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Now showing 1 - 4 of 4
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    Natural streamflow simulation for two largest river basins in Poland: A baseline for identification of flow alterations
    (Göttingen : Copernicus, 2016) Piniewski, Mikołaj; Cudennec, Christophe
    The objective of this study was to apply a previously developed large-scale and high-resolution SWAT model of the Vistula and the Odra basins, calibrated with the focus of natural flow simulation, in order to assess the impact of three different dam reservoirs on streamflow using the Indicators of Hydrologic Alteration (IHA). A tailored spatial calibration approach was designed, in which calibration was focused on a large set of relatively small non-nested sub-catchments with semi-natural flow regime. These were classified into calibration clusters based on the flow statistics similarity. After performing calibration and validation that gave overall positive results, the calibrated parameter values were transferred to the remaining part of the basins using an approach based on hydrological similarity of donor and target catchments. The calibrated model was applied in three case studies with the purpose of assessing the effect of dam reservoirs (Włocławek, Siemianówka and Czorsztyn Reservoirs) on streamflow alteration. Both the assessment based on gauged streamflow (Before-After design) and the one based on simulated natural streamflow showed large alterations in selected flow statistics related to magnitude, duration, high and low flow pulses and rate of change. Some benefits of using a large-scale and high-resolution hydrological model for the assessment of streamflow alteration include: (1) providing an alternative or complementary approach to the classical Before-After designs, (2) isolating the climate variability effect from the dam (or any other source of alteration) effect, (3) providing a practical tool that can be applied at a range of spatial scales over large area such as a country, in a uniform way. Thus, presented approach can be applied for designing more natural flow regimes, which is crucial for river and floodplain ecosystem restoration in the context of the European Union's policy on environmental flows.
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    Joint Editorial "on the future of journal publications in hydrology"
    (Göttingen : Copernicus, 2014) Blöschl, G.; Bárdossy, A.; Koutsoyiannis, D.; Kundzewicz, Z.W.; Littlewood, I.; Montanari, A.; Savenije, H.
    [No abstract available]
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    The HadGEM2-ES implementation of CMIP5 centennial simulations
    (Göttingen : Copernicus, 2011) Jones, C.D.; Hughes, J.K.; Bellouin, N.; Hardiman, S.C.; Jones, G.S.; Knight, J.; Liddicoat, S.; O'Connor, F.M.; Andres, R.J.; Bell, C.; Boo, K.-O.; Bozzo, A.; Butchart, N.; Cadule, P.; Corbin, K.D.; Doutriaux-Boucher, M.; Friedlingstein, P.; Gornall, J.; Gray, L.; Halloran, P.R.; Hurtt, G.; Ingram, W.J.; Lamarque, J.-F.; Law, R.M.; Meinshausen, M.; Osprey, S.; Palin, E.J.; Parsons, Chini, L.; Raddatz, T.; Sanderson, M.G.; Sellar, A.A.; Schurer, A.; Valdes, P.; Wood, N.; Woodward, S.; Yoshioka, M.; Zerroukat, M.
    The scientific understanding of the Earth's climate system, including thecentral question of how the climate system is likely to respond tohuman-induced perturbations, is comprehensively captured in GCMs and EarthSystem Models (ESM). Diagnosing the simulated climate response, andcomparing responses across different models, is crucially dependent ontransparent assumptions of how the GCM/ESM has been driven - especiallybecause the implementation can involve subjective decisions and may differbetween modelling groups performing the same experiment. This paper outlinesthe climate forcings and setup of the Met Office Hadley Centre ESM, HadGEM2-ES for the CMIP5 set of centennial experiments. We document theprescribed greenhouse gas concentrations, aerosol precursors, stratosphericand tropospheric ozone assumptions, as well as implementation of land-usechange and natural forcings for the HadGEM2-ES historical and futureexperiments following the Representative Concentration Pathways. Inaddition, we provide details of how HadGEM2-ES ensemble members wereinitialised from the control run and how the palaeoclimate and AMIPexperiments, as well as the "emission-driven" RCP experiments wereperformed.
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    Testing the detectability of spatio-temporal climate transitions from paleoclimate networks with the start model
    (Göttingen : Copernicus, 2014) Rehfeld, K.; Molkenthin, N.; Kurths, J.
    A critical challenge in paleoclimate data analysis is the fact that the proxy data are heterogeneously distributed in space, which affects statistical methods that rely on spatial embedding of data. In the paleoclimate network approach nodes represent paleoclimate proxy time series, and links in the network are given by statistically significant similarities between them. Their location in space, proxy and archive type is coded in the node attributes. We develop a semi-empirical model for Spatio- Temporally AutocoRrelated Time series, inspired by the interplay of different Asian Summer Monsoon (ASM) systems. We use an ensemble of transition runs of this START model to test whether and how spatio-temporal climate transitions could be detectable from (paleo)climate networks. We sample model time series both on a grid and at locations at which paleoclimate data are available to investigate the effect of the spatially heterogeneous availability of data. Node betweenness centrality, averaged over the transition region, does not respond to the transition displayed by the START model, neither in the grid-based nor in the scattered sampling arrangement. The regionally defined measures of regional node degree and cross link ratio, however, are indicative of the changes in both scenarios, although the magnitude of the changes differs according to the sampling. We find that the START model is particularly suitable for pseudo-proxy experiments to test the technical reconstruction limits of paleoclimate data based on their location, and we conclude that (paleo)climate networks are suitable for investigating spatio-temporal transitions in the dependence structure of underlying climatic fields.