@article{UberVandervaereZinetal.2018,
  author    = {Uber, Magdalena and Vandervaere, Jean-Pierre and Zin, Isabella and Braud, Isabelle and Heistermann, Maik and Legout, Cedric and Molinie, Gilles and Nord, Guillaume},
  title     = {How does initial soil moisture influence the hydrological response? A case study from southern France},
  series = {Hydrology and earth system sciences : HESS},
  volume    = {22},
  journal   = {Hydrology and earth system sciences : HESS},
  number    = {12},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1027-5606},
  doi       = {10.5194/hess-22-6127-2018},
  pages     = {6127 -- 6146},
  year      = {2018},
  abstract  = {The phi(ev) is calculated from high-resolution discharge and precipitation data for several rain events with a cumulative precipitation P-cum ranging from less than 5mm to more than 80 mm. Because of the high uncertainty of phi(ev) associated with the hydrograph separation method, phi(ev) is calculated with several methods, including graphical methods, digital filters and a tracer-based method. The results indicate that the hydrological response depends on (theta) over bar (ini): during dry conditions phi(ev) is consistently below 0.1, even for events with high and intense precipitation. Above a threshold of (theta) over bar (ini) = 34 vol \% phi(ev) can reach values up to 0.99 but there is a high scatter. Some variability can be explained with a weak correlation of phi(ev) with P-cum and rain intensity, but a considerable part of the variability remains unexplained. It is concluded that threshold-based methods can be helpful to prevent overestimation of the hydrological response during dry catchment conditions. The impact of soil moisture on the hydrological response during wet catchment conditions, however, is still insufficiently understood and cannot be generalized based on the present results.},
  language  = {en}
}
@article{NordBoudevillainBerneetal.2017,
  author    = {Nord, Guillaume and Boudevillain, Brice and Berne, Alexis and Branger, Flora and Braud, Isabelle and Dramais, Guillaume and Gerard, Simon and Le Coz, Jerome and Legout, Cedric and Molinie, Gilles and Van Baelen, Joel and Vandervaere, Jean-Pierre and Andrieu, Julien and Aubert, Coralie and Calianno, Martin and Delrieu, Guy and Grazioli, Jacopo and Hachani, Sahar and Horner, Ivan and Huza, Jessica and Le Boursicaud, Raphael and Raupach, Timothy H. and Teuling, Adriaan J. and Uber, Magdalena and Vincendon, Beatrice and Wijbrans, Annette},
  title     = {A high space-time resolution dataset linking meteorological forcing and hydro-sedimentary response in a mesoscale Mediterranean catchment (Auzon) of the Ardeche region, France},
  series = {Earth System Science Data},
  volume    = {9},
  journal   = {Earth System Science Data},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1866-3508},
  doi       = {10.5194/essd-9-221-2017},
  pages     = {29},
  year      = {2017},
  abstract  = {A comprehensive hydrometeorological dataset is presented spanning the period 1 January 201131 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km(2)) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradient channels of bedrock rivers which promotes the transfer of suspended solids downstream. The number of observed variables, the various sensors involved (both in situ and remote) and the space-time resolution (similar to km(2), similar to min) of this comprehensive dataset make it a unique contribution to research communities focused on hydrometeorology, surface hydrology and erosion. Given that rainfall is highly variable in space and time in this region, the observation system enables assessment of the hydrological response to rainfall fields. Indeed, (i) rainfall data are provided by rain gauges (both a research network of 21 rain gauges with a 5 min time step and an operational network of 10 rain gauges with a 5 min or 1 h time step), S-band Doppler dual-polarization radars (1 km(2), 5 min resolution), disdrometers (16 sensors working at 30 s or 1 min time step) and Micro Rain Radars (5 sensors, 100m height resolution). Additionally, during the special observation period (SOP-1) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). (ii) Other meteorological data are taken from the operational surface weather observation stations of Meteo-France (including 2m air temperature, atmospheric pressure, 2 m relative humidity, 10m wind speed and direction, global radiation) at the hourly time resolution (six stations in the region of interest). (iii) The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations estimate water discharge at a 2-10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity) and water samples are collected automatically during floods, allowing further geochemical characterization of water and suspended solids. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously measures water level and water temperature in headwater subcatchments (from 0.17 to 116 km(2)) at a time resolution of 2-5 min. A network of soil moisture sensors enables the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, concomitant observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. Finally, this dataset is considered appropriate for understanding the rainfall variability in time and space at fine scales, improving areal rainfall estimations and progressing in distributed hydrological and erosion modelling.},
  language  = {en}
}
@article{ZimmermannUberZimmermannetal.2015,
  author    = {Zimmermann, Alexander and Uber, Magdalena and Zimmermann, Beate and Levia, Delphis F.},
  title     = {Predictability of stemflow in a species-rich tropical forest},
  series = {Hydrological processes},
  volume    = {29},
  journal   = {Hydrological processes},
  number    = {23},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0885-6087},
  doi       = {10.1002/hyp.10554},
  pages     = {4947 -- 4956},
  year      = {2015},
  abstract  = {Numerous studies investigated the influence of abiotic (meteorological conditions) and biotic factors (tree characteristics) on stemflow generation. Although these studies identified the variables that influence stemflow volumes in simply structured forests, the combination of tree characteristics that allows a robust prediction of stemflow volumes in species-rich forests is not well known. Many hydrological applications, however, require at least a rough estimate of stemflow volumes based on the characteristics of a forest stand. The need for robust predictions of stemflow motivated us to investigate the relationships between tree characteristics and stemflow volumes in a species-rich tropical forest located in central Panama. Based on a sampling setup consisting of ten rainfall collectors, 300 throughfall samplers and 60 stemflow collectors and cumulated data comprising 26 rain events, we derive three main findings. Firstly, stemflow represents a minor hydrological component in the studied 1-ha forest patch (1.0\% of cumulated rainfall). Secondly, in the studied species-rich forest, single tree characteristics are only weakly related to stemflow volumes. The influence of multiple tree parameters (e.g. crown diameter, presence of large epiphytes and inclination of branches) and the dependencies among these parameters require a multivariate approach to understand the generation of stemflow. Thirdly, predicting stemflow in species-rich forests based on tree parameters is a difficult task. Although our best model can capture the variation in stemflow to some degree, a critical validation reveals that the model cannot provide robust predictions of stemflow. A reanalysis of data from previous studies in species-rich forests corroborates this finding. Based on these results and considering that for most hydrological applications, stemflow is only one parameter among others to estimate, we advocate using the base model, i.e. the mean of the stemflow data, to quantify stemflow volumes for a given study area. Studies in species-rich forests that wish to obtain predictions of stemflow based on tree parameters probably need to conduct a much more extensive sampling than currently implemented by most studies. Copyright (c) 2015 John Wiley \& Sons, Ltd.},
  language  = {en}
}
@misc{NordBoudevillainBerneetal.2017,
  author    = {Nord, Guillaume and Boudevillain, Brice and Berne, Alexis and Branger, Flora and Braud, Isabelle and Dramais, Guillaume and G{\´e}rard, Simon and Le Coz, J{\´e}r{\^o}me and Lego{\^u}t, C{\´e}dric and Molini{\´e}, Gilles and Van Baelen, Joel and Vandervaere, Jean-Pierre and Andrieu, Julien and Aubert, Coralie and Calianno, Martin and Delrieu, Guy and Grazioli, Jacopo and Hachani, Sahar and Horner, Ivan and Huza, Jessica and Le Boursicaud, Rapha{\"e}l and Raupach, Timothy H. and Teuling, Adriaan J. and Uber, Magdalena and Vincendon, B{\´e}atrice and Wijbrans, Annette},
  title     = {A high space-time resolution dataset linking meteorological forcing and hydro-sedimentary response in a mesoscale Mediterranean catchment (Auzon) of the Ard{\`e}che region, France},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {671},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41912},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419127},
  pages     = {29},
  year      = {2017},
  abstract  = {A comprehensive hydrometeorological dataset is presented spanning the period 1 January 201131 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km(2)) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradient channels of bedrock rivers which promotes the transfer of suspended solids downstream. The number of observed variables, the various sensors involved (both in situ and remote) and the space-time resolution (similar to km(2), similar to min) of this comprehensive dataset make it a unique contribution to research communities focused on hydrometeorology, surface hydrology and erosion. Given that rainfall is highly variable in space and time in this region, the observation system enables assessment of the hydrological response to rainfall fields. Indeed, (i) rainfall data are provided by rain gauges (both a research network of 21 rain gauges with a 5 min time step and an operational network of 10 rain gauges with a 5 min or 1 h time step), S-band Doppler dual-polarization radars (1 km(2), 5 min resolution), disdrometers (16 sensors working at 30 s or 1 min time step) and Micro Rain Radars (5 sensors, 100m height resolution). Additionally, during the special observation period (SOP-1) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). (ii) Other meteorological data are taken from the operational surface weather observation stations of Meteo-France (including 2m air temperature, atmospheric pressure, 2 m relative humidity, 10m wind speed and direction, global radiation) at the hourly time resolution (six stations in the region of interest). (iii) The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations estimate water discharge at a 2-10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity) and water samples are collected automatically during floods, allowing further geochemical characterization of water and suspended solids. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously measures water level and water temperature in headwater subcatchments (from 0.17 to 116 km(2)) at a time resolution of 2-5 min. A network of soil moisture sensors enables the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, concomitant observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. Finally, this dataset is considered appropriate for understanding the rainfall variability in time and space at fine scales, improving areal rainfall estimations and progressing in distributed hydrological and erosion modelling.},
  language  = {en}
}