@misc{AyzelVarentsovaErinaetal.2019,
  author    = {Ayzel, Georgy and Varentsova, Natalia and Erina, Oxana and Sokolov, Dmitriy and Kurochkina, Liubov and Moreydo, Vsevolod},
  title     = {OpenForecast},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1338},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-47329},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-473295},
  pages     = {17},
  year      = {2019},
  abstract  = {The development and deployment of new operational runoff forecasting systems are a strong focus of the scientific community due to the crucial importance of reliable and timely runoff predictions for early warnings of floods and flashfloods for local businesses and communities. OpenForecast, the first operational runoff forecasting system in Russia, open for public use, is presented in this study. We developed OpenForecast based only on open-source software and data-GR4J hydrological model, ERA-Interim meteorological reanalysis, and ICON deterministic short-range meteorological forecasts. Daily forecasts were generated for two basins in the European part of Russia. Simulation results showed a limited efficiency in reproducing the spring flood of 2019. Although the simulations managed to capture the timing of flood peaks, they failed in estimating flood volume. However, further implementation of the parsimonious data assimilation technique significantly alleviates simulation errors. The revealed limitations of the proposed operational runoff forecasting system provided a foundation to outline its further development and improvement.},
  language  = {en}
}
@misc{AyzelIzhitskiy2018,
  author    = {Ayzel, Georgy and Izhitskiy, Alexander},
  title     = {Coupling physically based and data-driven models for assessing freshwater inflow into the Small Aral Sea},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {703},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-42787},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-427873},
  pages     = {151 -- 158},
  year      = {2018},
  abstract  = {The Aral Sea desiccation and related changes in hydroclimatic conditions on a regional level is a hot topic for past decades. The key problem of scientific research projects devoted to an investigation of modern Aral Sea basin hydrological regime is its discontinuous nature - the only limited amount of papers takes into account the complex runoff formation system entirely. Addressing this challenge we have developed a continuous prediction system for assessing freshwater inflow into the Small Aral Sea based on coupling stack of hydrological and data-driven models. Results show a good prediction skill and approve the possibility to develop a valuable water assessment tool which utilizes the power of classical physically based and modern machine learning models both for territories with complex water management system and strong water-related data scarcity. The source code and data of the proposed system is available on a Github page (https://github.com/SMASHIproject/IWRM2018).},
  language  = {en}
}
@misc{FranckeFoersterBrosinskyetal.2018,
  author    = {Francke, Till and F{\"o}rster, Saskia and Brosinsky, Arlena and Sommerer, Erik and Lopez-Tarazon, Jose Andres and G{\"u}ntner, Andreas and Batalla Villanueva, Ramon J. and Bronstert, Axel},
  title     = {Water and sediment fluxes in Mediterranean mountainous regions},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {547},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41915},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419150},
  pages     = {13},
  year      = {2018},
  abstract  = {A comprehensive hydro-sedimentological dataset for the Is{\´a}bena catchment, northeastern (NE) Spain, for the period 2010-2018 is presented to analyse water and sediment fluxes in a Mediterranean mesoscale catchment. The dataset includes rainfall data from 12 rain gauges distributed within the study area complemented by meteorological data of 12 official meteo-stations. It comprises discharge data derived from water stage measurements as well as suspended sediment concentrations (SSCs) at six gauging stations of the River Is{\´a}bena and its sub-catchments. Soil spectroscopic data from 351 suspended sediment samples and 152 soil samples were collected to characterize sediment source regions and sediment properties via fingerprinting analyses. The Is{\´a}bena catchment (445 km 2 ) is located in the southern central Pyrenees ranging from 450 m to 2720 m a.s.l.; together with a pronounced topography, this leads to distinct temperature and precipitation gradients. The River Is{\´a}bena shows marked discharge variations and high sediment yields causing severe siltation problems in the downstream Barasona Reservoir. The main sediment source is badland areas located on Eocene marls that are well connected to the river network. The dataset features a comprehensive set of variables in a high spatial and temporal resolution suitable for the advanced process understanding of water and sediment fluxes, their origin and connectivity and sediment budgeting and for the evaluation and further development of hydro-sedimentological models in Mediterranean mesoscale mountainous catchments.},
  language  = {en}
}
@misc{DidovetsLobanovaBronstertetal.2017,
  author    = {Didovets, Iulii and Lobanova, Anastasia and Bronstert, Axel and Snizhko, Sergiy and Maule, Cathrine Fox and Krysanova, Valentina},
  title     = {Assessment of Climate Change Impacts on Water Resources in Three Representative Ukrainian Catchments Using Eco-Hydrological Modelling},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-394956},
  pages     = {18},
  year      = {2017},
  abstract  = {The information about climate change impact on river discharge is vitally important for planning adaptation measures. The future changes can affect different water-related sectors. The main goal of this study was to investigate the potential water resource changes in Ukraine, focusing on three mesoscale river catchments (Teteriv, UpperWestern Bug, and Samara) characteristic for different geographical zones. The catchment scale watershed model—Soil and Water Integrated Model (SWIM)—was setup, calibrated, and validated for the three catchments under consideration. A set of seven GCM-RCM (General Circulation Model-Regional Climate Model) coupled climate scenarios corresponding to RCPs (Representative Concentration Pathways) 4.5 and 8.5 were used to drive the hydrological catchment model. The climate projections, used in the study, were considered as three combinations of low, intermediate, and high end scenarios. Our results indicate the shifts in the seasonal distribution of runoff in all three catchments. The spring high flow occurs earlier as a result of temperature increases and earlier snowmelt. The fairly robust trend is an increase in river discharge in the winter season, and most of the scenarios show a potential decrease in river discharge in the spring.},
  language  = {en}
}
@phdthesis{Graeff2011,
  author    = {Gr{\"a}ff, Thomas},
  title     = {Soil moisture dynamics and soil moisture controlled runoff processes at different spatial scales : from observation to modelling},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-54470},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Soil moisture is a key state variable that controls runoff formation, infiltration and partitioning of radiation into latent and sensible heat. However, the experimental characterisation of near surface soil moisture patterns and their controls on runoff formation remains a challenge. This subject was one aspect of the BMBF-funded OPAQUE project (operational discharge and flooding predictions in head catchments). As part of that project the focus of this dissertation is on: (1) testing the methodology and feasibility of the Spatial TDR technology in producing soil moisture profiles along TDR probes, including an inversion technique of the recorded signal in heterogeneous field soils, (2) the analysis of spatial variability and temporal dynamics of soil moisture at the field scale including field experiments and hydrological modelling, (3) the application of models of different complexity for understanding soil moisture dynamics and its importance for runoff generation as well as for improving the prediction of runoff volumes. To fulfil objective 1, several laboratory experiments were conducted to understand the influence of probe rod geometry and heterogeneities in the sampling volume under different wetness conditions. This includes a detailed analysis on how these error sources affect retrieval of soil moisture profiles in soils. Concerning objective 2 a sampling strategy of two TDR clusters installed in the head water of the Wilde Weißeritz catchment (Eastern Ore Mountains, Germany) was used to investigate how well "the catchment state" can be characterised by means of distributed soil moisture data observed at the field scale. A grassland site and a forested site both located on gentle slopes were instrumented with two Spatial TDR clusters that consist of up to 39 TDR probes. Process understanding was gained by modelling the interaction of evapotranspiration and soil moisture with the hydrological process model CATFLOW. A field scale irrigation experiment was carried out to investigate near subsurface processes at the hillslope scale. The interactions of soil moisture and runoff formation were analysed using discharge data from three nested catchments: the Becherbach with a size of 2 km², the Rehefeld catchment (17 km²) and the superordinate Ammelsdorf catchment (49 km²). Statistical analyses including observations of pre-event runoff, soil moisture and different rainfall characteristics were employed to predict stream flow volume. On the different scales a strong correlation between the average soil moisture and the runoff coefficients of rainfall-runoff events could be found, which almost explains equivalent variability as the pre-event runoff. Furthermore, there was a strong correlation between surface soil moisture and subsurface wetness with a hysteretic behaviour between runoff soil moisture. To fulfil objective 3 these findings were used in a generalised linear model (GLM) analysis which combines state variables describing the catchments antecedent wetness and variables describing the meteorological forcing in order to predict event runoff coefficients. GLM results were compared to simulations with the catchment model WaSiM ETH. Hereby were the model results of the GLMs always better than the simulations with WaSiM ETH. The GLM analysis indicated that the proposed sampling strategy of clustering TDR probes in typical functional units is a promising technique to explore soil moisture controls on runoff generation and can be an important link between the scales. Long term monitoring of such sites could yield valuable information for flood warning and forecasting by identifying critical soil moisture conditions for the former and providing a better representation of the initial moisture conditions for the latter.},
  language  = {en}
}