Marco Franchini

TL;DR: In this paper, the authors compare some of the most well-known conceptual rainfall runoff models, using data for the Sieve watershed (an affluent of the Arno River), for which precipitation, temperature, and hourly flow rate values were available for a four-month period.

TL;DR: The TOPMODEL as discussed by the authors is a variable contributing area conceptual model in which the predominant factors determining the formation of runoff are represented by the topography of the basin and a negative exponential law linking the transmissivity of the soil with the distance to the saturated zone below the ground level.

TL;DR: In this article, a short-term, demand forecasting model was proposed for water distribution in real-time, near-optimal control of water-distribution networks based on the expected future demands for water, rather than just the present known requirements.

TL;DR: Three data-driven water level forecasting models are presented and discussed and it is shown that the two models based on the fuzzy logic approaches perform better when the physical phenomena considered are synthesised by both a limited number of variables and IF-THEN logic statements, while the ANN approach increases its performance when more detailed information is used.

TL;DR: In this paper, a GA-SQP was used to find the optimal parameter values during calibration of a conceptual rainfall runoff (CRR) model, where the GA was used as the starting point for a local optimization procedure based on Sequential Quadratic Programming (SQUP).