On the accurate representation of hydropower systems in large-scale hydrological models

Abstract

<p>Natural streamflow of most mountain catchments worldwide is altered as a consequence of hydropower exploitation and other water uses. Hydrological modelling in these watersheds represents a challenging task, as the streamflow alteration caused by hydropower production is linked to operational schedules as well as to geometrical and technical constraints, which are system specific. Key parameters controlling hydropower functioning are difficult to acquire, because protected by producers, hence modelling hydropower systems in large domains often resorts to simplified (and less realistic) approaches, in order to cope with the lack of information. However, the accuracy of the simulations depends critically on the reliability of the simplified assumptions, which varies among the proposed approaches. In this work we analyzed the impact of the simplifications typically introduced in modelling hydropower at the catchment and larger scales by assuming as reference HYPERstreamHS, a coupled hydrological and hydraulic model exploiting the information publicly available on single hydropower systems. We present an application of the proposed framework to the Adige river basin, a large watershed located in the south-eastern portion of the Alps, in which the presence of 39 large hydropower systems characterized by complex infrastructures, 22 of which connected to storage reservoirs, causes significant alterations of streamflow timing and magnitude. We demonstrate the benefit of accurately representing hydropower-related water diversions by analyzing how the model represents the observed streamflows at impacted sites and hydropower production at the regional scale. We also provide insights on how a simplified representation of large hydropower systems can lead to a biased evaluation of streamflow alterations at impacted sections and of hydropower production at several sites. Our results show that the effects of different simplifications that may be adopted in the modelling framework combine in a non-linear manner, thus complicating the overall evaluation of the associated impacts.</p>