(6):1181-1192
Artificial neural networks (ANNs) are used by hydrologists and engineers to forecast flows at the outlet of a watershed. They are employed in particular where hydrological data are limited. Despite these developments, practitioners still prefer conventional hydrological models. This study applied the standard conceptual HEC-HMS’s soil moisture accounting (SMA) algorithm and the multi layer perceptron (MLP) for forecasting daily outflows at the outlet of Khosrow Shirin watershed in Iran. The MLP [optimized with the scaled conjugate gradient] used the logistic and tangent sigmoid activation functions resulting into 12 ANNs. The R 2 and RMSE values for the best trained MPLs using the tangent and logistic sigmoid transfer function were 0.87, 1.875 m3 s?1 and 0.81, 2.297 m3 s?1, respectively. The results showed that MLPs optimized with the tangent sigmoid predicted peak flows and annual flood volumes more accurately than the HEC-HMS model with the SMA algorithm, with R 2 and RMSE values equal to 0.87, 0.84 and 1.875 and 2.1 m3 s?1, respectively. Also, an MLP is easier to develop due to using a simple trial and error procedure. Practitioners of hydrologic modeling and flood flow forecasting may consider this study as an example of the capability of the ANN for real world flow forecasting. 相似文献
20.
A quantitative approach for hydrological drought characterization, based on non-seasonal water storage deficit data from NASA’s Gravity Recovery and Climate Experiment (GRACE) satellite mission, is assessed. Non-seasonal storage deficit is the negative terrestrial water storage after deducting trend, acceleration and seasonal signals, and it is designated as a drought event when it persists for three or more continuous months. The non-seasonal water storage deficit is used for measuring the hydrological drought in southwestern China. It is found that this storage-deficit method clearly identifies hydrological drought onset, end and duration, and quantifies instantaneous severity, peak drought magnitude, and time to recovery. Moreover, it is found that severe droughts have frequently struck southwestern China in the past several decades, among which, the drought of 2011–2012 was the most severe; the duration was 10 months, the severity was ?208.92 km3/month, and the time to recovery was 17 months. These results compare well with the National Climate Center of China drought databases, which signifies that the GRACE-based non-seasonal water storage deficit has a quantitative effect on hydrological drought characterization and provides an effective tool for researching droughts. 相似文献