Projected Changes of Future Extreme Drought Events under Numerous Drought Indices in the Heilongjiang Province of China

Muhammad Imran Khan (), Dong Liu (), Qiang Fu (), Qaisar Saddique (), Muhammad Abrar Faiz (), Tianxiao Li (), Muhammad Uzair Qamar (), Song Cui () and Chen Cheng ()
Additional contact information
Muhammad Imran Khan: Northeast Agricultural University
Dong Liu: Northeast Agricultural University
Qiang Fu: Northeast Agricultural University
Qaisar Saddique: Northwest A&F University
Muhammad Abrar Faiz: Northeast Agricultural University
Tianxiao Li: Northeast Agricultural University
Muhammad Uzair Qamar: University of Agriculture
Song Cui: Northeast Agricultural University
Chen Cheng: Northeast Agricultural University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2017, vol. 31, issue 12, No 14, 3937 pages

Abstract: Abstract Effective drought prediction methods are essential for the mitigation of adverse effects of severe drought events. This study utilizes the Reconnaissance Drought Index, Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index to assess the occurrence of future drought events in the study area of the Heilongjiang province of China over a period of 2016–2099. The drought indices were computed from the meteorological data (temperature, precipitation) generated by the global climate model (HadCM3A2). Moreover, Mann-Kendall trend test was applied for the assessment of future climatic trends and detecting probable differences in the behaviour of various drought indices. Drought forecasting periods has been divided into three categories: the early phase (1916–2030), middle phase (2031–2060) and late phase (2061–2099). The occurrence of future droughts is also ranked according to their intensity (mild, moderate, severe and extreme drought). Based on the drought results, more number of drought events are expected to occur during 12-month drought analysis are, RDI during 2084–2098 (DD = 14, DS = −1.38), SPEI during 2084–2098 (DD = 14, DS = −1.33) and SPI during 2084–2095 (DD = 12, DS = −1.19). The 1st and 2nd months of the years studied predicted a warming trend, while the 7th, 8th, and 9th months predicted a wetter trend. Finally, it was observed that RDI is more sensitive to drought and indicated a high percentage of years under severe and extreme drought conditions during the drought frequency analysis. Conclusively, this study provides a strategies for water resources management and monitoring of droughts, in which drought indices like RDI can play a central role.

Keywords: Reconnaissance drought index; Warming trend; Projected changes; Drought extremes; GCMs (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s11269-017-1716-4 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:31:y:2017:i:12:d:10.1007_s11269-017-1716-4

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

DOI: 10.1007/s11269-017-1716-4

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 ().