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Uncertainties in future monsoon flow predictions in the context of projected climate change: A study of the Chaliyar River Basin.

Authors :
Ansa Thasneem S
Thampi SG
Chithra NR
Source :
Environmental research [Environ Res] 2023 Apr 01; Vol. 222, pp. 115301. Date of Electronic Publication: 2023 Jan 21.
Publication Year :
2023

Abstract

A major part of the annual rainfall in most parts of India is received during the monsoon. The Chaliyar River Basin in the state of Kerala is no exception with more than 85% of the annual rainfall occurring during the monsoon season. Evidences pointing towards the influence of anthropogenic activities on climate change have been reported from all over the world in recent years. One of the major problems encountered in the projection of future climate is the accumulation of uncertainties arising from different sources. This, in turn, would result in uncertainties in the predicted future streamflows. In this work, uncertainties in the monsoon flow predictions for a future period (2070-2099), stemming from the use of different climate models, hydrological models, and representative concentration pathways are analyzed. Uncertainty due to each of these sources and their interactions are partitioned by performing three-way analysis of variance. Results of the study indicate that the major source of uncertainty in the monsoon flow predictions is uncertainty from the climate models, which is about 83.73% of the total uncertainty in future monsoon flow predictions. Hydrological models account for about 5.38% and RCPs account for about 4.3% of the total uncertainty. About 6.57% is attributed to interactions between these three factors. Evaluation of the uncertainties in future monsoon flow predictions would facilitate informed decision making while formulating strategies for water management in the future.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2023 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1096-0953
Volume :
222
Database :
MEDLINE
Journal :
Environmental research
Publication Type :
Academic Journal
Accession number :
36693468
Full Text :
https://doi.org/10.1016/j.envres.2023.115301