Title page
Contents
Abstract 2
1. Introduction 4
2. Resilience investments and land value creation in a simple model 6
2.1. A simple urban economics model accounting for floods 6
2.2. Locations of floods impact household utility and aggregate land values 8
2.3. How are the results affected in open city settings or with absentee landowners? 11
3. Application to Buenos Aires 14
3.1. NEDUM-2D model and application to the urban area of Buenos Aires 14
3.2. Flood data and damages before and after resilience investments 15
4. Results 18
4.1. Potential land value creation in closed and open cities 18
4.2. Comparison of land value creation and avoided damages 22
4.3. Impact of relaxing FAR regulations on estimated land value creation 23
5. Approximating land value creation potential 25
6. Robustness of the analysis and driving forces 27
6.1. How does land value creation change across all sensitivity scenarios? 28
6.2. Avoiding worst cases: Which scenarios lead to low land value creation? 29
6.3. Seizing opportunities: Which scenarios lead to high land value creation? 30
6.4. What are the driving forces of land value creation and total avoided damages? 31
7. Conclusions and discussion 32
8. References 35
9. Appendix 39
9.1. Choice of NEDUM-2D model parameters 39
9.2. Data informing NEDUM-2D 39
9.3. NEDUM-2D validation 43
9.4. Land value creation approximation: utility changes from resilience investments 44
9.5. Supplementary sensitivity results 45
Table 1. Household utility (u), Aggregate land values (ALV), and city population (N) when floods affect a city compared to a no-flood situation in the four classic urban configurations... 12
Table 2. Household utility, aggregate land values and population variation compared to a no-flood situation depending on the location of flood prone areas and the severity... 13
Table 3. Aggregate impacts of the flood protection investments on land values, household utility and population in CCP and OCP setting and for the two sets of damage estimates... 22
Table 4. Main parameters in the NEDUM-2D model applied to Buenos Aires and sensitivity analyses ranges 28
Figure 1. Household utility and aggregate land value impacts of floods compared to a no-flood situation depending on the location of flood prone areas and the severity of floods... 10
Figure 2. The simulated and real urban area of the GBA+ region in 2012. The green shade corresponds to the simulation whilst the black is geographic data. The dark green shade... 15
Figure 3. Flood maps for the one in a hundred-year return period flood event before resilience investments 17
Figure 4. Flood depth-damage curve functions based on two different studies (Hallegatte et al. 2013; Englhardt et al. 2019) 18
Figure 5. Distribution of land value changes due to resilience investments in CCP (top) and OCP (bottom) settings 20
Figure 6. Maximum number of floors for residential purposes in CABA. Outside CABA, we assume that there are no building regulations 23
Figure 7. Cumulative distribution of aggregate land value change (left) and annualized land value change (right) across all 3000 scenarios. The outcomes under the calibrated... 29
Figure 8. Identification of scenarios leading to low aggregate land value change. The colormap indicates the fraction of scenarios for which land value creation is less than US$... 30
Figure 9. Identification of scenarios leading to favorable outcomes: aggregate land value creation of at least 33% of investment cost 31
Figure 10. Driving forces of the different outcome variables. The values indicate the total gain in impurity from using the indicated input parameter as the splitting feature in the... 32
Figure 11. One-way generalized costs of commuting for the GBA+ urban area based on the simplifying hypothesis that all jobs are situated in the center of Buenos Aires. The... 41
Figure 12. Land use exclusion map showing areas that are excluded from potential urbanization in the model for 2012 (Goytia and Pasquini 2013). Land used for "equipment... 42
Figure 13. Simulated and actual land values as a function of the distance to the city center 43
Figure 14. Simulated and actual population densities for all radios in GBA+ as a function of the distance to the city center 44
Figure 15. Cumulative distribution of ratio between annualized land value creation and annualized avoided damages across all 3000 scenarios 46
Figure 16. Identification of scenarios leading to favorable outcomes: aggregate land value creation of at least 100% of investment cost 46