Abstract
Abstract. The impacts of climate and land-use changes make the stationary assumption in hydrology obsolete. Moreover, there is still considerable uncertainty regarding the future evolution of the Earth’s climate and the extent of the alteration of flow regimes. Climate change impact assessment in the water sector typically involves a modelling chain in which a hydrological model is needed to generate hydrologic projections from climate forcings. Considering the inherent uncertainty of the future climate, it is crucial to assess the performance of the hydrologic model over a wide range of climates and their corresponding hydrologic conditions. In this paper, numerous, contrasted, climate sequences identified by a hidden Markov model (HMM) are used in a differential split-sample testing framework to assess the robustness of a hydrologic model. The differential split-sample test based on a HMM classification is implemented on the time series of monthly river discharges in the upper Senegal River basin in West Africa, a region characterized by the presence of low-frequency climate signals. A comparison with the results obtained using classical rupture tests shows that the diversity of hydrologic sequences identified using the HMM can help with assessing the robustness of the hydrologic model.
Highlights
According to some authors, humanity has entered a new geological epoch, the Anthropocene, characterized by rapid environmental changes due to human activities (Falkenmark et al, 2019)
Water engineers were able to design and operate water infrastructure based on the assumption that the climate was stationary and that time series of recorded hydrologic variables such as precipitation and river discharge were representative of future hydrologic conditions (Bernier, 1977; Payrastre, 2003; Naghettini, 2017)
As explained in the introduction, classical rupture tests make the distinction between only two periods, limiting the number of transitions that can be explored to assess the robustness of the hydrological model. This paper addresses this limitation by identifying multiple subsequences using a hidden Markov model (HMM), which are used in a differential split-sample testing framework
Summary
Humanity has entered a new geological epoch, the Anthropocene, characterized by rapid environmental changes due to human activities (Falkenmark et al, 2019). The first relies on the sequential coupling of models: general circulation models (GCMs) are run to project future precipitation and temperatures which are downscaled and used as inputs to hydrologic models whose outputs are processed by water systems models (Peel and Blöschl, 2011). This is consistent with the traditional “predict--act” decision-making paradigm (Weaver et al, 2013). In terms of decision-making paradigm, the idea here is to “minimize regret”
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
