no research has been done in case of real-time forecasting. Furthermore, many uncertainties are exist influencing to forecasting result. EnKF is the useful technique to address that issue by updating the model state and parameter during the real-time. The proposed framework significantly enhances the efficiency and accuracy of hydrological application in real-time forecasting, which plays an important role in the flood planning, management, and mitigating the flood risk during the golden time. In real-time process, the forecast rainfall and the flow at the current time are updated, the unified framework will be capable to automatically upgrade the ensemble model states and model parameters through Dual EnKF (dual states-parameters estimation); and the ensemble hydrologic predictions are estimated a seamlessly through PCE. Besides, to maximize the efficient in forecasting, the approach of GLUE (Generalized likelihood uncertainty estimation) is used to determine the ensemble size of model states and parameters sets, and the perturbed observation. The proposed approach is applied to the Vu Gia watershed in Vietnam to demonstrate its validity and applicability. A detailed comparison with the NAM hydrologic model shows that analyzing results with surrogate model are as good as those given by NAM model, while the forecasting results are significantly improved through automatic updating of states and parameters by EnKF; not only the good accuracy, but also the model can run nearly 10 times faster than the hydrologic model. Overall, the results indicate that the uncertainty propagation in real-time flood forecasting can be effectively characterized and robust through the proposed unified framework.

Any attempt for the application of integrated drought management, requires identifying and characterizing the event per se. The questions of scale, boundary, and of geographic areal extend are of central concern for any efforts of drought assessment, impacts identification, and thus of drought mitigation implementation mechanisms. The use of drought indices, such as Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), has often lead to pragmatic realization of drought duration, magnitude and spatial extend. The current effort presents the implementation of SPI and SPEI on a Pan-European scale and it is evaluated using existing precipitation and temperature data. The E-OBS gridded dataset for precipitation, minimum temperature, and maximum temperature were used, covering the period 1969 – 2018. The two indices were estimated for time steps of 6, and 12 months. The results for the application period of recurrent droughts indicate the potential that both indices offer for an improvement on drought management, comparability, identification of critical areas, threshold definitions, towards better planning and mobilization of resources for mitigation efforts.

Climate changes in the Mediterranean region especially those related to changes in rainfall distribution and occurrence of extreme events affect local economies. Agriculture is a sector strongly affected by climate conditions and concerns the majority of the Greek territory. The Gallikos river basin is an area of great interest regarding climate change impacts since it is an agricultural area depended on surface water resources and an area in which extreme events relatively often take place (e.g. floods). Long time series precipitation (27 years) and temperature data derived from measurement stations along with reanalysis data (ERA INTERIM) were used for the estimation of water availability and climate type over time in the area. The Standardized Precipitation Index and De Martonne aridity index was employed. The water flow measurements were correlated in order to investigate the interrelation between the different river branches and the extent of the meteorological changes effect in the basin. Descriptive statistics and cumulative curves were applied to check homogeneity of data. The results revealed that the climate type varies from semi arid to very wet and water availability ranges from moderately dry to extremely wet years. Reanalysis data overestimate precipitation. The meteorological changes affect at the same time the entire basin since the flow rate peaks occur simultaneously in the hydrographic network at different areas.

The detection of changes involves detailed analyses of hydrological data in order to prove the character of the changes. This paper focuses on an analysis of average monthly discharges of 14 stage-discharge gauging stations in Slovakia. The measured period is from 1931 to 2016. The using approaches are hydrological exploration methods, which were created by hydrologists due to attempt to describe the behaviour of hydrological time series. The methods have been used to identify a change point using the analysis of residuals, Pettit´s test and the analysis of the relationship of the mean annual flow deviations from the long-term annual flows and the deviations of the average monthly flows from the long-term average monthly flows. A considerable number of change points was identified in the 80's and 90's. The results of the analyses show changes in hydrological regime, but to confirm the outcome accuracy, it is necessary to examine also other hydrological and meteorological elements as e.g., precipitation and air temperature.

In recent decades, natural hazards have caused major disasters in the natural and man-made environment. Floods are one of the most devasting natural hazards with high mortality percentage, destruction of infrastructure and large financial losses. This study presents a methodological approach for flood risk management at lakes and adjacent areas that is based on the implementation of the EU Floods Directive (2007/60/EC) in Greece. Contemporary engineering approaches have been used for the estimation of the inflow hydrographs. The hydraulic-hydrodynamic simulations implemented in the following order: a) hydrologic modelling of lake tributaries and estimation flood flow inflow to the lake, b) flood inundation modelling of lake tributaries, c) simulation of the lake as a closed system, d) simulation of the lake outflows to the adjacent areas, e) simulation of flood inundation of rural and urban areas adjacent to the lake. The hydrologic modelling has been performed using the HEC-HMS model and the hydraulic-hydrodynamic simulations were implemented with the use of the two-dimensional HEC-RAS model. The simulations applied for three soil moisture conditions (dry, medium and wet) and three return periods (T = 50, T = 100 and T = 1000 years) and a methodology was followed for the flood inundation modelling in urban areas. Upper and lower estimates on water depths, flow velocities and inundation areas are estimated for all inflow hydrographs and for varying roughness coefficient values. The proposed methodology presents the necessary steps and the results for the assessment of flood risk management and mapping for lake and adjacent urban and rural areas. The methodology has been applied to Pamvotida lake, Epirus, Greece, which is the lake of Ioannina city.

In water scarce areas, policy makers frequently opt for water conservation and saving technologies (WCSTs) as a measure to ensure resource use sustainability, although this policy is subject to scientific and political debate. This work presents an application of an integrated methodological approach for analysing the costs and benefits of using WCSTs to achieve water policy objectives. The focus is on the measures aimed at reducing irrigation water abstraction under the 1⁠st and 2⁠nd cycle of Water Framework Directive implementation in the Guadalquivir River Basin (Southern Spain). The method is a combination of a multicriteria assessment of the main effects of water-saving investments at basin level, estimated using a selected group of indicators. In a second stage, a cost-benefit analysis is conducted. The study finds a benefit-to-cost ratio of 4.1/1 for the Guadalquivir River Basin, thus concluding that irrigation modernization in this case study has been a good social investment. The method can be extended to other hydrological systems (aquifer basins) to draw general conclusions.

The aims of this study are to quantify the effects of key properties of rainfall time series (frequency, duration, depth, rate and peak, time between events, length of series and precipitation thresholds, among others) on the hydrologic design of sustainable urban drainage systems (SuDS), to test a method for their estimation from daily time series and to quantify their uncertainty. Several typologies of SuDS infrastructures are designed to achieve a target treatment capacity. This target capacity is usually defined according to two methods: treating a percentage of the total volume of rainfall (50, 80, 90, 95, 99%) or treating a percentage of the total number of rainfall events (50, 80, 90, 95, 99%). We considered the city of Madrid as the case study, compiling 58 years of observed data (10-minute time step) and aggregating to daily time series. We obtained the design parameters from the full resolution dataset and then tested a simplified method to estimate them from daily time series of varying length. First, we calculated the design parameters for different storm thresholds (0, 1 and 2 millimeters). Second, we determined the design parameters from the aggregated daily time series by applying a temporal stochastic rainfall generator model (RainSimV3). We estimated the model parameters from daily data and generated 100 series of 58 years at 10-minute time step, and compared the results. Third, we generated 100 series of different lengths (20, 30, 40, 50, 58, 80 and 100 years). Fourth, we generated 100 series of 58 years at 10-minute time step (for each series length). Finally, we analyzed the uncertainty produced by the length of the observed data set. Results showed that, depending on the criteria adopted for the estimation of rainfall design parameters, SuDS structure volumes could vary up to 30 %. Further research includes the analysis of different climate locations.

Research questions related to a reliable estimate of flood discharges has always interested both hydrologists and civil engineers. Over the decades numerous methods have been proposed and used more or less successfully, all of them with known limitations restricting their use to a wide range of conditions and problems. In the past, the characteristics of hydrological extremes were mostly estimated by the methods of statistical analyses. As this type of methods is not suitable to estimate design discharges of high return periods, and by default does not account for uncertainty, a new family of methods is slowly taking place of the traditional approaches. Many of these methods are based on a combination of stochastic rainfall models (weather generators) and rainfall-runoff models, which enables to generate an arbitrary number of synthetic floods even in places with short or no records of river discharges available. In addition, as this type of methods produces flood hydrographs, they can also be used in a multivariate flood frequency analysis to estimate joint probabilities of two or more flood characteristics. This study presents a methodology for flood frequency analysis that combines stochastic models of both rainfall amounts and air temperatures with a lumped rainfall-runoff model to transfer the outputs of the stochastic models into a series of corresponding river discharges. Both of the stochastic models are single-site weather generators that produce continuous time series of mean areal daily rainfall amounts and air temperatures. In this study, the method was used to generate a time series of 10,000 years of mean daily discharges, which was used to build a flood frequency curve and to estimate extreme flood discharges of given return periods. The method was applied to a mountainous catchment of the River Váh in Slovakia.

Currently, there is general concern about the non-stationary behaviour of flood series. Consequently, several studies have been conducted to identify large-scale patterns of change in such flood series. In Spain, a general decreasing trend was found in the period 1959-2009. However, a multi-temporal trend analysis with varying starting and ending years showed that trend signs depended on the period considered. Flood oscillations could influence the results, especially when flood-rich and flood-poor periods are located at the beginning or end of the series. In Spain, a flood-rich period in 1950-1970 seemed to lead to the generalised decreasing trend, as it was located at the beginning of the flood series. Nevertheless, the multi-temporal test can only find potential flood-rich and flood-poor periods qualitatively. A methodology has been developed to identify statistically significant flood-rich and flood-poor periods. The expected variability of floods under the stationarity assumption is compared with the variability of floods in observed flood series. The methodology is applied to the longest streamflow series available in Spain. Seven gauging stations located in near-natural catchments with continuous observations in the period 1942-2014 are selected. Both annual maximum and peak-over-threshold series are considered. Flood-rich and flood-poor periods in terms of flood magnitudes and the annual count of exceedances over a given threshold are identified. A flood-rich period in the beginning of the series and a flood-poor period at its end are identified in most of the selected sites. Accordingly, a flood-rich period placed at the beginning of the series followed by a flood-poor period influence the generalised decreasing trend in flood series previously found in Spain.

A flow regime can be broadly categorised as perennial, intermittent, or ephemeral. Different conceptual models are needed to capture the behaviour of these different flow regimes, which reflect the differences in stream-groundwater hydrologic connectivity. As the hydrologic connectivity becomes more transient and a catchment’s runoff response more non-linear, such as for intermittent streams, the need for explicit representation of the groundwater increases. In the present study, we investigate the connection between Northern Etna Groundwater system and the Alcantara River Basin in Sicily. To this end, we apply a modified version of IHACRES rainfall-runoff model, whose input data are continuous series of concurrent daily streamflow, rainfall and temperature data. The structure of the model includes three different modules: (1) a non linear loss module that transforms precipitation to effective rainfall by considering the influence of temperature; (2) a linear module based on the classical convolution between effective rainfall and the unit hydrograph able to simulate the quick component of the runoff; and (3) another non linear modules that simulates the slow component of the runoff and that feeds the groundwater storage. From the sum of the quick and the slow components (except for groundwater losses, representing the aquifer recharge), the total streamflow is derived. This model structure is applied separately to sub-basins showing different hydrology and land use. The model is calibrated at Mojo cross section, where daily streamflow data are available. Point rainfall and temperature data are spatially averaged with respect to the considered sub-basins. Model calibration and validation are carried out for the period 1981-1984 and 1985-1988 respectively. Furthermore, the uncertainty of model parameters is analyzed by using Monte Carlo simulation.