Antecedent Flow Research Articles

The influence of multiple controls on structural and functional characteristics of macroinvertebrate community in a regulated Alpine river

AbstractIn the past 30 years, several studies have proved that the river flow regime is fundamental in structuring biotic communities. The condition of the ecosystem results not only from the occurrence of extreme events, such as floods and droughts but also from habitat availability and from its temporal variation. Describing the relationships between macroinvertebrate community characteristics and environmental gradients of flow, temperature, nutrient supplies, and habitat conditions is fundamental to understand ecological dynamics. This is the basis for predicting changes within the communities and in ecosystem functions and ultimately to properly manage and conserve the riverine ecosystems. Seven sites, along a 20‐km river sector, were surveyed for macroinvertebrates and water chemistry seasonally, from 2012 to 2016. Habitat conditions were assessed along a 500‐m stretch in each site. The river discharge was continuously monitored by two water level recorders and used to reconstruct various hydrological indices specific for each sampling location. During the sampling period, numerous high flow events and some prolonged periods of low flow were observed. Quantile regression was used to describe the effects of potential limiting factors on macroinvertebrate community, which were primarily driven by antecedent flow conditions and season whereas habitat conditions and water chemistry played only a minor role. Quantitative models have been developed to predict structural and functional characteristics of macroinvertebrate community as a function of antecedent flow conditions, habitat, and physicochemical water characteristics. Those models allow to identify the main drivers and predict the effect of different water management strategies to riverine ecosystem.

Stream Flow Forecasting in Mahanadi River Basin using Artificial Neural Networks

Suspended sediment prediction is essential for wearing awayof soil and sedimentation at time of peakinundation period. Several kinds of neural networks have been projected in preceding papers for applications in hydrological events. This research intelligence focuses on assessment of applicability of Recurrent Neural Network (RNN) and Radial Basis Function Network (RBFN) for forecasting flow on daily basis at gauging station in Mahanadi river basin. Superlative performance is assessed on basis of RMSE, R2 which was attained by the precipitation and antecedent flow as model inputs. Based on performance value RNN gives prominent value as compare to RBFN. In case of RBFN three transfer function Tan-sig, Log-sig, purelin are utilized for evaluating model performance. While Tan-sig function used model gives extent value of R2 that is0.9614 and 0.9843 for training and testing phase respectively.

Complementary data-intelligence model for river flow simulation

Despite of diverse progressions in hydrological modeling techniques, the necessity of a robust, accurate, reliable, and trusted expert system for real-time stream flow prediction still exists. The intention of the present study is to establish a new complementary data-intelligence (DI) model called wavelet extreme learning machine (WA-ELM) for forecasting river flow in a semi-arid environment. The monthly river flow data for the period 1991-2010 is used to calibrate and validate the applied predictive model, developed using antecedent flow data as predictor. The prediction efficiency of the developed WA-ELM model is validated against stand-alone ELM model. The performance of the models is diagnosed using multiple statistical metrics and graphical analysis visualization. The results reveal that incorporation of data pre-processing wavelet approach with ELM model enhances the river flow predictability. In quantitative term, the root-mean-square error (RMSE) and mean absolute error (MAE) measurements are reduced by 65% and 67% using WA-ELM over ELM model, respectively. The Taylor diagram reveals much closer proximity and the Violin plot shows similar distribution of WA-ELM simulated river flow to the observed river flow compared to stand-alone ELM simulated river flow. The hybridization of wavelet decomposition method with ELM model improves the ability of ELM model to extract the required information for modeling the non-stationary and high stochastic river flow pattern. Overall, the study reveals that WA-ELM can be a reliable methodology for modeling river flow in semi-arid environment and for different regimes (i.e., low-, medium- and high-flow).

Disturbance, nutrients, and antecedent flow conditions affect macroinvertebrate community structure and productivity in an Arctic river

AbstractClimate change is expected to alter disturbance regimes and biogeochemical cycles that underlie the structure and function of ecosystems worldwide. In the Arctic, rapid warming is already affecting these processes via changes in precipitation and thawing permafrost. We assessed how anticipated changes in disturbance regimes and nutrient availability may affect an arctic river ecosystem (Kuparuk River, Alaska) by analyzing temporal patterns of biofilm chlorophyll mass and macroinvertebrate community structure and productivity. Our study incorporated an upstream reach (sampled 2001–2012) and a downstream reach (sampled 2011–2012) to which phosphorus (P) was added to simulate increases in nutrient supply that are anticipated as permafrost thaws. Greater hydrologic disturbance during the open‐water season correlated with reduced algal biomass and invertebrate secondary production (range ∼ 2–7 g DM m−2 yr−1) in the following spring and summer. Bed disturbing flows also altered macroinvertebrate community structure with distinct “high‐flow” and “base‐flow” assemblages documented. Recovery time was shorter for chlorophyll mass and macroinvertebrate production (∼ 1 yr) than community structure (∼ 3 yr). Experimental P‐addition increased algal biomass and invertebrate production, but also resulted in a third macroinvertebrate assemblage dominated by mobile grazers rather than filter‐feeders. Our results suggest that a decrease in the return interval for bed disturbing floods to < 4 yr will result in persistent changes in macroinvertebrate community structure and fundamental alterations to the food web. These results also demonstrate how arctic river communities may be affected by increases in the magnitude and variability of river discharge and nutrient supplies that are anticipated as the climate warms.

Understanding the effects of river regulation on Atlantic salmon fry: The importance of channel morphology

AbstractRiver regulation influences hydrological regime, channel hydraulics, and habitat quality for freshwater biota. Environmental flow assessments typically require river managers to incorporate the requirements of different freshwater species and life stages in designing discharge regimes. However, these requirements can often conflict or be poorly quantified. There is therefore increasing interest in adaptive management whereby the ecological effects of changing flow regime can be monitored and assessed. This study investigated the effects of flow regulation on Atlantic salmon fry below an impoundment. The flow regime incorporated a compensation flow with an atypical seasonal profile where higher discharges were released in the summer than autumn and a spring high flow (freshet) to facilitate downstream migration of smolts through the dam. Saturation stocking and electrofishing were combined with hydraulic and habitat models to predict the effects of discharge on habitat quality and standardized fry densities. The discharge at which the highest standardized fry densities were observed varied depending on reach morphology, particularly channel roughness. Low fry survival was consistent with predictions of consistently low habitat quality during the spring freshet. Fish locations observed during electrofishing were not always consistent with contemporary flows and may reflect the influence of antecedent flows and high site fidelity. The combination of saturation stocking, hydraulic, and habitat models provides a valuable approach for assessing the effects of regulation. It is recommended that future freshets operate at night, that uninterrupted periods of high flow are avoided during the spring, and that compensation flows reflect natural seasonal patterns.

Monthly streamflow forecasting based on hidden Markov model and Gaussian Mixture Regression

Reliable streamflow forecasts can be highly valuable for water resources planning and management. In this study, we combined a hidden Markov model (HMM) and Gaussian Mixture Regression (GMR) for probabilistic monthly streamflow forecasting. The HMM is initialized using a kernelized K-medoids clustering method, and the Baum–Welch algorithm is then executed to learn the model parameters. GMR derives a conditional probability distribution for the predictand given covariate information, including the antecedent flow at a local station and two surrounding stations. The performance of HMM–GMR was verified based on the mean square error and continuous ranked probability score skill scores. The reliability of the forecasts was assessed by examining the uniformity of the probability integral transform values. The results show that HMM–GMR obtained reasonably high skill scores and the uncertainty spread was appropriate. Different HMM states were assumed to be different climate conditions, which would lead to different types of observed values. We demonstrated that the HMM–GMR approach can handle multimodal and heteroscedastic data.

Modeling Summer Month Hydrological Drought Probabilities in the United States Using Antecedent Flow Conditions

AbstractClimate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5‐11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best‐performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid‐Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.

Macroinvertebrate community responses to hydrological controls and groundwater abstraction effects across intermittent and perennial headwater streams

Intermittent rivers comprise a significant proportion of river networks globally and their spatial extent is predicted to increase with rising water abstraction pressures. Despite this, the ecological implications of hydrological modifications within intermittent rivers have received limited research attention. This paper examines macroinvertebrate assemblages across intermittent and perennial sections of headwater streams within the Hampshire Avon catchment (United Kingdom) over a five-year period. The composition of faunal assemblages was quantified in relation to four hydrological metrics: the duration of flowing conditions, the geographical proximity to the nearest perennial source along each watercourse (two observed flow parameters) and two modelled groundwater abstraction influences. The results highlight that macroinvertebrate communities inhabiting sites which dry periodically and are positioned at greater distances (>c. 2.5km) above the perennial source (the most upstream point of permanent flow within a given year) possessed the highest conservation values. These sites supported species that are rare in many areas of Europe (e.g. Ephemeroptera: Paraletophlebia werneri) or with limited geographical distribution across the United Kingdom (e.g. Trichoptera: Limnephilus bipunctatus). A range of faunal community diversity indices were found to be more sensitive to the antecedent flow duration and distance from the perennial source, rather than any effects of groundwater abstraction. Taxonomic richness responded most strongly to these observed flow parameters and varied more markedly with the distance from the perennial source compared to the antecedent flow duration. Several taxa were significantly associated with the observed flow parameters, particularly those predominantly inhabiting perennially flowing systems. However, the distance that such fauna could migrate into intermittent reaches varied between taxa. This research demonstrates the overriding importance of antecedent flow durations and the geographical proximity to perennial sources on macroinvertebrate communities within intermittent and perennial headwater streams.

Spatial and Temporal Patterns of CO2, CH4, and N2O Fluxes at the Soil-Atmosphere Interface in a Northern Temperate Forested Watershed

Forest soils are recognized as sources and sinks of greenhouse gases (GHG) (CO2, CH4, N2O), but there are limited data quantifying the magnitude of GHG fluxes at the soil-atmosphere interface across a range of landscape hydrogeomorphic conditions. In our study, GHG fluxes were measured in a forested watershed across a range of hydrogeomorphic locations (wetlands, hillslopes, riparian zones, etc) and evaluated in relation to temperature, antecedent flow conditions, and stream chemistry to help develop strategies to scale GHG emissions from the point scale to the watershed scale. Mean study period CO2 fluxes (0.61 to 2.89 gCm-2d-1) were positive at all sites, with larger fluxes occurring in well-drained soils. Negative fluxes (CH4 sinks) were found at the hillslope and lowland sites, while the wetland was a large source of CH4 emissions at the watershed scale. Mean CH4 fluxes ranged from -2.53 to 330.34 mgCm-2d-1. Nitrous oxide fluxes were low relative to other GHG fluxes (in terms of CO2 equivalent) and ranged between -0.72 to 0.70 mgNm-2d-1. Although carbon dioxide fluxes were positively correlated to soil temperature at all locations, CH4 and N2O fluxes were not significantly related to temperature, antecedent flow conditions, or stream chemistry at the watershed scale. However, strong differences in CO2 and CH4 fluxes related to landscape geomorphology were observed, and exceeded the magnitude of seasonal variations for CO2 and CH4 fluxes, suggesting that landscape hydrogeomorphology was likely a stronger predictor of GHG fluxes at the watershed scale than temperature and stream chemistry variables, at least within the confine of one watershed. In lieu of statistical approaches relying on environmental variables to predict GHG fluxes at the watershed scale, geomorphological approaches, potentially coupled with seasonal comparisons of GHG fluxes in each land class, might therefore be a promising research avenue to provide solid watershed wide estimates of GHG fluxes.

Multiscale Upstream and In Situ Precursors to the Elevated Mixed Layer and High-Impact Weather over the Midwest United States

Abstract Two severe MCSs over the upper Midwest United States resulted in >100 mm of rain in a ~24-h period and >200 severe weather reports, respectively, during 30 June–2 July 2011. This period also featured 100 (104) daily maximum high (low) temperature records across the same region. These high-impact weather events occurred in the presence of an elevated mixed layer (EML) that influenced the development of the severe MCSs and the numerous record high temperatures. The antecedent large-scale flow evolution was influenced by early season Tropical Cyclone Meari over the western North Pacific. The recurvature and subsequent interaction of Meari with the extratropical large-scale flow occurred in conjunction with Rossby wave train amplification over the North Pacific and dispersion across North America during 22 June–2 July 2011. The Rossby wave train dispersion contributed to trough (ridge) development over western (central) North America and the development of an EML and the two MCSs over the upper Midwest United States. A composite analysis of 99 warm-season days with an EML at Minneapolis, Minnesota, suggests that Rossby wave train amplification and dispersion across the North Pacific may frequently occur in the 7 days leading up to EMLs across the upper Midwest. The composite analysis also demonstrates an increased frequency of severe weather and elevated temperatures relative to climatology on days with an EML. These results suggest that EMLs over the upper Midwest may often be preceded by Rossby wave train amplification over the North Pacific and be followed by a period of severe weather and elevated temperatures.

Macro‐invertebrate Community Response to Multi‐annual Hydrological Indicators

AbstractFlow is widely considered one of the primary drivers of instream ecological response. Increasingly, hydroecological models form the basis of integrated and sustainable approaches to river management, linking flow to ecological response. In doing so, the most ecologically relevant hydrological variables should be selected. Some studies have observed a delayed macro‐invertebrate (ecological) response to these variables (i.e. a cumulative inter‐annual effect, referred to as multi‐annual) in groundwater‐fed rivers. To date, only limited research has been performed investigating this phenomenon. This paper examines the ecological response to multi‐annual flow indicators for a groundwater‐fed river. Relationships between instream ecology and flow were investigated by means of a novel methodological framework developed by integrating statistical data analysis and modelling techniques, such as principal component analysis and multistep regression approaches. Results demonstrated a strong multi‐annual multi‐seasonal effect. Inclusion of additional antecedent flows indicators appears to enhance overall model performance (in some cases, goodness of fit statistics such as the adjusted R‐squared value exceeded 0.6). These results strongly suggest that, in order to understand potential changes to instream ecology arising from changing flow regimes, multi‐annual and multi‐seasonal relationships should be considered in hydroecological modelling. © 2017 The Authors River Research and Applications Published by John Wiley & Sons Ltd.

Hydroclimate drivers and atmospheric teleconnections of long duration floods: An application to large reservoirs in the Missouri River Basin

A comprehensive framework is developed to assess the flood types, their spatiotemporal characteristics and causes based on the rainfall statistics, antecedent flow conditions, and atmospheric teleconnections. The Missouri River Basin (MRB) is used as a case study for the application of the framework. Floods are defined using the multivariate characteristics of annual peak, volume, duration, and timing. The temporal clustering of flood durations is assessed using a hierarchical clustering analysis, and low-frequency modes are identified using wavelet decomposition. This is followed by an identification of the synoptic scale atmospheric processes and an analysis of storm tracks that entered the basin and their moisture releases. Atmospheric teleconnections are distinctively persistent and well developed for long duration flood events. Long duration floods are triggered by high antecedent flow conditions which are in turn caused by high moisture release from the tracks. For short duration floods, these are insignificant and appear to occur random across the MRB in the recent half-century. The relative importance of hydroclimatic drivers (rainfall duration, rainfall intensity and antecedent flow conditions) in explaining the variance in flood duration and volume is discussed using an empirical log-linear regression model. The implication of analyzing the duration and volume of the floods in the context of flood frequency analysis for dams is also presented. The results demonstrate that the existing notion of the flood risk assessment and consequent reservoir operations based on the instantaneous peak flow rate at a stream gage needs to be revisited, especially for those flood events caused by persistent rainfall events, high antecedent flow conditions and synoptic scale atmospheric teleconnections.

Macroinvertebrate responses to flow and stream temperature variability across regulated and non‐regulated rivers

AbstractFlow regulation via impoundments threatens lotic ecosystems and the services they provide globally. Impoundments drastically alter flow and stream temperature variability within fluvial environments, but efforts to quantify ecohydrological and ecothermal responses to flow regulation in conjunction have been sparsely explored to date. This study examined macroinvertebrate community responses to antecedent flow (discharge) and stream temperature variability across paired regulated and non‐regulated systems associated with three reservoirs located in adjacent catchments. Community abundances, functional traits, and biomonitoring indices were examined, and ecological differences between non‐regulated and regulated sites were quantified, with the most sensitive faunal response being correlated against a suite of flow and thermal indices. Regulated sites exhibited reduced low‐flow variability and rapid increases in discharge during peak flows that regularly exceeded those conveyed by non‐regulated sites, while stream temperature variability was highly congruent between sites. Macroinvertebrate functional traits were particularly sensitive to flow regulation, and incorporating biomonitoring indices marginally improved the ecological discrimination between regulated and non‐regulated sites. Unlike community abundances, functional traits did not vary spatially between catchments, highlighting that such information could guide the implementation of regional environmental flows. Macroinvertebrate communities responded significantly to various hydrological parameters, particularly those associated with the timing of extreme flows, but were less sensitive to thermal controls. Future research should explore ecological responses to antecedent hydrological and stream temperature variability associated with flow regulation to provide a better understanding of the underlying mechanisms driving biotic alterations, which could guide future environmental flow methodologies.

Improving transfer functions to describe radiocesium wash-off fluxes for the Niida River by a Bayesian approach

This paper proposed methodological refinements of the generic transfer function approach to reconstruct radiocesium wash-off fluxes from contaminated catchments, by the integration of hydrological descriptors (passed volume of water, flow rate fluctuations and antecedent flow conditions). The approach was applied to the Niida River (Fukushima prefecture, Japan) for the period 03/2011-03/2015, for which daily flow rate (m3/s) and infrequent total radiocesium concentration (Bq/L) values were available from literature.Three models were defined, generic TF (Φ0), flow-corrected time variant (Φ1) and antecedent-flow corrected variant (Φ2). Calibration of these models’ parameters was performed with a Bayesian approach because it is particularly adapted to limited datasets and censored information, and it provides parameters distributions.The model selection showed strong evidence of model Φ2 (indicated by marginal likelihood), which integrates current and recent hydrology in its formulation, and lower prediction errors (indicated by RMSE and ME). Models Φ1 and Φ2 better described wash-off dynamics compared to model Φ0, due to the inclusion of one or several hydrological descriptors.From March 2011 to March 2015, model Φ2 estimated 137Cs export from Niida catchment between 0.32 and 0.67 TBq, with a median value of 0.49 TBq, which represents around 0.27% of the initial fallout and could represent a significant source-term to the Ocean compared to the direct release from Fukushima Dai-ichi Nuclear Power Plant (FDNPP). Moreover the remaining 99% of the initial radiocesium fallout within the catchment may constitute a persistent contamination source for wash-off.Although the proposed methodology brought improvements in the assessment of wash-off fluxes, it remains an empirical interpolation method with a limited predictive power, particularly for recent low activities. To improve predictions, modelling approaches require more observed data (particularly more activity values corresponding to more hydrological conditions), and the inclusion of more hydrological descriptors.

Sediment motion and velocity in a glacier-fed stream

Current understanding of coarse sediment transport (e.g. threshold for motion, travel length and virtual velocity) in mountain rivers is still quite limited, and even less is known about glacial streams. However, the hydrological characteristics of these systems (strong daily discharge fluctuations, high water turbidity) pose challenges to the use of tracers to monitor bed sediment dynamics, as tagged clasts are usually located after bedload events when flow stage has receded, e.g. by means of portable antennas in the case of Passive Integrated Transponders (PIT). The use of stationary antennas, still scarcely in use worldwide, to detect PIT-tagged particles has potential advantages in glacier-fed streams. If water discharge is monitored continuously, a stationary antenna provides real time data on the actual discharge at the moment of tracer particles passage. This study focuses on incipient motion and virtual velocity of bed particles measured by a stationary antennas system in a steep mountain channel (Saldur River, drainage area 18.6km2, Italian Alps) where significant daily discharge fluctuations and bedload transport occur as a result of a nivo-glacial regime. Four stationary antennas were installed 50-m apart in the study reach. A total of 629 PIT-tagged clasts were inserted in the studied reach between 2011 and 2014, ranging in size from 35mm to 580mm, with an overall recovery rate of around 44%. Critical discharge for sediment entrainment was obtained by detecting the movement of tracers placed immediately upstream of antennas. Virtual velocity was derived by knowing distances between the antennas and travel time of tracers. Results on initiation of motion show that the relationship between the size of transported tracers and the discharge measured at the time clasts were passing the stationary antenna is very weak. The influence of antecedent flows on incipient motion was thus investigated by dividing the highest discharge recorded between each PIT deployment and the subsequent entrainment by the actual critical discharge at the time of movement (ratio Qmax/Qc). Results show that approximately 50% of tracers moved at Qmax/Qc≤1.2, and that 73% of tracers moved at Qmax/Qc<1.5. Therefore, about 30% of tracers had to previously experience a discharge substantially greater than the one that actually mobilized them. Also, coarser particles moved at higher Qmax/Qc ratios, suggesting that higher antecedent flows may be needed to destabilize bed clustering. Results on the virtual velocity of the PIT-tagged clasts employed in the field show that the virtual velocity turned out to be highly variable (ranging from 101 to 10−5mmin−1) and weakly related to either particle size or flow discharge. However, virtual velocity was well correlated with the highest flow discharge experienced by each tracer normalized by a percentile of the flow duration curve. This evidence further stresses the importance of flow history on sediment entrainment and transport. Finally, the pros and cons of the deployed monitoring technology are discussed.

Downstream Dissipation of Storm Flow Heat Pulses: A Case Study and its Landscape‐Level Implications

AbstractStorms in urban areas route heat and other pollutants from impervious surfaces, via drainage networks, into streams with well‐described negative consequences on physical structure and biological integrity. We used heat pulses associated with urban storms as a tracer for pavement‐derived stormwater inputs, providing a conservative estimate of the frequency with which these pollutants are transported into and through protected stream reaches. Our study was conducted within a 1.5‐km reach in Durham, North Carolina, whose headwaters begin in suburban stormwater pipes before flowing through 1 km of protected, 100‐year‐old forest. We recorded heat‐pulse magnitudes and distances travelled downstream, analyzing how they varied with storm and antecedent flow conditions. We found heat pulses &gt;1°C traveled more than 1 km downstream of urban inputs in 11 storms over one year. This best‐case management scenario of a reach within a protected forest shows that urban impacts can travel far downstream of inputs. Air temperature and flow intensity controlled heat‐pulse magnitude, while heat‐pulse size, mean flow, and total precipitation controlled dissipation distance. As temperatures and sudden storms intensify with climate change, heat‐pulse magnitude and dissipation distance will likely increase. Streams in urbanized landscapes, such as Durham municipality, where 98.9% of streams are within 1 downstream km of stormwater outfalls, will be increasingly impacted by urban stormwaters.

Streamflow Prediction of Karuvannur River Basin Using ANFIS, ANN and MNLR Models

For the planning, design and management of water resources systems, streamflow forecasting is important. The use of artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS) and multiple nonlinear regression (MNLR) for predicting daily flow at the outlet of Karuvannur river basin, located in Thrissur district, is presented in this study. Precipitation data from nine raingauge stations were used to develop the models. Input vectors for simulations included different combinations of antecedent precipitation and flows, with different time lags. Performances of the models were evaluated with the RMSE and Nash-Sutcliffe model efficiency values. The results showed that ANFIS model predicts daily flow more accurately compared to ANN and MNLR models. Furthermore, ANFIS model with an input combination of antecedent flow with one day time lag and antecedent rainfall with three and four day time lags, is better than all other cases considered here. Therefore by using the ANFIS model with these 3 inputs we can forecast the daily discharge of Karuvannur river basin with a better accuracy.

A hydrologically sensitive invertebrate community index for New Zealand rivers

Identifying ecological response variables sensitive to hydrological change is a key step in determining the impacts of river flow alterations on aquatic ecosystems and in setting environmental flows that sustain certain ecological values. Building on the successful use of flow regime sensitive aquatic invertebrate indices in other countries, particularly the UK based Lotic Index for Flow Evaluation (LIFE), we provide two variants of a similar index for use in New Zealand (LIFENZ and a weighted variant: LIFENZ_W). As in the original LIFE, the New Zealand indices were based on water velocity preference categories assigned to aquatic invertebrate taxa using professional judgement. To calculate the indices a lookup table is used to assign a score to each taxon based on their velocity category and abundance. For the LIFENZ_W variant an additional step down weighted the scores if the taxon has a general compared to a more specific velocity preference. The two index variants were correlated with each other and to similar environmental parameters. Across a total of 74 sites, both indices were correlated with depth-averaged water velocity. Changes in index values, both between sites and temporally within sites, were predominantly associated with changes in hydrological parameters, such as the magnitude and length of time since a recent high flow, and to a lesser degree with other physico-chemical parameters. Commonly used indices in New Zealand designed to respond to nutrient enrichment (MCI and variants) were not correlated with local water velocity, but were correlated with antecedent flow conditions and were likely influenced by effects of flow stability on algal growth. Further testing of LIFENZ and LIFENZ_W in combination with MCI is recommended, particularly in rivers subject to more extreme hydrological and water quality stresses and with regard to other physical parameters such as hydraulic habitat. However, the LIFENZ and its weighted variant (LIFENZ_W) appear to be useful tools for understanding and managing the effects of hydrological alteration on aquatic invertebrate communities in New Zealand. As LIFENZ and LIFENZ_W were strongly correlated and only showed a relatively small deviation from a slope of 1 we recommend the use of the more straightforward LIFENZ in almost all circumstances.

Forecasting reservoir inflows using remotely sensed precipitation estimates: a pilot study for the River Naryn, Kyrgyzstan

ABSTRACTThis study explores the feasibility of applying remotely sensed precipitation estimates (in this case from the Tropical Rainfall Measuring Mission [TRMM]) for forecasting inflows to the strategically important Toktogul reservoir in the Naryn basin, Kyrgyzstan. Correlations between observed precipitation at Naryn and 0.5° TRMM totals is weaker for daily (r = 0.25) than monthly (r = 0.93) totals, but the Naryn gauge is representative of monthly TRMM precipitation estimates across ~60% of the basin. We evaluate predictability of monthly inflows given TRMM estimates, air temperature and antecedent flows. Regression model skill was superior to the zero order forecast (mean flow) for lead-times up to three months, and had lower errors in estimated peaks. Over 80% of the variance in monthly inflows is explained with three-month lead, and up to 65% for summer half-year average. The analysis also reveals zones that are delivering highest predictability and hence candidate areas for surface network expansion.Editor Z.W. Kundzewicz Associate editor Not assigned

Using abiotic drivers of fish spawning to inform environmental flow management

Summary Environmental flows are a key restoration technique for conserving ecological function in flow‐degraded rivers. Species‐specific, flow–biota relationships are increasingly being used to determine environmental flow needs and manage their use; however, many of these relationships are poorly described. We evaluate relationships between environmental variables and spawning intensity for a fish assemblage from the Murray River, Australia, over a ten‐year period. We developed a hierarchical multispecies model that accounted for incomplete detection to compare spawning outcomes of native and non‐native species using realistic, alternative, water management scenarios. Temperature was an important predictor of spawning intensity for all seven species studied, while both concurrent and antecedent flow conditions were important for many species. Our water management scenario testing accounted for these relationships and indicated that increasing the magnitude of smaller floods following lower antecedent flow conditions, at water temperatures of 18–20°C, achieves the greatest spawning outcome for native fish. Synthesis and applications. Our results indicate that principally temperature, and flow as a secondary variable, influence the timing and strength of fish spawning. The synthesis of these spawning relationships predicts that managers will achieve the greatest spawning return per unit of environmental water when flows are applied on top of an existing flow pulse. This study highlights the importance of considering a range of abiotic factors and the use of modelling scenarios to improve environmental flow outcomes.