Modelos Hidrologicos: Runoff Pedro Ribeiro de Andrade Gilberto Camara

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

Brazil 2000 Espinhaço Range

Minas Gerais State 2000

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Pico do Itacolomi do Itambé Serra do Lobo

Pico do Itacolomi do Itambé Serra do Lobo 9 km

rain N Pico do Itacolomi do Itambé Serra do Lobo

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

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

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}

Grid of Cells – Height

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

Neighborhood – based on height

Neighborhood – based on height Note that the process takes place in parallel in space

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

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

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