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Aim: We studied the distribution of freshwater macroinvertebrate taxa and traits to distinguish ecological gradients among the mining-controlled and natural headwaters, as well as rural and urban economic activities influences. Location: In 2016’s dry season, macroinvertebrate samples were collected at 40 locations in the Mashcon watershed, northern Peruvian Andes. Six locations were in the headwaters directly influenced by mining, eight near-pristine tributary headwaters,14 agricultural locations at midstream and 12 urban locations downstream. Methods: Eight traits (five biological and three ecological) were selected according to data availability, and modalities scores were assigned using the weighted and the dominant-trait approaches. The traits relative abundances and abiotic conditions were compared among watershed sections. The ecological interpretability of the ungrouped data was verified with a distance-based redundancy analysis. Results: The high-altitude mining section had fewer taxa types and abundance as well as distinct body forms distributions and prevalent body sizes in macroinvertebrate communities, relatable to the control of the mining headwaters. Physiological and ecological traits (respiration, mobility and attachment, food sources, feeding habits, saprobity and pH preferenda) differed among traits quantification approaches and were less informative at high altitudes. The ecological conditions from the near-pristine tributaries recovered in the vegetated midstream section, to again be affected in the downstream urban section. Main conclusions: Our results suggest the presence of ecological impairment despite the excellent physicochemical quality of the water discharged by the mine. The obtainment of autecological information at a higher taxonomic resolution, e.g. for ubiquitous taxa like Acari and Chironomidae, would be needed to advance the freshwater quality assessment of ecologically- and hydrogeochemically-complex Andean mining ecosystems. ispartof: Diversity And Distributions vol:28 issue:8 pages:1582-1596 status: accepted

Little Ruaha catchment has been recognized for its potential to support multi-projects including irrigated schemes, urban water supply and providing significant inflow to Mtera reservoir for hydropower generation and ultimately Julius Nyerere Hydropower Plant (JNHPP). Despite the potential, the catchment has experienced declining flows in the recent years. This study assessed the likely changes in streamflow due to future climate change in the Little Ruaha catchment for the period 2025-2060. General Circulation Model (GCM) datasets from ACCESS1.0, CNRM-CM5 and BCC-CSM1 models and RCP4.5 and RCP8.5 greenhouse gas concentration scenarios were selected as the representative scenarios. Impact of climate change on stream flows was assessed using the calibrated NAM hydrological model. The impact assessment results show that under the climate change scenario (2025–2060), the monthly maximum and minimum temperatures will increase in the range of 0.8 °C to 2 °C for both RCP4.5 and RCP8.5 scenarios. For the case of rainfall, average annual rainfall is expected to increase by about 10% compared to the baseline. However, the inter-annual variability of rainfall for the period between 2025 and 2060 shows the decreasing trend for RCP 8.5. The simulation results show that streamflow will decrease by about 30% and 6% for RCP4.5 and RCP8.5, respectively. Keywords: Hydrological modelling; climate change scenarios; hydrological impacts; Little Ruaha.

This dataset includes the daily hydrological simulations under climate change scenarios for the Manic-5 watershed in Canada and the Xiangjiang watershed in China. The format of all files is binary MATLAB file (.mat). The hydrological simulations for each watershed were obtained through an impact modeling chain, which comprises multiple options for each step. To be specific, three greenhouse gas emission scenarios (RCP2.6, RCP4.5 and RCP 8.5), 22 global climate models, 6 downscaling techniques, 5 hydrological models, and 5 sets of parameters for each hydrological model are included. Thus, there are overall 9900 hydrological simulations over the reference (1970-1999) and future (2070-2099) periods for each watershed. This dataset can be used to evaluate the overall uncertainty and uncertainty components in the modeling of hydrological impacts from climate change.

International audience; A warmer climate impacts streamflows and these changes need to be quantified to assess future risk, vulnerability, and to implement efficient adaptation measures. The climate simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), which have been the basis of most such assessments over the past decade, are being gradually superseded by the more recent Coupled Model Intercomparison Project Phase 6 (CMIP6). Our study portrays the added value of the CMIP6 ensemble over CMIP5 in a first North America wide comparison using 3,107 catchments. Results show a reduced spread of the CMIP6 ensemble compared to the CMIP5 ensemble for temperature and precipitation projections. In terms of flow indicators, the CMIP6 driven hydrological projections result in a smaller spread of future mean and high flow values, except for mountainous areas. Overall, we assess that the CMIP6 ensemble provides a narrower band of uncertainty of future climate projections, bringing more confidence for hydrological impact studies.

Climate change affects natural systems, leading to increased acceleration of global water cycle and substantial impacts on the productivity of tropical rivers and the several ecosystem functions they provide. However, the anticipated impacts of climate change in terms of frequency and intensity of extreme events (e.g., droughts and floods) on hydrological systems across regions could be substantially different. This study therefore aims to assess the impacts of climate change on the streamflow of a large river basin located in central Australia (Cooper Creek-Bulloo River Basin). Modified version of the hydrological model Hydrologiska Byrans Vattenbalansavdelning (HBV) was used in this study to generate daily streamflow. This model was first calibrated (2001–2010) and then validated for two independent periods (1993–1997 and 2011–2015). The model depicted a good performance in simulating observed streamflow. Climate projection data from multiple general circulation models (ACCESS1.0, CanESM2, CESM1-CAM5, CNRM-CM5, GFDL-ESM2M, HadGEM2-CC, MIROC5, NorESM1-M, ACCESS1-0, ACCESS1-3, CCSM4, CNRM-CM5, CSIRO-Mk3.6, GFDL-CM3, GFDL-ESM2M, HadGEM2, MIROC5, MPI-ESM-LR, and NorESM1-M) in various forms (raw, statistically downscaled, dynamically downscaled, and bias adjusted) were considered in this study. Results showed that three high resolution dynamically downscaled and bias adjusted models (ACCESS1-3, CNRM-CM5, and MPI-ESM-LR) from Terrestrial Ecosystem Research Network (TERN) dataset (v1.0.2) have better performance than other models considered, that is, in terms of capturing observed precipitation over the basin. Future climate projections of ensemble of these three models forced with RCP 4.5 and RCP 8.5 emission scenarios were then used to generate streamflow for 2050s (2040–2069) and 2080s (2070–2099). Results of the study indicated that mean annual precipitation was projected to decrease by up to −8% in 2050s and temperature was projected to increase by up to 4.66 °C in 2080s under the average and extreme emission scenarios, respectively. Mean annual, mean seasonal (December–February, March–May, June–August, September–November), and mean monthly streamflow were projected to decrease under different emission scenarios in 2050s and 2080s. These results indicate decreased water availability in the future as well as water cycle intensification. These changes in streamflow might have impacts on agriculture, natural ecosystem, and could lead to water restrictions. The outcome of this study can directly feed into frameworks for sustainable management of water resources and support adaptation strategies that rely on science and policy to improve water resources allocation in the region.

Anthropogenic activities such as damming have caused an alteration in the natural flow regime in many rivers around the world. In this study, the role of constructing a hydroelectric dam on the natural flow regime of the Kor River, Iran, is investigated. Nine different methods, which fall into the category of hydrological methods, were used to determine the environmental water requirement (EWR) of the Kor River. In addition, two indices are introduced to evaluate the environmental flow allocation in anthropogenic rivers. The results show that although the supply of environmental flow in some months is in relatively acceptable conditions on average, there is a deficiency in the allocation of EWR in the range of 1.92–30.2% in the spawning period of the dominant fish species. The proposed indicators can provide a general picture of the status of environmental flow allocation in rivers where little ecological data is available and the hydrological regime has changed due to human activities, particularly in rivers with hydropower plants. Moreover, after the construction of the dam, no major floods have occurred in the river, which has led to the loss of the morpho-ecological balance in the river and disruption of the natural state of habitats. Therefore, the negative impact of dam construction on the environmental conditions of the river should be considered in the active management of the dam outlets.

The quantification of climate change impacts on hydrology is subjected to multiple uncertainty sources. Large ensembles of hydrological simulations based on multimodel ensembles (MMEs) have been commonly applied to represent overall uncertainty of hydrological impacts. However, as increasing numbers of global climate models (GCMs) are being developed, how many GCMs in MMEs are sufficient to characterize overall uncertainty is not clear. Therefore, this study investigates the influences of GCM quantity on quantifying overall uncertainty and uncertainty contributions of multiple sources in hydrological impacts. Large ensembles of hydrological simulations are obtained through the permutation of 3 greenhouse gas emission scenarios, 22 GCMs, 6 downscaling techniques, 5 hydrological models (HMs), and 5 sets of HM parameters, which enables to decompose uncertainty components using analysis of variance. The influences of GCM quantity are investigated by repeatedly conducting uncertainty decomposition for hydrological simulations from subsets with different numbers of GCMs. The results show that GCMs are the leading uncertainty sources in evaluating changes in annual and peak streamflows, while for changes in low flow, other uncertainty sources except HM parameters also have large contributions to overall uncertainty. Furthermore, on the condition of using no more than five GCMs, there are large possibilities that the overall uncertainty and GCMs' uncertainty contribution are underestimated. Using around 10 GCMs can ensure that the median of different combinations generates similar uncertainty components as the whole ensemble. Therefore, it is recommended to use at least 10 GCMs in studies of climate change impacts on hydrology to thoroughly quantify uncertainty.

There is a high demand for openly accessible hydroclimatic data for climate change adaptation. Different data sources are available, however, discrepancy between the data can confuse users and should be evaluated and explained. This study, investigates how climate impact indicators (CIIs) developed for global users in the Copernicus Climate Change Service (C3S) are comparable to other openly available global data for water and climate. We found that, for temperature, datasets are comparable and climate impacts are thus considered robust. Important discrepancies arise in the precipitation indicators. Of the CIIs analysed in this study, the hydrological CIIs differ most so they should be used with care. These differences are probably caused by model uncertainty (hydrological model, HM; global climate model, GCM), ensemble size and model selection. A HM ensemble, as well as a GCM ensemble combined with improved model performance and selection criteria, should be used to ensure high-quality global water and climate services.

Study region Catchments: Wolzerbach, Raab; Styria; Austria. Study focus The study was carried out to investigate the fitness for purpose of the high-resolution Austrian National Climate datasets (OKS15) in hydrological applications. Provided as a standard for climate impact studies in Austria in 2016, the potential of the OKS15 data for hydrological impact studies has not previously been assessed. To fill this research gap, we evaluated the OKS15 datasets for the recent climate period (1961–2005) to determine their suitability for hydrological analyses. Hydro-meteorological indicators of the OKS15 datasets, as well as of the data used to obtain them by bias correcting and downscaling the EURO-CORDEX models, were assessed at different spatio-temporal scales and compared to the raw EURO-CORDEX data. The hydrological model WaSiM was driven with the different datasets to generate the hydrological simulations used for validation against long-term observations. New hydrological insights for the region Hydro-meteorological indicators obtained from OKS15 models are comparable to observations and associated with less uncertainty than the raw EURO-CORDEX data. We thus consider the OKS15 dataset basically appropriate for hydrological impact studies. However, despite bias correction, some biases in the OKS15 data remain and differences in timing, magnitude and spatial characteristics lead to deviations in hydrological indicators at different scales.

The consequences of climate change on food security in arid and semi-arid regions can be serious. Understanding climate change impacts on water balance is critical to assess future crop performance and develop sustainable adaptation strategies. This paper presents a climate change impact study on the water balance components of an agricultural watershed in the Mediterranean region. The restructured version of the Soil and Water Assessment Tool (SWAT+) model was used to simulate the hydrological components in the Sulcis watershed (Sardinia, Italy) for the baseline period and compared to future climate projections at the end of the 21st century. The model was forced using data from two Regional Climate Models under the representative concentration pathways RCP4.5 and RCP8.5 scenarios developed at a high resolution over the European domain. River discharge data were used to calibrate and validate the SWAT+ model for the baseline period, while the future hydrological response was evaluated for the mid-century (2006–2050) and late-century (2051–2098). The model simulations indicated a future increase in temperature, decrease in precipitation, and consequently increase in potential evapotranspiration in both RCP scenarios. Results show that these changes will significantly decrease water yield, surface runoff, groundwater recharge, and baseflow. These results highlight how hydrological components alteration by climate change can benefit from modelling high-resolution future scenarios that are useful for planning mitigation measures in agricultural semi-arid Mediterranean regions.

The aim of this work is to investigate the soil water budget across China by means of hydrological modeling under current and future climate conditions and to evaluate the sensitivity to soil parameters. For this purpose, observed precipitation and temperature data (1981–2010) and climate simulations (2021–2050, 2071–2100) at high resolution (about 14 km) on a large part of China are used as weather forcing. The simulated weather forcing has been bias corrected by means of the distribution derived quantile mapping method to eliminate the effects of systematic biases in current climate modeling on water cycle components. As hydrological models, two 1D models are tested: TERRA-ML and HELP. Concerning soil properties, two datasets, provided respectively by Food and Agriculture Organization and U.S. Department of Agriculture, are separately tested. The combination of two hydrological models, two soil parameter datasets and three weather forcing inputs (observations, raw and bias corrected climate simulations) results in five different simulation chains. The study highlights how the choice of some approaches or soil parameterizations can affect the results both in absolute and in relative terms and how these differences could be highly related to weather forcing in inputs or investigated soil. The analyses point out a decrease in average water content in the shallower part of the soil with different extents according to climate zone, concentration scenario and soil/cover features. Moreover, the projected increase in temperature and then in evapotranspirative demand do not ever result in higher actual evapotranspiration values, due to the concurrent variations in precipitation patterns.

There is growing interest in the capacity of mangrove ecosystems to sequester and store ‘blue carbon’. Here, we provide a synthesis of 66 dated sediment cores with previously calculated carbon accumulation rates in mangrove ecosystems to assess the effects of environmental and anthropogenic pressures. Conserved sedimentary environments were found to be within the range of the current global average for sediment accretion (approx. 2.5 mm yr –1 ) and carbon accumulation (approx. 160 g m −2 yr −1 ). Moreover, similar sediment accretion and carbon accumulation rates were found between mixed and monotypic mangrove forests, however higher mean and median values were noted from within the forest as compared to adjacent areas such as mudflats. The carbon accumulation within conserved environments was up to fourfold higher than in degraded or deforested environments but threefold lower than those impacted by domestic or aquaculture effluents (more than 900 g m −2 yr −1 ) and twofold lower than those impacted by storms and flooding (more than 500 g m −2 yr −1 ). These results suggest that depending on the type of impact, the blue carbon accumulation capacity of mangrove ecosystems may become substantially modified.

A physically based hydroclimatological model (AMUNDSEN) is used to assess future climate change impacts on the cryosphere and hydrology of the Ötztal Alps (Austria) until 2100. The model is run in 100 m spatial and 3 h temporal resolution using in total 31 downscaled, bias-corrected, and temporally disaggregated EURO-CORDEX climate projections for the representative concentration pathways (RCPs) 2.6, 4.5, and 8.5 scenarios as forcing data, making this - to date - the most detailed study for this region in terms of process representation and range of considered climate projections. Changes in snow coverage, glacierization, and hydrological regimes are discussed both for a larger area encompassing the Ötztal Alps (1850 km2, 862-3770 m a.s.l.) as well as for seven catchments in the area with varying size (11-165 km2) and glacierization (24-77 %). Results show generally declining snow amounts with moderate decreases (0-20 % depending on the emission scenario) of mean annual snow water equivalent in high elevations (> 2500 m a.s.l.) until the end of the century. The largest decreases, amounting to up to 25-80 %, are projected to occur in elevations below 1500 m a.s.l. Glaciers in the region will continue to retreat strongly, leaving only 4-20 % of the initial (as of 2006) ice volume left by 2100. Total and summer (JJA) runoff will change little during the early 21st century (2011-2040) with simulated decreases (compared to 1997-2006) of up to 11 % (total) and 13 % (summer) depending on catchment and scenario, whereas runoff volumes decrease by up to 39 % (total) and 47 % (summer) towards the end of the century (2071-2100), accompanied by a shift in peak flows from July towards June. © Author(s) 2018.

Precipitation extremes play a key role in flooding risks over the Huaihe River Basin, which is important to understand their hydrological impacts. Based on observed daily precipitation and streamflow data from 1958 to 2009, eight precipitation indices and three streamflow indices were calculated for the study of hydrological impacts of precipitation extremes. The results indicate that the wet condition intensified in the summer wet season and the drought condition was getting worse in the autumn dry season in the later years of the past 50 years. The river basin had experienced higher heavy rainfall-related flooding risks in summer and more severe drought in autumn in the later of the period. The extreme precipitation events or consecutive heavy rain day events led to the substantial increases in streamflow extremes, which are the main causes of frequent floods in the Huaihe River Basin. The large inter-annual variation of precipitation anomalies in the upper and central Huaihe River Basin are the major contributor for the regional frequent floods and droughts.

The impacts of invasions by alien plant species on the quantity of rainwater that reaches rivers and streams have been studied in several countries. Some studies have found that there is a large impact and others have found little or no impact. These conflicting conclusions can be explained largely by differences in the structure (e.g. height, depth of root systems) and the physiology (e.g. evergreen, deciduous, water stress tolerance) between the alien and the indigenous plant species. The greater the differences between the two, the greater the impact is likely to be., There have been many studies of the diverse impacts of invasions by alien plants but few have assessed impacts on water resources. We reviewed the information on the impacts of invasions on surface runoff and groundwater resources at stand to catchment scales and covering a full annual cycle. Most of the research is South African so the emphasis is on South Africa's major invaders with data from commercial forest plantations where relevant. Catchment studies worldwide have shown that changes in vegetation structure and the physiology of the dominant plant species result in changes in surface runoff and groundwater discharge, whether they involve native or alien plant species. Where there is little change in vegetation structure [e.g. leaf area (index), height, rooting depth and seasonality] the effects of invasions generally are small or undetectable. In South Africa, the most important woody invaders typically are taller and deeper rooted than the native species. The impacts of changes in evaporation (and thus runoff) in dryland settings are constrained by water availability to the plants and, thus, by rainfall. Where the dryland invaders are evergreen and the native vegetation (grass) is seasonal, the increases can reach 300–400 mm/year. Where the native vegetation is evergreen (shrublands) the increases are ∼200–300 mm/year. Where water availability is greater (riparian settings or shallow water tables), invading tree water-use can reach 1.5–2.0 times that of the same species in a dryland setting. So, riparian invasions have a much greater impact per unit area invaded than dryland invasions. The available data are scattered and incomplete, and there are many gaps and issues that must be addressed before a thorough understanding of the impacts at the site scale can be gained and used in extrapolating to watershed scales, and in converting changes in flows to water supply system yields.