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Few studies attempt to measure changes to discharge hydrographs during floods resulting from nature-based Solutions (NbS) for risk mitigation. The Q-NFM project in the UK has sought to measure and compare such changes for a wide range of NbS pilots applied to managed grasslands and woodlands. Also measured were underlying shifts in key hydrological processes leading to flood hydrograph changes of enhanced evaporation, hillslope-, channel- and floodplain-storage, and infiltration. How well particular NbS pilots changed these processes to reduce flood hydrographs was found to depend on the attributes of the NbS features and scheme. This learning is presented for the first time to highlight, with supporting evidence, seven potential criteria to help practitioners of flood risk management to improve existing and future designs of NbS for more effective flood mitigation within temperate grassland and woodland environments.

Gravel‐bed rivers widen and narrow as bar‐push and bank‐pull wax and wane through individual floods, yet over decades the channel often holds near constant width, evidence of coupling between inner‐bank deposition and outer‐bank erosion. Because large, event‐scale data sets are scarce and most field rivers have mixed grain‐size beds, the physics of this coupling remains uncertain. Here we use a unique Outdoor Experimental River Facility (OERF) with sediment recirculation to investigate this coupling in 50 m‐long, 3 m‐wide sine‐generated gravel‐bed channel using four identical seven‐stage flood hydrographs (129‐hr total duration). In an unvegetated experimental gravel‐bed channel with erodible banks (50% gravel; median size of 16 mm), twenty‐nine drone photogrammetry surveys (i.e., 2mm$2\\ \\mathrm{m}\\mathrm{m}$Digital Elevation Models) and bedload samples were collected to determine a novel thalweg‐centered volumetric framework and analysis that partitions every survey into inner‐bank and outer‐bank contributions. Flood peaks, though only 3% of the experiment duration, produced 83% of the 52% increase in planform area relative to the initial condition: centroid migration reached 1.3 m (27% of width), with the widening varying from one bend to the other. At peaks, bank‐pull dominated 50% of events and bar‐push 40%, whereas during rising and falling limbs symmetric widening prevailed (41%) with bar‐push still active (31%). Local context modulated these stage effects: under identical forcing, one bend damped toward a medium‐stability balance that approached a steady but non‐zero bar‐push/bank‐pull imbalance, a mid‐reach bend reached high stability with near‐balanced inner and outer bank volumetric changes, and an outlet‐proximal bend diverged into low‐stability widening. We conclude that in gravel channels the bar‐push/bank‐pull is both stage‐dependent and bend‐specific; short peaks set the morphodynamic trajectory, but sub‐bankfull limbs are responsible for most of the in‐channel geomorphic work.

Hydrological modeling academic studies have focused on the response to human-caused land use changes. The effects of land use change on flood degree in the catchment basin of Ekbatan Dam were investigated in this study, which looked at changes that occurred in 1985, 2000, and 2015. A combination of remote sensing and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) was used to achieve this goal. First, Landsat satellite images and sensors from Thematic Mapper, Enhanced Thematic Mapper Plus (ETM +), and Operational Land Imager were used to create land use maps for the target years. The weighted curve numbers (CN), a parameter related to infiltration, were then calculated for land uses. The extracted CN value, along with physiographic parameters and rainfall-runoff data, was then imported into the HEC-HMS model to simulate the effect of land use changes on runoff volume. After calibration and validation of the model using five (5) flood events, the simulation results showed an increase in the discharge peak volume of 64.3, 67.3, and 70.5 (m3/s) during the years 1985, 2000, and 2015, respectively, which resulted in an increase in the runoff height in these years as well.

In hydrological research, flood events can be analyzed by flood hydrograph coincidence. The duration of the flood hydrograph is a key variable to calculate the flood hydrograph coincidence risk probability and determining whether flood hydrograph coincidence occurs, while the actual duration of the flood hydrograph is neglected in most of existing related research. This paper creatively proposes a novel method to analyze the flood hydrograph coincidence risk probability by establishing a five-dimensional joint distribution of flood volumes, durations and interval time for two hydrologic stations. More specifically, taking the annual maximum flood of the upper Yangtze River and input from Dongting Lake as an example, the Pearson Type III and the mixed von Mises distributions were used to establish the marginal distribution of flood volumes, flood duration and interval time. Subsequently, the five-dimensional joint distribution based on vine copula was established to analyze the flood hydrograph coincidence risk probability. The results were verified by comparison with a historical flood sequence, which show that during 1951–2002, the hydrograph coincidence probabilities corresponding to its flood event coincidence volumes of 2.00 × 1011 m3, 4.00 × 1011 m3, and 6.00 × 1011 m3 are 0.213, 0.123, and 0.049, respectively. It has provided theoretical support for flood control safety and risk management in the middle and lower Yangtze River. This study also demonstrates the significant beneficial role of regulation by the Three Gorges Water Conservancy Project in mitigating flood risk of the Yangtze River. The hydrograph coincidence probability corresponding to its flood event coincidence volume of 2.00 × 1011 m3 has decreased by 0.141.

Hydrologic modeling using computer models has gained much attention in extreme flood event studies. Hydrologic Engineering Center Hydrologic Modelling System (HEC-HMS) is an extensively used software for streamflow generation in the hydrologic domain. This pilot study employs the HEC-HMS model in generating streamflows in the Chaliyar river basin, Kerala. Adequate representation of various water balance components of the hydrologic cycle is necessary for computing the surface and subsurface calculations. It is attained by combining appropriate sub-processes in the hydrological models. Remote sensing techniques integrated with Geographic Information Systems (GIS) are used in deriving the catchment characteristics. The simple canopy and surface methods are used to calculate the interception losses. The deficit-constant method is applied to estimate the infiltration losses, and the Clark unit hydrograph transforms the rainfall into runoff. The Muskingum method is used to route the reach segments within the watershed. Hydrometeorological data of the most influencing stations for the upstream Chaliyar basin are obtained by regionalization using the Thiessen polygon method. Daily precipitation data from four rain gauge stations, namely, Ambalavayal, Edakkara, Nilambur, and Manjeri, are used as the forcing inputs to the model. The streamflow data obtained from the Kuniyil gauge station is used to calibrate and validate the model. Various forecast skill scores like Probability of Detection (POD) and False Alarm Rate (FAR) are calculated from the categorical forecasts to quantify the forecast accuracy of the developed model. The model is used to simulate the intense flood event of 2019 in the Chaliyar basin.

Runoff data is crucial for development of water resources. Runoff data is however rarely available for ungauged catchments, especially in developing countries. Geomorphological instantaneous unit hydrographs (GIUH) models can be used for predicting runoff in poorly gauged catchments, but a challenge with these models is estimating the dynamic velocity parameter. In this study, three GIUH models were developed based on estimation of flow velocity using calibration of Manning’s n (GIUH-cal), peak discharge (GIUH-pq) and 30-min rain intensity (GIUH-I30). The objectives of this study were to (a) assess suitability of a GIUH model for simulating runoff in Gule catchment, northern Ethiopia and (b) evaluate performance of three velocity parameter estimation methods in simulating runoff using GIUH models. Runoff hydrographs of the GIUH models matched well with observed hygrographs for most rain events. The GIUH-cal model had the best performance, 18 out of 20 rain events resulting in Nash–Sutcliffe model efficiency (NSE) values of 0.53 to 0.95. The GIUH-pq and GIUH-I30 models performed satisfactorily with 12 of the 20 rain events resulting in NSE values greater than 0.50. Overall, the GIUH models underestimated peak discharge compared to observed data. The GIUH models were moderately sensitive to changes in flow velocity. Peak discharge and time to peak discharge were highly sensitive to changes in flow velocity. The developed GIUH models could be used for simulating flood hydrographs of the Gule catchment. Particularly, the GIUH-I30 model will be very useful for estimating direct surface runoff in the absence of streamflow data.

The risk analysis of reservoir regulation in the flood season is crucial and provides the valuable information for reservoir flood control, safety operation, and decision making, especially under climate change. The purpose of this study is to propose a framework for reasonably estimating the variation of reservoir regulation risk including the dam extreme risk and the overtopping risk during the flood season under climate change. The framework consists of an integrated diagnostic system for detecting the climate abrupt change time, a copula function-based bivariate statistical approach for modeling the dependence between the flood peak and flood volume, a Monte Carlo simulation for generating numerous random flood peak–volume pairs, and a risk calculation model for routing the design flood hydrographs to obtain the frequency curve of the maximum water level reached in front of dam and evaluating the reservoir regulation risk. The methodology was implemented in the Chengbihe reservoir in south China by using the 55-year (1963–2017) hydrometeorological data, including temperature, evaporation, precipitation, and streamflow, in the flood season. Results show that the hydrometeorological series during the flood season changed abruptly in 1992 and the entire data can be divided into two periods (1963–1992 and 1993–2017). The dam extreme risk and overtopping risk during the two periods are assessed, respectively, and a comparison analysis is made based on different flood limit water-level schemes (185.00–188.50 m). It demonstrates that both the dam extreme risk and the dam overtopping risk increase under the influence of climate change. The dam extreme risk increases by 22.91–95.03%, while the climate change-induced increase in the dam overtopping risk is between 38.62 and 123.59%, which indicates that the dam overtopping risk is more sensitive to climate change than the dam extreme risk. The risk evaluations in the study are of great significance in the safety operation and risk management of reservoirs under future climate change.

This study proposes a unified analytical framework for plotting design flood hydrographs (DFH) based on four characteristic parameters: total duration (Tt), time to peak (Tp), flood volume (W), and peak discharge (Qp) associated with specific exceedance probabilities. The objective is to improve the mathematical representation of hydrograph shapes for engineering applications and future updates of hydrological design standards. Leveraging a dataset of 150 representative cross-sections of Romanian rivers, the research employs normalized axes to facilitate a dimensionless comparative analysis. This study presents three modeling approaches: the Refined Rational Function (RRF), which significantly enhances the framework initially developed by Radu Cadariu; a [4/4] Padé approximant, transitioning from a second-degree to a fourth-degree rational framework and featuring a depressed quartic numerator and a fourth-degree denominator for superior degrees of freedom; and the plotting of non-parametric hydrographs via natural cubic spline interpolation. The results demonstrate that the RRF method extends the admissible range of the shape coefficient γ beyond the traditional interval 0.15–0.50, enabling representation of hydrographs with γ values up to 0.99. The [4/4] Padé approximant provides improved flexibility for asymmetric and multimodal hydrographs, while the natural cubic spline interpolation method ensures accurate reconstruction of atypical hydrographs with volume conservation errors below 3%. These methods offer a unified, objective framework, ensuring high accuracy and adaptability across diverse Romanian hydrological regimes.

Extreme floods have become common in Asian cities, with recent increases in urbanization and extreme rainfall driving increasingly severe and frequent events. Understanding the flood dynamic is essential for developing strategies to reduce risk and damage, thus ensuring the city’s protection. Channel roughness is a sensitive parameter in developing a hydraulic model for flood forecasting and flood inundation mapping. A High-resolution 2D HEC-RAS model was used to simulate the flood events of 1994, 1998, 2002, 2006, and 2015. The calibrated model, in terms of channel roughness, has been used to simulate the flood for the year 2006 in the river. The performance of the calibrated HEC-RAS-based model has been accessed by capturing the flood peaks of observed and simulated floods and computation of root mean squared error (RMSE) for the intermediated gauging stations on the lower Tapi River. Results revealed that there is good agreement between simulated and observed floods.

The design of a river-basin-specific flood hydrograph generator based on gauge records enables the generation of synthetic flood hydrographs for the dimensioning of hydraulic structures. Based on selected flow time series, flood waves can be described using four parameters based on flood characteristic simulations, as described by Leichtfuss and Lohr (1999). After successfully adapting suitable distribution functions, dependencies in the load structure are quantified in the next step using copula functions. This newly developed approach builds on the procedure proposed by Bender and Jensen (2012), which assumes hydrological independence. Using copula functions results in increased accuracy in the extended flood characteristic simulation. Moreover, considerable enhancements are achieved through the utilization of genetic algorithms, wherein the descending branch of the flood hydrograph is adjusted by employing an additional variable factor. Subsequently, any number of synthetic flood hydrographs can be generated by combining these parameters. In keeping with the principle of Monte Carlo simulation, a sufficiently high number of synthetic events results in extreme conditions with a low probability of occurrence being reliably represented. Hence, this endeavor has the potential to enhance result reproducibility and prediction quality. As a result, this expanded approach can be employed to provide dependable assessments regarding inflows aimed at optimizing reservoir capacity, for instance.