cell level, , which can be acquired either with population censuses or through global population data sets such as WorldPop or Landscan<sup>17</sup> for example. ii aa Using this reduced form approximation and using the model’s own prediction of the spatial distribution of households in the urban area , we estimate annual and aggregate land value creation from resilience investments to be respectively US$ 8.5 million and US$ 425 million. These numbers are reasonably close ii aa to our fully fledged model results of US$ 7.6 million and US$ 379 million but they overestimate them by 12% in both cases. There is always a tradeoff between the benefits and the drawbacks of model complexity. Given the simplicity of producing estimates for the reduced form expression in terms of data and modeling requirements, we consider this to be a promising result and approach that could be used in locations where data is scarce so as to produce quick estimates of land value creation potential from resilience investments.

6 Robustness of the analysis and driving forces Systematic sensitivity analyses of model results are useful for two reasons. First, whereas most parameter values are the result of a careful calibration procedure, there nonetheless remains irreducible uncertainty, and it is useful to explore the consequences of deviations from the central estimations. Second, aggregate land value creation from resilience investments materializes across a long-time horizon, when housing and land markets have adjusted, new construction has occurred, and households’ locational choices have evolved.<sup>18</sup> When we look into the future, even assuming that the static parameters informing the model are perfectly calibrated, there are uncertainties pertaining to their stability over time as various agents’ behaviors can vary, for example as a response to exogenous changes in construction techniques.

To evaluate the robustness of the results, we recalculate aggregate land value creation not only using the calibrated model parameters, but also across various combinations of parameterizations. In particular, we recalculate land value creations across 3,000 scenarios in the Closed City with Public ownership of land setting (CCP) and using the conservative flood-depth damage curves provided in Hallegatte et al. (2013). We restrict the sensitivity analysis to one city setting and one flood-depth damage curve because we have already explored the impact of different choices in previous sections and we wish to isolate the contribution of model parameters to land value creation estimates. We choose the CCP setting and the lower bound flood-depth damage curve as these yield more conservative estimates of land value creation from flood mitigation estimates. The choice of the closed city setting is also more likely to be valid in the short to medium-term as potential in-migration cannot happen instantaneously. Each scenario comprises different model parameterization sampled<sup>19</sup> from the uncertainty range as presented in Table 4.<sup>20</sup> It

> 17 Accessible at: https://www.worldpop.org/methods/populations and <u>https://landscan.ornl.gov/.</u>

> 18 Local land value increases, as opposed to aggregate net land value change, can occur in the very short term as soon as the flood mitigation works have been announced even, consistent with the assumption of land prices corresponding to their highest and best use and developers/landowners’ perfect foresight. We are however interested in aggregate land value creation after land and housing market mediation, which can only manifest itself over time.

> 19 We use a Latin Hypercube Sampling (LHS) function and make use of the option to minimize the sum of betweencolumn squared correlations.

> 20 Table 4 also presents the values and the signification of the main parameters of the NEDUM-2D model applied to Buenos Aires in our baseline calibration. It also explains how these were obtained (through calibration processes, informed by data, borrowing from the literature or through assumptions), and how these parameter values relate to those found in the literature.

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