1. Modelos Hidrologicos: Runoff Pedro Ribeiro de Andrade Gilberto Camara

2. How can geospatial data feed CA models?  Grid of cells  Neighbourhood  Finite set of discrete states  Finite set of transition rules  Initial state  Discrete time

3. Brazil 2000 Espinhaço Range

4. Minas Gerais State 2000

6. View

7. Pico do Itacolomi do Itambé Serra do Lobo

8. Pico do Itacolomi do Itambé Serra do Lobo 9 km

9. rain N Pico do Itacolomi do Itambé Serra do Lobo

10. A very simple runoff model  Grid of cells  Neighbourhood  Finite set of discrete states  Finite set of transition rules  Initial state  Discrete time

11. Acessing a cell space in a database host = "gis-bigdata.uni-muenster.de” user = "terraview", password = "terralib” database = “cabeca”

12. cells = CellularSpace { dbType = "mysql", host = "gis-bigdata.uni-muenster.de", database = "cabeca", user = "terraview", password = "terralib", theme = "cells90x90", select = {"height_ as height", "soilWater"}, autoload = true}

13. Grid of Cells – Height

14. Initial state – Rain in the heighest cells 1000mm of rain in the cells above 200m height

15. Neighborhood – based on height 4834 30 21 37 33 34 25 23

16. Neighborhood – based on height 4834 30 21 37 33 34 25 23 Note that the process takes place in parallel in space

17. States and transitions DryWet  What is the behavior of each state?  Are both states necessary?

18. Relaxing cellular automata definitions  Grid of cells  Neighbourhood (not fixed)  Finite set of discrete states  Finite set of transition rules  Initial state (geospatial data)  Discrete time

19. Questions  How to verify whether the model is correctly implemented?  What are the limitations of this model?