Project summary

Extreme hydrological events such as floods and droughts are becoming more frequent, more severe, and less predictable as a result of climate change, posing increasing challenges for society. Mountain areas are particularly vulnerable due to the current impacts of climate change, landscape disturbance, and human interventions. The combined effect of changes operating at different temporal and spatial scales in variable physiography in different regions leads to increasing non-stationarity of hydrological processes and reduced confidence in understanding and predicting extreme processes.

The research aims to explore the changing scope of the occurrence, driving forces, spatial patterns, and dynamics of hydrological extremes in montane regions in the Czech Republic and Central Europe. Better understanding the combined effects of the principal drivers of change and understanding their effects under variable environmental conditions on streamflow nonstationarity is critical for reliable hydrological predictions and the design of adaptation measures.

The objectives of the PhD research project are (i) to explore the changing patterns of the occurrence, and dynamics of hydrological extremes in montane regions in the Czech Republic and Central Europe, (ii) to elucidate the contribution of drivers of change, and (iii) to model the combined effects in transient montane environments.

The research will be conducted at different spatial scales. The observations at own sensor networks providing high-resolution hydrometeorological monitoring in experimental catchments will reveal patterns of changes in the dynamics of extreme flow events. The spatial aspects and effects of physiography will be studied using long-term observations at gauging stations in different montane basins.

The research should bring new insights into dynamic natural processes and at the same time be innovative in terms of hydrological and hydroinformatics research methodology. Advanced data analysis and modeling techniques, including machine learning and non-linear analytical methods, will be used to cope with large volumes of heterogeneous data and environmental non-stationarity.

The candidate will be a member of the Research group of hydrology at the Department of Physical Geography and Geoecology, Faculty of Science, Charles University, Prague. Close cooperation with the interdisciplinary teams within the OP JAC Natural and Anthropogenic Georisks project at the Faculty of Science, Charles University, is expected.

Selected publications of the research group related to the project

Langhammer, J., 2023. Flood Simulations Using a Sensor Network and Support Vector Machine Model. Water, 15(11), 2004; https://doi.org/10.3390/w15112004.

Jenicek, M., Hnilica, J., Nedelcev, O., Sipek, V. (2021). Future changes in snowpack will impact seasonal runoff and low flows in Czechia. Journal of Hydrology: Regional Studies, 37, 100899. https://doi.org/10.1016/j.ejrh.2021.100899.

Lendzioch T, Langhammer J, Vlček L, Minařík R. (2021): Mapping the Groundwater Level and Soil Moisture of a Montane Peat Bog Using UAV Monitoring and Machine Learning. Remote Sensing. 13(5):907. https://doi.org/10.3390/rs13050907.

Nedelcev O., Jenicek, M. (2021). Trends in seasonal snowpack and their relation to climate variables in mountain catchments in Czechia, Hydrological Sciences Journal, 66 (16), 2340-2356. https://doi.org/10.1080/02626667.2021.1990298.

Langhammer, J., Bernsteinová, J., 2020. Which Aspects of Hydrological Regime in Mid-Latitude Montane Basins Are Affected by Climate Change?. Water, 12(8), 2279. https://doi.org/10.3390/w12082279

Su, Y., Langhammer, J., Jarsjo, J. (2017). Geochemical responses of forested catchments to bark beetle infestation: Evidence from high frequency in-stream electrical conductivity monitoring, Journal of Hydrology, 550, 635–649. https://doi.org/10.1016/j.ecohyd.2017.06.002

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