TY - JOUR
T1 - A Probabilistic Weighted Joint Aggregative Drought Index (PWJADI) criterion for drought monitoring systems
AU - Ali, Zulfiqar
AU - Hussain, Ijaz
AU - Faisal, Muhammad
AU - Almanjahie, Ibrahim M.
AU - Ahmad, Ishfaq
AU - Khan, Dost Muhammad
AU - Grzegorczyk, Marco
AU - Qamar, Saida
N1 - Funding Information:
Authors are very grateful to the Deanship of Scientific Research at King Khalid University, Kingdom of Saudi Arabia for their administrative and technical support and for funding this work through research groups program under the project number RGP-1/103/40.
Publisher Copyright:
© 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Drought is a complex natural hazard. Its several adverse impacts are prevailing in almost all climatic zones around the world. In this regards, drought monitoring and forecasting play a vital role in making drought mitigation policies. Therefore, several drought monitoring tools based on probabilistic models had been developed for precise and accurate inferences of drought severity and its effects. However, risk of inaccurate determination of drought classes always exists in probabilistic models. To overcome this issue, we proposed a new system based Probabilistic Weighted Joint Aggregative Drought Index (PWJADI) criterion for three multi-scalar drought indices, namely Standardized Precipitation Index (SPI), Standardized Precipitation Temperature Index (SPTI), and Standardized Precipitation Evapotranspiration Index (SPEI) at one-month time scale. By the basic assumption of the Markov chain, the PWJADI is based on the temporal switched weights that are propagated from the transition probability matrix of each temporal classification of drought index. Application of the proposed method is made for three meteorological stations of Pakistan. We found that our proposed model has ability to restructure the drought classes by capturing and bending the information from the historical behaviour of each drought class. Consequently, to make accurate and precise drought mitigation policies, the proposed method may integrate into effective drought monitoring systems.
AB - Drought is a complex natural hazard. Its several adverse impacts are prevailing in almost all climatic zones around the world. In this regards, drought monitoring and forecasting play a vital role in making drought mitigation policies. Therefore, several drought monitoring tools based on probabilistic models had been developed for precise and accurate inferences of drought severity and its effects. However, risk of inaccurate determination of drought classes always exists in probabilistic models. To overcome this issue, we proposed a new system based Probabilistic Weighted Joint Aggregative Drought Index (PWJADI) criterion for three multi-scalar drought indices, namely Standardized Precipitation Index (SPI), Standardized Precipitation Temperature Index (SPTI), and Standardized Precipitation Evapotranspiration Index (SPEI) at one-month time scale. By the basic assumption of the Markov chain, the PWJADI is based on the temporal switched weights that are propagated from the transition probability matrix of each temporal classification of drought index. Application of the proposed method is made for three meteorological stations of Pakistan. We found that our proposed model has ability to restructure the drought classes by capturing and bending the information from the historical behaviour of each drought class. Consequently, to make accurate and precise drought mitigation policies, the proposed method may integrate into effective drought monitoring systems.
KW - drought classifications
KW - drought index
KW - drought monitoring systems
KW - Markov chain
UR - http://www.scopus.com/inward/record.url?scp=85077685131&partnerID=8YFLogxK
U2 - 10.1080/16000870.2019.1588584
DO - 10.1080/16000870.2019.1588584
M3 - Article
AN - SCOPUS:85077685131
SN - 0280-6495
VL - 71
JO - Tellus, Series A: Dynamic Meteorology and Oceanography
JF - Tellus, Series A: Dynamic Meteorology and Oceanography
IS - 1
M1 - 1588584
ER -