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Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which result in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement. In our study, we use ANOVA (analyses of variance) to allocate and quantify the main sources of uncertainty in the hydrological impact modelling chain. In turn we determine the statistical significance of different sources of uncertainty. We achieve this by using a set of five climate models and up to 13 hydrological models, for nine large scale river basins across the globe, under four emissions scenarios. The impact variable we consider in our analysis is daily river discharge. We analyze overall water availability and flow regime, including seasonality, high flows and low flows. Scaling effects are investigated by separately looking at discharge generated by global and regional hydrological models respectively. Finally, we compare our results with other recently published studies. We find that small differences in global temperature rise associated with some emissions scenarios have mostly significant impacts on river discharge-however, climate model related uncertainty is so large that it obscures the sensitivity of the hydrological system.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

An approach is proposed to assess hydrological simulation uncertainty originating from internal atmospheric variability. The latter is one of three major factors contributing to uncertainty of simulated climate change projections (along with so-called \"forcing\" and \"climate model\" uncertainties). Importantly, the role of internal atmospheric variability is most visible over spatio-temporal scales of water management in large river basins. Internal atmospheric variability is represented by large ensemble simulations (45 members) with the ECHAM5 atmospheric general circulation model. Ensemble simulations are performed using identical prescribed lower boundary conditions (observed sea surface temperature, SST, and sea ice concentration, SIC, for 1979–2012) and constant external forcing parameters but different initial conditions of the atmosphere. The ensemble of bias-corrected ECHAM5 outputs and ensemble averaged ECHAM5 output are used as a distributed input for the ECOMAG and SWAP hydrological models. The corresponding ensembles of runoff hydrographs are calculated for two large rivers of the Arctic basin: the Lena and Northern Dvina rivers. A number of runoff statistics including the mean and the standard deviation of annual, monthly and daily runoff, as well as annual runoff trend, are assessed. Uncertainties of runoff statistics caused by internal atmospheric variability are estimated. It is found that uncertainty of the mean and the standard deviation of runoff has a significant seasonal dependence on the maximum during the periods of spring–summer snowmelt and summer–autumn rainfall floods. Noticeable nonlinearity of the hydrological models' results in the ensemble ECHAM5 output is found most strongly expressed for the Northern Dvina River basin. It is shown that the averaging over ensemble members effectively filters the stochastic term related to internal atmospheric variability. Simulated discharge trends are close to normally distributed around the ensemble mean value, which fits well to empirical estimates and, for the Lena River, indicates that a considerable portion of the observed trend can be externally driven.

Hydrological modeling system was developed as a tool addressed supporting flood risk management by the existing and projected reservoirs in the Amur River basin. The system includes the physically-based semi-distributed model of runoff generation ECOMAG coupled with a hydrodynamic MIKE-11 model to simulate channel flow in the main river. The case study was carried out for the middle part of the Amur River where large reservoirs are located on the Zeya and Bureya Rivers. The models were calibrated and validated using streamflow measuruments at the different gauges of the main river and its tributaries. Numerical experiments were carried out to assess the effect of the existing Zeya and Bureya reservoirs regulation on 850 km stretch of the middle Amur River stage. It was shown that in the absence of the reservoirs, the water levels downstream of the Zeya and Bureya Rivers would be 0.5–1.5 m higher than the levels measured during the disastrous flood of 2013. Similar experiments were carried out to assess possible flood protection effect of new projected reservoirs on the Zeya and Bureya Rivers.

A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia), is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics) that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast), and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast). We have studied the following: (1) whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2) whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form) outperform the operational forecasts of the April–June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period) obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

The problem of raising the level of protein supply in the diet of the population of the Russian Federation is still relevant. To solve this problem it is important to investigate protein food reserves, while priority is given to a combination of vegetable and animal proteins. Fish and non-fish water fishing is paid particular attention as a potential source of protein, because of almost inexhaustible world ocean reserves and the prospects for their use. The aim of the work is the scientific study and practical implementation of preparation and evaluation of the quality of pasty concentrates of aquatic organisms, as well as health food products based on them using hydro-mechanical dispersion. The scientific background of technological aspects of the production of aquatic pasty concentrate from hydrobionts (cyst Artemia Salina) using hydro-mechanical dispersion is presented in the article. Consumer characteristics, conditions and terms of the concentrate storage are identified. New data on the effectiveness evaluation of paste concentrate from cyst Artemia to increase the body's immune properties are obtained in the experiments with animals. The expediency of development and industrial production of cheese products using pasty concentrates of aquatic organisms is based. Regulated quality parameters, modes and terms of their storage are established.

Ensuring the competitiveness of Russian producers of food products is impossible without achieving the consistent quality and food safety. Special attention in this paper is paid to the introduction of relevant management systems at the enterprises of the food processing industry. A significant number of the currently available standards and specifications enables the management of any enterprise to choose the most appropriate variant for the given enterprise: to implement a single system or a set of systems which can represent the integrated management system (IMS). The main point in this choice is the idea of these types of management systems and of the potential, additional opportunities, and advantages that can be obtained due to their implementation at the enterprises. The responsibility of food manufacturers for the implementation and maintenance of procedures based on the principles of HACCP (Hazard Analysis and Critical Control Points) also determines the relevance of the topic. The evaluation of management systems, which are possible to implement at the food enterprises, has been conducted according to the following criteria: solvability of problems, applicability for the food enterprises and the possible effect from the implementation (a potential). The availability of fundamentals for the integration of management systems has been shown, the concept of IMS has been discussed and the need for IMS from the food enterprises has been identified The detailed plan of IMS development has been proposed. The possibility and the attractiveness of the development, implementation of other management systems in the food processing industry, in particular, the environmental management systems, management systems of occupational safety and health, energy management systems, models of ethical and social management have been established. The approach to the choice of IMS components has been confirmed on the basis of the utility definition and potential advantages of each management system separately. The model of the development and implementation of the \"optimal\" integrated management system of quality and safety for the food enterprises has been offered. The basic point of it is the process model as the main part of the \"optimal\" IMS of the food enterprise.

A physically based soil frost depth model usable with air temperature data and precipitation data, is presented. Snow depth is calculated from precipitation data using a physical snow cover model. The soil frost depth model is tested in one small basin, with a five-year calibration and verification period. Results from snow depth and soil frost depth simulation were satisfactory also in the verification period. In the second stage simulated frost depth information was used to develop an HBV-runoff model version, attempting to simulate the possible effect of soil frost on runoff. The simulation results are presented. These results suggest that soil frost does not have a very important effect on runoff in this forested basin.

Celery stalks are a source of useful nutritional substances. However, their shelf-life is short, so processing them into the powder of infrared (IR) drying is the optimal way to keep their useful properties. Using celery stalks in powder form can prolongate their shelf-life and introduce them into bakery products formulations. Thus, bakery products range will expand, what contributes to the aims of bakery enterprises sustainable development. The paper shows the research results in the development of new bakery production using celery stalks powder of IR-drying. The experiments showed that the celery stalks powder slightly changes carrying out the technological process, and the bakery product has got high sensory characteristics and nutritional value. So, the developed technology can be implemented practically.