Multi-factor joint return period of rainstorms and its agricultural risk analysis in Liaoning Province, China

Feng, Yu; Li, Ying; Zhang, Zhiru; Gong, Shiyu; Liu, Meijiao; Peng, Fei

doi:10.1080/19475705.2019.1660727

Cited by 9 publications

(3 citation statements)

References 22 publications

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“…Copula function is used for joint analysis of several drought characteristic variables with correlation. Copula function has been widely used in the study of drought disaster [24], flood disaster [25], rainstorm disaster [26] and other meteorological disasters. Its theoretical basis was first proposed by Sklar [27], which can well describe the correlation between two variables.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

Wang

Rong

et al. 2021

Water

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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.

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Section: Introductionmentioning

confidence: 99%

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

Wang

Rong

et al. 2021

Water

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“…Under the influence of global climate warming and human activities, the water cycle of the ecosystem speeds up and its stability decreases, leading to a sharp increase in the occurrence frequency of abnormal precipitation disasters, such as rainstorm disaster, drought disaster, flood disaster and snow disaster [1][2][3][4]. Dryness/wetness are the most common natural disasters in the world, which occur frequently, cause great losses and affect a wide range of areas [5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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

Zhang

Rong

et al. 2021

Water

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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.

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“…The effects of different tillage methods on crop water consumption and yield has been discussed, but there have been few studies on yield prediction ( Yu et al, 2020 ). The Standardized Precipitation Evapotranspiration Index (SPEI), one of the most commonly-used agricultural drought indices, not only considers precipitation, but also the impact of temperature on crop growth ( Feng et al, 2019 ; Shaukat et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Effects of fallow tillage on winter wheat yield and predictions under different precipitation types

Feng¹,

Lin²,

Yu³

et al. 2021

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In northern China, precipitation that is primarily concentrated during the fallow period is insufficient for the growth stage, creates a moisture shortage, and leads to low, unstable yields. Yield prediction in the early growth stages significantly informs field management decisions for winter wheat (Triticum aestivum L.). A 10-year field experiment carried out in the Loess Plateau area tested how three tillage practices (deep ploughing (DP), subsoiling (SS), and no tillage (NT)) influenced cultivation and yield across different fallow periods. The experiment used the random forest (RF) algorithm to construct a prediction model of yields and yield components. Our results revealed that tillage during the fallow period was more effective than NT in improving yield in dryland wheat. Under drought condition, DP during the fallow period achieved a higher yield than SS, especially in drought years; DP was 16% higher than SS. RF was deemed fit for yield prediction across different precipitation years. An RF model was developed using meteorological factors for fixed variables and soil water storage after tillage during a fallow period for a control variable. Small error values existed in the prediction yield, spike number, and grains number per spike. Additionally, the relative error of crop yield under fallow tillage (5.24%) was smaller than that of NT (6.49%). The prediction error of relative meteorological yield was minimum and optimal, indicating that the model is suitable to explain the influence of meteorological factors on yield.

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Multi-factor joint return period of rainstorms and its agricultural risk analysis in Liaoning Province, China

Cited by 9 publications

References 22 publications

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

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

Effects of fallow tillage on winter wheat yield and predictions under different precipitation types

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