scholarly journals Analysis of Characteristics of Dry–Wet Events Abrupt Alternation in Northern Shaanxi, China

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2384
Author(s):  
Junhui Wang ◽  
Guangzhi Rong ◽  
Kaiwei Li ◽  
Jiquan Zhang

In this study, Yulin city and Yan’an city in northern Shaanxi Province were taken as the study area. Based on the diurnal dry–wet events abrupt alternation index DWAAI, the joint probability distribution of two characteristic variables of “urgency” and “alternation” of dry–wet events abrupt alternation was established by using copula function, and the characteristics of dry–wet events abrupt alternation were analyzed. DWAAI was calculated from daily precipitation data and the applicability of the index was verified. On this basis, the two characteristic variables of “urgency” and “alternation” were separated, and the appropriate marginal distribution function was selected to fit them, and the correlation between the two variables was evaluated. Finally, the appropriate copula function was selected to fit the bivariate of each station, and the joint cumulative probability and recurrence period of the two variables were calculated. The results show that the DWAAI index is suitable for the identification of dry–wet events abrupt alternation in the study area. Light and moderate dry–wet events abrupt alternation occurs more frequently, while severe events rarely occur in the study area. The frequency of severe dry–wet events abrupt alternation in Jingbian station and its northern area is greater than that in the southern area, and the risk of dry–wet events abrupt alternation of disasters in the northern area is higher. The greater the degree of “urgency” and “alternation”, the greater the joint cumulative probability and the greater the return period. The return period of severe dry–wet events abrupt alternation was more than five years, while the return period of light and moderate dry–wet events abrupt alternation was less than five years.

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1445
Author(s):  
Junhui Wang ◽  
Guangzhi Rong ◽  
Kaiwei Li ◽  
Jiquan Zhang

Precipitation is low and drought occurs frequently in Northern Shaanxi. To study the characteristics and occurrence and development of drought events in Northern Shaanxi is beneficial to the prevention and control of drought disasters. Based on the monthly rainfall data of 10 meteorological stations in Northern Shaanxi from 1960 to 2019, the characteristic variables of drought events at each meteorological station in Northern Shaanxi were extracted by using run theory and copula function. The joint probability distribution and recurrence period were obtained by combining the duration and intensity of drought, and the relationship between drought characteristics and crop drought affected area was studied. The results show that (1) from 1960 to 2019, drought events mainly occurred in Northern Shaanxi with long duration and low severity, short duration and high severity, or short duration and low severity, among which the frequency of drought events that occurred in Yuyang and Baota districts was higher. The frequency of light drought and extreme drought was more in the south and less in the north, while the frequency of moderate drought and severe drought was more in the north and less in the south. (2) The optimal edge distribution of drought intensity and drought duration in Northern Shaanxi is generalized Pareto distribution, and the optimal fitting function is Frank copula function. The greater the duration and intensity of drought, the greater the cumulative probability and return period. (3) The actual recurrence interval and the theoretical recurrence interval of drought events in Northern Shaanxi were close, and the error was only 0.1–0.3a. The results of the joint return period can accurately reflect the actual situation, and this study can provide effective guidance for the prevention and management of agricultural dryland in Northern Shaanxi.


2010 ◽  
Vol 37-38 ◽  
pp. 1525-1528
Author(s):  
Wen Jun Xu ◽  
Hong Ming Yang ◽  
Ming Yong Lai ◽  
Shuang Wang

Based on Extreme Value Theory (EVT), the Generalized Pareto Distributions (GPDs) of meteorological variables wind speed and freezing precipitation is simulated. Considering the dependence of them, a joint probability distribution is calculated by the Copula function. Further more, the probability distributions of ice loads and wind loads on transmission lines are analyzed, and the failure probability of broken lines and collapsed towers under ice storms is calculated. The accuracy and validity of this analytical method is demonstrated with comparison between numerical results and the historical datas of Chen Zhou power transmission systems.


2018 ◽  
Vol 66 (3) ◽  
pp. 279-284
Author(s):  
Jinping Zhang ◽  
Jiayi Li ◽  
Xixi Shi

Abstract Based on the data series of the annual reference crop evapotranspiration (ET0) and the amount of irrigation water (IR) from 1970 to 2013 in the Luhun irrigation district, the joint probability distribution of ET0 and IR is established using the Gumbel-Hougaard copula function. Subsequently, the joint probability, the conditional joint probability, and the conditional return period of rich−poor encounter situations of ET0 and IR are analysed. The results show that: (1) For the joint probabilities of rich−poor encounter situations of ET0 and IR, the asynchronous encounter probability is slightly larger than the synchronous encounter probability. (2) When IR is in rich state or ET0 is in poor state, the conditional joint probability is larger, and the conditional return period is smaller. (3) For a certain design frequency of ET0, if the design frequency decreases, the conditional joint probability of the amount of irrigation water will decrease, therefore the encounter probability of them will decrease. (4) For a certain design frequency of the amount of irrigation water, if the design frequency decreases, the conditional joint probability of ET0 will increase, thus the encounter probability of them will increase.


2014 ◽  
Vol 62 (3) ◽  
pp. 218-225 ◽  
Author(s):  
Jinping Zhang ◽  
Zhihong Ding ◽  
Jinjun You

Abstract River runoff and sediment transport are two related random hydrologic variables. The traditional statistical analysis method usually requires those two variables to be linearly correlated, and also have an identical marginal distribution. Therefore, it is difficult to know exactly the characteristics of the runoff and sediment in reality. For this reason, copulas are applied to construct the joint probability distribution of runoff and sediment in this article. The risk of synchronous-asynchronous encounter probability of annual rich-poor runoff and sediment is also studied. At last, the characteristics of annual runoff and sediment with multi-time scales in its joint probability distribution space are simulated by empirical mode decomposition method. The results show that the copula function can simulate the joint probability distribution of runoff and sediment of Huaxia hydrological station in Weihe River well, and that such joint probability distribution has very complex change characteristics at time scales.


2010 ◽  
Vol 143-144 ◽  
pp. 414-418
Author(s):  
Shuang Wang ◽  
Hong Ming Yang ◽  
Shuang Zuo ◽  
Wen Jun Xu ◽  
Bin Zhang

Wind power at different locations may has a significant degree of correlation. A copula function, in this paper, is employed to characterize the Joint Probability Distribution (JPD) of wind power from multiple wind farms considering their correlation. Based on this, an optimal dispatch model of power system with multiple wind farms is proposed based on Chance Constrained Programming (CCP) to describe the randomness of wind power. And a new method named Sample Average Approximation (SAA) is used to transform the chance constrians in CCP. Finally the Particle Swarm Optimization (PSO) is used to solve the dispatch model. Simulation results show the affectivity of this model and method, which will be highly useful for optimal dispatch of power system with multiple wind farms.


2020 ◽  
pp. 1-24
Author(s):  
Pan Wang ◽  
Haihe Li ◽  
Xiaoyu Huang ◽  
Zheng Zhang ◽  
Sinan Xiao

Abstract For the reliability-oriented sensitivity analysis with respect to the parameters of input variables, by introducing the copula function to describe the joint probability distribution with dependent input variables, the reliability-oriented sensitivity can be decomposed into independent sensitivity and dependent sensitivity, which can be used to measure the influence of distribution parameters separately. Since the parameters of multivariate copula function are difficult to be estimated and not flexible in high dimension, the bivariate copulas are preferred in practice. Then the vine copula model is employed to transform the multivariate joint probability density function (PDF) into the product of multiple bivariate copulas and marginal PDF of all variables. Based on copula theory, the computation of reliability-oriented sensitivity with dependent variables can be transformed into the computation of a kernel function for each marginal PDF and the computation of a copula kernel function for each pair-copula PDF involved in the vine factorization. A general numerical approach is proposed to compute the separate sensitivity. Then, some numerical examples and engineering applications are employed to validate the rationality of the proposed method.


Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2223
Author(s):  
Ming Zhong ◽  
Jiao Wang ◽  
Tao Jiang ◽  
Zhijun Huang ◽  
Xiaohong Chen ◽  
...  

Flash flooding is a phenomenon characterized by multiple variables. Few studies have focused on the extracted variables involved in flash flood risk and the joint probability distribution of the extracted variables. In this paper, a novel methodology that integrates the Apriori algorithm and copula function is presented and used for a flood risk analysis of Arizona in the United States. Due to the various rainfall indices affecting the flash flood risk, when performing the Apriori algorithm, the accumulated 3-h rainfall and accumulated 6-h rainfall were extracted as the most fitting rainfall indices. After comparing the performance of copulas, the Frank copula was found to exhibit the best fit for the flash flood hazard; thus, it was used for a bivariate joint probability analysis. The bivariate joint distribution functions of P–Q, PA–Q, PB–Q, and D–Q were established, and the results showed an increasing trend of flash flood risk with increases in the rainfall indices and peak flow; however, the risk displayed the least significant relation with the duration of the flash flood. These results are expected to be useful for risk analysis and decision making regarding flash floods.


2021 ◽  
Author(s):  
Manqiu Hao ◽  
Cheng Gao ◽  
Jian Chen

Abstract Taking the Taihu Lake Basin as an example, in this study, the characteristics of the rainfall factors in the study area were analyzed using daily rainfall data from 1955 to 2018. Three factors, i.e., the contribution rate of the rainfall in the flood season, the rainfall frequency, and the maximum daily rainfall, were selected to determine the optimal probability distribution function for each single factor. Furthermore, the root mean square error (RMSE) goodness of fit test was used to determine the optimal copula function for the three-dimensional joint probability distribution characteristics of the rainfall factors. The research results show that the three-dimensional copula joint probability method contains much more information than the results of the single variable probability calculation. The copula function can be used to analyze the multi-dimensional joint distribution of rainfall factors, which can fill the gap in research on multiple rainfall factors.


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