Extreme Flow Research Articles

Investigation of the impact of extreme flood flow on the Shatt Al-Arab River and Marsh system

Investigation of the impact of extreme flood flow on the Shatt Al-Arab River and Marsh system

The Past Is Never Dead: Soil Pollution from Mining in the Copiapó River Basin (Northern Chile)

This short paper analyses the concentrations of two major components (Fe, S) and eight trace elements (As, Au, Co, Cu, Hg, Ni, Mn, Zn) in soils and tailings from Tierra Amarilla (northern Chile) using ICP-Ms analysis. The levels of As, Au, Cu, Fe and S are very high and come from polymetallic sulphides from nearby mines, together with minor contributions of Co, Ni and Mn. Hg has its origin in the extreme seasonal flows of the Copiapó River, which erodes the dumps of old precious metal mines. These high concentrations require further analysis of possible metal immobilisation techniques, bioavailability or analysis in cultivated plants.

Evaluation of flood metrics across the Mississippi-Atchafalaya River Basin and their relation to flood damages.

Societal risks from flooding are evident at a range of spatial scales and climate change will exacerbate these risks in the future. Assessing flood risks across broad geographical regions is a challenge, and often done using streamflow time-series records or hydrologic models. In this study, we used a national-scale hydrological model to identify, assess, and map 16 different streamflow metrics that could be used to describe flood risks across 34,987 HUC12 subwatersheds within the Mississippi-Atchafalaya River Basin (MARB). A clear spatial difference was observed among two different classes of metrics. Watersheds in the eastern half of the MARB exhibited higher overall flows as characterized by the mean, median, and maximum daily values, whereas western MARB watersheds were associated with flood indicative of high extreme flows such as skewness, standardized streamflow index and top days. Total agricultural and building losses within HUC12 watersheds were related to flood metrics and those focused on higher overall flows were more correlated to expected annual losses (EAL) than extreme value metrics. Results from this study are useful for identifying continental scale patterns of flood risks within the MARB and should be considered a launching point from which to improve the connections between watershed scale risks and the potential use of natural infrastructure practices to reduce these risks.

Structural and hydrodynamic modelling of the probability of breakage of branching and plate coral colonies

Climate change is amplifying the intensity of severe weather events, with coastal regions such as coral reefs facing heightened vulnerability to cyclonic wave forces. Structural models to predict bending stress and breakage of corals have been developed for coral colonies to enhance comprehension and prediction of the effects of hydrodynamic disturbances on coral reefs. However, there is scope for improving these predictions by evolving the methodology for quantifying complicated and variable coral morphologies. This study aims to predict breakage thresholds for two of the most prevalent coral morphologies: branching and plate corals (using Acropora muricata and Acropora hyacinthus as study species). Laboratory and field measurements were taken to assess coral morphologies and material characteristics. Morphological features of 47 branching colonies and 100 plate colonies were surveyed at the study site (Heron Reef, southern GBR) and the tensile strength of 80 coral samples was obtained by in situ and laboratory testing. Three-dimensional structural models of branching and plate coral colonies were developed, encompassing multiple coral colonies with varying morphological patterns from relatively shallow (5-7 m) to deep (9-12 m) zones. Model results were calibrated and verified with existing data, revealing that velocity thresholds of 1.7 m/s and 5.0 m/s would destroy 90% of the simulated branching coral structures growing in the deep and shallow parts of the forereef zone, respectively. In contrast, the plate corals have sufficient margins of safety even in extreme flow conditions (7 m/s). Additionally, skeletal strength and structural performance were adjusted based on varying degrees of bioerosion inside the coral skeleton. A higher probability of breakage was observed as the extent of bioerosion increased. The laboratory experiments of hydrodynamic loads on coral colony show that the sheltering effect due to one or two neighbouring colonies in the upwave direction is negligible. These models can be easily adjusted to provide predictions for other coral species, shapes, levels of bioerosion, and locations (e.g., sheltered or exposed areas). Comprehensive predictions about the level of expected damage and rubble generation in different areas can be used in reef management planning and restoration prioritization.

Assessing hydrological changes in the Ganga River with the range of variability approach

ABSTRACT The study quantitatively assesses the hydrological alterations induced by the Luv Kush Barrage on the Ganga River, India, using the Range of Variability Approach (RVA) to analyze changes in flow conditions before and after the barrage construction. The Ganga River, a crucial water source for millions, has experienced significant hydrological changes due to human interventions, notably the construction of the Luv Kush Barrage. Employing indicators of hydrological alteration (IHAs), we compared pre-impact (1972–1994) and post-impact (2001–2014) flow data to ascertain the barrage’s effects on the river’s flow regime. Our findings reveal significant alterations in the magnitude of monthly streamflow, especially during the monsoon season, with notable decreases in July, August, and September. Alterations were observed in the annual extreme flow conditions, frequency, and duration of high and low pulses, indicating a comprehensive impact on the river’s natural flow patterns. These alterations affect the river’s ecological health, affecting aquatic habitats, fishery resources, and community livelihoods dependent on the river. The study underscores the necessity for integrated water resource management practices that consider the ecological and socio-economic implications of hydrological alterations.

Analysis of flow regime classification in the Omo-Gibe River Basin: insights into fluid dynamics in Ethiopia

ABSTRACT The study investigates flow regime in the Omo-Gibe River Basin to address hydrological complexity caused by precipitation and catchment features. Despite employing various methodologies, daily flow data highlight the need for a more comprehensive understanding of flow variability. The study aims to scrutinize flow regime classification, emphasizing the challenges posed by the basin's unique hydrological dynamics, with the ultimate goal of improving water management practices in the region. Using XLSTAT (Excel statistics software), the average base flow index (60.66%), zero flow index (0.25%), coefficient of variation (1.56%), and flashiness index (0.276%) were determined to be the primary hydrological indices that contributed to streamflow characterization. Finally, flow regime classification was described as non-perennial (13%) or perennial (87%) using the shape of the flow duration curve and this hydrological index. However, the magnitude of extreme flow events was judged depending on flow duration curve and calibrated by the flashiness index computed in the study. The study's findings serve as an input for streamflow regionalization and the foundation for future research on the ecology and hydrology of Ethiopia's river basins as well as the management of the water resources throughout the Omo-Gibe River Basin.

Microbial community storm dynamics signal sources of "old" stream water.

Accurate characterization of the movement of water through catchments, particularly during precipitation event response, is critical for hydrological efforts such as contaminant transport modeling or prediction of extreme flows. Abiotic hydrogeochemical tracers are commonly used to track sources and ages of surface waters but provide limited details about transit pathways or the spatial dynamics of water storage and release. Alternatively, biotic material in streams is derived from thousands of taxa originating from a variety of environments within watersheds, including groundwater, sediment, and upslope terrestrial environments, and this material can be characterized with genetic sequencing and bioinformatics. We analyzed the stable water isotopes (δ18O and δ2H) and microbiome composition (16S rRNA gene amplicon sequencing) of the Marys River of western Oregon, USA during an early season storm to describe the processes, storage, and flowpaths that shape surface water hydrology. Stable water isotopes (δ18O and δ2H) typified an event response in which stream water is composed largely of 'old' water introduced to the catchment before the storm, a common though not well understood phenomenon. In contrast, microbial biodiversity spiked during the storm, consisting of early- and late-event communities clearly distinguishable from pre-event communities. We applied concentration-discharge (cQ) analysis to individual microbial taxa and found that most Alphaproteobacteria sequences were positively correlated (i.e., were mobilized) with discharge, whereas most sequences from phyla Gammaproteobacteria and Bacteroidota were negatively correlated with discharge (i.e., were diluted). Source predictions using the prokaryote habitat preference database ProkAtlas found that freshwater-associated microbes composed a smaller fraction of the microbial community during the stream rise and a larger fraction during the recession, while soil and biofilm-associated microbes increased during the storm and remained high during recession. This suggests that the "old" water discharged during the storm was likely stored and released from, or passed through, soil- and biofilm-rich environments, demonstrating that this approach adds new, biologically derived tracer information about the hydrologic pathways active during and after this event. Overall, this study demonstrates an approach for integrating information-rich DNA into water resource investigations, incorporating tools from both hydrology and microbiology to demonstrate that microbial DNA is useful not only as an indicator of biodiversity but also functions as an innovative hydrologic tracer.

Wavelet optical flow velocimetry of a scramjet combustor using high-speed frame-straddling focusing schlieren images

Scramjet combustors feature ultra-high-speed turbulent reacting flows with high temperatures and intense luminescence. Measurement of velocity fields under such extreme conditions presents great challenges. The present work demonstrated a seedless velocimetry approach using focusing schlieren images (FSIs) of high spatiotemporal resolution in a scramjet engine. Two fuel mass flow rates (Case1 and Case2) were investigated with corresponding global equivalence ratios of 0.27 and 0.13, respectively. The FSIs enabled by the employment of a high-speed pulsed LED light source are characterized by an effective exposure of 100 ns, and a 500-ns frame-straddling time interval with full resolution of 1280 × 800 pixels recorded at 76 kHz. The 100-ns exposure allows for capturing of transient high-speed flow motion without blurring, and the 500-ns time interval ensures an appropriate spatiotemporal correlation between subsequent schlieren images for high-speed reacting flows. A wavelet-based optical flow velocimetry (wOFV) algorithm was developed and applied to the FSIs. In contrast to the correlation-based algorithms widely employed in PIV for distinct particles, the wOFV algorithm suits better FSIs with continuous variation in brightness. The maximal velocities in the main duct of the scramjet combustor were measured to be approximately 550 m s-1 and 1100 m s-1 for Case 1 and Case2, suggestively corresponding to subsonic and supersonic combustion modes, respectively. The measured velocity inside the cavity is generally below 200 m s-1 for both cases. Recirculation regions and their dynamic motions inside the cavity were well resolved. In summary, the development of the novel velocimetry approach holds great potential for applications in extreme flow conditions. Novelty and Significance Statement: Present work demonstrates a seedless velocimetry approach based on high-speed frame-straddling focusing schlieren imaging coupled with the novel wavelet optical flow velocimetry (wOFV) algorithm. Velocity field measurement realized in a scramjet combustor with high spatiotemporal resolution (1280 × 800 pixels at 38 kHz) for the first time, showing great abilities to accommodate wide velocity range and to resolve dynamic flow characteristics with potentials for broader future applications.

Monitoring of River Morphological Change Using Remote Sensing and Hec-Ras in Lusi River, Indonesia

Changes in river flow have become a natural cycle of the river. The Lusi River has problems with meanders due to sediment transport, which is difficult to control. A combination of GIS with RS and HEC-RAS simulation was used to monitor river flow. The water monitoring method utilizes four water indices: NDWI, MNDWI, ANDWI, and SAVI, while the MPM-Toffaleti method is used for simulation. By combining the four methods, accuracy values of 0.68 to 0.92 and precision levels of 0.60 to 0.93 were obtained. MNDWI obtained quite high results compared to other indices. The results showed that the Lusi Riverexperienced quite extreme flow changes. Two flow cuts occurred. Considerable erosion occurred from 2003 to 2013 with a total lost area of 0.1943 km2, while from 2013 to 2023, there was erosion of 0.1177 km2. The HEC-RAS simulation of the Lusi River experienced erosion of 60 to 70.4 percent of the length of the stream. Changes in the riverbed in 2013 were found to be -1.1 ± 2.03 m, and then in 2023, the range of changes in the riverbed was -2.69 ± 1.29 m. Based on the results of the index and simulation of the Lusi River experiencing erosion in the flow, the level of erosion has increased every period.

Continental Scale Regional Flood Frequency Analysis: Combining Enhanced Datasets and a Bayesian Framework

Flood frequency analysis at large scales, essential for the development of flood risk maps, is hindered by the scarcity of gauge flow data. Suitable methods are thus required to predict flooding in ungauged basins, a notoriously complex problem in hydrology. We develop a Bayesian hierarchical model (BHM) based on the generalized extreme value (GEV) and the generalized Pareto distribution for regional flood frequency analysis at high resolution across a large part of North America. Our model leverages annual maximum flow data from ≈20,000 gauged stations and a dataset of 130 static catchment-specific covariates to predict extreme flows at all catchments over the continent as well as their associated statistical uncertainty. Additionally, a modification is made to the data layer of the BHM to include peaks over threshold flow data when available, which improves the precision of the discharge level estimates. We validated the model using a hold-out approach and found that its predictive power is very good for the GEV distribution location and scale parameters and improvable for the shape parameter, which is notoriously hard to estimate. The resulting discharge return levels yield a satisfying agreement when compared with the available design peak discharge from various government sources. The assessment of the covariates’ contributions to the model is also informative with regard to the most relevant underlying factors influencing flood-inducing peak flows. According to the developed aggregate importance score, the key covariates in our model are temperature-related bioindicators, the catchment drainage area and the geographical location.

Data-driven transient lift attenuation for extreme vortex gust–airfoil interactions

We present a data-driven feedforward control to attenuate large transient lift experienced by an airfoil disturbed by an extreme level of discrete vortex gust. The current analysis uses a nonlinear machine-learning technique to compress the high-dimensional flow dynamics onto a low-dimensional manifold. While the interaction dynamics between the airfoil and extreme vortex gust are parametrized by its size, gust ratio and position, the wake responses are well captured on this simple manifold. The effect of extreme vortex disturbance about the undisturbed baseline flows can be extracted in a physically interpretable manner. Furthermore, we call on phase-amplitude reduction to model and control the complex nonlinear extreme aerodynamic flows. The present phase-amplitude reduction model reveals the sensitivity of the dynamical system in terms of the phase shift and amplitude change induced by external forcing with respect to the baseline periodic orbit. By performing the phase-amplitude analysis for a latent dynamical model identified by sparse regression, the sensitivity functions of low-dimensionalized aerodynamic flows for both phase and amplitude are derived. With the phase and amplitude sensitivity functions, optimal forcing can be determined to quickly suppress the effect of extreme vortex gusts towards the undisturbed states in a low-order space. The present optimal flow modification built upon the machine-learned low-dimensional subspace quickly alleviates the impact of transient vortex gusts for a variety of extreme aerodynamic scenarios, providing a potential foundation for flight of small-scale air vehicles in adverse atmospheric conditions.

The Impacts of Dams on Streamflow in Tributaries to the Lower Mekong Basin

The Lower Mekong Basin has had extensive hydropower dam development, which changes its hydrologic conditions and threatens the exceptional aquatic biodiversity. This study quantifies the degree of hydrologic change between pre-impact (1965–1968) and post-impact (2018–2021) peak hydropower development in two major tributaries of the Lower Mekong Basin—the Sekong River, with the fewest dams, and the Sesan River, with the most dams. Both rivers have historically supported migratory fishes. We used daily pre- and post-impact data and the Indicators of Hydrologic Alteration framework to evaluate streamflow changes from dam development. We found significant changes in low- and high-magnitude flows in the pre- and post-impact periods of dam development. For the Sekong River, minimum flow had large fluctuations, with increases of 290% to 412% compared to the pre-impact period, while the Sesan River’s minimum flow ranged from 120% to 160% more than pre-impact. Dry season flows increased by 200 ± 63% on average in the Sekong River, which was caused by releases from upstream dams. Meanwhile, the Sesan River’s dry season flows increased by 100 ± 55% on average. This study indicates that seasonal flow changes and extreme flow events occurred more frequently in the two basins following dam construction, which may threaten the ecosystem’s function.

The effects of flow extremes on native and non‐native stream fishes in Puerto Rico

Abstract Globally, freshwater fishes are among the taxa most vulnerable to climate change but are generally understudied in tropical island ecosystems where climate change is predicted to alter the intensity, frequency and duration of extreme flow events. These changes may impact stream ecosystems and native and non‐native biota in complex ways. We compiled an extensive dataset of fish assemblages collected at 119 sites across the Caribbean island of Puerto Rico from 2005 to 2015. We coupled these data with stream flow indices and dam height to understand associations between flow and fish assemblage structure. Sixteen percent of sites contained exclusively non‐native species, 34% contained exclusively native species, and 50% contained native and non‐native species. We built generalised linear models and conducted all subsets model selection to identify extreme flow variables explaining variation in native and non‐native species richness and biomass. We also built models to determine the combined effects of extreme flows and the presence of non‐native species on native species richness and biomass. Extreme flows and dam height were important in explaining variations in native and non‐native species richness and biomass. Model averages showed native biomass decreased by 0.42 kg/ha with a 1‐m increase in dam height, by 0.05 kg/ha with 1 cm/s increase in maximum mean daily high flow and by 3.45 kg/ha with each additional day increase in maximum high flow duration, and increased by 2.06 kg/ha with each additional day increase in mean high flow duration. Model averages predicted that non‐native biomass increased by 1.32 kg/ha with a 1‐m increase in dam height and by 0.01 kg/ha with each additional day increase in mean high flow duration, and decreased by 0.36 kg/ha with each additional day increase in maximum high flow duration. Model averages also predicted an increase in native and non‐native biomass of 0.71 gage and 0.06 kg/ha, respectively, with each additional day increase in maximum low flow duration. The combined effects of non‐native species presence and extreme flows changed the relationship between maximum high and low flow durations and native biomass. Model averages showed that native biomass increased by 1.83 kg/ha with each additional day increase in maximum high flow duration and decreased by 2.52 kg/ha with each additional day increase in maximum low flow duration when non‐native species were present. Native fishes may be able to better cope with longer maximum durations of low flows than expected when non‐native fishes are absent. In mixed fish assemblages, extended maximum durations of high flows may act as a control of non‐native species and dampen their negative effect on native species, but longer maximum durations of low flows may heighten the negative effects of non‐native fishes. Our results are informative for tropical island ecosystems globally and can guide the management and conservation of native fishes, particularly when faced with the dual threats of climate change and non‐native species. Managers may consider increasing efforts to conserve native fishes in Caribbean rivers by maintaining connectivity and habitat complexity while preventing non‐native species introductions.

Influence of corrugated tube structure and flow rate on the hydrogen absorption performance of metal hydride reactor and structural optimization

The metal hydride bed (MHB) reactor is an effective instrument for storing hydrogen. However, thermal stress causes the cooling tube expansion inside the MHB. The long-term effects will lead to the failure of the cooling tube. To absorb the thermal stress and reduce the deformation of the cooling tubes, this article establishes an MHB reactor with corrugated cooling tubes to study its hydrogen absorption performance. The results prove that some parameters are adversarial and flow rate patterns are complex (such as extreme flow rate and insufficient flow rate) in the hydrogen absorption process of the corrugated tube MHB reactor, which makes it impossible to optimize the structure of the corrugated tube through the gradient method. Under the condition of a fixed corrugated tube volume of 3×10−6m3 and a cooling water volumetric flow rate of 0.5×10−4m3/s, the structural parameters of the corrugated tube are optimized by the Monte Carlo algorithm. According to the optimized results (N=8, ro=4.25 mm, ri=3.98 mm, do=3.17 mm, di=4.33 mm), the hydrogen absorption efficiency of the corrugated tube MHB reactor (reaction fraction 0.758) is 1.36 times that of the straight tube (reaction fraction 0.557) at 560 s. Thus, the corrugated tube can reduce thermal stress and improve the heat transfer effect. This research is beneficial in improving long-term stability, enhancing operational efficiency, and reducing the volume and weight of large MHB reactors.

Enhancing hydrological data completeness: A performance evaluation of various machine learning techniques using probabilistic fusion imputer with neural networks for streamflow data reconstruction

The present-day accessibility of streamflow data, particularly in the developing countries, is often marked by a multitude of data shortfalls or distortions. This study investigates the estimate of missing streamflow data using machine learning approaches, including K-nearestneighbour (KNN), Predictive Mean Matching (PMM), Random Forest (RF) and a novel technique of Probabilistic Fusion Imputer with Neural Networks (PROFINN). This study tackles the issue of data insufficiency in such time series considering the inclusion of numerous hydrological parameters by means of RF feature selector, to determine the most significant ones among them. The study explores the efficacy of selected models on various data gaps under different hydrological scenarios, including diverse flow characteristics (mean, high and low flows) and gap lengths (long and short gaps, continuous and discontinuous gaps) and presents a pattern of ranking system that assesses the level of suitability of each technique for various data gaps. This study underscore PROFINN’s remarkable performance across all scenarios, yielding an average Root Mean Square Error (RMSE) of 0.91 and an average Nash-Sutcliffe Efficiency (NSE) value of 0.93 when applied for an intermittent river system of Pamba in Southern Kerala, India. RF follows PROFINN in the imputation of extreme flows as well as long and short gap scenarios. KNN closely follows PROFINN for the imputation of continuous and discontinuous gap scenarios. This study augments the significance of tailored machine learning techniques in enhancing the integrity of hydrological datasets, offering valuable insights for effective decision-making in water resource management and related fields. Furthermore, the success of PROFINN in streamflow data imputation suggests its potential extension to other hydrological research domains, like historical data reconstruction assisting climate change studies and future water resources planning, emphasizing the broader relevance and applicability of this study’s findings.

Investigating the utility of satellite-based precipitation products for simulating extreme discharge events: an exhaustive model-driven approach for a tropical river basin in India.

Satellite-based precipitation estimates are a critical source of information for understanding and predicting hydrological processes at regional or global scales. Given the potential variability in the accuracy and reliability of these estimates, comprehensive performance assessments are essential before their application in specific hydrological contexts. In this study, six satellite-based precipitation products (SPPs), namely, CHIRPS, CMORPH, GSMaP, IMERG, MSWEP, and PERSIANN, were evaluated for their utility in hydrological modeling, specifically in simulating streamflow using the Variable Infiltration Capacity (VIC) model. The performance of the VIC model under varying flow conditions and timescales was assessed using statistical indicators, viz., R2, KGE, PBias, RMSE, and RSR. The findings of the study demonstrate the effectiveness of VIC model in simulating hydrological components and its applicability in evaluating the accuracy and reliability of SPPs. The SPPs were shown to be valuable for streamflow simulation at monthly and daily timescales, as confirmed by various performance measures. Moreover, the performance of SPPs for simulating extreme flow events (streamflow above 75%, 90%, and 95%) using the VIC model was assessed and a significant decrease in the performance was observed for high-flow events. Comparative analysis revealed the superiority of IMERG and CMORPH for streamflow simulation at daily timescale and high-flow conditions. In contrast, the performances of CHIRPS and PERSIANN were found to be poor. This study highlights the importance of thoroughly assessing the SPPs in modeling diverse flow conditions.

3D Simulation of an Extreme SAID Flow Channel

AbstractSpace‐based observations of the signatures associated with STEVE show how this phenomenon might be closely related to an extreme version of a SAID channel. Measurements show high velocities (>4 km/s), high temperatures (>4,000 K), and very large current density drivers (up to 1 μA/m2). This phenomena happens in a small range of latitudes, less than a degree, but with a large longitudinal span. In this study, we utilize the GEMINI model to simulate an extreme SAID/STEVE. We assume a FAC density coming from the magnetosphere as the main driver, allowing all other parameters to adjust accordingly. We have two main objectives with this work: show how an extreme SAID can have velocity values comparable or larger than the ones measured under STEVE, and to display the limitations and missing physics that arise due to the extreme values of temperature and velocity. Changes had to be made to GEMINI due to the extreme conditions, particularly some neutral‐collision frequencies. The importance of the temperature threshold at which some collision frequencies go outside their respective bounds, as well as significance of the energies that would cause inelastic collisions and impact ionization are displayed and discussed. We illustrate complex structures and behaviors, emphasizing the importance of 3D simulations in capturing these phenomena. Longitudinal structure is emphasized, as the channel develops differently depending on MLT. However, these simulations should be viewed as approximations due to the limited observations available to constrain the model inputs and the assumptions made to achieve sensible results.

Climate Driven Trends in Historical Extreme Low Streamflows on Four Continents

AbstractUnderstanding temporal trends in low streamflows is important for water management and ecosystems. This work focuses on trends in the occurrence rate of extreme low‐flow events (5‐ to 100‐year return periods) for pooled groups of stations. We use data from 1,184 minimally altered catchments in Europe, North and South America, and Australia to discern historical climate‐driven trends in extreme low flows (1976–2015 and 1946–2015). The understanding of low streamflows is complicated by different hydrological regimes in cold, transitional, and warm regions. We use a novel classification to define low‐flow regimes using air temperature and monthly low‐flow frequency. Trends in the annual occurrence rate of extreme low‐flow events (proportion of pooled stations each year) were assessed for each regime. Most regimes on multiple continents did not have significant (p < 0.05) trends in the occurrence rate of extreme low streamflows from 1976 to 2015; however, occurrence rates for the cold‐season low‐flow regime in North America were found to be significantly decreasing for low return‐period events. In contrast, there were statistically significant increases for this period in warm regions of NA which were associated with the variation in the Pacific Decadal Oscillation. Significant decreases in extreme low‐flow occurrence rates were dominant from 1946 to 2015 in Europe and NA for both cold‐ and warm‐season low‐flow regimes; there were also some non‐significant trends. The difference in the results between the shorter (40‐year) and longer (70‐year) records and between low‐flow regimes highlights the complexities of low‐flow response to changing climatic conditions.

Comparative Study of Low Flow Frequency Analysis Using Bivariate Copula Model at Soyanggang Dam and Chungju Dam

A univariate analysis that relies solely on precipitation data in low flow frequency analysis is a technique to express meteorological drought, so it is limited to analyzing the characteristics of hydrological drought related to available water resources. In addition, if the data for the model calibration are insufficient, the uncertainty of a single variable limits the construction of a reliable model. To improve this problem, a frequency analysis was performed by constructing a bivariate copula model as a multivariate model with a high correlation between variables targeting reservoir inflows. The methodology utilizes the theory of runs to identify low flow events, establishing a threshold based on the mandatory regional water supply plan, and determining the low flow duration and cumulative water deficit. The Gumbel copula function, effective in capturing correlations between hydrological variables, was applied to derive a joint bivariate probability distribution, facilitating the calculation of combined low flow event return periods. This study compared low flow frequencies at Soyanggang dam (’74–’22) and Chungju dam (’86–‘22), which are in the same Han River basin but have different capacities and water demands, using a bivariate copula model. The top four extreme low flow events for the two adjacent dam basins did not occur in the same year and, in the years of the extreme low flow events at one of the two dam basins, there was an insignificant magnitude at the remaining dam basin. This result is noteworthy because it shows that the possibility of extreme low flow events appearing simultaneously in both watersheds is not as high as expected. The operational efficiency can be improved by setting the coordinated operation rules of the two reservoirs using the copula dependency structure.

Multi-decadal floodplain classification and trend analysis in the Upper Columbia River valley, British Columbia

Abstract. Floodplain wetland ecosystems experience significant seasonal water fluctuation over the year, resulting in a dynamic hydroperiod, with a range of vegetation community responses. This paper assesses trends and changes in land cover and hydroclimatological variables, including air temperature, river discharge, and water level in the Upper Columbia River Wetlands (UCRW), British Columbia, Canada. A land cover classification time series from 1984 to 2022 was generated from the Landsat image archive using a random forest algorithm. Peak river flow timing, duration, and anomalies were examined to evaluate temporal coincidence with observed land cover trends. The land cover classifier used to segment changes in wetland area and open water performed well (kappa of 0.82). Over the last 4 decades, observed river discharge and air temperature have increased, precipitation has decreased, the timing of peak flow is earlier, and the flow duration has been reduced. The frequency of both high-discharge events and dry years have increased, indicating a shift towards more extreme floodplain flow behavior. These hydrometeorological changes are associated with a shift in the timing of snowmelt, from April to mid-May, and with seasonal changes in the vegetative communities over the 39-year period. Thus, woody shrubs (+6 % to +12 %) have expanded as they gradually replaced marsh and wet-meadow land covers with a reduction in open-water area. This suggests that increasing temperatures have already impacted the regional hydrology, wetland hydroperiod, and floodplain land cover in the Upper Columbia River valley. Overall, there is substantial variation in seasonal and annual land cover, reflecting the dynamic nature of floodplain wetlands, but the results show that the wetlands are drying out with increasing areas of woody/shrub habitat and loss of aquatic habitat. The results suggest that floodplain wetlands, particularly marsh and open-water habitats, are vulnerable to climatic and hydrological changes that could further reduce their areal extent in the future.