TY - JOUR A1 - Bronstert, Axel A1 - Creutzfeldt, Benjamin A1 - Gräff, Thomas A1 - Hajnsek, Irena A1 - Heistermann, Maik A1 - Itzerott, Sibylle A1 - Jagdhuber, Thomas A1 - Kneis, David A1 - Lueck, Erika A1 - Reusser, Dominik A1 - Zehe, Erwin T1 - Potentials and constraints of different types of soil moisture observations for flood simulations in headwater catchments JF - Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards N2 - Flood generation in mountainous headwater catchments is governed by rainfall intensities, by the spatial distribution of rainfall and by the state of the catchment prior to the rainfall, e. g. by the spatial pattern of the soil moisture, groundwater conditions and possibly snow. The work presented here explores the limits and potentials of measuring soil moisture with different methods and in different scales and their potential use for flood simulation. These measurements were obtained in 2007 and 2008 within a comprehensive multi-scale experiment in the Weisseritz headwater catchment in the Ore-Mountains, Germany. The following technologies have been applied jointly thermogravimetric method, frequency domain reflectometry (FDR) sensors, spatial time domain reflectometry (STDR) cluster, ground-penetrating radar (GPR), airborne polarimetric synthetic aperture radar (polarimetric SAR) and advanced synthetic aperture radar (ASAR) based on the satellite Envisat. We present exemplary soil measurement results, with spatial scales ranging from point scale, via hillslope and field scale, to the catchment scale. Only the spatial TDR cluster was able to record continuous data. The other methods are limited to the date of over-flights (airplane and satellite) or measurement campaigns on the ground. For possible use in flood simulation, the observation of soil moisture at multiple scales has to be combined with suitable hydrological modelling, using the hydrological model WaSiM-ETH. Therefore, several simulation experiments have been conducted in order to test both the usability of the recorded soil moisture data and the suitability of a distributed hydrological model to make use of this information. The measurement results show that airborne-based and satellite-based systems in particular provide information on the near-surface spatial distribution. However, there are still a variety of limitations, such as the need for parallel ground measurements (Envisat ASAR), uncertainties in polarimetric decomposition techniques (polarimetric SAR), very limited information from remote sensing methods about vegetated surfaces and the non-availability of continuous measurements. The model experiments showed the importance of soil moisture as an initial condition for physically based flood modelling. However, the observed moisture data reflect the surface or near-surface soil moisture only. Hence, only saturated overland flow might be related to these data. Other flood generation processes influenced by catchment wetness in the subsurface such as subsurface storm flow or quick groundwater drainage cannot be assessed by these data. One has to acknowledge that, in spite of innovative measuring techniques on all spatial scales, soil moisture data for entire vegetated catchments are still today not operationally available. Therefore, observations of soil moisture should primarily be used to improve the quality of continuous, distributed hydrological catchment models that simulate the spatial distribution of moisture internally. Thus, when and where soil moisture data are available, they should be compared with their simulated equivalents in order to improve the parameter estimates and possibly the structure of the hydrological model. KW - Soil moisture KW - Remote sensing KW - Hydrological modelling KW - Flood forecasting KW - Soil moisture measurement comparison Y1 - 2012 U6 - https://doi.org/10.1007/s11069-011-9874-9 SN - 0921-030X SN - 1573-0840 VL - 60 IS - 3 SP - 879 EP - 914 PB - Springer CY - New York ER - TY - JOUR A1 - Kneis, David A1 - Buerger, Gerd A1 - Bronstert, Axel T1 - Evaluation of medium-range runoff forecasts for a 50 km(2) watershed JF - Journal of hydrology N2 - We generated medium-range forecasts of runoff for a 50 km(2) headwater catchment upstream of a reservoir using numerical weather predictions (NWPs) of the past as input to an operational hydrological model. NWP data originating from different sources were tested. For a period of 8.5 years, we computed daily forecasts with a lead time of +120 h based on an empirically downscaled version of the ECMWF's ensemble prediction system. For the last 3.5 years of the test period, we also tried the deterministic COSMO-EU forecast disseminated by the German Weather Service for lead times of up to +72 h. Common measures of skill indicate superiority of the ensemble runoff forecast over single-value forecasts for longer lead times. However, regardless of which NWP data were being used, the probability of event detection (POD) was found to be generally lower than 50%. In many cases, values in the range of 20-30% were obtained. At the same time, the false alarms ratio (FAR) was often found to be considerably high. The observed uncertainties in the hydrological forecasts were shown to originate from both the insufficient quality of precipitation forecasts as well as deficiencies in hydrological modeling and quantitative precipitation estimation. With respect to the anticipatory control of reservoirs in the studied catchment, the value of the tested runoff forecasts appears to be limited. This is due to the unfavorably low POD/FAR ratio in conjunction with a high cost-loss ratio. However, our results indicate that, in many cases, major runoff events related to snow melt can be successfully predicted as early as 4-5 days in advance. KW - Runoff forecast KW - Small catchments KW - Forecast verification KW - Reservoir control Y1 - 2012 U6 - https://doi.org/10.1016/j.jhydrol.2011.11.005 SN - 0022-1694 VL - 414 IS - 2 SP - 341 EP - 353 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Costa, Alexandre Cunha A1 - Bronstert, Axel A1 - Kneis, David T1 - Probabilistic flood forecasting for a mountainous headwater catchment using a nonparametric stochastic dynamic approach JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - Hydrological models are commonly used to perform real-time runoff forecasting for flood warning. Their application requires catchment characteristics and precipitation series that are not always available. An alternative approach is nonparametric modelling based only on runoff series. However, the following questions arise: Can nonparametric models show reliable forecasting? Can they perform as reliably as hydrological models? We performed probabilistic forecasting one, two and three hours ahead for a runoff series, with the aim of ascribing a probability density function to predicted discharge using time series analysis based on stochastic dynamics theory. The derived dynamic terms were compared to a hydrological model, LARSIM. Our procedure was able to forecast within 95% confidence interval 1-, 2- and 3-h ahead discharge probability functions with about 1.40 m(3)/s of range and relative errors (%) in the range [-30; 30]. The LARSIM model and the best nonparametric approaches gave similar results, but the range of relative errors was larger for the nonparametric approaches. KW - streamflow probabilistic forecasting KW - time series analysis KW - stochastic dynamical systems KW - parametric and nonparametric comparison Y1 - 2012 U6 - https://doi.org/10.1080/02626667.2011.637043 SN - 0262-6667 VL - 57 IS - 1 SP - 10 EP - 25 PB - Routledge, Taylor & Francis Group CY - Abingdon ER -