Reduction of Errors in Hydrological Drought Monitoring – A Novel Statistical Framework for Spatio-Temporal Assessment of Drought

Zulfiqar Ali (), Asad Ellahi (), Ijaz Hussain (), Amna Nazeer (), Sadia Qamar (), Guangheng Ni () and Muhammad Faisal ()
Additional contact information
Zulfiqar Ali: Tsinghua University
Asad Ellahi: Quaid-I-Azam University
Ijaz Hussain: Quaid-I-Azam University
Amna Nazeer: COMSATS University Islamabad
Sadia Qamar: University of Sargodha
Guangheng Ni: Tsinghua University
Muhammad Faisal: University of Bradford

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2021, vol. 35, issue 13, No 5, 4363-4380

Abstract: Abstract Continuous and accurate drought monitoring has an important role in early warning drought mitigation policies. This study aims to provide an accurate standardized drought monitoring indicator by enhancing the representative characteristics of precipitation data using advanced statistical methods. We proposed a two-phase statistical procedure index – the Regional Multi-Component Gaussian Hydrological Drought Assessment (RMcGHDA) – for accurate drought monitoring under a multi-auxiliary variable-based sampling estimator and K-Component Gaussian Mixture Distribution (CGMD) model. The first phase of our proposed method increases the regional representativeness of the data under Spatio-temporal settings and the second phase describes the use of the Twelve-Component Gaussian Mixture Distribution (CGMD) model in the standardization stage of SDIs. We applied the proposed framework to 52 meteorological stations in Pakistan and compared the RMcGHDA performance with existing methods using Pearson correlation (r) and spatial patterns of various drought categories. We found significant differences between RMcGHDA and existing methods (i.e., Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)) for drought assessment. By the rationale of the data improvement under-sampling estimator and the use of multi-component Gaussian function, these differences indicate that RMcGHDA provides a practical and accurate way for drought assessment.

Keywords: Climate change; Drought; Auxiliary information; Pearson correlation (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11269-021-02952-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:35:y:2021:i:13:d:10.1007_s11269-021-02952-x

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-021-02952-x

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().