Short-term river water-level forecasting is essential for operational hydrology, supporting flood warning and water management. Although deep learning models such as Long Short-Term Memory (LSTM) networks have gained attention, classical statistical approaches including Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) remain attractive due to their interpretability and efficiency. This study presents a controlled comparison between ARIMA/SARIMA and stacked LSTM models for 7-day-ahead water-depth forecasting using synthetic daily hydrographs representing normal, drought, and flood regimes. Model performance is assessed using a rolling-origin forecasting strategy that generates multiple overlapping predictions, reducing bias from short validation windows. Forecast skill is evaluated through standard error metrics and hydrology-oriented indicators, including the Global Forecast Skill Index (GFSI). Results show comparable median performance between SARIMA and LSTM across regimes, with no statistically significant differences detected by nonparametric tests. Apparent differences in flood conditions should be interpreted cautiously due to limited sample representation. Overall, increased model complexity does not inherently guarantee superior predictive skill in this univariate short-term setting, highlighting the importance of rigorous evaluation design in comparative forecasting studies.

The Tulcea municipality is frequently exposed to rainfall-generated floods, with its lower downtown area (located in the Danube’ former meadow, now protected by dikes) being flooded two to three times per year. In this study, our objective was to understand the generation mechanism of these rainfall-triggered urban floods and to identify tailored mitigation options. Due to the lack of reliable information on the sewage network (diameters, slope, material) and the uncertain sewage outflows during heavy rain events, a rather simplified approach was preferred by the authors of this paper. The data processing was performed using GIS tools, with appropriate accounting of the digital terrain modelling, ortho-photos, administrative boundaries of the Tulcea municipality, delineation of the urban catchments, imagery of the frequently flooded areas, and the urban sewage network. Subsequently, a fast hydrological modelling and a volume-based flooding approach were developed in order to identify and evaluate the flooded urban areas under extreme rainfall events. Upon the completion of the calibration and validation processes, numerical simulations were run that considered the design storms of different return periods. Due to the high slopes of the hills, hence the short concentration time of the pluvial waters, a Sponge City approach does not seem as though it would be easy to implement. A more efficient solution utilising large-capacity buried urban retention tanks in the lower part of the municipality was alternatively identified. Further on, this solution will be supported by a set of green measures.

Almost all multipurpose reservoirs in Romania were put into operation 30–50 years ago or even earlier. Meanwhile, a large volume of hydrologic data has been collected, and the initial design flood should be reconsidered. Consequently, the operating rules of flow control structures (bottom gates and weir gates) should be re-examined, mainly for medium and low-frequency floods. The design flood is not unique, being characterized by different shapes and time to peak, which has consequences for flood mitigation rules. Identifying the critical design flood is an important preliminary step, although it is usually neglected in flood management. Simulating the operation of the Stânca–Costești reservoir on the Prut River, it was found that the design flood corresponding to the maximum value of the compactness coefficient is the most difficult to mitigate considering the specific conditions of the dam and the reservoir: the prescribed conservation level in the reservoir, and the design flood volume of medium and rare floods that far exceeds the flood control volume. These conditions can jeopardize both dam safety and downstream flood protection. The main steps of the proposed approach are as follows: (1) developing the hydraulic model; (2) statistical processing of the registered floods and defining critical design floods for different AEPs (Annual Exceedance Probabilities); (3) deriving optimal operation rules based on a simulation-optimization model; (4) implementing real-time adaptive operation of the mechanical outlets; and (5) critically assessing the operating rules after the event. Based on the hydrological forecast, if necessary, new outlets are put into operation while keeping the ones already activated. Based on the hydrological forecast and properly operated, the safety of the Stânca–Costești dam is guaranteed even in the event of a 0.1% CC (Climate Change) flood. However, for floods greater than 1% magnitude, the carrying capacity of the downstream riverbed is exceeded. The main gaps addressed in this paper are the following: (1) the establishment of critical design floods, and (2) the adaptive operating rules of outlet devices aimed at optimizing flood control results, using short-term flood forecasts.

Droughts are natural disasters with a significant impact on the economy and social life. Prolonged droughts can cause even more damage than floods. The novelty of this work lies in the definition of a synthetic drought hydrograph (SDH) which can be derived at each gaging station of a river network. Based on drought hydrographs (DHs) recorded for a selected gaging station, the SDH is statistically characterized and provides valuable information to water managers regarding available water resources during the drought period. The following parameters of the registered drought hydrograph (DH) are proposed: minimum drought discharge $Q_D^{min}$, drought duration $D_D$ and deficit volume $V_D$. All these parameters depend on the drought threshold $Q_T$, which is chosen based on either pure hydrological considerations or on socio-economic consequences. For the same statistical parameters of the drought, different shapes of the synthetic drought hydrograph (SDH) can be considered. In addition, the SDH varies according to the probabilities of exceedance of the minimum drought discharge and deficit volume.

Intensity–Duration–Frequency (IDF) curves are essential tools in the design of stormwater management systems and are often used over long periods without frequent updates. However, the continuous collection of rainfall data and the expansion of monitoring networks call for regular revisions of these curves. In Romania, current engineering and hydrological practices still rely on regionalized IDF graphs developed in 1973. Given the ongoing effects of climate change—particularly the increased frequency and, more significantly, intensity of extreme rainfall events—updating these curves has become critical. Incorporating recent observations is essential not only for methodological accuracy but also to support climate-resilient infrastructure design. This study employs updated IDF curves provided by the National Administration of Meteorology, based on 30 years of precipitation records from 68 meteorological stations across Romania. The main objective is to evaluate alternative regionalization approaches—including clustering methods, geographic proximity analysis, and hourly precipitation isolines for a 1:10 Annual Exceedance Frequency—to develop a new regionalization model and the corresponding nationwide IDF relationships. A comparative analysis using raster-based regional rainfall datasets from both the 1973 and 2025 regionalizations revealed significant changes in precipitation patterns. Short-duration rainfall events (5, 10, and 30 min) have increased in intensity across most regions, while long-duration events (3, 6, 12, and 24 h) have generally decreased in magnitude in several areas. These findings highlight a growing trend toward more intense short-term convective storms, underlining the urgent need for improved flash flood prevention and urban stormwater management strategies.

IDF curves are widely used to develop the design storm and usually remain in use for long periods of time. However, continuous data collection and the addition of new monitoring stations require updates to the existing curves. In Romania, current prac-tice is still based on curves established in 1973. Climate change significantly alters the frequency and mostly the intensity of extreme rainfall events, justifying the need to update the IDF curves. In addition to using recent observations, updating these curves is essential to support the adaptation of infrastructure to changing climatic conditions. This study analyzed the IDF curves from 68 meteorological stations using data records from the last 30 years. Different approaches were analyzed to obtain a new regionalization, including clus-tering, geographic proximity, or hourly precipitation isolines for a frequency of 1:10. Using rasterized regional rainfall data obtained based on the 1973 and 2025 IDF curves, percentage precipitation differences were calculated. The results indicate that the value of short-term precipitation (5’, 10’, 30’) increased in most of Romania, while long-term events (3 h, 6 h, 12 h or 24 h) largely recorded a decrease in precipitation value in many areas. The increase in short-term torrential rainfall highlights the need for active prevention and management of urban flash floods.