Spatiotemporal and joint probability behavior of temperature extremes over the Himalayan region under changing climate

Goswami, Uttam; Bhargav, K.; Hazra, Budhaditya; Goyal, Manish Kumar

doi:10.1007/s00704-017-2288-1

Cited by 20 publications

(6 citation statements)

References 46 publications

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“…The present study evaluated various members of Archimedean Copula family and selected the best members (used in the present study, mentioned later) to apply in the construction of joint probability distributions of rainfall with soil moisture and that of rainfall with run‐off for each of the sub‐basins. Some of the commonly used Archimedean Copula family members are Clayton, Frank, Gumbel, Ali‐Mikhail‐Haq and Joe (Ayantobo et al, 2019; Azam et al, 2018; Fan et al, 2017; Goswami et al, 2018; Reddy & Ganguly, 2011). The criteria of best Copula correspond to a member, which is characterized by the lowest values of Akaike's information criterion (AIC; Akaike, 1974; Maier, 2013; Sadegh et al, 2017; Wang & Liu, 2006).…”

Section: Methodsmentioning

confidence: 99%

Multivariate drought analysis for the temperature homogeneous regions of India: Lessons from the Gomati River basin

Bhatt

Mall

Raju

et al. 2022

Meteorological Applications

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Droughts inflict significant loss on agricultural economies. Gomati River basin, the area of the present study, is located within the Ganga River floodplains, which approximately coincide with the north central temperature homogeneous region (NCTHR) of India. Gomati basin is a non-perennial one supporting water intensive agricultural crops. To ascertain the occurrence of droughts (if any) from 1986 to 2015 within Gomati River basin, in terms of inter-dependencies of drought causing variables through study of multivariate drought indices, is the main objective of the present study. Soil Water Assessment Tool (SWAT) was used in combination with the Copula approach to construct multivariate standardized drought indices (MSDIs) for drought onset detection through simulation in the face of data scarcity. Although MSDI based assessment of the basin as a whole did not detect any droughts, in the upper basin, MSDIs indicated the possibilities of impending agricultural droughts marked by their consistent variability around near-normal conditions. This methodology can be used to detect drought situations in data scarce non-perennial river basins within the Ganga River floodplains including the NCTHR of India.

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Section: Methodsmentioning

confidence: 99%

Multivariate drought analysis for the temperature homogeneous regions of India: Lessons from the Gomati River basin

Bhatt

Mall

Raju

et al. 2022

Meteorological Applications

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“…2.6 | Copula-based joint return period A copula-based joint return period can be used to overcome under-or over-estimates of risk related to extreme events such as floods and droughts. The return period is described as the average interval between successive events (Liu et al, 2015;Uttam et al, 2018). Assuming that x and y are the extreme value thresholds of climatic parameters with the copula function (C (F X (X), F Y (Y)), the joint return period of the two variables, when both the X and Y variables exceed a certain value (…”

Section: Copula-based Conditional Probabilitymentioning

confidence: 99%

“…Recently, copula functions have been used for multivariate analysis of annual peak floods, flood, and drought return periods, and similar climate-related extremes (Bracken, Holman, Rajagopalan, & Moradkhani, 2018;Chen, Zhang, Xiao, Singh, & Zhang, 2016;J. Li, Zhang, Chen, & Singh, 2015;Mesbahzadeh et al, 2019;Mirakbari et al, 2010;Uttam, Goswami, Bhargav, Hazra, & Goyal, 2018;Q. Zhang, Li, Singh, & Xu, 2013).…”

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confidence: 99%

“…However, few studies have been carried out on the joint frequency analysis of climate parameters and their extreme values under climate change conditions. For instance, Uttam et al (2018) investigated the joint behavior of extreme precipitation by means of climate change indices based on the bivariate copulas in the present and future periods. Joint modeling of temperature and precipitation parameters can help clarify the risk of phenomena such as flood and drought in the future climate change.…”

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confidence: 99%

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Observed and projected trends of extreme precipitation and maximum temperature during 1992–2100 in Isfahan province, Iran using REMO model and copula theory

Mirakbari

Mesbahzadeh

Sardoo

et al. 2020

Natural Resource Modeling

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Meteorological extreme events have a major impact on water resources, economic development, and ecosystem health. In this study, maximum precipitation and maximum temperature indices were derived for Isfahan province, in central Iran, over the historical and future (2020-2100) periods. Precipitation and maximum temperature data from the REMO model under RCP4.5 scenario were used to investigate changes in extreme values over the future period. The results showed that extreme precipitation in the historical and future periods has respectively a decreasing and increasing trend. Based on the extreme indices, temperature in the study area has a significant increasing trend in the baseline and future period. Various combinations of extreme precipitation indicators were created for joint modeling by copula theory. Copula modeling for the three weather stations for which REMO had satisfactory performance in simulating extremes over the historic period showed that the average return period of extreme precipitation combinations will be reduced in the future period compared to the historical period at Daran and Shahreza, while the average return period of combinations will have both increasing and decreasing trends at Naeen. Recommendations for Resource Managers• Knowing information about the probability of occurrence of extreme precipitation with a certain value that exceeds a certain threshold will help planning for water resource systems under drought conditions and future increasing temperature.• The joint return period of extreme precipitation can help to know the return period of extreme events such as floods and droughts.• The findings of this study are important to assess the prediction of climate extreme. Also, these results can be useful to provide the appropriate strategies for water resources managers in drought conditions under future increasing temperature. K E Y W O R D S climate change, Copula, extreme precipitation and maximum temperature indices, REMO

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“…Copulas [23] are known as an effective means for describing the dependence between random variables, thus expected to be suitable for studying competition or dependence among multi-objectives. Recently, different copulas have been employed for the multivariate analysis of spatiotemporal change in probabilistic forecasting of seasonal droughts [24], multivariate real-time droughts assessment [25], joint return periods of precipitation and temperature extremes [26], flood frequency analysis [27,28], risk analysis [29], energy environmental optimization [30][31][32], stochastic hydrological simulation [33] and so on, while its application in the research field of multi-objective competition relationship has not yet emerged. A key feature of copula is to characterize the dependency structure of two or more variables, either cross-correlation or auto-correlation [34], making it a promising method for the multi-objective questions.…”

Section: Introductionmentioning

confidence: 99%

Copula-Based Research on the Multi-Objective Competition Mechanism in Cascade Reservoirs Optimal Operation

Zhao

Huang

et al. 2019

Water

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Water resources systems are often characterized by multiple objectives. Typically, there is no single optimal solution which can simultaneously satisfy all the objectives but rather a set of technologically efficient non-inferior or Pareto optimal solutions exists. Another point regarding multi-objective optimization is that interdependence and contradictions are common among one or more objectives. Therefore, understanding the competition mechanism of the multiple objectives plays a significant role in achieving an optimal solution. This study examines cascade reservoirs in the Heihe River Basin of China, with a focus on exploring the multi-objective competition mechanism among irrigation water shortage, ecological water shortage and the power generation of cascade hydropower stations. Our results can be summarized as follows: (1) the three-dimensional and two-dimensional spatial distributions of a Pareto set reveal that these three objectives, that is, irrigation water shortage, ecological water shortage and power generation of cascade hydropower stations cannot reach the theoretical optimal solution at the same time, implying the existence of mutual restrictions; (2) to avoid subjectivity in choosing limited representative solutions from the Pareto set, the long series of non-inferior solutions are adopted to study the competition mechanism. The premise of sufficient optimization suggests a macro-rule of ‘one falls and another rises,’ that is, when one objective value is inferior, the other two objectives show stronger and superior correlation; (3) the joint copula function of two variables is firstly employed to explore the multi-objective competition mechanism in this study. It is found that the competition between power generation and the other objectives is minimal. Furthermore, the recommended annual average water shortage are 1492 × 104 m3 for irrigation and 4951 × 104 m3 for ecological, respectively. This study is expected to provide a foundation for selective preference of a Pareto set and insights for other multi-objective research.

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Spatiotemporal and joint probability behavior of temperature extremes over the Himalayan region under changing climate

Cited by 20 publications

References 46 publications

Multivariate drought analysis for the temperature homogeneous regions of India: Lessons from the Gomati River basin

Multivariate drought analysis for the temperature homogeneous regions of India: Lessons from the Gomati River basin

Observed and projected trends of extreme precipitation and maximum temperature during 1992–2100 in Isfahan province, Iran using REMO model and copula theory

Copula-Based Research on the Multi-Objective Competition Mechanism in Cascade Reservoirs Optimal Operation

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