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This study investigates the sensitivity and uncertainty of hydrological droughts frequencies and severity in the Weihe Basin, China during 1960-2012, by using six commonly used univariate probability distributions and three Archimedean copulas to fit the marginal and joint distributions of drought characteristics. The Anderson-Darling method is used for testing the goodness-of-fit of the univariate model, and the Akaike information criterion (AIC) is applied to select the best distribution and copula functions. The results demonstrate that there is a very strong correlation between drought duration and drought severity in three stations. The drought return period varies depending on the selected marginal distributions and copula functions and, with an increase of the return period, the differences become larger. In addition, the estimated return periods (both co-occurrence and joint) from the best-fitted copulas are the closet to those from empirical distribution. Therefore, it is critical to select the appropriate marginal distribution and copula function to model the hydrological drought frequency and severity. The results of this study can not only help drought investigation to select a suitable probability distribution and copulas function, but are also useful for regional water resource management. However, a few limitations remain in this study, such as the assumption of stationary of runoff series.

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“…In this study, the return period of droughts can be defined by drought duration or drought severity as [30]:…”

Section: Return Period Of Droughtsmentioning

confidence: 99%

Uncertainty of Hydrological Drought Characteristics with Copula Functions and Probability Distributions: A Case Study of Weihe River, China

Zhao

Lü

et al. 2017

Water

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“…In fact, while the 3-and 6-month SPI describe droughts that affect plant life and farming, the 12-and 24-month SPI influence the way how water supplies/reserves are managed [52,53]. Angelidis et al [54] offered a meticulous description of the method to compute the SPI.…”

Section: Standardized Precipitation Indexmentioning

confidence: 99%

SPI Trend Analysis of New Zealand Applying the ITA Technique

Caloiero

2018

Geosciences

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Abstract:A natural temporary imbalance of water availability, consisting of persistent lower-than-average or higher-than-average precipitation, can cause extreme dry and wet conditions that adversely impact agricultural yields, water resources, infrastructure, and human systems. In this study, dry and wet periods in New Zealand were expressed using the Standardized Precipitation Index (SPI). First, both the short term (3 and 6 months) and the long term (12 and 24 months) SPI were estimated, and then, possible trends in the SPI values were detected by means of a new graphical technique, the Innovative Trend Analysis (ITA), which allows the trend identification of the low, medium, and high values of a series. Results show that, in every area currently subject to drought, an increase in this phenomenon can be expected. Specifically, the results of this paper highlight that agricultural regions on the eastern side of the South Island, as well as the north-eastern regions of the North Island, are the most consistently vulnerable areas. In fact, in these regions, the trend analysis mainly showed a general reduction in all the values of the SPI: that is, a tendency toward heavier droughts and weaker wet periods.

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“…Many researchers have used the Standardized Precipitation Index (SPI) to investigate, predict and evaluate the frequency and duration of droughts [12][13][14][15][16][17][18][19][20][21]. The aim of this study is to investigate climate change impacts on drought in Karoon3 watershed in the future using SPI and different scenarios of AOGCM by an stochastic weather generator model known as LARS-WG.…”

Section: Introductionmentioning

confidence: 99%

Climate change impact on meteorological droughts in watershed scale (case study: southwestern Iran)

Shahbazi

2014

IJET

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Drought is one of the major natural disasters in the world which has a lot of social and economic impacts. There are various factors that affect climate changes; the investigation of this incident is also sensitive. Climate scenarios of future climate change studies and investigation of efficient methods for investigating these events on drought should be assumed. This study intends to investigate climate change impacts on drought in Karoon3 watershed in the future. For this purpose, the atmospheric general circulation models (GCM) data under Intergovernmental Panel on Climate Change (IPCC) scenarios should be investigated. In this study, watershed drought under climate change impacts will be simulated in future periods (2011 to 2099). In this research standard precipitation index (SPI) was calculated using mean monthly precipitation data in Karoon3 watershed. SPI was calculated in 6, 12 and 24 months periods. Statistical analysis on daily precipitation and minimum and maximum daily temperature was performed. To determine the feasibility of future periods meteorological data production of LRAS-WG5 model, calibration and verification was performed for the base year . Meteorological data simulation for future periods under General Circulation Models and climate change IPCC scenarios was performed and then the drought status using SPI under climate change effects analyzed. Results showed that differences between monthly maximum and minimum temperature will decrease under climate change and spring precipitation shall increase while summer and autumn rainfall shall decrease. The most increase of precipitation will take place in winter and in December. Normal and wet SPI category is more frequent in B1 and A2 emissions scenarios than A1B. Wet years increases in the study area during 2011-2030 period and the more continuous drought years gradually increases during 2046-2065 period, the more severe and frequent drought will occur during the 2080-2099 period.

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Cited by 305 publications

References 8 publications

Uncertainty of Hydrological Drought Characteristics with Copula Functions and Probability Distributions: A Case Study of Weihe River, China

Uncertainty of Hydrological Drought Characteristics with Copula Functions and Probability Distributions: A Case Study of Weihe River, China

SPI Trend Analysis of New Zealand Applying the ITA Technique

Climate change impact on meteorological droughts in watershed scale (case study: southwestern Iran)

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