Extreme Low Flow Research Articles

Antimony Flux and Transport Dynamics in a Mining‐Impacted River Is Linked to Catchment Hydrodynamics and Climate Oscillations

ABSTRACTWe investigate how seasonal flow variations and a climatic regime that is dominated by the El Niño–Southern Oscillation (ENSO) influence Sb flux dynamics in an Australian river impacted by mining. Sampling (n = 496) spans a hydrologically complex 7‐year period of drought, bushfires and floods from 2016 to 2023, during which 17% of samples exceeded the Sb drinking water guideline concentration (3 μg L−1). Aqueous Sb (SbAq) concentration–discharge (C–Q) relationships are non‐continuous/non‐linear across the flow range, with chemodynamic behaviour at moderate flows reflecting hydrological connection to the primary Sb‐source area combined with variable dilution. In contrast chemostatic behaviour occurred at extreme low and high flows, reflecting hydrological disconnection from the source area and persistent dilution, respectively. SbAq was significantly positively correlated (p < 0.01, Spearman's ρ = 0.58) with a Q index representing the proportional contribution of sub‐catchment flow from the mineral‐field area, suggesting sufficient localised rainfall in the Sb mining‐impacted sub‐catchment contributes to downstream peaks in SbAq concentrations. Aqueous and particulate Sb (SbP) annual loads (La) during the study period spanned 24–5174 and 1.2–2820 kg, respectively and were strongly flow dependant with extreme interannual variability reflecting dry and wet years. We extrapolate daily load‐daily discharge (Ld–Qd) relationships for SbAq and SbP to estimate Ld over a 53‐year period (1970–2023) of continuous Q data (mean total Sb La = 1865 kg ± [SE] 247). Positive correlations between the annual Southern Oscillation Index and both Sb La (p < 0.05) and proportional SbP La over 53 years suggests ENSO fluctuations influence annual Sb transport dynamics. Upstream SbP load estimates correspond with downstream estimates of coastal floodplain sedimentary Sb mass, with approximately 10%–45% of the estimated SbP exported downstream since approximately 1880 accumulated on the Macleay coastal floodplain. Data suggest at current rates of export, complete flushing‐leaching of mine tailings‐derived Sb from the upper Macleay catchment may take in the order approximately 600–1000 years.

Catchment-scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan

Abstract. The impact of drought on environmental flow (EF) in 27 catchments of the Indus Basin is studied from 1980–2018 using indicators of hydrologic alterations (IHAs). The standardized precipitation evapotranspiration index (SPEI) was systematically propagated from one catchment to another using principal component analysis (PCA). Threshold regression is used to determine the severity of drought (scenario 1, drought severity that causes low flows) and the month (scenario 2, months where drought has resulted in low flows) that trigger low flows in the Indus Basin. The impact of drought on low EFs is quantified using range of variability analysis (RVA), which is an integrated component of the IHA used to study the hydrological alterations in environmental flow components (EFCs) by comparing the pre- and post-impact periods of human and/or climate interventions in EFCs. The hydrological alteration factor (HAF) is calculated for each catchment in the Indus Basin. The results show that most of the catchments were vulnerable to drought during the periods of 1984 to 1986, 1991/1992, 1997 to 2003, 2007 to 2008, 2012 to 2013, and 2017 to 2018. On a longer timescale (SPEI-12), drought is more severe in the lower Indus Basin (LIB) than in the upper Indus Basin (UIB). The IHA pointed out that drought significantly impacts the distribution of EFCs, particularly extremely low flow (ELF) and low flow (LF). The magnitude and frequency of the ELF and LF events increase as drought severity increases. The threshold regression provided useful insights, indicating that moderate drought can trigger ELF and LF at shorter timescales (SPEI-1 and SPEI-6) in the UIB and middle Indus Basin (MIB). Conversely, severe and extreme droughts trigger ELF and LF at longer timescales (SPEI-12) in the LIB. The threshold regression also divided the entire study period (1980–2018) into different time periods (scenario 2), which is useful for quantifying the impact of drought on low EFs using the SPEI coefficient. Higher SPEI coefficients are observed in the LIB, indicating high alterations in EF due to drought. HAF showed high alterations in EF in most of the catchments throughout the year except in August and September. Overall, this study provided useful insights for analysing the effects of drought on EF, especially during low flows.

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.

Advancing Environmental Flows Science: Hindcasting and Forecasting Flow–Ecology Relationships

To advance current environmental flow standards in Texas, we developed field, laboratory, and analytical methods to model recruitment dynamics of indicator species selected to cover a range of population responses to flow variation. Preliminary investigations were conducted in three central Texas river basins to evaluate the feasibility of these methods for formulating and evaluating the state's environmental flow standards. Age analysis allowed back‐calculation of dates of fish hatching, mussel recruitment, and tree germination for estimation of temporal variation in recruitment. Recruitment data were then analyzed in relation to flow regime components. Statistical models were derived for flow–recruitment relationships of Shoal Chub Macrhybopsis hyostoma, Smallmouth Buffalo Ictiobus bubalus, threeridge mussel Amblema plicata, and boxelder Acer negundo. The Shoal Chub model was used to hindcast recruitment dynamics in the Brazos River, revealing a decline in recruitment after dam construction. The Smallmouth Buffalo model revealed that strong year‐classes were positively associated with springtime pulses of long duration but negatively associated with frequent short‐duration pulses. Results for the threeridge mussel were not as easily interpreted, but for all three river basins generally showed weaker recruitment during periods with extreme low and high flows. The boxelder model revealed positive associations between recruitment and high flow components and was used to forecast the probability of germination under five simulated flow regime scenarios, thereby providing an additional means for evaluating the suitability of environmental flow standards. Assessment of how hydrology influences recruitment provides an evidence‐based method to hindcast responses to past flow regimes and forecast responses to future flow scenarios, thereby providing a basis for evaluating environmental flow standards and water management options.

Micro-Catchments, Macro Effects: Natural Water Retention Measures in the Kylldal Catchment, Germany

Floods are among the most devastating and financially burdensome natural disasters in Europe. The combined impact of climate change and land use change is expected to exacerbate and intensify the destructive consequences of river floods. In this study, we analysed the effects of wetland restoration on peak and base flows and on water quality in the Kylldal catchment of the Kyll River in the German Middle Mountains using the Soil and Water Assessment Tool+ (SWAT+). Monthly median daily discharge increases varied between 3% and 33% in the studied (micro)catchments. The higher median flow rates show that discharge peaks were attenuated and distributed over a longer period, making both extreme peak flows and low flows less common. Peak flows tended to decrease, with the largest effects between late fall and early spring when peak flow values decreased by up to 18%. The annual maximum peak flows in each of the three micro-catchments decreased by 12–24% on average. The occurrence of daily average flow rates larger than 1 m3 s−1 was up to 45% lower after wetland restoration. Low flows increased by up to 21% and 13% in the summer and fall, respectively, which suggests that drought risk also decreases after wetland restoration. Average nitrogen exports decreased by 38–50% in the project areas and by 20% at the catchment level. Average phosphorus exports decreased by 52–67% in the project areas and by 25% at the catchment level. The study highlights the potential of wetland restoration for improving hydrological services, mitigating flood risks, and enhancing water quality. Restoring and maintaining freshwater ecosystems and their natural sponge functions is crucial for effectively managing water resources and addressing the challenges posed by climate change and land use changes.

Enhanced Role of Streamflow Processes in the Evolutionary Trends of Dissolved Organic Carbon.

Investigating dissolved organic carbon (DOC) dynamics and drivers in rivers enhances the understanding of carbon-environment linkages and support sustainability. Previous studies did not fully consider the dynamic nature of key drivers that influence the long-term changing trends in DOC concentration over time (the controlling factors and their roles in DOC trend can undergo alterations over time). We analyzed 42 years (1979-2018) of hydrometeorology, sulfate SO4, and DOC data from a 5.42 km2 watershed in central-southern Ontario, Canada. Our findings reveal a significant (p ≤ 0.01) overall increase in DOC concentrations, mainly due to the coevolution of SO4 and streamflow trends, especially the extreme flows. Over the 42-year period, the changing trend of streamflow (especially the extreme high or low flows) have significantly (p < 0.05) intensified their influence on DOC trends, increasing by an average of 30%. Conversely, the impact of SO4 has weakened, experiencing an average decrease of 32.6%. The upward trend in the annual average DOC concentration is attributed to the increasing number of maximum flow days within a year, while the decreasing trend in the number of minimum flow days has a contrasting effect. In other words, changes in maximum and minimum flow days have a counteracting effect on the DOC concentration trends. These results underscore the importance of considering the effects of altered streamflow processes on carbon cycle changes under evolving environmental conditions.

The role of rewilding in mitigating hydrological extremes: State of the evidence

AbstractLandscape rewilding has the potential to help mitigate hydrological extremes by allowing natural processes to function. Our systematic review assessed the evidence base for rewilding‐driven mitigation of high and low flows. The review uncovers a lack of research directly addressing rewilding, but highlights research in analogue contexts which can, with caution, indicate the nature of change. There is a lack of before‐after studies that enable deeper examination of temporal trajectories and legacy effects, and a lack of research on the scrub and shrubland habitats common in rewilding projects. Over twice as much evidence is available for high flows compared to low flows, and fewer than one third of studies address high and low flows simultaneously, limiting our understanding of co‐benefits and contrasting effects. Flow magnitude variables are better represented within the literature than flow timing variables, and there is greater emphasis on modeling for high flows, and on direct measurement for low flows. Most high flow studies report a mitigating effect, but with variability in the magnitude of effect, and some exceptions. The nature of change for low flows is more complex and suggests a higher potential for increased low flow risks associated with certain trajectories but is based on a very narrow evidence base. We recommend that future research aims to: capture effects on both high and low flow extremes for a given type of change; analyze both magnitude and timing characteristics of flow extremes; and examine temporal trajectories (before and after data) ideally using a full before‐after‐control‐impact design.This article is categorized under: Human Water &gt; Value of Water Science of Water &gt; Hydrological Processes Science of Water &gt; Water Extremes Water and Life &gt; Conservation, Management, and Awareness

Enhancing short-term streamflow forecasting of extreme events: A wavelet-artificial neural network hybrid approach

Accurate short-term streamflow forecasting models are crucial for effective water resource management, enabling timely responses to extreme flood or drought events and mitigating potential socioeconomic damage. This study proposes robust hybrid Wavelet Artificial Neural Network (WANN) models for real-world hydrological applications. Two WANN variants, WANNone and WANNmulti, are proposed for short-term streamflow forecasting of extreme (high and low) flows at eight gauging stations within Brazil's Paraíba do Sul River basin. WANNone directly feeds both the original streamflow data and the decomposed components obtained through an À Trous wavelet transform into the ANN architecture. Conversely, WANNmulti utilizes separate ANNs for the original data, with the final streamflow estimate reconstructed via the inverse wavelet transform of the individual ANN outputs. The performance of these WANN models is then compared against conventional ANN models. In both approaches, Bayesian optimization is employed to fine-tune the hyperparameters within the ANN architecture. The WANN models achieved superior performance for 7-day streamflow forecasts compared to conventional ANN models. WANN models yielded high R2 values (>0.9) and low MAPE (4.8%–14.7%) within the expected RMSE range, demonstrating statistically significant improvements over ANN models (71% and 75% reduction in RMSE and MAPE, respectively, and 69% increase in R2). Further analysis revealed that WANNmulti models generally exhibited superior performance for low extreme flow predictions, while WANNone models achieved the highest accuracy for high extreme flows at most stations. WANN models' strong performance suggests their value for real-time flood warnings, enabling improved decision-making in areas like flood/drought mitigation and urban water planning.

Evaluating indicators of hydrologic alteration to demonstrate the impact of open-pit lignite mining on the flow regimes of small and medium-sized rivers

Our study provides a retrospective evaluation of the perturbances of the opencast mining on the small river. Based on a standard 'before-after-control-impact' approach, we assess the impact of disturbances on aquatic ecosystems. For this purpose, we used IHA (Index of Hydrological Alteration) statistics to fully quantify the impact of open-pit mine on flow regimes of small-to-medium-size rivers. The analysis results in flow data captured in the 33 parameters of the range variability approach (RVA) and five ecological flow components (EFC). This approach helped us comprehensively evaluate the alteration in the flow regime in areas of open-pit mining on the example of the Noteć River, a typical lowland river. We conclude that the level integrated hydrologic alterations to this river under the influence of the groundwater depression cone and water from the mine dewatering are high, as assessed by the RVA and EFC methods. Specifically, this work uses the IHA framework to verify the necessity of including a specific group of indicators. Our analysis shows that for the post-impact period on the investigated river, the functioning of the river ecosystem was degraded. One of the EFC components completely disappeared at both water gauge stations. There were also profound hydrologic alterations, such as increased frequency or duration of “extreme low flows” at one station; at the second station, “high flow pulses” occurred more frequently. More than 65 % of the altered parameters in five IHA groups were modified drastically. In the river section affected by the groundwater depression cone, both the minimum and maximum flows decreased by 20 % to 55 %. In the section where water from the mine dewatering is fed in, the minimum flows changed by + 170 to + 230 %. The use of the IHA tool provides an opportunity for environmental flow restoration of water conditions in degraded post-mining areas.

Increasing volatility of reconstructed Morava River warm-season flow, Czech Republic

Study regionThe Morava River basin, Czech Republic, Danube Basin, Central Europe. Study focusHydrological summer extremes represent a prominent natural hazard in Central Europe. River low flows constrain transport and water supply for agriculture, industry and society, and flood events are known to cause material damage and human loss. However, understanding changes in the frequency and magnitude of hydrological extremes is associated with great uncertainty due to the limited number of gauge observations. Here, we compile a tree-ring network to reconstruct the July–September baseflow variability of the Morava River from 1745 to 2018 CE. An ensemble of reconstructions was produced to assess the impact of calibration period length and trend on the long-term mean of reconstruction estimates. The final estimates represent the first baseflow reconstruction based on tree rings from the European continent. Simulated flows and historical documentation provide quantitative and qualitative validation of estimates prior to the 20th century. New hydrological insights for the regionThe reconstructions indicate an increased variability of warm-season flow during the past 100 years, with the most extreme high and low flows occurring after the start of instrumental observations. When analyzing the entire reconstruction, the negative trend in baseflow displayed by gauges across the basin after 1960 is not unprecedented. We conjecture that even lower flows could likely occur in the future considering that pre-instrumental trends were not primarily driven by rising temperature (and the evaporative demand) in contrast to the recent trends.

Comprehensive evaluation of environmental flows in the Yangtze River regulated by two large dams

The ecological sustainability of rivers and floodplains depends on their natural flows. Dam construction on rivers has dramatically altered the hydrologic regimes, in turn affecting aquatic ecosystem integrity. The environmental flow components was applied to exam the impacts of the two dams (i.e., the Gezhouba Dam and the Three Gorges Dam) on downstream flows of the Yangtze River, China. Due to the operation of the two dams, the Yangtze River's flow regimes became homogenous through increasing streamflow during the dry season and decreasing streamflow in the flood season. The monthly low flows from January to April significantly increased by 14-31%, while October and November low flows significantly decreased by 18-25%. We observed the decreased duration and frequency of extreme low flows and floods, particularly the disappearance in large floods. These homogenous flows strongly influence the aquatic biodiversity. To alleviate the hydrologic alteration and minimize the negative ecological influence, low flows should be lower and floods should be reestablished as a natural state. The flow characteristics of duration, timing and rate of change should also be incorporated into the environmental flow recommendations. Our results could provide a potential solution to the tradeoffs between water resources exploitation and natural water requirement in the highly regulated rivers.

500-year reconstruction of Dez River discharge in southwestern Iran from tree rings

Long-term river discharge records are essential for water resource management, especially in semi-arid regions. However, the short instrumental records in Iran and the limited availability of local paleoclimate proxies to extend these records hinder our understanding of the full range of hydrologic variability. To help overcome these constraints, we have used annually-resolved tree-ring width chronologies from a network of sites spanning the eastern Mediterranean to the Tibetan Plateau to develop the first multi-centennial (∼500 years) river discharge reconstruction for the Dez River basin, a catchment that supports substantial water extraction in southwestern Iran. A Hierarchical Bayesian Regression (HBR) model accompanied by parsimonious predictor selection was used to derive the most robust model output. The selection method retained 26 precipitation-sensitive tree-ring width chronologies, mainly from regions with similar hydroclimate features to the Dez River basin. The resulting reconstruction of the most downstream gauging station accounts for 62% of the variance in river discharge observations, closely matching known historical events and other regional reconstructions. Notably, the underlying recurrence pattern of extreme flow conditions suggests floods were more frequent than low flow extremes (i.e., droughts) during much of the 18th and early 19th centuries. In contrast, during the early 17th century, droughts were more frequent. Worryingly, the frequency of both floods and droughts has increased simultaneously since the beginning of the twentieth century. Our reconstruction could be used to assess current water allocation strategies under conditions similar to past extended dry periods. When combined with future projections, they can help provide more robust assessment scenarios for water management.

Copula-based joint modelling of extreme river temperature and low flow characteristics in the risk assessment of aquatic life

Compounding the joint impact of extreme river temperature and low flow characteristics can harm the aquatic habitat of certain organisms (e.g., ecototherm fish) and freshwater ecosystems. Considering only river temperature or low flow via univariate frequency distribution as a stress indicator would be incomplete. Maximum water temperature and low flow series are strongly negatively correlated; thus, their joint probability distribution can be helpful to assess better the risks associated with joint extreme events. This study incorporated the 2-D parametric copulas in the bivariate joint modelling of annual maximum river water temperature and corresponding low flow. This proposed bivariate framework is applied to 5 independent and identically distributed stations in Switzerland. Parametric 1-D probability density functions are employed in modelling the univariate marginal distribution of both variables separately. The efficacy of eighteen different parametric class negatively dependent 2-D copulas is tested. The best-fitted copulas and selected marginals are used to estimate joint return periods for quantiles corresponding to multiple return periods. The joint return periods of annual maximum temperatures conditional to low flows or vice versa are also estimated. Investigation reveals that the occurrence of bivariate events simultaneously is less frequent in the AND-joint case than in the OR-joint event case for all stations. Also, OR-return periods are less (nearly half) the value of univariate return periods. Secondly, higher conditional return periods are observed in annual maximum temperature (or low flow) when increasing the percentile value of the conditioning variable, i.e., low flow (or maximum temperature). Also, when the low flow (or water temperature) conditioning variable is fixed, higher bivariate event return periods are observed at a higher water temperature (or low flow) value. In conclusion, these estimated bivariate statistics can help provide a more complete picture for an adequate assessment of the risks associated with cold-water species.

Extreme Low Flow during Long-Lasting Phases of River Runoff in the Central Part of the East European Plain

In the rivers of the central part of the East European Plain (the Volga at Staritsa, the Oka at Kaluga, and the Don at Stanitsa Kazanskaya), long phases (10–15 years or more) of increased/decreased annual and seasonal runoff have occurred, as well as differences in the frequencies of extremely low flow conditions from the late 19th century to 2020. Phase boundaries were identified by cumulative deviation curves and statistical homogeneity. The frequencies of specific water flow values were estimated using the empirical curves of the exceedance probability of annual and seasonal water flows based on their long-term time series. In the century-long changes of rivers considered, two long contrasting phases were revealed. These phases are characterized by increased and decreased runoff of hydrological seasons. Near simultaneously, a phase of increased runoff was first observed for the freshet season. On the contrary, phases of decreased runoff were first observed for low-water seasons. The runoff phases differ significantly in duration and differences in flow. Significant differences were revealed in the frequency of low-water years for a low runoff with an exceedance probability above or equal to 75% and above or equal to 95%.

Melting Alpine Water Towers Aggravate Downstream Low Flows: A Stress‐Test Storyline Approach

AbstractDroughts can lead to extreme low flow situations in rivers, with resulting severe impacts. Upstream snow and ice melt in many of the world's mountain water towers can alleviate the hydrological consequences of drought, yet global warming threatens the cryosphere. To improve the understanding of melt water contributions during drought in the case of future glacier retreat, we developed stress‐test storyline scenarios to model streamflow and tested them in the European river Rhine basin. Meteorological conditions of past drought and low flow years in Europe, 1976, 2003, and 2018, were repeated at three future moments in time, representing nowadays, near future and far future conditions. The latter two conditions were obtained by climate projections under the RCP8.5 scenario. Results show that the low flow situations caused by the meteorological drought situations aggravate in future conditions, more so for the far future and for the year 2003 because of the relatively large glacier ice melt contribution in the past. Summer (July–September) streamflow may decline by 5%–25% far downstream and 30%–70% upstream and the duration of extreme low flow situations may double compared to the selected past drought events. These results are relevant for the Rhine as a major European river but stand exemplary for many other river basins and highlight the importance of cryospheric changes for downstream low flow situations in a changing climate. The stress‐test scenarios allow a glimpse into future extreme low flow events aiding adaptation planning, and might be adapted to include other important low flow drivers.

How do inorganic nitrogen processing pathways change quantitatively at daily, seasonal, and multiannual scales in a large agricultural stream?

Abstract. Large agricultural streams receive excessive inputs of nitrogen. However, quantifying the role of these streams in nitrogen processing remains limited because continuous direct measurements of the interacting and highly time-varying nitrogen processing pathways in larger streams and rivers are very complex. Therefore, we employed a monitoring-driven modelling approach with high-frequency in situ data and the river water quality model Water Quality Analysis Simulation Program (WASP) 7.5.2 in the 27.4 km reach of the sixth-order agricultural stream called Lower Bode (central Germany) for a 5-year period (2014–2018). Paired high-frequency sensor data (15 min interval) of discharge, nitrate, dissolved oxygen, and chlorophyll a at upstream and downstream stations were used as model boundaries and for setting model constraints. The WASP model simulated 15 min intervals of discharge, nitrate, and dissolved oxygen with Nash–Sutcliffe efficiency values higher than 0.9 for calibration and validation, enabling the calculation of gross and net dissolved inorganic nitrogen uptake and pathway rates on a daily, seasonal, and multiannual scale. Results showed daily net uptake rate of dissolved inorganic nitrogen ranged from −17.4 to 553.9 mgNm-2d-1. The highest daily net uptake could reach almost 30 % of the total input loading, which occurred at extreme low flow in summer 2018. The growing season (spring and summer) accounted for 91 % of the average net annual uptake of dissolved inorganic nitrogen in the measured period. In spring, both the DIN gross and net uptake were dominated by the phytoplankton uptake pathway. In summer, benthic algae assimilation dominated the gross uptake of dissolved inorganic nitrogen. Conversely, the reach became a net source of dissolved inorganic nitrogen with negative daily net uptake values in autumn and winter, mainly because the release from benthic algae surpassed uptake processes. Over the 5 years, average gross and net uptake rates of dissolved inorganic nitrogen were 124.1 and 56.8 mgNm-2d-1, which accounted for only 2.7 % and 1.2 % of the total loadings in the Lower Bode, respectively. The 5-year average gross DIN uptake decreased from assimilation by benthic algae through assimilation by phytoplankton to denitrification. Our study highlights the value of combining river water quality modelling with high-frequency data to obtain a reliable budget of instream dissolved inorganic nitrogen processing which facilitates our ability to manage nitrogen in aquatic systems. This study provides a methodology that can be applied to any large stream to quantify nitrogen processing pathway dynamics and complete our understanding of nitrogen cycling.

Assessing the effects of irrigation and hydropower dams on river communities using taxonomic and multiple trait-based approaches

Rivers and streams have suffered multiple transformations to attend the increasing water demands worldwide. Among these, dams and reservoirs cause some of the most severe ecological impacts on rivers, altering the river flow and thermal regimens, nutrient and sediment fluxes, and network connectivity. However, in the context of the different dam purposes and operational schemes, knowledge of the ecological impacts on the riverine biota is still limited. In this study, our main goal was to assess dam-related effects (e.g. hydrological and thermal alteration, water quality changes) on river biological communities and identify key ecological responses associated to flow regulation. To achieve this, diatom, macroinvertebrate, and fish communities were surveyed in control (n = 8) and impacted (n = 11) streams (i.e. downstream of irrigation or hydropower dams) along three consecutive years. The study design aimed at minimising the environmental variability among control and impacts using previously established hydrological classifications. This allowed focusing primarily on the effects of dam operation schemes. In addition to traditional biotic indices based on the composition and structure of these communities, we assessed community-level responses using trait-based analyses with multivariate and fourth-corner analyses. The ecological changes varied with dam purpose and, in general, favoured disturbance-tolerant traits. Common biotic indices did not consistently respond to dam uses; trait-based analyses, in contrast, provided a more detailed picture of the dam-related effects on the studied river communities, with macroinvertebrate traits showing the strongest correlations to dam-related hydrological and physico-chemical variables, followed by diatoms and fish. Changes in the biological communities downstream of irrigation dams were mostly related to the inversion of the seasonal flow regimes (e.g. increases in the summer flows and magnitude of low flow extremes; decreases in the winter flows and in the frequency and magnitude of extreme high flow events) and the reduction of nutrient concentration. These changes favoured planktonic diatoms, macroinvertebrates with short life cycles and small body sizes, and fish feeding on the water column. Hydropower dams elevated significantly the rate of flow change and water temperature, favouring low profile adnate diatoms, multivoltine and passively dispersed macroinvertebrates, and scrapers. The key relationships identified in our study are useful to underpin river biodiversity conservation strategies and to set future research directions aiming at reducing the negative effects of dam operation schemes.

Evaluation of Remote Sensing-Based Evapotranspiration Datasets for Improving Hydrological Model Simulation in Humid Region of East China

Conventional calibration methods used in hydrological modelling are based on runoff observations at the basin outlet. However, calibration with only runoff often produces reasonable runoff but poor results for other hydrological variables. Multi-variable calibration with both runoff and remote sensing-based evapotranspiration (ET) is developed naturally, due to the importance of ET and its data availability. This study compares two main calibration schemes: (1) calibration with only runoff (Scheme I) and (2) multi-variable calibration with both runoff and remote sensing-based ET (Scheme II). ET data are obtained from three remote sensing-based ET datasets, namely Penman–Monteith–Leuning (PML), FLUXCOM, and the Global Land Evaporation Amsterdam Model (GLEAM). The aforementioned calibration schemes are applied to calibrate the parameters of the Distributed Hydrology Soil Vegetation Model (DHSVM) through ε-dominance non-dominated sorted genetic algorithm II (ε-NSGAII). The results show that all three ET datasets have good performance for areal ET in the study area. The DHSVM model calibrated based on Scheme I produces acceptable performance in runoff simulation (Kling–Gupta Efficiency, KGE = 0.87), but not for ET simulation (KGE &lt; 0.7). However, reasonable simulations can be achieved for both variables based on Scheme II. The KGE value of runoff simulation can reach 0.87(0.91), 0.72(0.85), and 0.75(0.86) in the calibration (validation) period based on Scheme II (PML), Scheme II (FLUXCOM), and Scheme II (GLEAM), respectively. Simultaneously, ET simulations are greatly improved both in the calibration and validation periods. Furthermore, incorporating ET data into all three Scheme II variants is able to improve the performance of extreme flow simulations (including extreme low flow and high flow). Based on the improvement of the three datasets in extreme flow simulations, PML can be utilized for multi-variable calibration in drought forecasting, and FLUXCOM and GLEAM are good choices for flood forecasting.

Estimation of Low Flow Statistics for Sustainable Water Resources Management in South Australia

The Magnitude and occurrence of extreme low flow events are needed in setting minimum flows to protect the instream users. As the true distribution is not normally known, the identification of the most appropriate distribution function that describes the extreme low flow data of a catchment is essential in estimating reliable low flow quantiles at various average recurrence intervals (ARI). The aim of this study is to conduct a comparative assessment of the performance of three plausible distribution functions for estimating low flow quantiles. The investigation was carried out by using 27-gauge stations within South Australia (SA), the driest state in Australia. The best distribution function out of the three selected distributions; Log Normal (LN), Log Pearson Type 3 (LP3), and Generalized Extreme Value (GEV for each of the three selected annual minima series (7-day, 15-day and 30-day) at each gauged catchments was identified. The estimated low flow quantiles from using these three distribution functions were compared using RMSE values estimated through Monte Carlo simulation studies. For the majority of the selected study catchments, GEV fitted using L moments was found to be the best method for estimating low flow quantiles at ARIs over 10 years (≥14%), while at low ARI, LP3 fitted using the Method of Moments (MOM) was shown to outperform (≥17%) the other methods.