Hristos Tyralis

TL;DR: In this article, a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts is described. But despite the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work.

TL;DR: This work popularizes RF and their variants for the practicing water scientist, and discusses related concepts and techniques, which have received less attention from the water science and hydrologic communities.

TL;DR: This work compares 11 stochastic and 9 ML methods regarding their multi-step ahead forecasting properties by conducting 12 extensive computational experiments based on simulations, and indicates that stoChastic and ML methods may produce equally useful forecasts.

TL;DR: The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables, which could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.

TL;DR: In this paper, the predictability of monthly temperature and precipitation by applying automatic univariate time series forecasting methods to a sample of 985 40-year-long monthly temperature, and 1552 40 -yearlong monthly precipitation time series was investigated.