Flooding in Aalborg Municipality : - Models and Planning
Student thesis: Master Thesis and HD Thesis
- Mette Christiansen
- Heidi Højriis Poulsen
10. term, Master of Science in Geography (Master Programme)
Climate change is a fact. Europe’s annual average temperature has increased more than the global annual average, and Europe’s annual average is expected to increase by 1.0-5.5 ˚C by 2080-2100 compared to the annual average temperature in the period 1961-1990 (European Environment Agency, 2008: 41 ff.).
Climate change comes with various consequences some of which are drought, heat waves, heavy rain, melting of the polar ice caps, increasing sea temperatures and rising sea level.
The rising sea level is the focus of the report at hand, specifically modelling of flooding to facilitate adaption to climate change and rising sea levels. Rising sea levels can induce flooding of coastal areas and more extreme weather can increase the risk of surges in such areas, which has large human and economic costs.
To reduce the consequences of climate change it is necessary to reduce the emission of greenhouse gases but at the same time it is important for society to adapt to the changing climate. The Danish government has devised “A strategy for adaption to climate change in Denmark” (Energistyrelsen, 2008), whose objective it is to ensure that climate change is incorporated in planning and development to a greater extent. The EU’s directive on the assessment and management of flood risks (Europaparlamentet og Rådet, 2007) ensures that the member states are prepared for rising sea levels. It is important that local government in the member states (municipalities etc.) integrate climate change and rising sea levels in their planning efforts.
In this report flood models for Aalborg Municipality are devised. These models help identify areas that are at risk of being flooded. Four different methods for flood modelling in GIS are utilised, which are: the bathtub method, cellular automata (using rook’s rule and queen’s rule) and cost distance. These methods are then compared. The four methods of flood modelling each have pros and cons. The bathtub method is the simplest of the four methods, but also the least accurate. The results are unreliable, since connection to water is not a criterion. The most complex methods are cellular automata – rook’s rule and queen’s rule. A python script is necessary to aid in executing the thousands of needed iterations. Nevertheless cellular automata are the most applicable in planning. Connection to water is a criterion and it is possible to define the neighbourhood used (rook’s rule or queen’s rule). Rook’s rule underestimates the flooding whereas Queen’s rule overestimates. Use of both rook’s rule and queen’s rule could be beneficial. Trough testing it is found that the choice of neighbourhood has a greater influence on the results than choosing between cell sizes of 2 m or 5 m. The cost distance method is relatively simple and quick but it is not possible to define which neighbourhood should be used.
The flood models composed by means of cellular automata (rook’s and queen’s rule) and cost distance are compared to the flood model applied in Aalborg Municipality’s actual climate strategy. In all three models a larger area is flooded than in Aalborg Municipality’s model. It can have consequences if a larger area is flooded and the municipality is not prepared for it.
The flood models can be very useful in planning, but it can also be useful to know the land use in potentially flooded areas. It can be hard, however, to know about the land use at the time of flooding, due to the long time frame. The land use can change in the potentially flooded areas before the flooding occurs. The simulation program Land Use Change Impact Analysis (LUCIA) makes modelling of the future land use possible and by means of LUCIA a land use scenario based on Aalborg Municipality’s plan for future residential and industrial areas is modelled. No new industrial areas, developed in the period 2000-2040, will be flooded as a consequence of Aalborg Municipality’s plans but as much as 14 hectares of new residential areas, developed in that period are at risk of flooding. Aalborg Municipality is recommended to refrain from new residential developments in these areas.
Climate change comes with various consequences some of which are drought, heat waves, heavy rain, melting of the polar ice caps, increasing sea temperatures and rising sea level.
The rising sea level is the focus of the report at hand, specifically modelling of flooding to facilitate adaption to climate change and rising sea levels. Rising sea levels can induce flooding of coastal areas and more extreme weather can increase the risk of surges in such areas, which has large human and economic costs.
To reduce the consequences of climate change it is necessary to reduce the emission of greenhouse gases but at the same time it is important for society to adapt to the changing climate. The Danish government has devised “A strategy for adaption to climate change in Denmark” (Energistyrelsen, 2008), whose objective it is to ensure that climate change is incorporated in planning and development to a greater extent. The EU’s directive on the assessment and management of flood risks (Europaparlamentet og Rådet, 2007) ensures that the member states are prepared for rising sea levels. It is important that local government in the member states (municipalities etc.) integrate climate change and rising sea levels in their planning efforts.
In this report flood models for Aalborg Municipality are devised. These models help identify areas that are at risk of being flooded. Four different methods for flood modelling in GIS are utilised, which are: the bathtub method, cellular automata (using rook’s rule and queen’s rule) and cost distance. These methods are then compared. The four methods of flood modelling each have pros and cons. The bathtub method is the simplest of the four methods, but also the least accurate. The results are unreliable, since connection to water is not a criterion. The most complex methods are cellular automata – rook’s rule and queen’s rule. A python script is necessary to aid in executing the thousands of needed iterations. Nevertheless cellular automata are the most applicable in planning. Connection to water is a criterion and it is possible to define the neighbourhood used (rook’s rule or queen’s rule). Rook’s rule underestimates the flooding whereas Queen’s rule overestimates. Use of both rook’s rule and queen’s rule could be beneficial. Trough testing it is found that the choice of neighbourhood has a greater influence on the results than choosing between cell sizes of 2 m or 5 m. The cost distance method is relatively simple and quick but it is not possible to define which neighbourhood should be used.
The flood models composed by means of cellular automata (rook’s and queen’s rule) and cost distance are compared to the flood model applied in Aalborg Municipality’s actual climate strategy. In all three models a larger area is flooded than in Aalborg Municipality’s model. It can have consequences if a larger area is flooded and the municipality is not prepared for it.
The flood models can be very useful in planning, but it can also be useful to know the land use in potentially flooded areas. It can be hard, however, to know about the land use at the time of flooding, due to the long time frame. The land use can change in the potentially flooded areas before the flooding occurs. The simulation program Land Use Change Impact Analysis (LUCIA) makes modelling of the future land use possible and by means of LUCIA a land use scenario based on Aalborg Municipality’s plan for future residential and industrial areas is modelled. No new industrial areas, developed in the period 2000-2040, will be flooded as a consequence of Aalborg Municipality’s plans but as much as 14 hectares of new residential areas, developed in that period are at risk of flooding. Aalborg Municipality is recommended to refrain from new residential developments in these areas.
Language | Danish |
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Publication date | 8 Jun 2011 |
Number of pages | 118 |
Keywords | Flooding, Models , LUCIA, GIS, Cellular automata, Climate change |
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