Flash floods are of major relevance in natural disaster management in the Mediterranean region. In many cases, the damaging effects of flash floods can be mitigated by adequate management of flood control reservoirs. This requires the development of suitable models for optimal operation of reservoirs. A probabilistic methodology for calibrating the parameters of a reservoir flood control model (RFCM) that takes into account the stochastic variability of flood events is presented. This study addresses the crucial problem of operating reservoirs during flood events, considering downstream river damages and dam failure risk as conflicting operation criteria. These two criteria are aggregated into a single objective of total expected damages from both the maximum released flows and stored volumes (overall risk index). For each selected parameter set the RFCM is run under a wide range of hydrologic loads (determined through Monte Carlo simulation). The optimal parameter set is obtained through the overall risk index (balanced solution) and then compared with other solutions of the Pareto front. The proposed methodology is implemented at three different reservoirs in the southeast of Spain. The results obtained show that the balanced solution offers a good compromise between the two main objectives of reservoir flood control management

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A qualitative research study was conducted through explorative workshops to better understand the experiences, perceptions, needs, and expectations of the users and potential users of virtual human factors (VHF) tools. Five VHF tools were presented to ergonomists, engineers, and managers who participated in four whole‐day interactive workshops: HF enabled predetermined motion time systems (PMTS), discrete event simulation (DES), complex and simple digital human models (DHM), and virtual reality (VR). Data were collected by note‐takers, digital audio recording, and written feedback. Identified characteristics shared by the tools were organized into 9 categories that act as a motivational or deterring factor for the use of the tool: time, cost, training, difficulty of use, trustworthiness, graphics, flexibility, usefulness, and report presentation. Other tool specific areas of improvement were also identified by participants to help developers improve these design instruments.

Collaborative Learning Patterns (CLPs)

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Keywords:Hydropower generation Adjustable speed operation Energy and operational gains Irrigation reservoir This paper deals with the issue of adjustable speed operation (ASO) of hydropower plants. The main idea of this technique is to allow the turbine speed to change in accordance with hydraulic conditions, thus improving the overall unit efficiency. General technical aspects of ASO are further discussed with special emphasis on the energy and operational benefits that may potentially result from its application. In order to assess these benefits, annual operation of a hydropower plant associated to an irrigation reservoir has been simulated under different scenarios, with both adjustable and fixed speed. Turbine operating range proved to be wider with ASO. In addition, simulation results confirm that considerable energy gains are expected to be obtained.