► We assess the model performance as function of climate and catchment controls. ► Model performance increases with area and wetness of catchment. ► Peak errors decrease with area and wetness of ...catchment.
Flood runoff is simulated for 57 catchments in Austria and Southern Germany. Catchment sizes range from 70 to 25,600
km
2, elevations from 200 to 3800
m and mean annual precipitation from 700 to 2000
mm. A semi-distributed conceptual water balance model on an hourly time step is used to examine how model performance (both calibration and validation) is related to the hydroclimatic characteristics of the catchments. Model performance of runoff is measured in terms of four indices, the Nash–Sutcliffe model efficiency, the volume error, the percent absolute peak errors and the error in the timing of the peaks. The simulation results indicate that the model performance in terms of the Nash–Sutcliffe model efficiency has a tendency to increase with mean annual precipitation, mean annual runoff, the long-term ratio of rainfall and total precipitation and catchment size. Peak errors have a tendency to decrease with climatological variables as well as with catchment size. Catchment size is the most important control on the model performance but also the ratio rain/precipitation is an important factor. The hydrograph shapes tend to improve with the spatial scale and magnitude of the precipitation events. Calibration and validation results are consistent in terms of these controls on model performance.
► The article deals with the discharge forecasting in an alpine environment. ► The performance of hydrological models under operational conditions is quantified. ► There is no dependency of error ...levels to the forecast lead times. ► Larger discharges show a smaller bandwidth of erroneous discharge simulations.
During recent years a hybrid model has been set up for the operational forecasting of flood discharges in the 6750
km
2 Tyrolean part of the River Inn catchment in Austria. The catchment can be characterized as a typical alpine area with large variations in altitude. The paper is focused on the error analysis of discharge forecasts of four main tributary catchments simulated with hydrological water balance models. The selected catchments cover an area of 2230
km
2, where the non-glaciated and glaciated parts are modeled using the semi-distributed HQsim and the distributed model SES, respectively.
The forecast errors are evaluated as a function of forecast lead time and forecasted discharge magnitude using 14 events from 2007 to 2010. The observed and forecasted precipitation inputs were obtained under operational conditions. The mean relative bias of the forecasted discharges revealed to be constant with regard to the forecast lead time, varying between 0.2 and 0.25 for the different catchments. The errors as a function of the forecasted discharge magnitude showed large errors at lower values of the forecast hydrographs, where errors decreased significantly at larger discharges being relevant in flood forecasting.
The catchment of the river Inn is located in the Swiss and Austrian Alps. In the frame of the flood forecasting system "HoPI" (Hochwasserprognose für den Tiroler Inn), the Austrian part of the river ...Inn and its tributaries are covered within a hybrid numerical model. The runoff from the glacierized headwaters of the south-western Inn tributaries is calculated using the Snow- and Icemelt Model "SES" which utilizes a spatially-distributed energy balance approach; within SES, the accumulation and melting processes for snow, firn, and ice are considered. It is of great importance that such a type of model is used in the simulation of alpine areas since in these regions stream flow is influenced by the accumulation and melt of snow and ice and snow-free glaciers have also the potential to increase or even induce flood flow. For a prototype of the forecast system, SES was calibrated using the snow depletion of a glacier, but later, following the first results during the operational mode, the model was recalibrated and validated using remotely-sensed data covering all 13 glacierized catchments. Using the final snow-parameter setting, a simulation run of 15 hydrological years without any state corrections achieved overall agreements between observed and simulated snow cover ranging from 68% to 88% for all individual catchments. Runoff was calibrated and validated using the data from three different gauges. A parameter set, including both validated snow and runoff parameters, was applied for the modelling of a fourth gauged catchment and also achieved accurate results. This final unique parameterization was transferred to the remaining, ungauged watersheds.
In 2002, a 100 year flood at the Austrian Danube and some of its tributaries has caused significant damage. As a consequence and to fulfill future flood management strategies flood forecasting ...systems were developed for several Danube tributaries in Upper Austria and Lower Austria. The forecasting model shown includes all Austrian Danube tributaries and has been in operational use since 2006. The paper gives a general overview of the hydrologic flood forecasting model for the Danube tributaries. Runoff is estimated for all tributaries to the Austrian Danube with a total size of more than 90.000 km^sup 2^. The model is based on a semi conceptual water balance model. The catchments are divided into sub-basins with sizes ranging from 25 km^sup 2^ to 25.000 km^sup 2^ according to on-line available gauging stations. Hourly data from 90 discharge gauges from 2003 to 2009 were used to calibrate the runoff model in the catchments. In the operational forecasting mode these data are used for the updating procedure. Precipitation and temperature data were provided by the Austrian Meteorological Service as a real mean values for the same period. MODIS-Data are used to verify the output of the snow routine. Simulation results from different calibration periods are shown. Hydrologic forecasts are based on meteorological forecasts, also provided on an hourly basis by the Austrian Meteorological Service. Both deterministic and ensemble forecasts cover a time span of 48 hours. A real time updating procedure based on ensemble Kalman filtering is implemented to have the best state variables of the model at the beginning of an event. The results of the hydrologic forecasting model provide the basis for a hydraulic 1D-model of the Danube river (Reichel, 2006). PUBLICATION ABSTRACT
FLOOD WARNINGS FOR RAILWAYS IN AUSTRIA Nester, Thomas; Schöbel, Andreas; Drabek, Ulrike ...
Modelling in Civil Environmental Engineering (Online),
09/2010
3
Journal Article
Recenzirano
In August 2002 a passenger train was stopped by a flood wave at the river Salzach between Werfen and Golling (Salzburg). In August 2005, railway tracks were destroyed by a flood in Western Austria ...and caused a freight train to derail, in the east of the country floods along the river Morava (Lower Austria) set railway tracks under water. As a consequence of these events, the Austrian railway company decided to establish a warning system in which existing forecasting models were included. A pilot project of such a warning system showed that an effective flood warning could have been issued in sufficient time for the 2002 event in Salzburg. As existing warning systems supply forecasts for gauges along the river, this information has to be transferred to critical locations along the track. Therefore, the identification of dangerous sections along the railway tracks had to be carried out in a first step. This was achieved by combining data from different sources in a GIS application. The forecasted runoff was combined with additional steady and unsteady hydraulic river stage simulations taking into account the contribution of the catchment area between the gauge and the critical location to calculate critical water levels along the reach for the event of August 2002. This method was then used to identify endangered parts in the entire Austrian railway network. PUBLICATION ABSTRACT
Flood Forecasting for the River Inn Senfter, S.; Leonhardt, G.; Oberparleiter, C. ...
Sustainable Natural Hazard Management in Alpine Environments,
09/2009
Book Chapter
The river Inn as the main river in Tyrol moulds the settlement and economic area in Northern Tyrol in a considerable way. 66 % of the area drains into the Inn, whereas the remaining 34% drain into ...the Lech, the Grossache and the Drau in East Tyrol. The Inn flows through Tyrol for about 200 km, from the Swiss border at Martinsbruck to Kufstein, where it leaves Tyrol and flows into Bavaria/Germany (Fig. 2.1).
Runoff generation is a result of the interplay of a range of processes, the relative magnitudes of which vary, among other things, with climate, catchment properties, and catchment scale. The ...variability of runoff generation processes within a mountain catchment and the variability from event to event is one particularly intriguing aspect. A better understanding of these spatio-temporal patterns of runoff generation is critical for obtaining realistic model simulations of events, such as extreme floods, and of run-off behaviour associated with changes in environmental and land use conditions. Estimating runoff generation is very difficult as it involves a high degree of extrapolation. Difficulties in accurately assessing runoff in mountains have been highlighted by local-scale field experiments (e.g. Scherrer 1997), observations in experimental basins (e.g. Anderson et al. 1997; Kirnbauer and Haas 1998; Torres et al. 1998; Müller and Peschke 2000; Uchida et al. 2001), and modelling studies (e.g. Moore and Grayson 1991) that emphasize the spatially highly heterogeneous nature of runoff. Also, different runoff processes may dominate at different spatial scales (see e.g. Blöschl 1996; Uhlenbrook and Leibundgut 1997). Although it is possible to estimate runoff for yet unobserved situations with hydrological simulation models, the reliability of such estimates is notoriously poor, particularly when moving from the plot scale or small catchment scale to medium sized catchments (DFG 1995). There is still a gap between the understanding of runoff generation processes at the plot scale and process-based hydrological modelling at the catchment scale.
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