The water-energy nexus holds paramount relevance in the context of the transition to a carbon free energy system, being water the only renewable energy source with reliable storage capacity.
Modelling hydropower production in a large domain over a long time window represents an open challenge due to a variety of reasons: firstly, high-resolution, large-scale hydrological modelling in a context of uncertainty needs calibration, thus representing a computationally intensive task due to the large domain and time window over which calibration is needed; secondly, as stated by many works in literature, hydropower production modelling and in particular reservoir modelling is a very information-demanding procedure, and excessive simplifications adopted to face the lack of information might lead to consistent bias in the predictions.
This thesis can be subdivided into three main parts: firstly, the model that was used to perform every analysis, HYPERstreamHS, will be presented. The model is a continuous, large-scale hydrological model embedding a dual-layer MPI framework (i.e. Message Passing Interface, a common standard in parallel computing) that ensures optimal scalability of the model, greatly reducing the computation time needed. Explicit simulation of water diversions due to hydropower production is also included in the model, and adopts only publicly available information, making the model widely applicable. Secondly, a first validation of the model will be presented, and the adopted approach will be compared with some other approaches commonly found in literature, showing that the inclusion of a high level of detail is crucial to ensure a reliable performance of the model; this first application was performed on the Adige catchment, where extensive information on human systems was available, and allowed to effectively assess which information were indispensable and which, in turn, could be simplified to some extent while preserving model performance. Finally, the model setup has been applied on a relevant portion of the Western Italian Alps; in this case, two different meteorological input forcing data sets were adopted, in order to assess the differences in their performance in terms of hydropower production modelling. This latter study indeed represents a preliminary analysis and will provide stepping stone to extend the modelling framework to the Italian Alpine Region.
| Identifer | oai:union.ndltd.org:unitn.it/oai:iris.unitn.it:11572/266707 |
| Date | 11 June 2020 |
| Creators | Galletti, Andrea |
| Contributors | Galletti, Andrea, Majone, Bruno, Bellin, Alberto |
| Publisher | Università degli studi di Trento, place:Trento |
| Source Sets | Università di Trento |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | firstpage:1, lastpage:151, numberofpages:151 |
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