2020
DOI: 10.1080/02626667.2020.1767782
|View full text |Cite
|
Sign up to set email alerts
|

Uncertainty assessment in river flow projections for Ethiopia’s Upper Awash Basin using multiple GCMs and hydrological models

Abstract: Uncertainty in climate change impacts on river discharge in the Upper Awash Basin, Ethiopia, is assessed using five MIKE SHE hydrological models, six CMIP5 general circulation models (GCMs) and two representative concentration pathways (RCP) scenarios for the period 2071-2100. Hydrological models vary in their spatial distribution and process representations of unsaturated and saturated zones. Very good performance is achieved for 1975-1999 (NSE: 0.65-0.8; r: 0.79-0.93). GCM-related uncertainty dominates varia… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

3
5
0
1

Year Published

2020
2020
2024
2024

Publication Types

Select...
10

Relationship

2
8

Authors

Journals

citations
Cited by 23 publications
(9 citation statements)
references
References 71 publications
(80 reference statements)
3
5
0
1
Order By: Relevance
“…This follows widely reported GCM-related uncertainty within the overall 'cascade of uncertainty' in climate change impacts (Wilby & Dessai 2010) for river systems around the world (e.g. Vetter et al 2015;Krysanova et al 2017;Chan et al 2020). As described by Thompson et al (2017), both increases and decreases in river discharge across the Upper Niger of varying magnitude are projected by the different GCM groups.…”
Section: Discussionsupporting
confidence: 73%
“…This follows widely reported GCM-related uncertainty within the overall 'cascade of uncertainty' in climate change impacts (Wilby & Dessai 2010) for river systems around the world (e.g. Vetter et al 2015;Krysanova et al 2017;Chan et al 2020). As described by Thompson et al (2017), both increases and decreases in river discharge across the Upper Niger of varying magnitude are projected by the different GCM groups.…”
Section: Discussionsupporting
confidence: 73%
“…Water management in this basin is very poor and the amount of water abstraction for irrigation and other purpose is not registered. Due to the limited available information, such as water used for irrigation and for other sectors, required to accurately calibrate the model, most studies focus on the upper part of the basin (Chan et al, 2020;Gebrechorkos et al, 2019a;Mersha et al, 2018). Thus, the model accuracy decreases with an increase in drainage area (e.g., from Melka-Kuntrea to Tendaho) due to a large amount of water abstracted (e.g.…”
Section: Discussionmentioning
confidence: 99%
“…In addition, future runoff predictions are often subject to large uncertainties due to choices made during the modeling process, e.g., GCMs, emission scenarios, hydrological models, different sources of data, etc. [23][24][25][26][27]69,70]. Research has indicated that the selection of scenarios can significantly affect watersheds with snowmelt [27], and the uncertainty associated with GCMs plays a crucial role in predicting high and average flows [69,70].…”
Section: Discussionmentioning
confidence: 99%