Annual Minimum Flow Research Articles

Non-stationary models for hydrological extremes in the mountain rivers of the Argentinean Central Andes

ABSTRACT The assessment of extreme hydrological events relies on the assumption that time series are independent and identically distributed. However, empirical evidence contradicts this assumption, indicating the presence of nonstationarity, including trends, step changes, or both, in the river records of the Argentinean Central Andes. This study proposes the use of generalized additive models in location, scale and shape (GAMLSS) to model the annual maximum and minimum flow of seven rivers. Firstly, the presence of trends and step changes was assessed. Subsequently, the models were formulated considering time and various climatic indices as covariates. The findings reveal declining trends and negative jumps over the past 50 to 70 years. The location parameters of the models exhibit linear or smoothing dependence with time or climate indices covariates. Different modes of climate variability are associated with hydrological extremes. The nonstationary models provide a novel complementary framework for water resource planning in the region.

Spatial Variability of Average Annual and Monthly Minimum River Flow in Poland

The aim of this article is to analyse the spatial variability of SNQ, the average annual minimum river flow, as well as SNQm (m = 1, 2, …12), the average monthly minimum river flow in Poland. The data were obtained from the Institute of Meteorology and Water Management – National Research Institute (IMWM-NRI) in the form of the daily flow series from the period between 01 Nov 1990 and 31 Oct 2020 from 433 gauging cross-sections located within the territory of Poland. The results of the analyses are presented on maps of the physiographic regions of Poland (the Coastlands, the Lakelands, the Lowlands, the Highlands, the Carpathians and the Sudety Mountains). In order to compare SNqm – the unit average minimum monthly flow between the physiographic regions, the Kruskal-Wallis test with the Dunn (Bonferroni) adjustment was performed. In order to evaluate the spatial variability of the SNqm, the hypothesis was verified for each gauging station that the Spearman correlation coefficient between the SNqm and the zero point of the gauge was different from zero. The SNqm flow changed over the year. As expected, the highest values were observed in March and April, and the lowest in July and August. Regardless of the month, the rivers in the central part of Poland (the Lowlands) were less water abundant than those in other regions of the country while the greatest flows were observed in the mountain rivers. Statistically, no difference was observed between the SNqm in the Coastlands, the Carpathians and the Sudety Mts., and in nearly all of the months between the SNqm in the Lakelands and the Lowlands. In the whole territory of Poland, the river flow was dependent on the altitude of the catchment, while the strongest correlation was observed in the mountain regions.

Prospective analysis of low flows in a climate change context in West Africa: case of the N’zo-Sassandra watershed (West of Côte d’Ivoire)

The objective of this study is to analyze the prospective of the low water flows of the N'zo-Sassandra River located in the West of Ivory Coast. The hydroclimatic data used (rainfall, ETP, flow) extend on the one hand over the historical period (1961-2017) and on the other hand over the future period 2071-2100 (CORDEX data). The methodological approach adopted is based on the analysis of past low flows, the climate prospective analysis and the hydrological prospective analysis. The hydrological impact variable used is the annual minimum monthly mean flow (MAMF). Thus, a pessimistic climate forecast scenario was used (RCP 8.5.). This climate scenario was then fed into a rainfall-runoff hydrological model (GR2M model) calibrated to the 1961-1990 reference period and validated over the 1991-2017 period. In response to the climate forcing, future monthly low-flow rates (MAMF) were simulated. An increase in the number of flows in the class ]0-4] m3/s was observed, reflecting low flows in the 2071–2100-time frame. The best statistical law retained following the frequency analysis of the low-water flows is the lognormal law. By 2071-2100, a decrease in rainfall (-19.2%) and an increase in temperature (+3.9°C) are predicted in the N'zo-Sassandra watershed. Frequent low-water flows estimated from the lognormal law have shown a bias of -50.38%, which translates into a decrease of half of the frequent low-water flows by the end of the 21st century compared to the current period. This decrease in flows will have consequences on the availability of water resources for irrigation, fishing, breeding, drinking water supply, navigation, etc. This is why we propose as alternative resources for agricultural needs, groundwater which is less impacted by global changes.

Hydrology and hydrological extremes under climate change scenarios in the Bosque watershed, North-Central Texas, USA

This study evaluates hydrology and hydrological extremes under future climate change scenarios. The climate change scenarios were developed from multiple Global Circulation Models (GCMs), Representative Concentration Pathway (RCP) scenarios, and statistical downscaling techniques. To ensure hydrological model robustness, the Soil Water Assessment Tool (SWAT) was calibrated and validated using the Differential Split Sample Test (DSST) approach. The model was also calibrated and validated at the multi-gauges of the watershed. Future climate change scenarios revealed a reduction in precipitation (in the order of −9.1% to 4.9%) and a consistent increase in maximum temperature (0.34°C to 4.10°C) and minimum temperature (−0.15 °C to 3.7°C) in different climate model simulations. The climate change scenarios triggered a reduction of surface runoff and streamflow and a moderate increase in evapotranspiration. Future climate change scenarios projected a decrease in high flow (Q5) and low flow (Q95). A higher reduction of Q5 and annual minimum flow is also simulated in future climate scenarios, whereas an increase in annual maximum flow is simulated in climate change scenarios developed from the RCP8.5 emission scenario. The study suggests optimal water management structures which can reduce the effect of change in high and low flows.

Hydrological Drought Frequency Analysis in Water Management Using Univariate Distributions

The study of extreme phenomena in hydrology generally involves frequency analysis and a time series analysis. In this article we provide enough mathematics to enable hydrology researchers to apply a wide range of probability distributions in frequency analyses of hydrological drought. The article presents a hydrological drought frequency analysis methodology for the determination of minimum annual flows, annual drought durations and annual deficit volumes for exceedance probabilities common in water management. Eight statistical distributions from different families and with different numbers of parameters are used for the frequency analysis. The method of ordinary moments and the method of linear moments are used to estimate the parameters of the distributions. All the mathematical characteristics necessary for the application of the eight analyzed distributions, for the method of ordinary moments and the method of linear moments, are presented. The performance of the analyzed distributions is evaluated using relative mean error and relative absolute error. For the frequency analysis of the annual minimum flows, only distributions that have a lower bound close to the annual minimum value should be used, a defining characteristic having the asymptotic distributions at this value. A case study of hydrological drought frequency analysis is presented for the Prigor River. We believe that the use of software without the knowledge of the mathematics behind it is not beneficial for researchers in the field of technical hydrology; thus, the dissemination of mathematical methods and models is necessary. All the research was conducted within the Faculty of Hydrotechnics.

RiTiCE: River Flow Timing Characteristics and Extremes in the Arctic Region

(1) Background: river ice has a significant impact on nearly 66% of rivers in the Northern Hemisphere. Ice builds up during winter when the flow gradually reduces to its lowest level before the spring melt is initiated. Ice-induced floods can happen quickly, posing a risk to infrastructure, hydropower generation, and public safety, in addition to ecological repercussions from the scouring and erosion of the riverbeds. (2) Methods: we used the annual daily hydrograph to develop a RiTiCE tool that detects the break-up date and develops indices to analyze timing characteristics of extreme flow in the Tana and Tornio Rivers. (3) Results: the study showed that low-flow periods in two rivers had a significant trend with a confidence level of 95%. Additionally, it was observed that the occurrence date of seasonal 90-day low- and high-flow periods occurred earlier in recent years. Conversely, the Tana River showed a negative trend in its annual minimum flow over the century, which is the opposite of what happened with the Tornio River. (4) Conclusions: the method can be used to detect the date when the river ice breaks up in a given year, leading to a better understanding of the river ice phenomenon.

Plotting Position for Low Flow Frequency Analysis at Jempol River Streamflow Station

Low flow frequency analysis is an important technique for calculating the probability of river flow availability during crucial low flow seasons, such as drought. It is also useful to predict the low flow information of a river in volume and frequency for future planning and construction of water resource projects since the low flow has a significant impact on water quality, water supply, and river sustainability conditions. Therefore, this study was performed to determine the low flow frequency analysis of the Jempol River streamflow station using Weibull and Gringorten plotting position formulas. The average recurrence interval (ARI) of 2-, 5-, 10-, 25-, 50-, and 100-year were determined based on 18 years of historical streamflow data. The study illustrates the annual minimum flow magnitude of 1-, 4-, 7-, and 30-day durations for the study area. It shows that the Gringorten formula tends to give higher estimation values up to 18% compared to the Weibull formula when the flow duration increase. Therefore, the outcome of this study could be used in the future for any project related to the low flow information of Jempol River.

The Dynamics of Hydrological Extremes under the Highest Emission Climate Change Scenario in the Headwater Catchments of the Upper Blue Nile Basin, Ethiopia

Climate change and its impact on surface runoff in the upper Blue Nile basin and sub-basins have been widely studied in future climate projections. However, the impact on extreme flow events of rivers is barely investigated discretely. In this paper, the change in temperature and rainfall under the Representative Concentration Pathway (RCP) highest emission scenario (RCP 8.5) and its impact on the high flow and low flow simulated by the Soil and Water Assessment Tool (SWAT 2012) in major watersheds of the Lake Tana Basin has been evaluated by comparing the baseline period (1971–2000) with the 2020s (2011–2040), 2050s (2041–2070), and 2080s (2071–2100). The high flows of watersheds were selected by the Annual Maximum Series (AMS) model, whereas the low-flow watersheds were selected by the 7-day sustained mean annual minimum flow method. The result showed that the highest change in maximum temperature ranged from 2.93 °C to 5.17 °C in monthly time scales in the 2080s. The increment in minimum temperature is also more prominent in the 2080s and it is expected to rise by 4.75 °C. Inter-annual variability of the change in rainfall has shown increasing and decreasing patterns. The highest increments are expected by 22.37%, 25.58%, and 29.75% in the 2020s, 2050s, and 2080s, respectively, whereas the projected highest decrease in rainfall dictates the decrease of 6.42%, 7.11%, and 9.26% in 2020s, 2050s, and 2080s, respectively. Due to changes in temperature and rainfall, the low flow is likely to decrease by 8.39%, 8.33%, 6.21%, and 5.02% in Ribb, Gumara, Megech, and Gilgel Abay watersheds, respectively, whereas the high flow of Gilgel Abay, Megech, Gumara, and Ribb watersheds are expected to increase by 13.94%, 12.16%, 10.90%, and 10.24%, respectively, every 30 years.

A century of variations in extreme flow across Finnish rivers

River flow in cold climates is known to be one of the hydrological systems most affected by climate change, playing a central role in the sustainability of downstream socio-ecological systems. Numerous studies on the temporal and spatial variations of streamflow characteristics have been done, and a comprehensive study on the variation of hydrologic extremes is becoming increasingly important. This study evaluated the long-running changes in the magnitude, time, and inter-annual variability of hydrologic extremes, including high and low flow in 16 major Finnish rivers. We applied four new hydrologic extreme indices for summer–winter low flow ratio, spring-absolute high flow ratio, time-to-peak index, and increasing rate index during the snowmelt period to analyze the spatiotemporal variations of extreme streamflow from 1911 to 2020. The most detected trends in flow regimes have started in the last six decades and become more severe from 1991 to 2020, which is likely to be dominated by anthropogenic global warming. The results also indicated that alteration of low pulses in most rivers was associated with an increase (decrease) in winter (summer) flows, suggesting the annual minimum flow in summer frequently contradicts natural hydrologic regimes in Arctic rivers. Southern Finland has experienced higher variations in extreme hydrology over the last century. A new low flow regime was detected for southern rivers, characterized by frequent annual minimum flow in summer instead of winter. Moreover, the annual maximum flow before/after spring dictated a new high-flow regime characterized by frequent double peak flows in this region.

Comprehensive low-flow analysis of the Vipava river

The article presents the results of the analysis of low flows at 5 gauging stations on the Vipava River, which has a Dinaric pluvial-nival regime (catchment area of 590 km2). The low-flow statistics show that the gauging station Vipava stands out with the lowest values. Baseflow index (BFI) values are comparable among the considered stations and are around 0.40. Relatively low BFI values indicate low soil permeability. A high similarity between the mean annual minimum 7-day flow (MAM7) and the 95th percentile exceedance discharge (Q95) at all gauging stations indicates a temperate climate. The highest flows values occur in spring and autumn, and the lowest in summer. In wet years there are relatively large fluctuations in flow, while in dry years the flow consists mainly of baseflow. This is also confirmed with the flow duration curves analysis. The seasonality analysis shows a predominant summer regime with low flows.

Trends of extreme flows of the Krishna river at a barrage, India

ABSTRACT The present study analyzes trends of extreme flows for the Krishna river at the Prakasam barrage, Vijayawada of Andhra Pradesh state, India. Annual maximum and minimum flows are considered using available data from the CWC (Central Water Commission) portal from 1965–1966 to 2019–2020. The trend analysis of extreme flows is carried out using the Mann-Kendall trend test, Sen’s slope, and modified Mann-Kendall test, that is, bootstrapped Mann-Kendall trend test with optional bias-corrected pre-whitening. Also, R programming is applied for the trend analysis of extreme flows. Extreme annual flows are in decreasing trend. Annual maximum flow has significant decreasing trend with Sen’s slope of 105.52 cumecs per year. Annual minimum flow has insignificant decreasing trend at a magnitude of 0.0002 cumecs per year. Trend results of the present study are useful for the trend analysis of extreme river flows.

Latitudinal variation in freshwater mussel potential maximum length in Eastern North America

Abstract As body size often predicts energetic requirements and fecundity, understanding the drivers behind size variation is important. Neo‐Bergmann's rule states that larger individuals are found at higher latitudes and this size variation is attributable to temperature gradients. In ectotherms, this macroecological pattern has mixed support within the literature—both the direction and mechanism of size correlation with latitude varies. We asked if two species of freshwater mussels with different thermal niche preferences, Amblema plicata and Lampsilis cardium, follow neo‐Bergmann's rule and what mechanisms might drive that latitudinal variation. Lampsilis cardium is a thermally sensitive species intolerant of high temperatures, and A. plicata is more tolerant of a wide range of temperatures. We predicted that the thermally sensitive species at southern latitudes would have stunted growth in the summer and that this stunting would produce a steeper relationship with latitude than in the thermally tolerant species. We collected and thin‐sectioned 113 A. plicata shells from 23 sites and 85 Lampsilis cardium shells from 12 sites across a latitudinal gradient in the eastern U.S.A. We used back‐calculated size‐at‐age data to determine logistic growth parameters for each taxon across this gradient. We used Bayesian model selection to evaluate how environmental information correlated with potential maximum size. We found that both mussel species reached a larger potential maximum size at higher latitudes, with the thermally sensitive species having the larger increase in potential maximum size across the gradient when compared to the thermally tolerant species. Average annual water temperature explained mussel potential maximum size better than annual catchment precipitation, annual minimum flow ratio, and species identity. Both increased average water temperature and annual catchment precipitation, two predicted outcomes of climate change, were associated with smaller potential maximum size. Reductions in mussel maximum size due to climate change induced shifts in temperature regimes and precipitation patterns could lead to reduced reproductive output of this threatened guild and subsequent changes in ecosystem function and services, such as decreased biofiltration. As climate change alters precipitation patterns and stream productivity, and increases water temperature, understanding size variation and its cause in aquatic organisms will be important for managing these vulnerable populations.

Spatial and Temporal Patterns of Low-Flow Changes in Lowland Rivers

At the beginning of the 21st century, ongoing climate change led to research into extreme streamflow phenomena. This study aimed to assess the patterns of low-flow changes in different hydrological regions of Lithuania using selected hydrological indices (the annual minimum 30-day flow (m3 s−1) of the warm period—30Q), its duration, and deficit volume (below the 80th and 95th percentile flow: 30Q80 and 30Q95). Differences in low-flow indices in separate hydrological regions and over different periods (1961–2020, 1961–1990, 1991–2020) were analyzed, applying the HydroOffice tool, the TREND software package, and mapping using the Kriging interpolation. The highest specific indices of 30Q were estimated in the Southeastern hydrological region (3.97 L/s·km2) and the lowest in the Central hydrological region (1.47 L/s·km2). In general, the 30Q values in the periods 1961–2020 and 1991–2020 had no trends. In 1961–1990, trends in 30Q data were significantly positive, and positive in most investigated rivers of the Western and Central hydrological regions. The average number of dry days at both thresholds decreased in the Western and Southeastern hydrological regions and increased in the Central hydrological region comparing two subperiods.

Achieving sustainable low flow using hydropower reservoir for ecological water management in Glomma River Norway

Generally, low flow in rivers occur as a result of extended period of dryness which is likely attributed to drought. Drought is a natural occurrence as an outcome of reduction in precipitation in a region for a long time. Hence, low flow is a growing concern as there are possibilities of more reduced flows in rivers. However, reservoirs can be utilized to mitigate negative effects on the supply of water in dry periods and supply water for other purposes. This study aims at verifying how the low flow condition of Glomma River in Norway has been progressively sustained by hydropower reservoirs. Water Evaluation and Planning Systems (WEAP) software was used for modelling the natural streamflow condition of Glomma River, which is the longest river in Norway, using two unregulated sub-basins within the Glomma catchment. Findings from this study presents that the period between January and March are critical periods in Glomma River. Results show that the values the annual minimum low flow gotten from the three gauges suggest the flow after regulation has increased significantly as opposed to before regulation. The daily average flow is simulated by WEAP to be an average of 100 m3/s during the low flow periods and an average discharge of 350 m3/s during the summer. However, the result indicates that the flow in the summer has reduced by 80% in majority of the years. In addition, Nash Sutcliffe efficiency (NSE) for the two sub basins used for this study was 0.9 and 0.76, respectively. Also, the calculation of the coefficient of determination (R2) resulted in 0.85 and 0.78 respectively for the two sub basins. In particular, findings from this study presents evidence on the low flow condition in Glomma River prior to its regulation and how the regulation has sustained the flow.

Investigation of the Long-Term Trends in the Streamflow Due to Climate Change and Urbanization for a Great Lakes Watershed

Climate change and rapid urbanization could possibly increase the vulnerability of the Great Lakes Basin, Canada, which is the largest surface freshwater system in the world. This study explores the joint impact of climate change and land-use changes on the hydrology of a rapidly urbanizing Credit River watershed which lets out into Lake Ontario 25 km southwest of downtown Toronto, Ontario (ON), Canada; we began by classifying the watershed into urban and rural sections. A non-parametric Mann–Kendall test and the Sen slope estimator served to detect and describe the annual-, seasonal-, and monthly-scale trends in the climate variables (temperature, precipitation, and evapotranspiration), as well as the streamflow characteristics (median annual streamflow, baseflow, Runoff Coefficients (RC), Flow Duration Curve (FDC), Center of Volume (COV), and Peak Over Threshold (POT)) since 1916 for four rural and urban sub-watersheds. The temperature, precipitation and evapotranspiration (1950–2019) showed significant increasing trends for different months and seasons. Furthermore, the results indicated that the median annual streamflow, 7-day annual minimum flow, and days above normal are increasing; meanwhile, the annual maximum streamflow is decreasing. A total of 230 datasets were tested for their trends; of these, 80% and 20% increasing and decreasing trends were obtained, respectively. Of the total, significant trends (<0.05%) of 32% and 2% increasing and decreasing, respectively, were observed. The results of the FDC analysis indicated a decline in the annual and winter 10:90 exceedance ratio over the years for the rural and urban sub-watershed gauges. The BFI results show that the BFI of the rural areas was, on average, 18% higher than that of the urban areas. In addition, the RC also showed the influence of land-use and population changes on the watershed hydrology, as the RC for the urban gauge area was 19.3% higher than that for the rural area gauge. However, the difference in the RC was the lowest (5.8%) in the summer. Overall, the findings from this study highlight the annual, seasonal, and monthly changes in the temperature, precipitation, evapotranspiration, and streamflow in the watershed under study. Based on the available monitored data, it was difficult to quantify the changes in the streamflow over the decade which were attributable to population growth and land-cover use and management changes due to municipal official planning in the watershed.

A multi‐scale study of the dominant catchment characteristics impacting low‐flow metrics

AbstractLow flows can impact water use and instream ecology. Therefore, reliable predictions of low‐flow metrics are crucial. In this study, we assess which catchment characteristics (climate, topography, geology and landcover) can explain the spatial variability of low‐flow metrics at two different scales: the regional scale and the small headwater catchment scale. For the regional‐scale analysis, we calculated the mean 7‐day annual minimum flow (qmin), the mean of the flow that is exceeded 95% of the year (q95), and the master recession constant (C) for 280 independent gauging stations across the Swiss Plateau and the Swiss Alps for the 2000–2018 period. We assessed the relation between 44 catchment characteristics and the three low‐flow metrics based on correlation analysis and a random forest model. Low‐flow magnitudes across the Swiss Plateau were positively correlated with the fraction of the area covered by sandstone bedrock or alluvium, and with the area that has a slope between 10° and 30°. Across the Swiss Alps, low‐flow magnitudes were positively correlated with the fraction of area with slopes between 30° and 60°, and the area with glacial deposits and debris cover. There was good agreement between observations and predictions by the random forest regression model with the top 11 catchment characteristics for both regions: for 80% of the Swiss Plateau catchments and 60% of the Swiss Alpine catchments, we could predict the three low‐flow metrics within an error of 30%. The residuals of the regression model, however, varied across short distances, suggesting that local catchment characteristics affect the variability of low‐flow metrics. For the local‐scale headwater catchments, we conducted 1‐day snapshot field campaigns in 16 catchments during low‐flow periods in 2015 and 2016. The measurements in these sub‐catchments also showed that areas with sandstone bedrock and a good storage‐to‐river connectivity had above average low‐flow magnitudes. Including knowledge on local catchment characteristics may help to improve regional low‐flow predictions, however, not all local catchment characteristics were useful descriptors at larger scales.

Seasonality and Drivers of Low Flows Across Europe and the United States

AbstractLow river flows can negatively impact society and the riverine environment. Thus, it is useful to predict their seasonal timing and reveal their main drivers. The typical timing of low flows varies between regions, yet systematic overviews across Europe and the United States are rare. Here, we identify regional patterns of the seasonal timing of annual minimum flows, and the consistency of that timing, across 1860 European and US catchments. Catchments where low flows typically occur during late summer or winter tend to have more consistent low‐flow timings. We compare the timing of annual low flows with that of potential climatic drivers. Low flows in 89% of the European and 86% of the US catchments exhibit a statistically significant (p < 0.05) overlap in timing with at least one potential climatic driver. In most catchments, low flows tend to occur during the warm season, reflecting a period of high potential evapotranspiration exceeding precipitation. In the higher elevation European Alps, Scandinavia, the Rocky Mountains, and the Upper Midwest and Plains states, low flows mostly occur during winter as a result of freezing temperatures which inhibit snowmelt. Binomial statistics also enabled us to statistically exclude individual climatic drivers for certain regions. The regional patterns of timings and drivers of low flows across Europe and the contiguous US can inform low‐flow management, provide context for the evolution of low flows under climate change, and point to processes that require attention in future low‐flow research.

Comparison of Generalized Extreme Value, Log Normal and Weibull Distributions for Assessment of Low-Flow

Assessment of low-flow is an important aspect for water quality management, reservoir storage design, determining minimum release policy and safe surface water withdrawals. For which, the annual minimum d-day average flow is generally adopted procedure for characterizing the low-flow in a stream, which can be obtained by averaging the flow using moving average method for ‘d’ consecutive days viz., 7-, 10-, 14- and 30- days. This paper presents a study on comparison of three probability distributions such as Generalized Extreme Value, 2-parameter Log Normal (LN2) and Weibull adopted in estimation of low-flow for river Cauvery at Kollegal gauging site. The parameters are determined by three methods viz., method of moments, maximum likelihood method and L-Moments (LMO), and are used for estimation of low-flow. The adequacy of fitting probability distributions adopted in low-flow frequency analysis is evaluated by quantitative assessment through Goodness-of-Fit (viz., Chi-Square and Kolmogorov-Smirnov) and diagnostic (viz., correlation coefficient and root mean squared error) tests, and qualitative assessment using the fitted curves of the estimated low-flow. The results of quantitative and qualitative assessments indicate that LN2 (LMO) is better suited amongst three distributions adopted in estimation of 7-, 10-, 14- and 30- day low-flows for river Cauvery at Kollegal site.

Future changes in annual, seasonal and monthly runoff signatures in contrasting Alpine catchments in Austria

Abstract. Hydrological regimes of alpine catchments are expected to be strongly affected by climate change, mostly due to their dependence on snow and ice dynamics. While seasonal changes have been studied extensively, studies on changes in the timing and magnitude of annual extremes remain rare. This study investigates the effects of climate change on runoff patterns in six contrasting Alpine catchments in Austria using a process-based, semi-distributed hydrological model and projections from 14 regional and global climate model combinations for two representative concentration pathways, namely RCP4.5 and RCP8.5. The study catchments represent a spectrum of different hydrological regimes, from pluvial–nival to nivo-glacial, as well as distinct topographies and land forms, characterizing different elevation zones across the eastern Alps to provide a comprehensive picture of future runoff changes. The climate projections are used to model river runoff in 2071–2100, which are then compared to the 1981–2010 reference period for all study catchments. Changes in the timing and magnitude of annual maximum and minimum flows, as well as in monthly runoff and snowmelt, are quantified and analyzed. Our results indicate a substantial shift to earlier occurrences in annual maximum flows by 9 to 31 d and an extension of the potential flood season by 1 to 3 months for high-elevation catchments. For low-elevation catchments, changes in the timing of annual maximum flows are less pronounced. Magnitudes of annual maximum flows are likely to increase by 2 %–18 % under RCP4.5, while no clear changes are projected for four catchments under RCP8.5. The latter is caused by a pronounced increase in evaporation and decrease in snowmelt contributions, which offset increases in precipitation. In the future, minimum annual runoff will occur 13–31 d earlier in the winter months for high-elevation catchments, whereas for low-elevation catchments a shift from winter to autumn by about 15–100 d is projected, with generally larger changes for RCP8.5. While all catchments show an increase in mean magnitude of minimum flows by 7–30% under RCP4.5, this is only the case for four catchments under RCP8.5. Our results suggest a relationship between the elevation of catchments and changes in the timing of annual maximum and minimum flows. For the magnitude of the extreme flows, a relationship is found between catchment elevation and annual minimum flows, whereas this relationship is lacking between elevation and annual maximum flow.

Analysis on variation characteristics of the minimum flow at Datong Station under the influence of the Three Gorges Reservoir

As an important hydrological control station in the lower reaches of the Yangtze River, the Datong Station can provide guidance for regulating downstream water withdrawal activities by studying the characteristics of its changes during the dry season. This study selected the annual minimum flow index, applied linear trend method, Mann-Kendall method and wavelet analysis method to analyze its trend and periodic change characteristics, and analyzed the empirical frequency changes before and after the operation of the Three Gorges Reservoir, and obtained the following conclusions: The annual minimum flow series shows a significant increase trend, showing the characteristics of multi-period nesting in periodic changes, in which the first main period is 35-year. At the same frequency, the corresponding flow after the Three Gorges Reservoir operation was all larger than that before.