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Bayesian network based procedure for regional drought monitoring: The Seasonally Combinative Regional Drought
Zulfiqar Ali1, Ijaz Hussain2, Marco Andreas Grzegorczyk3
1School of Statistics, Minhaj University, Lahore, 54000, Pakistan; Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan.
Abstract:
Drought is a complex natural hazard. It occurs due to a prolonged period of deficient in rainfall amount in a certain region. Unlike other natural hazards, drought hazard has a recurrent occurrence. Therefore, comprehensive drought monitoring is essential for regional climate control and water management authorities. In this paper, we have proposed a new drought indicator: the Seasonally Combinative Regional Drought Indicator (SCRDI). The SCRDI integrates Bayesian networking theory with Standardized Precipitation Temperature Index (SPTI) at varying gauge stations in various month/seasons. Application of SCRDI is based on five gauging stations of Northern Area of Pakistan. We have found that the proposed indicator accounts the effect of climate variation within a specified territory, accurately characterizes drought by capturing seasonal dependencies in geospatial variation scenario, and reduces the large/complex data for future drought monitoring. In summary, the proposed indicator can be used for comprehensive characterization and assessment of drought at a certain region.
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