The evolution of the major achievements in water lifting devices with emphasis on the major technologies over the centuries is presented and discussed. Valuable insights into ancient water lifting technologies with their apparent characteristics of durability, adaptability, and sustainability are provided. A comparison of the relevant technological developments in several early civilizations is carried out. These technologies are the underpinning of modern achievements in water engineering. They represent the best paradigm of probing the past and facing the future. A timeline of the historical development of water pumps worldwide through the last 5500 years of the history of mankind is presented. A chronological order is followed with emphasis on the major civilizations.

Defining flood-prone areas is particularly important for policy makers, in order to design mitigation strategies and implement flood risk management planning. The present research applies a multicriteria index method to assess flood hazard areas at a river basin scale, in a geographic information system (GIS) environment. The developed methodology has been applied for an area in northeastern Greece, by processing information of seven parameters: flow accumulation, distance from the drainage network, elevation, land use, rainfall intensity and geology. The method assigns a relative importance to each of the parameters for the occurrence and magnitude of flooding, and the relevant weight values are defined through an “analytical hierarchy process”. Subsequently, and according to the relative importance of each index, the spatial information is superimposed, resulting in a flood hazard map of the studied region, an area in northern Greece. The obtained results indicate flood-prone zones, with a very high flood hazard mainly occurring at the lowlands in the vicinity of the drainage network. The provided flood hazard map supports planning activities and mitigation plans that are crucial to protect both the agricultural activities and existing infrastructure from future flood events.

The occurrence of flash floods in urban catchments within the Mediterranean climate zone has witnessed a substantial rise due to climate change, underscoring the urgent need for early-warning systems. This paper examines the implementation of an early flood monitoring and forecasting system (EMFS) to predict the critical overflow level of a small urban stream on Lesvos Island, Greece, which has a history of severe flash flood incidents requiring rapid response. The system is supported by a network of telemetric stations that measure meteorological and hydrometric parameters in real time, with a time step accuracy of 15 min. The collected data are fed into the physical Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS), which simulates the stream’s discharge. Considering the HEC-HMS’s estimated outflow and other hydro-meteorological parameters, the EMFS uses long short-term memory (LSTM) neural networks to enhance the accuracy of flood prediction. In particular, LSTMs are employed to analyze the real-time data from the telemetric stations and make multi-step predictions of the critical water level. Hydrological time series data are utilized to train and validate the LSTM models for short-term leading times of 15 min, 30 min, 45 min, and 1 h. By combining the predictions obtained by the HEC-HMS with those of the LSTMs, the EMFS can produce accurate flood forecasts. The results indicate that the proposed methodology yields trustworthy behavior in enhancing the overall resilience of the area against flash floods.