TY - JOUR
T1 - Proposing a new framework for analyzing the severity of meteorological drought
AU - Niaz, Rizwan
AU - Almazah, Mohammed M.A.
AU - Al-Rezami, A. Y.
AU - Ali, Zulfiqar
AU - Hussain, Ijaz
AU - Omer, Talha
N1 - Publisher Copyright:
© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2023
Y1 - 2023
N2 - The quantitative description of meteorological drought from various geographical locations and indicators is crucial for early drought warning to avoid its negative impacts. Therefore, the current study proposes a new framework to comprehensively accumulate spatial and temporal information for meteorological drought from various stations and drought indicators (indices). The proposed framework is based on two major components such as the Monthly-based Monte Carlo Feature Selection (MMCFS,) and Monthly-based Joint Index Weights (MJIW). Besides, three commonly used SDI are jointly assessed to quantify drought for selected geographical locations. Moreover, the current study uses the monthly data from six meteorological stations in the northern region for 47 years (1971-2017) for calculating SDI values. The outcomes of the current research explicitly accumulate regional spatiotemporal information for meteorological drought. In addition, results may serve as an early warning to the effective management of water resources to avoid negative drought impacts in Pakistan.
AB - The quantitative description of meteorological drought from various geographical locations and indicators is crucial for early drought warning to avoid its negative impacts. Therefore, the current study proposes a new framework to comprehensively accumulate spatial and temporal information for meteorological drought from various stations and drought indicators (indices). The proposed framework is based on two major components such as the Monthly-based Monte Carlo Feature Selection (MMCFS,) and Monthly-based Joint Index Weights (MJIW). Besides, three commonly used SDI are jointly assessed to quantify drought for selected geographical locations. Moreover, the current study uses the monthly data from six meteorological stations in the northern region for 47 years (1971-2017) for calculating SDI values. The outcomes of the current research explicitly accumulate regional spatiotemporal information for meteorological drought. In addition, results may serve as an early warning to the effective management of water resources to avoid negative drought impacts in Pakistan.
KW - homogeneous region
KW - Monte Carlo feature selection
KW - Spatio-temporal
KW - standardized drought index
KW - steady-state probabilities
UR - https://www.scopus.com/pages/publications/85153088752
U2 - 10.1080/10106049.2023.2197512
DO - 10.1080/10106049.2023.2197512
M3 - Article
AN - SCOPUS:85153088752
SN - 1010-6049
VL - 38
JO - Geocarto International
JF - Geocarto International
IS - 1
M1 - 2197512
ER -