Future Hydrological Drought Analysis Considering Agricultural Water Withdrawal Under SSP Scenarios

Jin Hyuck Kim, Jang Hyun Sung, Shamsuddin Shahid, Eun Sung Chung

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Hydrological drought is assessed through river flow, which depends on river runoff and water withdrawal. This study proposed a framework to project future hydrological droughts considering agricultural water withdrawal (AWW) for shared socioeconomic pathway (SSP) scenarios. The relationship between AWW and potential evapotranspiration (PET) was determined using a deep belief network (DBN) model and then applied to estimate future AWW using projections of the twelve global climate models (GCMs). 12 GCMs were bias-corrected using the quantile mapping method, climate variables were generated, and river flow was estimated using the soil and water assessment tool (SWAT) model. The standardized runoff index (SRI) was used to project the changes in hydrological drought characteristics. The results revealed a higher occurrence of severe droughts in the future. Droughts would be more frequent in the near future (2021–2060) than in the far future (2061–2100) and more severe when AWW is considered. Droughts would also be more severe for SSP5-8.5 than for SSP2-4.5. The study revealed that the increased PET due to rising temperatures is the primary cause of the increased drought frequency and severity. The AWW will accelerate the drought severities in the future in the Yeongsan River basin.

Original languageEnglish
Pages (from-to)2913-2930
Number of pages18
JournalWater Resources Management
Volume36
Issue number9
DOIs
StatePublished - Jul 2022

Keywords

  • Agricultural water withdrawal
  • CMIP6
  • Deep belief network
  • Reliability ensemble average
  • Shared socioeconomic pathways
  • Standardized runoff index

Fingerprint

Dive into the research topics of 'Future Hydrological Drought Analysis Considering Agricultural Water Withdrawal Under SSP Scenarios'. Together they form a unique fingerprint.

Cite this