Past studies on the impacts of climate change (CC) on Alpine hydropower production have focused on high-head accumulation power plants. We provide one of the first comprehensive, simulation-based ...studies on CC impacts on Alpine Run-of-River (RoR) production, also considering effects of environmental flow requirements and technical increase potential. We simulate future electricity production under three emissions scenarios for 21 Swiss RoR plants with a total production of 5.9 TWh a−1. The simulations show an increase in winter production (4 % to 9 %) and a decrease in summer production (−2 % to −22 %), which together lead to an annual decrease of about −2 % to −7 % by the end of the century. The production loss due to environmental flow requirements is estimated at 3.5 % of the annual production; the largest low-elevation RoR power plants show little loss, while small and medium-sized power plants are most affected. The potential for increasing production by optimising the design discharge amounts to 8 % of the annual production. The largest increase potential is related to small and medium-sized power plants at high elevations. The key results are: i) there is no linear relationship between CC impacts on streamflow and on RoR production; the impacts depend on the usable streamflow volume, which is influenced by the Flow Duration Curve, environmental flow requirements, and design discharge; ii), the simulated production impacts show a strong correlation (>0.68) with the mean catchment elevation. The plants at the highest elevations even show an increase in annual production of 3 % to 23 %, due to larger shares of precipitation falling as rain instead of snow. These general results are transferable to RoR production in similar settings in other Alpine locations and should be considered in future assessments. Future work could focus on further technical optimisation potential, considering detailed operational data.
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•Climate change will lead to more winter RoR production and less summer production.•Most of the analysed RoR power plants show a decrease in future annual production.•The changes depend strongly on the elevation and plant-specific characteristics.•Future RoR production does not depend linearly on projected changes in streamflow.•Changes in production do not necessarily mean a linear change in financial revenue.
•Time trend- and precipitation-informed models are tested.•31 gauging stations with 55 years of data were used.•Precipitation-informed models outperform time trend-informed models.•Tested models ...yielded significantly different flood quantiles.•The best-fitting model is to some extent related to the flow regime.
Estimation of reliable design discharges under variable climate is a key challenge for today’s engineers. Therefore, researchers are intensively exploring different alternative approaches in order to improve standard methods for design discharge estimation. Paper investigates the performance of time-invariant, time trend- and precipitation-informed models based on generalized extreme value (GEV) distribution for 31 Slovenian discharge gauging stations with data availability from 1961 until 2015. Different rainfall durations are used as covariates in the case of precipitation-informed models. The selected catchments are located in different climate regions and characterized by five flow regimes. The results indicate that in most cases precipitation-informed models gave better fit to the measured data comparing to time-invariant and time trend-informed models. Relative differences in the design discharge estimations associated with 10- and 100-year return periods using time trend- and precipitation-informed models compared to time-invariant model were up to 60%. Additionally, the results indicate that identified best-fitting model of individual gauging station can to some extent be related to its flow regime.
Substantial evidence shows that the frequency of hydrological extremes has been changing and is likely to continue to change in the near future. Non-stationary models for flood frequency analyses are ...one method of accounting for these changes in estimating design values. The objective of the present study is to compare four models in terms of goodness of fit, their uncertainties, the parameter estimation methods and the implications for estimating flood quantiles. Stationary and non-stationary models using the GEV distribution were considered, with parameters dependent on time and on annual precipitation. Furthermore, in order to study the influence of the parameter estimation approach on the results, the maximum likelihood (MLE) and Bayesian Monte Carlo Markov chain (MCMC) methods were compared. The methods were tested for two gauging stations in Slovenia that exhibit significantly increasing trends in annual maximum (AM) discharge series. The comparison of the models suggests that the stationary model tends to underestimate flood quantiles relative to the non-stationary models in recent years. The model with annual precipitation as a covariate exhibits the best goodness-of-fit performance. For a 10% increase in annual precipitation, the 10-year flood increases by 8%. Use of the model for design purposes requires scenarios of future annual precipitation. It is argued that these may be obtained more reliably than scenarios of extreme event precipitation which makes the proposed model more practically useful than alternative models.
Rainfall-runoff modelling has always been of great importance in hydrology. Recently, the Event-Based Approach for Small and Ungauged Basins (EBA4SUB) model, based on the instantaneous unit ...hydrograph (IUH) formulation, was released. The EBA4SUB model was originally developed considering only the surface flow, and in this work it has been generalized considering also the subsurface flow. The aim is to make EBA4SUB applicable both for Hortonian and/or for Dunne-Black mechanisms, proposing the so-called Generalized EBA4SUB model (GEBA4SUB). Here, GEBA4SUB and EBA4SUB are compared at the event scale, using observed rainfall-runoff events, and in estimating design discharge, using extreme value observations. In both cases, the results suggest that GEBA4SUB could outperform EBA4SUB, with improvements from 15% to over 100%.
Longitudinal connectivity is one of the prime issues addressed in river restoration our days. At the same time, mitigation of climate change impacts by modes of renewable energy increasingly puts ...pressure on the remaining free flowing river stretches for hydroelectricity production. At the site level, this trade‐off manifests in the negotiation of water for upstream and downstream fish passage versus losses for hydroelectricity production. This study has compiled and analysed 193 studies evaluating fish passes designed to provide upstream migration for all species and size classes of the respective river system. The overall assessment of functioning and discharge dedicated to fish pass maintenance, site, and river characters were provided by the studies. The main objective here was deriving general guidance for the minimum amount of water needed for fully functioning upstream fish passage in relation to river size. There was a significant correlation between functionality and design discharge of a fish pass. Fully functioning fish passes (N = 92) had median design discharge of 5% of the mean average discharge of the river, restrictedly functioning of 1.1% and not functioning of 0.22%. A power model could be derived of design discharge needs in relation to river discharge, which is inversely related to river size. In large rivers, a rather small share of mean discharge is sufficient, whereas in small rivers, it cannot be further downscaled due to dimensions. This model might provide first guidance in adjusting needs for both hydroelectricity generation and fish conservation in regulated rivers.
Urgency of Precipitation Intensity-Duration-Frequency (IDF) estimation using the most recent data has grown significantly due to recent intense precipitation and cloud burst circumstances impacting ...infrastructure caused by climate change. Given the continually available digitized up-to-date, long-term, and fine resolution precipitation dataset from the United States Department of Agriculture Forest Service’s (USDAFS) Experimental Forests and Ranges (EF) rain gauge stations, it is both important and relevant to develop precipitation IDF from onsite dataset (Onsite-IDF) that incorporates the most recent time period, aiding in the design, and planning of forest road-stream crossing structures (RSCS) in headwaters to maintain resilient forest ecosystems. Here we developed Onsite-IDFs for hourly and sub-hourly duration, and 25-yr, 50-yr, and 100-yr design return intervals (RIs) from annual maxima series (AMS) of precipitation intensities (PIs) modeled by applying Generalized Extreme Value (GEV) analysis and L-moment based parameter estimation methodology at six USDAFS EFs and compared them with precipitation IDFs obtained from the National Oceanic and Atmospheric Administration Atlas 14 (NOAA-Atlas14). A regional frequency analysis (RFA) was performed for EFs where data from multiple precipitation gauges are available. NOAA’s station-based precipitation IDFs were estimated for comparison using RFA (NOAA-RFA) at one of the EFs where NOAA-Atlas14 precipitation IDFs are unavailable. Onsite-IDFs were then evaluated against the PIs from NOAA-Atlas14 and NOAA-RFA by comparing their relative differences and storm frequencies. Results show considerable relative differences between the Onsite- and NOAA-Atlas14 (or NOAA-RFA) IDFs at these EFs, some of which are strongly dependent on the storm durations and elevation of precipitation gauges, particularly in steep, forested sites of H. J. Andrews (HJA) and Coweeta Hydrological Laboratory (CHL) EFs. At the higher elevation gauge of HJA EF, NOAA-RFA based precipitation IDFs underestimate PI of 25-yr, 50-yr, and 100-yr RIs by considerable amounts for 12-h and 24-h duration storm events relative to the Onsite-IDFs. At the low-gradient Santee (SAN) EF, the PIs of 3- to 24-h storm events with 100-yr frequency (or RI) from NOAA-Atlas14 gauges are found to be equivalent to PIs of more frequent storm events (25–50-yr RI) as estimated from the onsite dataset. Our results recommend use of the Onsite-IDF estimates for the estimation of design storm peak discharge rates at the higher elevation catchments of HJA, CHL, and SAN EF locations, particularly for longer duration events, where NOAA-based precipitation IDFs underestimate the PIs relative to the Onsite-IDFs. This underscores the importance of long-term high resolution EF data for new applications including ecological restorations and indicates that planning and design teams should use as much local data as possible or account for potential PI inconsistencies or underestimations if local data are unavailable.
For channelized, flood‐regulated rivers, morphological changes are avoided as much as possible. Extraordinarily high flows in the past, however, have demonstrated that channelized rivers may also ...become morphologically active, especially when a discharge exceeds the design discharge, such as in hundred‐year floods. However, the morphodynamic potentials and critical flows in such cases have hardly been investigated, and the flood risk to human settlements is therefore poorly understood. The present study aims to analyse the critical flow conditions in Flåmselva, western Norway and the consequences of morphological adjustment on the Froude number from an extraordinary flood event in 2014. Based on a step‐backwater modelling approach, three different high‐resolution river bathymetries of Flåmselva were investigated: (i) pre‐flood, (ii) post‐flood and (iii) re‐channelized morphology. The results showed that due to the 2014 flood, large parts that were in critical flow conditions in the pre‐flood stage (>1), exhibited significantly lower Froude numbers in the post‐flood stage. It turned out that the artificially created plane‐bed morphologies in flood‐regulated channelized rivers can act as drivers for critical flow conditions and that structural as well as non‐structural measures should consider non‐fluvial, semi‐fluvial and fluvial sediment deposits in rivers and floodplains in terms of flood risk management.
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