1. Faculty of Environment: Martin Neruda, Tomáš Přikryl, Jitka Fikarová River Board Povodí Ohře: Lucie Tichá Belfast, Questor, 9.3.-12.3.2010

3. Content Monitoring in Chabařovice and Most lakes Rehabilitation of Černý potok stream Rainfall-runoff modelling with Artificial Neural Networks

4. Chabařovice lake Measuring profiles: Eutrophication reservoir: 3 places: − 1) inside the reservoir - in the other end of the reservoir − 2) inside the reservoir - around the outlet − 3) outside of the reservoir - below the outlet in the channel Chabařovice lake: 1 place – inside the lake in the north – west part

5. Chabařovice lake – area of interest

6. Measuring profiles

7. Methodology Catch a small fish and plankton with special net Make a conservation in a small plastic bottle with a chemicals Idea is to say which species of fish come to the lake because of their influence to the fish stock From the last year: research of plankton species to have a detailed picture about the lake‘s ecosystem

8. Eutrophication lake - in the other end of the reservoir 23. 7. 2009 – fish results: 10 pieces of Scardinius erythrophthalmus + 1 piece of Tinca tinca

9. Eutrophication reservoir - around the outlet 28. 7. 2009 – fish results: 10 pieces of Scardinius erythrophthalmus 26. 10. 2009 – plankton results: Cyclops vicinus, Moina macrocopa, Ceriodaphnia reciculata – lots of them

10. Eutrophication lake - below the outlet in the channel No fish species Plenty of the invertebrates (juveniles of insects), many species of plankton – failed the conservation

11. Chabařovice lake – inside the lake in NW part Aimed only to plankton: 7. 9. 2009 Metacyclops gracilis, Melosira varicus, cyclops sp. Daphnia magna – many of them

12. Most lake – new one Profiles: 2 places 1) In side „ Most “ lake 2) Small lake above Most lake

13. Most lake - inside 14. 8. 2009 small species of plankton 12. 11. 2009 Chydorus sphaericus, Daphnia magna, Acanthocyclops nanus – many of them

14. Small lake above the Most lake 5 pieces of Scardinius erythrophthalmus Small species of plankton (algae)

16. Černý potok stream In Ore mountains – north from Usti – boarder with Germany 2 phases of rehabilitation: 1) 1st August- 31st December 2009 2) 1st August 2010 – 31st December 2010 Organised by Agency for Nature Conservation and Landscape Protection of the Czech Republic in Ústí nad Labem Pictures from October 2009:

21. Information about Rainfall-runoff modelling Main goal: improving flood warning system in Czech Hydrometeorological Institute For small size river basins Based on several time series of hourly measured data For short time runoff predictions (1-6 hours) based on runoff and rainfall data

22. R-R modelling Significant data for prediction (made by correlation analysis): runoff data, short time rainfall history, API values Multilayer perceptron Radial basis function Results made in 6 weeks internship (Petr Paščenko) within the scope of the project HPC Europa 2 at the EPCC Department of the Edinburgh University

23. Results Ploučnice River Main problem: - overtraining of the network – poor generalization - small number of extreme events which makes it difficult for a model to predict the amplitude of the event

24. Results Experiments with absolute and relative runoff prediction Neural model shows about 5 % improvement in terms of efficiency coefficient over linear models

25. Results B est behavior - Multilayer perceptrons with one hidden layer trained by back propagation algorithm and predicting relative runoff Genetically evolved input filter improves the performance of yet another 5 %

26. Future Experiments in on-line prediction using real-time data from Smeda River (Jizerské hory mountains) with 6 hours lead time forecast Following the operational reality we will focus on classification of the runoffs into flood alert levels

27. Results

30. The two diagrams show the statistically relevant input variables for the two linear regression models. The red cells variables have 0.001, the violet have 0.01, the blue 0.1 and the white cells stand for less significant inputs.

33. Thank you for your attention