The Spatiotemporal Weighted Efficient Drought Index-A new generalized procedure of regional drought indicator

Ali，Farman1; Riaz，Saba2; Ali，Zulfiqar3; Qamar，Sadia4; Li，Bing Zhao1; Khan，Muhammad Asif5

2022-07-01

10.1002/eco.2454

Ecohydrology   Impact Factor & Quartile

1936-0584

1936-0592

Drought is a multifaceted climate phenomenon. Due to recent climate warming, the risk of drought has increased. Regional drought management requires accurate regional drought characterization to prepare early warning drought mitigation policies. Therefore, a more flexible and efficient procedure is necessary for characterizing drought at a regional level. This study provides a new spatiotemporal weighting scheme for integrating precipitation data from various meteorological stations located in a specific region. Consequently, this article presents a new generalized regional drought indicator-The Spatiotemporal Weighted Efficient Drought Index (STWEDI). The methodology of STWEDI consists of two stages: (1) The first stage combines the meteorological data of various stations located in a certain region under the proposed weighting scheme, and (2) the second stage standardizes the cumulative distribution function (CDF) of mixture probability models. In application, this research estimated the time series data of STWEDI of seven regions containing a varying number of meteorological stations. To assess the performance of STWEDI, we compared the time series data of STWEDI with the most commonly used Standardized Precipitation Index (SPI) using the Pearson correlation. Results show that STWEDI is strongly correlated with individual SPIs in all the clusters and scales. Moreover, we found that STWEDI is strongly associated with SPI at all time scales. These statistical measures show that STWEDI is the more effective drought indicator for regional drought monitoring.

climate warming drought mixture probability models Standardized Precipitation Index

SCI ; EI

English

Others

National Natural Science Foundation of China program[41801339] ; Natural Science Foundation of Hubei Province, China[2020CFB615]

Environmental Sciences & Ecology ; Water Resources

Ecology ; Environmental Sciences ; Water Resources

WOS:000827699300001

WILEY

20222912378029

Climate change ; Climate models ; Correlation methods ; Distribution functions ; Drought ; Time series

Meteorology:443 ; Atmospheric Properties:443.1 ; Precipitation:443.3 ; Water Resources:444 ; Mathematics:921 ; Probability Theory:922.1 ; Mathematical Statistics:922.2

2-s2.0-85134221889

Web of Science

1.School of Mathematics and Statistics,Beijing Institute of Technology,Beijing,China
2.Department of Computer Science,SZABIST Islamabad Campus,Islamabad,Pakistan
3.College of Statistical and Actuarial Sciences,University of the Punjab: Lahore,Pk,Lahore,Pakistan
4.Department of Statistics,University of Sargodha,Sargodha,Pakistan
5.Earth System and Global Change Lab,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,China

Ali，Farman,Riaz，Saba,Ali，Zulfiqar,et al. The Spatiotemporal Weighted Efficient Drought Index-A new generalized procedure of regional drought indicator[J]. Ecohydrology,2022.

Ali，Farman,Riaz，Saba,Ali，Zulfiqar,Qamar，Sadia,Li，Bing Zhao,&Khan，Muhammad Asif.(2022).The Spatiotemporal Weighted Efficient Drought Index-A new generalized procedure of regional drought indicator.Ecohydrology.

Ali，Farman,et al."The Spatiotemporal Weighted Efficient Drought Index-A new generalized procedure of regional drought indicator".Ecohydrology (2022).