2020
DOI: 10.1007/s10113-020-01615-8
|View full text |Cite
|
Sign up to set email alerts
|

Sensitivity of discharge projections to potential evapotranspiration estimation in Northern Tunisia

Abstract: Tunisia has a long history of coping with water scarcity, and the quantification of climate change impacts on runoff is important for future water management. A major requirement for such studies is an estimation of potential evapotranspiration (PET), which is challenging as many regions often lack the observational data needed for physically based PET equations. In this study, different PET estimation approaches were used to study the impact of PET estimation on discharge projections for catchments in Norther… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
7
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
7
2

Relationship

1
8

Authors

Journals

citations
Cited by 19 publications
(7 citation statements)
references
References 51 publications
0
7
0
Order By: Relevance
“…While the use of the Budyko framework highlights moderate-to-important impacts of taking into account CO 2 in PE formulations, how this could reflect on hydrological projections made with rainfall-runoff hydrological models might not be straightforward. The impact of PE formulations on discharge projections is still under debate, some studies pointing to either a low impact (Dakhlaoui et al 2020) or a high impact (Seiller and Anctil 2016). Specifically, the presence of a parameter calibration in most hydrological models might distort the relationship between PE anomalies and runoff anomalies (Oudin et al 2006) and could lead to different results from those simulated with the Budyko framework.…”
Section: Comparing Changes With Previous Model Experimentsmentioning
confidence: 99%
“…While the use of the Budyko framework highlights moderate-to-important impacts of taking into account CO 2 in PE formulations, how this could reflect on hydrological projections made with rainfall-runoff hydrological models might not be straightforward. The impact of PE formulations on discharge projections is still under debate, some studies pointing to either a low impact (Dakhlaoui et al 2020) or a high impact (Seiller and Anctil 2016). Specifically, the presence of a parameter calibration in most hydrological models might distort the relationship between PE anomalies and runoff anomalies (Oudin et al 2006) and could lead to different results from those simulated with the Budyko framework.…”
Section: Comparing Changes With Previous Model Experimentsmentioning
confidence: 99%
“…They are located in the main hydrographical basins (rivers) of Northern Tunisia: Extreme North, Ichkeul, High Medjerdah and Cap Bon, having a strategic role as a surface water supplier for the country (Ben Fraj et al 2019). The climate of the study catchments could be categorized as semi-arid to humid Mediterranean climate with a warm season (Dakhlaoui et al 2017(Dakhlaoui et al , 2020. The catchment's hydro-climatic characteristics are reported in Figure 1.…”
Section: Study Catchmentsmentioning
confidence: 99%
“…The regional pattern changes in annual runoff obtained in this study are, however, in agreement with previous studies (Donnelly et al 2017;Dayon et al 2018) that used more complex hydrological models: a pronounced decline in mean streamflow in the southern part of While the use of the Budyko framework highlights moderate-to-important impacts of taking into account CO2 in PE formulations, how this could reflect on hydrological projections made with rainfall-runoff hydrological models might not be straightforward. The impact of PE formulations on discharge projections is still under debate, some studies pointing to either a low impact (Dakhlaoui et al 2020) or a high impact (Seiller and Anctil 2016). Specifically, the presence of a parameter calibration in most hydrological models might distort the relationship between PE anomalies and runoff anomalies (Oudin et al 2006) and could lead to different results from those simulated with the Budyko framework.…”
Section: Comparing Changes With Previous Model Experimentsmentioning
confidence: 99%