Hydroclimatic aggregate drought index (HADI): a new approach for identification and categorization of drought in cold climate regions

Bazrkar, Mohammad Hadi; Zhang, Jianglong; Chu, Xuefeng

doi:10.1007/s00477-020-01870-5

Cited by 9 publications

(9 citation statements)

References 35 publications

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“…The variable thresholds for HADI and SHADI were close. This result was in accordance with the finding by Bazrkar & Chu (2021), where the output from a grid-based hydrologic model (GHM) (Chu et al 2019) in a different study period (2003)(2004)(2005)(2006)(2007) was used. The clustering method was used to derive these variable thresholds based on the probabilities of occurrences of those values considering both spatial and temporal distributions of droughts.…”

Section: Selection Of the Best Categorization Methodssupporting

confidence: 91%

“…That drought was referred to as a snow drought since the RRB experienced the lowest precipitation and the highest temperature in the cold seasons in that dry decade. However, the 1930s drought known as the Great Drought was due to low precipitation in the warm seasons (Bazrkar & Chu 2021). Therefore, different drought indices with the capabilities of addressing different types of drought are required.…”

Section: Study Areamentioning

confidence: 99%

“…Following this suggestion, 10 drought indices were used to evaluate the performance of CBS-SVR. The multivariate HADI and SHADIBazrkar & Chu 2021) distinguished drought and snow drought in cold climate…”

mentioning

confidence: 99%

“…The R-mode correlation-based principal component analysis (PCA) was employed to aggregate rainfall (RF), snowmelt (SM), surface runoff (R), and soil water storage (SWS) in the calculation of HADI. Precipitation and snowpack (SP) were used, instead of rainfall and snowmelt in HADI, to calculate SHADI to enhance the capability of identifying snow drought(Bazrkar & Chu 2021). Two bivariate standardized drought indices were also used.…”

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confidence: 99%

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Development of category-based scoring support vector regression (CBS-SVR) for drought prediction

Bazrkar

Chu

2022

Journal of Hydroinformatics

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Using the existing measures for training numerical (non-categorical) prediction models can cause misclassification of droughts. Thus, developing a drought category-based measure is critical. Moreover, the existing fixed drought category thresholds need to be improved. The objective of this research is to develop a category-based scoring support vector regression (CBS-SVR) model based on an improved drought categorization method to overcome misclassification in drought prediction. To derive variable threshold levels for drought categorization, K-means (KM) and Gaussian mixture (GM) clustering are compared with the traditional drought categorization. For drought prediction, CBS-SVR is performed by using the best categorization method. The new drought model was applied to the Red River of the North Basin (RRB) in the USA. In the model training and testing, precipitation, temperature, and actual evapotranspiration were selected as the predictors, and the target variables consisted of multivariate drought indices, as well as bivariate and univariate standardized drought indices. Results indicated that the drought categorization method, variable threshold levels, and the type of drought index were the major factors that influenced the accuracy of drought prediction. The CBS-SVR outperformed the support vector classification and traditional SVR by avoiding overfitting and miscategorization in drought prediction.

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Section: Selection Of the Best Categorization Methodssupporting

confidence: 91%

Section: Study Areamentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Development of category-based scoring support vector regression (CBS-SVR) for drought prediction

Bazrkar

Chu

2022

Journal of Hydroinformatics

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“…All these indices have good statistical performance for certain types of drought: meteorological, hydrological or hydrogeological. Sometimes, the results obtained by using one index were not validated in the values produced by others, which lead to the development of more complex indices, in order to account for the multi-scalar nature of drought: Hao and AghaKouchak (2013), developed a multivariate standardized drought index (MSDI), Waseem et al (2015) developed a new composite drought index for multivariate drought assessment, Liu et al (2016) developed a copula-based joint streamflow drought index (JSDI), Hadi et al (2020) created a new approach for the identification and categorization of drought in cold climate regions, the hydroclimatic aggregate drought index (HADI), and Li et al (2021), constructed a combined drought index based on bivariate joint distribution (BCDIbcf).…”

Section: Introductionmentioning

confidence: 99%

Multi-scale approach for different type of drought in temperate climatic conditions

2021

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Drought with its occurrence and manifestations at all levels of the natural components, yields both direct and indirect negative effects, on the ecological systems, water resources, social, as well as economic aspects of life. Therefore, any analysis that concerns this phenomenon, must be carried out at a multi-scalar level, addressing all manifestation levels (meteorological, hydrological, and hydrogeological drought). Standardized evaluation indices (for precipitation-SPI, evaporation-, -SPEI, streamflow-SDI and groundwater-SGI) have been used to analyze the evolution of the drought phenomena in Eastern Romania, for 1, 3, 6 and 12 months’ time-scales, applied to seven groundwater bodies. The results of the analysis complement the observations concerning the evolution of meteorological drought (using SPI and SPEI) in the East European region, by highlighting the drought sequences of the last two decades of the last century. Those are accompanied by the meteorological drought sequences which occurred on extensive areas, starting from 2007, until present, with direct effects in river discharge and increases in groundwater level depths. The Bravais–Pearson correlation coefficient shows a close connection between meteorological and hydrological drought (r ~ 0.45 to 0.68) and between hydrological and groundwater drought (r ~ 0.42 to 0.74) for wells with piezometric level under 5 m depth. In the larger context of climate scenarios which envision an increase in air temperature, and a decrease in the atmospheric hydrological input, the increase in the drought frequency is obvious, with direct effects on all-natural components that are dependent on the hydrological resources.

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Spatiotemporal variation of drought in Iraq for shared socioeconomic pathways

Hamed

Sammen

Nashwan

et al. 2022

Stoch Environ Res Risk Assess

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Hydroclimatic aggregate drought index (HADI): a new approach for identification and categorization of drought in cold climate regions

Cited by 9 publications

References 35 publications

Development of category-based scoring support vector regression (CBS-SVR) for drought prediction

Development of category-based scoring support vector regression (CBS-SVR) for drought prediction

Multi-scale approach for different type of drought in temperate climatic conditions

Spatiotemporal variation of drought in Iraq for shared socioeconomic pathways

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