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EROSION
Person
Class
Person
Publication
Programmes
prof. RNDr. Jakub Langhammer Ph.D.
Academic staff at Faculty of Science
1 study programme
9 classes
240 publications
Study programme
programme
Hydrology and Hydrogeology
🇨🇿 Bc. |
Faculty of Science
Classes
class
Advanced instrumental techniques in hydrological research
MBCPLUS013 |
Faculty of Science
class
Hydrology
MPGS0070 |
Faculty of Science
class
Current Trends in Hydrology and Hydrogeology
MZ330E005 |
Faculty of Science
class
Application of Geoinformatics in Physical Geography
MZ330P104 |
Faculty of Science
class
Hydroinformatics
MZ330P114 |
Faculty of Science
class
Extreme Hydrometeorological Phenomena and Processes
MZ330P116 |
Faculty of Science
class
Flood Risk Management
MZ330P134 |
Faculty of Science
class
Geoinformatics in Physical Geography
MZ330P48 |
Faculty of Science
class
Water Quality
MZ330P93 |
Faculty of Science
Publications
publication
Analysis of efficiency of pollution reduction measures in rural basin using MIKE Basin model. Case study: Olšava river basin
2014 |
Faculty of Science
publication
Assessment of spatial and temporal changes of ecological status of streams in Czechia: A geographical approach
2013 |
Faculty of Science
publication
Impact of landscape and fluvial disturbance on the dynamics of fluvial processes in mountain areas
2012 |
Faculty of Science
publication
Present changes in water soil erosion hazard and the response to suspended sediment load
2012 |
Faculty of Science
publication
Evaluation of suspended load changes using AnnAGNPS and SWAT semi-empirical models
2008 |
Faculty of Science
publication
Suspended sediment load and soil erosion processes in mesoscale catchment areas
2007 |
Faculty of Science
publication
Modelling of the erosion risk in the Blšanka river basin
2007 |
Faculty of Science
publication
Czech Republic
2006 |
Faculty of Science
publication
Modelling the nonpoint pollution sources in conditions of changing landuse - final report
Publication without faculty affiliation
publication
Flood Simulations Using a Sensor Network and Support Vector Machine Model
2023 |
Faculty of Science
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