2021
DOI: 10.1080/02626667.2021.1895437
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Climate change impact and uncertainty analysis on hydrological extremes in a French Mediterranean catchment

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Cited by 19 publications
(14 citation statements)
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“…This process results in a balanced data set, which is essential to correctly assess the contribution of each modeling step and to avoid inducing a biased estimation of the variance explained by a specific modeling step being over-or underrepresented. This framework was successfully applied by Lemaitre-Basset et al (2021) to analyze projected hydrological uncertainties with an incomplete ensemble of projections. Analysis of variance (ANOVA) methods are frequently used to quantify the contribution of different models to total uncertainty.…”
Section: Quantifying and Partitioning Projected Pe Uncertaintiesmentioning
confidence: 99%
“…This process results in a balanced data set, which is essential to correctly assess the contribution of each modeling step and to avoid inducing a biased estimation of the variance explained by a specific modeling step being over-or underrepresented. This framework was successfully applied by Lemaitre-Basset et al (2021) to analyze projected hydrological uncertainties with an incomplete ensemble of projections. Analysis of variance (ANOVA) methods are frequently used to quantify the contribution of different models to total uncertainty.…”
Section: Quantifying and Partitioning Projected Pe Uncertaintiesmentioning
confidence: 99%
“…Second, the deviations arise from the modelling chain (Figure 2). There are different sources of uncertainty from the estimation of the greenhouse gas emission scenarios to the calculation of HIs, and each stage has its own contribution to the total uncertainty (Vidal et al, 2016;Lemaitre-Basset et al, 2021). The determination of these contributions is a key point in climate change impact studies (Hattermann et al, 2017), which requires further analyses.…”
Section: Impact Of the Use Of Climate Projections In Sidra-ru On Hydr...mentioning
confidence: 99%
“…In its successive reports, the IPCC stated that the climate will be subject to several changes by 2100, including an increasing number of rapid and intense events (Garner et al, 2015), such as flash floods (Kundzewicz et al, 2014;Yin et al, 2016;Xu et al, 2019;Zhang et al, 2019), and a global increase in air temperature (IPCC, 2008(IPCC, , 2014 resulting in more frequent drought events (Prudhomme et al, 2014). Numerous studies have been carried out to assess the impact of climate change on the hydrological cycle, both at the catchment and regional levels, mostly on hydrologically unmodified systems and at large spatial scales (Khaliq et al, 2009;Arnell and Gosling, 2016;Carvalho-Santos et al, 2016;Lemaitre-Basset et al, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…A Bayesian data augmentation technique, the QUALYPSO method (Evin et al, 2019;Evin, 2020), was applied to deal with the lack of balance in terms of representation within the combinations of climate models (GCMs/RCMs) and RCPs (see gaps in Table 1). This framework was successfully applied by Lemaitre-Basset et al (2021) to analyse projected hydrological uncertainties with an incomplete ensemble of projections. ANOVA methods are frequently used to quantify the contribution of different models to total uncertainty.…”
Section: Quantifying and Partitioning Projected Pe Uncertaintiesmentioning
confidence: 99%