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Hydrological modelling in the anthroposphere: predicting local runoff in a heavily modified high-alpine catchment

Authors :
Karsten Schulz
Johannes Wesemann
Mathew Herrnegger
Source :
Journal of Mountain Science. 15:921-938
Publication Year :
2018
Publisher :
Springer Science and Business Media LLC, 2018.

Abstract

Hydrological models within inflow forecasting systems for high-alpine hydropower reservoirs can provide valuable information as part of a decision support system for the improvement of hydropower production or flood retention. The information, especially concerning runoff, is however rarely available for the calibration of the hydrological models used. Therefore, a method is presented to derive local runoff from secondary information for the calibration of the model parameters of the rainfallrunoff model COSERO. Changes in water levels in reservoirs, reservoir outflows, discharge measurements at water intakes and in transport lines are thereby used to derive the local, “natural” flow for a given sub-catchment. The proposed method is applied within a research study for the OBB Infrastructure Railsystem division in the Stubache catchment in the central Austrian Alps. Here, the OBB operates the hydropower scheme “Kraftwerksgruppe Stubachtal”, which consists of 7 reservoirs and 4 hydropower stations. The hydrological model has been set up considering this human influences and the high natural heterogeneity in topography and land cover, including glaciers. Overall, the hydrological model performs mostly well for the catchment with highest NSE values of 0.78 for the calibration and 0.79 for the validation period, also considering the use of homogeneous parameter fields and the uncertainty of the derived local discharge values. The derived runoff data proved to be useful information for the model calibration. Further analysis, examining the water balance and its components as well as snow cover, showed satisfactory simulation results. In conclusion, a unique runoff dataset for a small scale high-alpine catchment has been created to establish a hydrological flow prediction model which in a further step can be used for improved and sustainable hydropower management.

Details

ISSN :
19930321 and 16726316
Volume :
15
Database :
OpenAIRE
Journal :
Journal of Mountain Science
Accession number :
edsair.doi...........006aa1b6ce9865f0cb4389aaa47a76ee
Full Text :
https://doi.org/10.1007/s11629-017-4587-5