TY - JOUR
T1 - Non-stationary influences of large-scale climate drivers on low flow extremes in Southeast Australia
AU - Goswami, Pallavi
AU - Peterson, Tim J.
AU - Mondal, Arpita
AU - Rüdiger, Christoph
N1 - Funding Information:
P. Goswami was funded by a PhD scholarship from the IITB‐Monash Research Academy, whose support we greatly acknowledge. The authors are also thankful to the Editor, Associate Editor, and the two anonymous reviewers whose suggestions improved the quality of the paper. Developers and contributors of all the R packages used for the analysis are acknowledged. Open access publishing of this work was facilitated by Monash University, as part of the Wiley ‐ Monash University agreement via the Council of Australian University Librarians.
Funding Information:
P. Goswami was funded by a PhD scholarship from the IITB-Monash Research Academy, whose support we greatly acknowledge. The authors are also thankful to the Editor, Associate Editor, and the two anonymous reviewers whose suggestions improved the quality of the paper. Developers and contributors of all the R packages used for the analysis are acknowledged. Open access publishing of this work was facilitated by Monash University, as part of the Wiley - Monash University agreement via the Council of Australian University Librarians.
Publisher Copyright:
© 2022. The Authors.
PY - 2022/7
Y1 - 2022/7
N2 - The intensity, duration, and frequency (IDF) of low streamflow events are often considered stationary in time. Given droughts are likely to become more frequent and extreme, here those IDFs are analyzed for their non-stationarity in relation to three climate drivers, namely, the El Niño-Southern Oscillation, the Indian Ocean Dipole, and the Southern Annular Mode. For this, low flow events were identified for 161 unregulated catchments in Victoria, Australia. The relationship between the climate drivers and the IDFs were developed using covariate-based non-stationary statistical models. We found that several of these catchments exhibit strong non-stationary influences from the climate modes. Such catchments have a higher probability of experiencing more intense, prolonged, and/or frequent low flows when a dry phase of these climate drivers occurs. We found that catchments having strong evidence of non-stationary frequency (n = 77) were more compared to those having non-stationary intensity (n = 19) or duration (n = 34). Further, we derived projected indices of these climate drivers from CMIP5 models for the RCP8.5 scenario. These indicate an intensification in the dry phase of the climate drivers. Using information of the projected indices in the IDF models, we found that future dry phases of these climate drivers are likely to further increase the probability of experiencing higher magnitudes of low flow IDFs in catchments non-stationary in these characteristics in relation to one or more of these climate drivers. Frequency shows greater response to future dry phases of these drivers than intensity or duration of low flows.
AB - The intensity, duration, and frequency (IDF) of low streamflow events are often considered stationary in time. Given droughts are likely to become more frequent and extreme, here those IDFs are analyzed for their non-stationarity in relation to three climate drivers, namely, the El Niño-Southern Oscillation, the Indian Ocean Dipole, and the Southern Annular Mode. For this, low flow events were identified for 161 unregulated catchments in Victoria, Australia. The relationship between the climate drivers and the IDFs were developed using covariate-based non-stationary statistical models. We found that several of these catchments exhibit strong non-stationary influences from the climate modes. Such catchments have a higher probability of experiencing more intense, prolonged, and/or frequent low flows when a dry phase of these climate drivers occurs. We found that catchments having strong evidence of non-stationary frequency (n = 77) were more compared to those having non-stationary intensity (n = 19) or duration (n = 34). Further, we derived projected indices of these climate drivers from CMIP5 models for the RCP8.5 scenario. These indicate an intensification in the dry phase of the climate drivers. Using information of the projected indices in the IDF models, we found that future dry phases of these climate drivers are likely to further increase the probability of experiencing higher magnitudes of low flow IDFs in catchments non-stationary in these characteristics in relation to one or more of these climate drivers. Frequency shows greater response to future dry phases of these drivers than intensity or duration of low flows.
KW - climate teleconnections
KW - droughts
KW - extreme value theory
KW - Generalized Linear Models
KW - IDF of low flows
KW - non-stationarity
UR - https://www.scopus.com/pages/publications/85134879684
U2 - 10.1029/2021WR031508
DO - 10.1029/2021WR031508
M3 - Article
AN - SCOPUS:85134879684
SN - 0043-1397
VL - 58
JO - Water Resources Research
JF - Water Resources Research
IS - 7
M1 - e2021WR031508
ER -