135 research outputs found

    Large-basin hydrological response to climate model outputs: uncertainty caused by internal atmospheric variability

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    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

    Dynamic-stochastic modeling of snow cover formation on the European territory of Russia

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    A dynamic-stochastic model, which combines a deterministic model of snow cover formation with a stochastic weather generator, has been developed. The deterministic snow model describes temporal change of the snow depth, content of ice and liquid water, snow density, snowmelt, sublimation, re-freezing of melt water, and snow metamorphism. The model has been calibrated and validated against the long-term data of snow measurements over the territory of the European Russia. The model showed good performance in simulating time series of the snow water equivalent and snow depth. The developed weather generator (NEsted Weather Generator, NewGen) includes nested generators of annual, monthly and daily time series of weather variables (namely, precipitation, air temperature, and air humidity). The parameters of the NewGen have been adjusted through calibration against the long-term meteorological data in the European Russia. A disaggregation procedure has been proposed for transforming parameters of the annual weather generator into the parameters of the monthly one and, subsequently, into the parameters of the daily generator. Multi-year time series of the simulated daily weather variables have been used as an input to the snow model. Probability properties of the snow cover, such as snow water equivalent and snow depth for return periods of 25 and 100 years, have been estimated against the observed data, showing good correlation coefficients. The described model has been applied to different landscapes of European Russia, from steppe to taiga regions, to show the robustness of the proposed technique

    Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments

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    It has been well established that during the late Quaternary, the Khvalynian transgression of the Caspian Sea occurred, when the sea level rose tens of meters above the present level. Here, we evaluate the physical feasibility of the hypothesis that the maximum phase of this extraordinary event (known as the “Early Khvalynian transgression”) could be initiated and maintained for several thousand years solely by hydroclimatic factors. The hypothesis is based on recent studies dating the highest sea level stage (well above +10 m a.s.l.) to the final period of deglaciation, 17–13 kyr BP, and studies estimating the contribution of the glacial waters in the sea level rise for this period as negligible. To evaluate the hypothesis put forward, we first applied the coupled ocean and sea-ice general circulation model driven by the climate model and estimated the equilibrium water inflow (irrespective of its origin) sufficient to maintain the sea level at the well-dated marks of the Early Khvalynian transgression as 400–470 km3 yr−1. Secondly, we conducted an extensive radiocarbon dating of the large paleochannels (signs of high flow of atmospheric origin) located in the Volga basin and found that the period of their origin (17.5–14 ka BP) is almost identical to the recent dating of the main phase of the Early Khvalynian transgression. Water flow that could form these paleochannels was earlier estimated for the ancient Volga River as 420 km3 yr−1, i.e., close to the equilibrium runoff we determined. Thirdly, we applied a hydrological model forced by paleoclimate data to reveal physically consistent mechanisms of an extraordinarily high water inflow into the Caspian Sea in the absence of a visible glacial meltwater effect. We found that the inflow could be caused by the spread of post-glacial permafrost in the Volga paleocatchment. The numerical experiments demonstrated that the permafrost resulted in a sharp drop in infiltration into the frozen ground and reduced evaporation, which all together generated the Volga runoff during the Oldest Dryas, 17–14.8 kyr BP, up to 360 km3 yr−1 (i.e., the total inflow into the Caspian Sea could reach 450 km3 yr−1). The closeness of the estimates of river inflow into the sea, obtained by three independent methods, in combination with the previously obtained results, gave us reason to conclude that the hypothesis put forward is physically consistent.</p

    ĐžĐżĐžŃĐ°ĐœĐžĐ” ĐŒĐ°ĐșŃ€ĐŸĐŒĐ°ŃŃˆŃ‚Đ°Đ±ĐœĐŸĐč струĐșтуры ĐżĐŸĐ»Ń ŃĐœĐ”Đ¶ĐœĐŸĐłĐŸ ĐżĐŸĐșŃ€ĐŸĐČĐ° раĐČĐœĐžĐœĐœĐŸĐč Ń‚Đ”Ń€Ń€ĐžŃ‚ĐŸŃ€ĐžĐž с ĐżĐŸĐŒĐŸŃ‰ŃŒŃŽ ĐŽĐžĐœĐ°ĐŒĐžĐșĐŸ-ŃŃ‚ĐŸŃ…Đ°ŃŃ‚ĐžŃ‡Đ”ŃĐșĐŸĐč ĐŒĐŸĐŽĐ”Đ»Đž Đ”ĐłĐŸ Ń„ĐŸŃ€ĐŒĐžŃ€ĐŸĐČĐ°ĐœĐžŃ

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    Possibilities to investigate the spatial structure of snow cover by means of dynamic-stochastic model are discussed in this article. Basin of the Cheboksary reservoir (area of 376 500 sq.km) was used as an example. Results of numerical experiments show that our dynamic-stochastic model of the snow cover formation reproduces a snow field structure with adequate accuracy. The fractal dimensions of the modeled fields are in good correspondence with respective dimensions of fields obtained from data of the in situ observations.ĐŸĐŸĐșĐ°Đ·Đ°ĐœŃ‹ ĐČĐŸĐ·ĐŒĐŸĐ¶ĐœĐŸŃŃ‚Đž ĐŽĐžĐœĐ°ĐŒĐžĐșĐŸ-ŃŃ‚ĐŸŃ…Đ°ŃŃ‚ĐžŃ‡Đ”ŃĐșĐŸĐč ĐŒĐŸĐŽĐ”Đ»Đž Ń„ĐŸŃ€ĐŒĐžŃ€ĐŸĐČĐ°ĐœĐžŃ ŃĐœĐ”Đ¶ĐœĐŸĐłĐŸ ĐżĐŸĐșŃ€ĐŸĐČĐ° ĐŽĐ»Ń ĐžŃŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžŃ ĐŸŃĐŸĐ±Đ”ĐœĐœĐŸŃŃ‚Đ”Đč Đ”ĐłĐŸ ĐżŃ€ĐŸŃŃ‚Ń€Đ°ĐœŃŃ‚ĐČĐ”ĐœĐœĐŸĐč струĐșтуры ĐœĐ° ĐżŃ€ĐžĐŒĐ”Ń€Đ” Ń‚Đ”Ń€Ń€ĐžŃ‚ĐŸŃ€ĐžĐž бассДĐčĐœĐ° Đ§Đ”Đ±ĐŸĐșсарсĐșĐŸĐłĐŸ ĐČĐŸĐŽĐŸŃ…Ń€Đ°ĐœĐžĐ»ĐžŃ‰Đ° (ĐżĐ»ĐŸŃ‰Đ°ĐŽŃŒ 376 500 ĐșĐŒ2). ĐŸŃ€Đ”ĐŽŃŃ‚Đ°ĐČĐ»Đ”ĐœŃ‹ Ń€Đ”Đ·ŃƒĐ»ŃŒŃ‚Đ°Ń‚Ń‹ Ń‡ĐžŃĐ»Đ”ĐœĐœŃ‹Ń… эĐșŃĐżĐ”Ń€ĐžĐŒĐ”ĐœŃ‚ĐŸĐČ, ĐżĐŸĐșĐ°Đ·Ń‹ĐČающОД, Ń‡Ń‚ĐŸ Ń€Đ°Đ·Ń€Đ°Đ±ĐŸŃ‚Đ°ĐœĐœĐ°Ń ĐŒĐŸĐŽĐ”Đ»ŃŒ с ŃƒĐŽĐŸĐČлДтĐČĐŸŃ€ĐžŃ‚Đ”Đ»ŃŒĐœĐŸĐč Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚ŃŒŃŽ ĐČĐŸŃĐżŃ€ĐŸĐžĐ·ĐČĐŸĐŽĐžŃ‚ струĐșтуру ĐżĐŸĐ»Ń ŃĐœĐ”Đ¶ĐœĐŸĐłĐŸ ĐżĐŸĐșŃ€ĐŸĐČĐ°. ЀраĐșŃ‚Đ°Đ»ŃŒĐœŃ‹Đ” Ń€Đ°Đ·ĐŒĐ”Ń€ĐœĐŸŃŃ‚Đž Ń€Đ°ŃŃŃ‡ĐžŃ‚Đ°ĐœĐœŃ‹Ń… ĐżĐŸĐ»Đ”Đč уĐșĐ°Đ·Đ°ĐœĐœŃ‹Ń… хараĐșтДрОстОĐș блОзĐșĐž Đș ŃĐŸĐŸŃ‚ĐČДтстĐČŃƒŃŽŃ‰ĐžĐŒ Ń€Đ°Đ·ĐŒĐ”Ń€ĐœĐŸŃŃ‚ŃĐŒ ĐżĐŸĐ»Đ”Đč, ĐŸŃ†Đ”ĐœŃ‘ĐœĐœŃ‹ĐŒ ĐżĐŸ ĐŽĐ°ĐœĐœŃ‹ĐŒÂ ŃĐœĐ”ĐłĐŸĐŒĐ”Ń€ĐœŃ‹Ń… ĐœĐ°Đ±Đ»ŃŽĐŽĐ”ĐœĐžĐč

    Chapter 4: Water

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    This chapter assesses observed and projected climate-induced changes in the water cycle, their current impacts and future risks on human and natural systems and the benefits and effectiveness of water-related adaptation efforts now and in the future

    Advancing catchment hydrology to deal with predictions under change

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    Throughout its historical development, hydrology as an earth science, but especially as a problem-centred engineering discipline has largely relied (quite successfully) on the assumption of stationarity. This includes assuming time invariance of boundary conditions such as climate, system configurations such as land use, topography and morphology, and dynamics such as flow regimes and flood recurrence at different spatio-temporal aggregation scales. The justification for this assumption was often that when compared with the temporal, spatial, or topical extent of the questions posed to hydrology, such conditions could indeed be considered stationary, and therefore the neglect of certain long-term non-stationarities or feedback effects (even if they were known) would not introduce a large error. However, over time two closely related phenomena emerged that have increasingly reduced the general applicability of the stationarity concept: the first is the rapid and extensive global changes in many parts of the hydrological cycle, changing formerly stationary systems to transient ones. The second is that the questions posed to hydrology have become increasingly more complex, requiring the joint consideration of increasingly more (sub-) systems and their interactions across more and longer timescales, which limits the applicability of stationarity assumptions. Therefore, the applicability of hydrological concepts based on stationarity has diminished at the same rate as the complexity of the hydrological problems we are confronted with and the transient nature of the hydrological systems we are dealing with has increased. The aim of this paper is to present and discuss potentially helpful paradigms and theories that should be considered as we seek to better understand complex hydrological systems under change. For the sake of brevity we focus on catchment hydrology. We begin with a discussion of the general nature of explanation in hydrology and briefly review the history of catchment hydrology. We then propose and discuss several perspectives on catchments: as complex dynamical systems, self-organizing systems, co-evolving systems and open dissipative thermodynamic systems. We discuss the benefits of comparative hydrology and of taking an information-theoretic view of catchments, including the flow of information from data to models to predictions. In summary, we suggest that these perspectives deserve closer attention and that their synergistic combination can advance catchment hydrology to address questions of change

    Twenty-three unsolved problems in hydrology (UPH) – a community perspective

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    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 on-line 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 focussed on 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
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