Search

In several hydrological studies the need for consistency in hydrological modeling was highlighted. To achieve model consistency, it is required that all relevant hydrological processes are evaluated for accuracy in their spatio-temporal representation under consideration of available observations. In this study, we transfer the idea of hydrological consistency to water quality modeling. We focus on water quality modelling in rural mesoscale catchments and the interaction with agricultural production systems and their management. Based on several studies, we have developed a guideline which includes the following six challenges:Representation of rural landscape: Spatial and temporal patterns of land use and land management are critical to adequately represent water quality in models. Remote sensing and land use models are very useful resources to be exploited. Accuracy in model structure and model parameters: The transfer of a model diagnostic analysis to water quality leads to a better understanding of how water quality variables are controlled by model structures and corresponding model parameters. Check of multiple model output for consistency: Assessing multiple model outputs regarding their temporal, spatial and process performance using observed time series, remotely sensed spatial patterns, knowledge about transport pathways and even soft data can significantly enhance model consistency. Joint multi-metric calibration of discharge and water quality for all magnitudes: Multi-metric calibration using performance metrics and signature measures both for discharge and water quality, such as flow and nitrate duration curve, leads to more balanced model simulations that represent all magnitudes of discharge and water quality accurately. Scenarios and storylines for reliable land management: Scenarios and storylines should be co-developed with stakeholders in the river basin to increase realism and the acceptance of model results. They should be coherent in space and time, and provide a mix of available management options. Consistent interpretation of impacts on water quality: The interpretation of scenarios can be supported by diagnostic tools to show the effectiveness of measures and their combinations while considering their costs and impacts on ecosystem services. In our contribution, we give examples and further details regarding each challenge to give insights how to achieve consistency in water quality modelling.

AimInvasive alien species are a growing problem worldwide due to their ecological, economic and human health impacts. The “killer shrimp” Dikerogammarus villosus is a notorious invasive alien amphipod from the Ponto-Caspian region that has invaded many fresh and brackish waters across Europe. Understandings of large-scale population dynamics of highly impactful invaders such as D. villosus are lacking, inhibiting predictions of impact and efficient timing of management strategies. Hence, our aim was to assess trends and dynamics of D. villosus as well as its impacts in freshwater rivers and streams.LocationEurope.MethodsWe analysed 96 European time series between 1994 and 2019 and identified trends in the relative abundance (i.e. dominance %) of D. villosus in invaded time series, as well as a set of site-specific characteristics to identify drivers and determinants of population changes and invasion dynamics using meta-regression modelling. We also looked at the spread over space and time to estimate the invasion speed (km/year) of D. villosus in Europe. We investigated the impact of D. villosus abundance on recipient community metrics (i.e. abundance, taxa richness, temporal turnover, Shannon diversity and Pielou evenness) using generalized linear models.ResultsPopulation trends varied across the time series. Nevertheless, community dominance of D. villosus increased over time across all time series. The frequency of occurrences (used as a proxy for invader spread) was well described by a Pareto distribution, whereby we estimated a lag phase (i.e. the time between introduction and spatial expansion) of approximately 28 years, followed by a gradual increase before new occurrences declined rapidly in the long term. D. villosus population change was associated with decreased taxa richness, community turnover and Shannon diversity.Main ConclusionOur results show that D. villosus is well-established in European waters and its abundance significantly alters ecological communities. However, the multidecadal lag phase prior to observed spatial expansion suggests that initial introductions by D. villosus are cryptic, thus signalling the need for more effective early detection methods.

Understanding current and possible future alterations of water resources under climate change and increased water demand allows for better water and environmental management decisions in arid regions. This study aims at analyzing the impact of groundwater demand and climate change on groundwater sustainability and hydrologic regime alterations in a wadi system in central Iran. A hydrologic model is used to assess streamflow and groundwater recharge of the Halilrood Basin on a daily time step under five different scenarios over the baseline period (1979–2009) and for two future scenario periods (near future: 2030–2059 and far future: 2070–2099). The Indicators of Hydrologic Alteration (IHA) with a set of 32 parameters are used in conjunction with the Range of Variability Approach (RVA) to evaluate hydrologic regime change in the river. The results show that groundwater recharge is expected to decrease and is not able to fulfill the increasing water demand in the far future scenario. The Halilrood River will undergo low and moderate streamflow alteration under both stressors during the near future as RVA alteration is classified as “high” for only three indicators, whereas stronger alteration is expected in the far future, with 11 indicators in the high range. Absolute changes in hydrologic indicators are stronger when both climate change and groundwater demand are considered in the far future simulations, since 27 indicators show significant changes, and the RVA shows high and moderate levels of changes for 18 indicators. Considering the evaluated RVA changes, future impacts on the freshwater ecosystems in the Halilrood Basin will be severe. The developed approach can be transferred to other wadi regions for a spatially distributed assessment of water resources sustainability.

We examined how communities of macroinvertebrates occurring in functional process zones (FPZs) are affected by the location of FPZs in the river continuum. We delineated FPZs for three rivers displaying significant disparities in elevation, annual precipitation, valley shape, and other valley‐scale hydrogeomorphic variables. We extracted corresponding macroinvertebrate community data from the US National Water Quality Monitoring Council database and matched it to the stream order (SO) and FPZ delineations. We examined community structure in the three rivers by partitioning the variances associated with the FPZ and SO delineations. Then, we examined community variation as patterns of beta‐diversity for communities of FPZs in different SOs. In total, 23 FPZ‐SO configurations were examined. SO and FPZ delineations contributed similarly to the variance in the structure of macroinvertebrate communities. Taxa turnover accounted for the majority of the compositional change in communities of FPZs along the river continuum, while the functional composition showed primarily a nested structure. Pairwise comparison of communities for each FPZ along the river continuum showed that significant differences in community composition occurred at high SO in the three examined rivers. In this manuscript, we show that communities of FPZs are only partially comparable along the river continuum as significant compositional changes occur when comparing communities of FPZs in distant SOs. We bring, therefore, new elements to improve the interpretation of the River Ecosystem Synthesis concept that can have wider implications for understanding the biocomplexity of hydrogeomorphic patchiness in river networks.

Water resources are precious in arid and semi-arid areas such as the Wadis of Iran. To sustainably manage these limited water resources, the residents of the Iranian Wadis have been traditionally using several water use systems (WUSs) which affect natural hydrological processes. In this study, WUSs and soil and water conservation measures (SWCMs) were integrated in a hydrological model of the Halilrood Basin in Iran. The Soil and Water Assessment Tool (SWAT) model was used to simulate the hydrological processes between 1993 and 2009 at daily time scale. To assess the importance of WUSs and SWCMs, we compared a model setup without WUSs and SWCMs (Default model) with a model setup with WUSs and SWCMs (WUS-SWCM model). When compared to the observed daily stream flow, the number of acceptable calibration runs as defined by the performance thresholds (Nash-Sutcliffe efficiency (NSE)≥0.68, −25%≤percent bias (PBIAS)≤25% and ratio of standard deviation (RSR)≤0.56) is 177 for the Default model and 1945 for the WUS-SWCM model. Also, the average Kling-Gupta efficiency (KGE) of acceptable calibration runs for the WUS-SWCM model is higher in both calibration and validation periods. When WUSs and SWCMs are implemented, surface runoff (between 30% and 99%) and water yield (between 0 and 18%) decreased in all sub-basins. Moreover, SWCMs lead to a higher contribution of groundwater flow to the channel and compensate for the extracted water by WUSs from the shallow aquifer. In summary, implementing WUSs and SWCMs in the SWAT model enhances model plausibility significantly.

Stream ecosystems are impacted by multiple stressors in complex spatio-temporal interactions. The lack of understanding of these interactions and impacts hampers the successful restoration of streams and rivers. The German Research Foundation-funded collaborative research centre RESIST (https://sfb-resist.de/index.html) aims to disentangle these complex dependencies applying a novel theoretical framework: the ‘Asymmetric Response Concept’. The concept hypothesizes that degradation and recovery processes depend on different, non-linear biotic and abiotic interactions between stressors, environmental variables, and organisms. Therefore, unprecedented data and information are required which are collected through lab and field experiments, species sampling, observations of environmental variables and modelling.High-resolution ecohydrological modelling is a core component in this process to provide historic information on water quality in two mesoscale catchments (Boye with 124km² and Kinzig with 1065km²) in Germany. Due to history, storage- and hysteresis effects in the hydrologic system, the spatio-temporal dynamics of in-stream environmental variables follow an asymmetric function to degradation and recovery. The model SWAT+ (Soil and Water Assessment Tool) is therefore applied to simulate streamflow as well as the water quality components temperature, oxygen, nitrogen components and salinity (TONS) at more than 20 sites in each catchment.We present the conceptual framework of the approach, including data sources and data collection, model parameterization, required code adaptations, calibration techniques and expected results.

The geographic distribution of streams and rivers drives a multitude of patterns and processes in hydrology, geomorphology, geography, and ecology. Therefore, a hydrographic network that accurately delineates both small streams and large rivers, along with their topographic and topological properties, with equal precision would be indispensable in the earth sciences. Currently, available global hydrographies do not feature small headwater streams in great detail. However, these headwaters are vital because they are estimated to contribute to more than 70 % of overall stream length. We aimed to fill this gap by using the MERIT Hydro digital elevation model at 3 arcsec (∼90 m at the Equator) to derive a globally seamless, standardised hydrographic network, the “Hydrography90m”, with corresponding stream topographic and topological information. A central feature of the network is the minimal upstream contributing area, i.e. flow accumulation, of 0.05 km2 (or 5 ha) to initiate a stream channel, which allowed us to extract headwater stream channels in great detail. By employing a suite of GRASS GIS hydrological modules, we calculated the range-wide upstream flow accumulation and flow direction to delineate a total of 1.6 million drainage basins and extracted globally a total of 726 million unique stream segments with their corresponding sub-catchments. In addition, we computed stream topographic variables comprising stream slope, gradient, length, and curvature attributes as well as stream topological variables to allow for network routing and various stream order classifications. We validated the spatial accuracy and flow accumulation of Hydrography90m against NHDPlus HR, an independent, national high-resolution hydrographic network dataset of the United States. Our validation shows that the newly developed Hydrography90m has the highest spatial precision and contains more headwater stream channels compared to three other global hydrographic datasets. This comprehensive approach provides a vital and long-overdue baseline for assessing actual streamflow in headwaters and opens new research avenues for high-resolution studies of surface water worldwide. Hydrography90m thus offers significant potential to facilitate the assessment of freshwater quantity and quality, inundation risk, biodiversity, conservation, and resource management objectives in a globally comprehensive and standardised manner. The Hydrography90m layers are available at https://doi.org/10.18728/igb-fred-762.1 (Amatulli et al., 2022a), and while they can be used directly in standard GIS applications, we recommend the seamless integration with hydrological modules in open-source QGIS and GRASS GIS software to further customise the data and derive optimal utility from it.

International audience; Globalization has led to the introduction of thousands of alien species worldwide. With growing impacts by invasive species, understanding the invasion process remains critical for predicting adverse effects and informing efficient management. Theoretically, invasion dynamics have been assumed to follow an "invasion curve" (S-shaped curve of available area invaded over time), but this dynamic has lacked empirical testing using large-scale data and neglects to consider invader abundances. We propose an "impact curve" describing the impacts generated by invasive species over time based on cumulative abundances. To test this curve's large-scale applicability, we used the data-rich New Zealand mud snail Potamopyrgus antipodarum, one of the most damaging freshwater invaders that has invaded almost all of Europe. Using long-term (1979-2020) abundance and environmental data collected across 306 European sites, we observed that P. antipodarum abundance generally increased through time, with slower population growth at higher latitudes and with lower runoff depth. Fifty-nine percent of these populations followed the impact curve, characterized by first occurrence, exponential growth, then long-term saturation. This behaviour is consistent with boom-bust dynamics, as saturation occurs due to a rapid decline in abundance over time. Across sites, we estimated that impact peaked approximately two decades after first detection, but the rate of progression along the invasion process was influenced by local abiotic conditions. The S-shaped impact curve may be common among many invasive species that undergo complex invasion dynamics. This provides a potentially unifying approach to advance understanding of large-scale invasion dynamics and could inform timely management actions to mitigate impacts on ecosystems and economies.

Production of a large ensemble of climate simulations suitable for impact assessments is an attempt to enhance our knowledge about the associated uncertainties in future projections. However, the actual quantification of the change in the climate and its impact relies on the ensemble of models selected, particularly given the wide availability of climatic simulations from various initiatives, i.e. CMIP5, CORDEX.Here, we hypothesize that historical streamflow observations contain valuable information to investigate practices for the selection of climate model ensembles. We apply eight selection methods (based on democracy, diversity of GCM, diversity of RCM, maximum information minimum redundancy, best performing hindcasted climate depiction, best performing hydrological model, simple climate model averaging and reliable ensemble average) to subset an ensemble available from 16 combinations of Euro-CORDEX GCM-RCM by comparing observed to simulated streamflow shift of the Danube from a reference period (1960–1989) to an evaluation period (1990–2014). Simulations are carried out with the well-performing Upper Danube COSERO hydrological model, spanning a calibration and evaluation period of more than 100 years. Comparison against no selection shows that an informed selection of ensemble members improves the quantification of climate change impacts where methods that maintain the diversity and information content of the full ensemble are favourable. In addition, the method followed allows the assessment which individual climate models perform best, where only three of 16 models were able to correctly reproduce the direction of streamflow change in each season.Prior to carrying out climate impact assessments, we propose splitting the long-term historical data and using it to test climate model performance, sub-selection methods, and their agreement in reproducing the indicator of interest, which further provide the expectable benchmark of near- and far-future impact assessments. This test can further be applied in multi-basin experiments to obtain a better understanding of uncertainty propagation and uncertainty reduction in hydrological impact studies.

Most Wadi systems of the world are threatened by climate change and unsustainable consumption through different water use systems (WUS) which can result in an alteration of the hydrologic regime, a deterioration of water resources, and their valuable ecosystems. The objective of this study is to assess the impact of climate change and growing water demand on the alteration of the Halilrood River’s flow regime and the associated impacts on the ecosystem of the Jazmorian wetland in central Iran. The Soil and Water Assessment Tool (SWAT) model is used to simulate the flow regime of the near and far future (2030-2059 and 2070-2099). Based on 32 Indicators of Hydrologic Alteration (IHA) in conjunction with the Range of Variability Approach (RVA) alterations in the flow regime are evaluated. Impacts of three scenarios for future water use (No-, Constant-, and Projected-WUS) are assessed. No-WUS assumes pristine conditions in the future when no water use system are included in the model (no demand) and we only account for the impact of climate change; Constant-WUS assumes unaltered groundwater demand in the future; and Projected-WUS corresponds to the increases in the number of water use systems in the future (increasing demand). Flow regime alteration assessment indicates that climate change will severely affect the magnitude of monthly and annual extreme flows, frequency and duration of high and low Pulses in the Halilrood Basin, especially in the far future. The comparison of model simulations under different scenarios shows that the impact of climate change was more intense when growing water demand in the future is taken into account. The result of the RVA test indicates moderate and high level of changes for 18 indicators, thus likely affecting the environmental flows required for the health of the downstream wetland.

Understanding current and possible future alterations of water resources under climate change and increased water withdrawal allows for better water and environmental management decisions in arid regions. This study aims at analyzing the impact of groundwater withdrawals and climate change on groundwater sustainability and hydrologic regime alterations in a Wadi system in central Iran. A hydrologic model is used to assess streamflow and groundwater recharge of the Halilrood Basin on a daily time step under different scenarios over a model setup period (1979–2009) and for two future scenario periods (near future: 2030–2059 and far future: 2070–2099). The Indicators of Hydrologic Alteration (IHA) with a set of 32 parameters are used in conjunction with the Range of Variability Approach (RVA) to evaluate hydrologic regime change in the river. The results show that groundwater recharge is expected to decrease, and is not able to fulfil the increasing water demand in the far future scenario. The Halilrood River will undergo low and moderate flow alteration under both stressors during the near future as RVA alteration is classified as high for only three indicators, while in the far future, 11 indicators lie in high range. Absolute changes in hydrologic indicators are stronger when both climate change and withdrawals are considered in the far future simulations, since 27 indicators show significant changes and RVA show high and moderate level of changes for 18 indicators. Considering the evaluated RVA changes, future impacts on the freshwater ecosystems in the Halilrood Basin will be severe. The developed approach can be transferred to other Wadi regions for a spatially-distributed assessment of water resources sustainability.

A recent global meta‐analysis reported a decrease in terrestrial but increase in freshwater insect abundance and biomass (van Klink et al., Science 368, p. 417). The authors suggested that water quality has been improving, thereby challenging recent reports documenting drastic global declines in freshwater biodiversity. We raise two major concerns with the meta‐analysis and suggest that these account for the discrepancy with the declines reported elsewhere. First, total abundance and biomass alone are poor indicators of the status of freshwater insect assemblages, and the observed differences may well have been driven by the replacement of sensitive species with tolerant ones. Second, many of the datasets poorly represent global trends and reflect responses to local conditions or nonrandom site selection. We conclude that the results of the meta‐analysis should not be considered indicative of an overall improvement in the condition of freshwater ecosystems. This article is categorized under: Water and Life > Conservation, Management, and Awareness, Relying on abundance or biomass and examining nonrepresentative datasets limits our ability to infer the condition of freshwater insect communities globally. Photo by Jeremy Monroe, Freshwaters Illustrated: a caddisfly larva from an Oregon Coastal stream, USA (Limnephilidae: Dicosmoecus sp.)., Federal Agency for Nature Conservation (BfN) http://dx.doi.org/10.13039/100010606, NSF Macrosystems Biology Program, Leibniz‐Gemeinschaft http://dx.doi.org/10.13039/501100001664

Freshwater ecosystems have higher proportions of extinct and threatened species than terrestrial and marine ecosystems, with populations of vertebrates declined by 83% between 1970 and 2018. The pressing question is: what are the main drivers for this decline? Here we investigate the reasons for the loss of freshwater biodiversity using globally available gridded datasets at 0.5° spatial resolution on precipitation and temperature, land cover and land use, water use and dams as well as daily hydrological streamflow simulations from the ISIMIP initiative.Across the past 50 years, we constructed annual change maps of the environmental variables along the global river networks and calculated time-variant indicators of hydrologic alteration (IHA) to depict hydrological change. We then calculated normalized indicators (e.g. proportion of threatened species) describing the current freshwater biodiversity status through species data aggregation of the International Union for Conservation of Nature's Red List of Threatened Species (IUCN Red List) categories.By applying classification and regression trees (CART), we highlight the importance of environmental- and hydrological change on the freshwater biodiversity status based on IUCN Red List assessments on each grid cell globally. Our results reveal a large-scale spatial classification of the environmental variables and their potential impact on the ongoing freshwater biodiversity crisis.

The estimation of pesticide concentrations in surface water bodies with models is a critical component of the environmental and human health risk assessment process. The most recent version of the Soil and Water Assessment Tool (SWAT+) provides new features that are useful for pesticide exposure assessments. This research is the first SWAT+ pesticide simulation study and was conducted to evaluate SWAT+’s new features and to assess its ability to predict pesticide and metabolite concentrations. The evaluation was conducted based upon a comparison of the results from seven different model configurations with high-resolution monitoring data. The results showed that (1) SWAT+ is able to simulate the formation of degradation compounds and predict resulting concentrations in surface water, (2) an accurate representation of transport processes for pesticide exposure assessments is important, and (3) an appropriate degree of realism can be achieved with a rule-based probabilistic pesticide application schedule if information about the annual percent crop treated, a typical application rate, and a typical application window is available. The accuracy of the pesticide concentration simulations with the new features of SWAT+ in the present study demonstrates the model’s ability to provide more accurate estimates with reduced uncertainty compared to SWAT simulations.

Hydrological indicators such as duration, frequency, magnitude, rate and timing of flow events are used to evaluate and, in models, predict the response of aquatic species to hydrological conditions. Hydrological models are generally optimized without considering specific species preferences by minimizing overall differences between observed and simulated flows using common hydrological objective functions. We hypothesize that hydrological models optimized to implicitly consider species’ flow preferences will yield more reliable predictors. To test this hypothesis, we developed a flexible evaluation method in which the hydrological model was optimized for different objective functions. We tested this concept for benthic invertebrates and selected seven species-relevant hydrological indicators as well as four objective functions based on commonly used hydrological performance criteria. Model parameterizations for these cases were assessed on their ability to reproduce an indicator-based performance criterion developed by applying feature scaling to the indicators. The results show that three indicator-based objective functions performed up to 14% better than the standard hydrological performance criterion KGE. When optimizing for individual or multiple indicators, we found that it is important to consider that other indicators are compromised. An evaluation of this trade-off showed a considerable range in indicator values and implausible indicator depictions. We conclude that optimizing hydrological models to depict species preferences most effectively requires consideration of different objective functions that are based on hydrological indicators. Doing so, instead of simply optimizing to standard hydrological objective functions, can yield a rewarding result in terms of a more species-tailored model parameterization and, ultimately, a better prediction of aquatic species.

Reliable simulations of hydrological models require that model parameters are precisely identified. In constraining model parameters to small ranges, high parameter identifiability is achieved. In this study, it is investigated how precisely model parameters can be constrained in relation to a set of contrasting performance criteria. For this, model simulations with identical parameter samplings are carried out with a hydrological model (SWAT) applied to three contrasting catchments in Germany (lowland, mid-range mountains, alpine regions). Ten performance criteria including statistical metrics and signature measures are calculated for each model simulation. Based on the parameter identifiability that is computed separately for each performance criterion, model parameters are constrained to smaller ranges individually for each catchment. An iterative repetition of model simulations with successively constrained parameter ranges leads to more precise parameter identifiability and improves model performance. Based on these results, a more consistent handling of model parameters is achieved for model calibration.

The Universal Soil Loss Equation (USLE) is the most commonly used model to assess soil erosion by water. The model equation quantifies long-term average annual soil loss as a product of the rainfall erosivity R, soil erodibility K, slope length and steepness LS, soil cover C and support measures P. A large variety of methods exist to derive these model inputs from readily available data. However, the estimated values of a respective model input can strongly differ when employing different methods and can eventually introduce large uncertainties in the estimated soil loss. The potential to evaluate soil loss estimates at a large scale are very limited, due to scarce in-field observations and their comparability to long-term soil estimates. In this work we addressed (i) the uncertainties in the soil loss estimates that can potentially be introduced by different representations of the USLE input factors and (ii) challanges that can arise in the evaluation of uncertain soil loss estimates with observed data. In a systematic analysis we developed different representations of USLE inputs for the study domain of Kenya and Uganda. All combinations of the generated USLE inputs resulted in 756 USLE model setups. We assessed the resulting distributions in soil loss, both spatially distributed and on district level for Kenya and Uganda. In a sensitivity analysis we analyzed the contributions of the USLE model inputs to the ranges in soil loss and analyzed their spatial patterns. We compared the calculated USLE ensemble soil estimates to available in-field data and other study results and addressed possibilities and limitations of the USLE model evaluation. The USLE model ensemble resulted in wide ranges of estimated soil loss, exceeding the mean soil loss by over an order of magnitude particularly in hilly topographies. The study implies that a soil loss assessment with the USLE is highly uncertain and strongly depends on the realizations of the model input factors. The employed sensitivity analysis enabled us to identify spatial patterns in the importance of the USLE input factors. The C and K factors showed large scale patterns of importance in the densely vegetated part of Uganda and the dry north of Kenya, respectively, while LS was relevant in small scale heterogeneous patterns. Major challenges for the evaluation of the estimated soil losses with in-field data were due to spatial and temporal limitations of the observation data, but also due to measured soil losses describing processes that are different to the ones that are represented by the USLE.

Shallow bays along the fringe of an estuarine channel impact salinity distribution. The primary mechanism of impact has been termed “tidal trapping,” and is a result of the phase difference...

For discussing and planning sustainable land management of river basins, stakeholders need suitable information on spatio-temporal patterns of natural processes and human actions. This study shows an approach to use ecohydrological modelling results for assessing water-related ecosystem services in three lowland river basins in Western Siberia. Based on the results of the ecohydrological model SWAT (Soil and Water Assessment Tool, Arnold et al., 1998), simulated output variables were used as indicators for the two regulating services water flow regulation and erosion regulation. The model results were translated into a relative ecosystem service valuation scale, which facilitates the comparison of different ecosystem services and which serves as the base for the applied mapping approach. The ecosystem service maps show different spatial and seasonal patterns. Although the daily modelling results were aggregated to seasonal maps to generate an understandable amount of information for stakeholders, differences can be depicted: during snowmelt, low regulation can be determined, especially for water flow regulation, but a very high regulation was calculated for the vegetation period during summer and for the winter period. Erosion regulation is high in two basins during all seasons. Spatio-temporal differences were modelled only for the largest basin. The SWAT model serves as a suitable quantification method for the assessment of the selected water-related regulating services.

In this study, we analyse possible future climatic changes in three catchments, namely, Pyshma, Vagai and Loktinka located in the Western Siberian lowland region, and the resulting impact on hydrological regimes. It involved downscaling the GCM outputs based on the established statistical relationship between large-scale atmospheric variables and station data and simulating the effects of climate change on hydrological regimes via hydrological modelling. This was done for RCP 2.6, 4.5 and 8.5 based on second-generation Canadian Earth System Model used in the IPCC fifth assessment report. This paper provides the first climate change projections on a local scale in these catchments. The statistical downscaling showed that there will be an increase in both maximum and minimum temperature at all stations under all scenarios. The mean annual daily precipitation increased in Loktinka and Pyshma basins under all scenarios, but there was no clear trend in Vagai basin. The possible increase in annual precipitation is mostly due to the projected increase in autumn and winter precipitation. Annual streamflow tends to increase in all catchments under all scenarios.

Understanding the connections between climate, anthropogenic impacts, and hydrology is fundamental for assessing future climate change. However, a comprehensive methodology is lacking to understand significant changes in the discharge regime and their causes. We propose an approach that links change point tests with hydrologic metrics applied to two Vietnamese catchments where both climatic and anthropogenic changes are observed. The change points in discharge series are revealed by six widely used change point tests. Then, 171 hydrologic metrics are investigated to evaluate all possible hydrological changes that occurred between the pre- and post-change point period. The tests showed sufficient capabilities to detect hydrological changes caused by precipitation alterations and damming. Linking the change point tests to the hydrological metrics had three benefits: (1) the significance of each detected change point was evaluated, (2) we found which test responds to which hydrologic metric, and (3) we were able to disentangle the hydrological impacts of the climatic and anthropogenic changes. Due to its objectivity, the presented method can improve the interpretation of anthropogenic changes and climate change impacts on the hydrological system.

Understanding and quantifying the effects of future climate change is currently one of the most pressing challenges in science and of high relevance for society. Most future climate change studies consider changes between arbitrary time periods. We specify these time periods by splitting climate-change impacted streamflow time series at instances of highest change, by using statistical tests. We used the daily streamflow from 2000 to 2099 simulated from a comprehensive ensemble of the EURO-CORDEX climate change data in three basins across Germany (Treene, lowland; Kinzig, mid-range mountain; and Ammer, pre-alpine). Change points in each basin were detected by using six change point tests. The robustness of changes was analyzed with a bootstrapping procedure. A set of 32 Indicators of Hydrologic Alteration (IHA) was used to examine characteristics of hydrologic changes in the simulated discharge time series between pre- and post-change-point period in absolute change and in deviation of the Range of Variability Approach (RVA). The results show that the occurrence of change points due to climate change is spread throughout the decades, but strongly clustered in the current and upcoming decade. The selection of global and regional climate models impacts the occurrence of change points to a greater extent than the choice of greenhouse gas emission scenarios and bias correction method. The highest significant alteration of IHA occurs in the lowland-, less in the alpine- and least in the mid-range mountain catchment. The transition of hydrologic regimes to an alternative state after the identified change points is likely to occur because the majority of indicators move out of the current state of RVA. We further notice ecoregion-dependent changes in summer discharges and extreme low flows, which increase in the lowland and decrease in the pre-alpine catchment. This may have a detrimental effect on local aquatic communities. We conclude that the combined analysis of simulated climate scenarios, change points and IHA enables a better interpretability of potential future hydrological changes both in timing and severity and provides an early warning signal of changes for climate change mitigation.

Freshwater species are adapted to and depend on various discharge conditions, such as 32 indicators of hydrologic alteration (IHA). Knowing how these indicators will be altered under climate change is essential for predicting species response and to develop mitigation concepts. The simulation of IHA under climate change is subject to considerable uncertainties which should be considered to obtain credible and robust predictions. Therefore, we investigated the major uncertainties inherent in climate change data and processing: general circulation model (GCM) and regional climate model (RCM) choice, representative concentration pathway (RCP) scenario, bias correction (BC) method, all within three mesoscale catchments in the European ecoregions: Central Plains, Central Highlands, and Alpine. Highest uncertainties were caused by the GCM and RCM choice, followed by the type of BC and the RCP. For the prediction, we reduced these uncertainties tailored to the ideal depiction of the IHA in each ecoregion. Together with a significance test, this enabled a robust depiction of the change in IHA for two future time periods. We found diverging changes within the ecoregions, caused by the complex interaction between precipitation, temperature and the governing catchment hydrological processes. The results provide an important basis for further impact research, especially for ecological freshwater studies.

River ecosystems are influenced by natural processes and anthropogenic impacts at different spatial and temporal scales. Understanding these complex interactions for current conditions is the first requirement to be able to simulate the impact of changes in a catchment on river ecosystems. Climate change causes alterations of hydrologic patterns such as seasonal flow and extreme flows. Knowing the magnitude and frequency of these alterations is the second requirement for simulating climate change implications in river ecosystems. The third requirement is an appropriate implementation of these multiple processes in a model cascade; for example, ranging from hydrological via hydraulic models to biological predictions. Scenario simulations with a model cascade detect the impact of changes in stressors on river ecosystems at different spatial and temporal scales. Uncertain aspects within this model cascade require a special focus in order to obtain reliable predictions.

Publisher's version (útgefin grein), This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come., We would like to thank the members of the IAHS, EGU, AGU and IAH for supporting this initiative. The LinkedIn group and overall secretariat was hosted by the IAHS, the Splinter meeting by EGU and the Vienna Catchment Science Symposium by the Vienna Doctoral Programme on Water Resource Systems (DK W1219-N28) funded by the Austrian Science Funds (FWF)., "Peer Reviewed"

The relevance of hydrological processes varies in space and time resulting in typical temporal patterns for catchments. Contrasting catchments moreover differ in their catchment metrics. Hydrological models claim to be able to reproduce typical temporal patterns of dominant processes using site-specific model parameters. Thus, patterns of temporal dynamics in dominant modelled processes and their corresponding dominant parameters are a fingerprint of how a model represents the hydrological behaviour of a catchment and how these process patterns vary between contrasting catchments. In this study, we demonstrate how catchment metrics, modelled processes and parameter dominances can be jointly used to characterise catchments. We assess how catchment characteristics are represented in spatio-temporal process dynamics in models and how to understand the reasons for hydrological (dis)similarity among catchments along a landscape gradient. For this purpose, catchment metrics which characterise contrasting landscapes (lowland, mid-range mountain and alpine catchments) are related to dominant processes and parameters which were provided by a temporally resolved sensitivity analysis (TEDPAS) and simulations of a hydrological model. Our study shows that the applied model is able to represent the different processes and their seasonal variability according to the specific hydrological conditions of the study catchments. By analysing catchment metrics, modelled processes and model parameters jointly, we show that the largest differences are identified for the alpine catchment, whilst similarities are found among the other catchments. Following a landscape gradient, high flow phases are dominated by different flow components. In contrast, the model shows groundwater dominance in low flow phases in non-alpine catchments while in the alpine catchment low flows in winter are mainly controlled by snow processes. The joint analysis of catchment metrics, temporal dynamics of dominant processes and parameters can therefore be used to better disentangle similarities and differences among catchments from different landscapes.

We used the hydrologically corrected Multi-Error- Removed Improved-Terrain Digital Elevation Model at a 3 arc- second (90 m) spatial resolution to derive a seamless, standardized stream network by using GRASS-GIS hydrological modules. We compared the spatial accuracy of the derived stream network with the NHDPlusV2 dataset across the conterminous Unites States. The results demonstrate that spatial accuracy is in the order of 1 pixel displacement compared to the NHDPlusV2 locations, indicating a high level of accuracy. The implemented methodology will be extended to a global scale hydrography in an upcoming project.

Even though soil loss in the lowlands imposes not as much a restriction on land use and agricultural productivity as in erosion affected mountainous areas, the input of fine sediment into the rivers and streams is a concern due to water quality issues and substrate siltation. Drains, river banks and agricultural fields are the three main sources of fine sediment in lowland regions. For a successful implementation of measures to decrease sediment input a well-founded knowledge of the individual entry pathways is essential. To assess the importance of possible entry pathways, a GIS based methodology (SEPAL) has been established combining the ABAG, a river bank erosion formula and a regression approach to include the contributions of drains. SEPAL has been applied on a study catchment in Northern Germany. The results show that 15% of the sediment input into the river comes from agricultural drains, 71% from river banks and 14% from adjacent fields. A comparison of the results with field-mapping and -sampling shows that the approach is plausible. The calculated total annual sediment input is 616 t yr−1, while the measured suspended sediment load is 636 t yr−1. It can be concluded that the methodology is suitable for estimating sediment entry pathways and annual sediment loads in lowland catchments as a base for modelling projects and further investigations. However, further work is necessary for gaining sound knowledge about uncertainties and especially about the processes forcing sediment input from drains.

Global change has the potential to affect river flow conditions which are fundamental determinants of physical habitats. Predictions of the effects of flow alterations on aquatic biota have mostly been assessed based on species ecological traits (e.g., current preferences), which are difficult to link to quantitative discharge data. Alternatively, we used empirically derived predictive relationships for species’ response to flow to assess the effect of flow alterations due to climate change in two contrasting central European river catchments. Predictive relationships were set up for 294 individual species based on (1) abundance data from 223 sampling sites in the Kinzig lower-mountainous catchment and 67 sites in the Treene lowland catchment, and (2) flow conditions at these sites described by five flow metrics quantifying the duration, frequency, magnitude, timing and rate of flow events using present-day gauging data. Species’ abundances were predicted for three periods: (1) baseline (1998–2017), (2) horizon 2050 (2046–2065) and (3) horizon 2090 (2080–2099) based on these empirical relationships and using high-resolution modeled discharge data for the present and future climate conditions. We compared the differences in predicted abundances among periods for individual species at each site, where the percent change served as a proxy to assess the potential species responses to flow alterations. Climate change was predicted to most strongly affect the low-flow conditions, leading to decreased abundances of species up to −42%. Finally combining the response of all species over all metrics indicated increasing overall species assemblage responses in 98% of the studied river reaches in both projected horizons and were significantly larger in the lower-mountainous Kinzig compared to the lowland Treene catchment. Such quantitative analyses of freshwater taxa responses to flow alterations provide valuable tools for predicting potential climate-change impacts on species abundances and can be applied to any stressor, species, or region. OA gold - CA extern

Land use and land cover changes are important issues globally resulting in changing hydrological and ecological conditions. In addition to field sampling and measurements, we applied a model cascade comprising an ecohydrological model and a species distribution model. We developed five land use scenarios (three deforestation and two afforestation scenarios) for our Chinese study basin in the Poyang lake area. In detail, we assessed the impact of land use changes on the hydrologic regime and stream macroinvertebrate distributions for the most likely deforestation scenario.

The preferences of aquatic invertebrate species for specific substrata at the river bottom have been subject of many studies. Several authors classified the substratum preferences of species or higher taxonomic units. Most of these compilations, however, are based on literature analyses and expert knowledge as opposed to the analysis of original data. To enhance our knowledge of invertebrate substratum preferences, we applied a ‘Multi-level pattern’ analysis based on almost 1000 substrate-specific invertebrate samples. The samples were taken in 18 streams in Germany, the Netherlands and Austria, comprising a total of 40 sampling sites and equally covering lowland and mountain streams. The main objectives of our analysis were (I) to derive substratum preferences of taxa in lowland and mountain streams, (II) to compare the preferences with existing data and (III) to compare species substratum associations between lowland and mountain streams. Of the 290 taxa analyzed, 188 were associated significantly to specific substrata. Twenty-five taxa in lowland streams and 51 taxa in mountain streams prefer one or two substratum types (of nine substratum types considered in total). In contrast, 112 species (mountain streams n = 84, lowland streams n = 28) are associated significantly with a broader range of substrata. We compared the classifications derived from our data analysis with those provided in the freshwaterecology.info database ( www.freshwaterecology.info ). Our results support the existing classifications of substratum preferences in most cases (70%). For 25 species, substratum preferences for both lowland and mountain streams were derived, many of them indicating different substratum associations in the two stream groups. As substratum preferences differed between closely related species, preferences should always be given at the species level as opposed to coarser taxonomic units.

Current knowledge regarding the flow preferences of benthic stream invertebrates is mostly based on qualitative data or expert knowledge and literature analysis. These established flow preferences are difficult to use in predictions of the effects of global change on aquatic biota. To complement the existing categories, we performed a large-scale analysis on the distribution of stream invertebrates at stream monitoring sites in order to determine their responses to various hydrological conditions. We used 325 invertebrate surveys from environmental agencies at 238 sites paired to 217 gauges across Germany covering a broad range of hydrological conditions. Based on these data, we modelled the respective probabilities of occurrences for 120 benthic invertebrate taxa within this hydrological range using hierarchical logistic regression models. Our analyses revealed that more than one-third of the taxa (18–40%) can be considered as ubiquitous and having a broad hydrological tolerance. Furthermore, 22–41% of the taxa responded to specific ranges of flow conditions with detectable optima. “Duration high flow event” represented the flow parameter that correlated best with the abundance of individual taxa, followed by “rate of change average event”, with 41 and 38% of the taxa showing a peak in their probability of occurrence at specific ranges of these metrics, respectively. The habitat suitability for these taxa may be potentially affected by global change-induced hydrological changes. Quantified hydrological traits of individual taxa might therefore support stream management and enable the prediction of taxa responses to flow alteration. The hydrological traits of stream benthic invertebrates may be used in forecasting studies in central Europe, and the methods used in this study are suitable for application in other regions with different flow regimes.

Aim Highly complex interactions between the hydrosphere and biosphere, as well as multifactorial relationships, characterize the interconnecting role of streams and rivers between different elements of a landscape. Applying species distribution models (SDMs) in these ecosystems requires special attention because rivers are linear systems and their abiotic and biotic conditions are structured in a linear fashion with significant influences from upstream/downstream or lateral influences from adjacent areas. Our aim was to develop a modelling framework for benthic invertebrates in riverine ecosystems and to test our approach in a data-rich study catchment. Location We present a case study of a 9-km section of the lowland Kielstau River located in northern Germany. Methods We linked hydrological, hydraulic and species distribution models to predict the habitat suitability for the bivalve Sphaerium corneum in a riverine system. The results generated by the hydrological model served as inputs into the hydraulic model, which was used to simulate the resulting water levels, velocities and sediment discharge within the stream channel. Results The ensemble model obtained good evaluation scores (area under the receiver operating characteristic curve 0.96; kappa 0.86; true skill statistic 0.95; sensitivity 86.14; specificity 85.75). Mean values for variables at the sampling sites were not significantly different from the values at the predicted distribution (MannWhitney U-test P > 0.05). High occurrence probabilities were predicted in the downstream half of the 9-km section of the Kielstau. The most important variable for the model was sediment discharge (contributing 40%), followed by water depth (30%), flow velocity (19%) and stream power (11%). Main conclusions The hydrological and hydraulic models are able to produce predictors, acting at different spatial scales, which are known to influence riverine organisms; which, in turn, are used by the SDMs as input. Our case study yielded good results, which corresponded well with ecological knowledge about our study organism. Although this method is feasible for making projections of habitat suitability on a local scale (here: a reach in a small catchment), we discuss remaining challenges for future modelling approaches and large-scale applications.