Socio-hydrological modelling of flood-risk dynamics: comparing the resilience of green and technological systems

Figures & data

Table 1. Time-varying variables of the dynamic model, data type and initial conditions used in the experiment for the two case studies: the People’s Republic of Bangladesh (BGD) and Rome, Italy.

		Data /Proxy		Units		Initial conditions
Variable	Description	BGD	Rome	BGD	Rome	BGD	Rome
W	Flood magnitude	Flooded area	High-water levels	km^2	m
F	Relative flood damage	Economic losses		10^6 USD
D	Floodplain density	GDP	Population density	Normalized*	Normalized**	0.09	0.001
H	Flood protection level		Levee height		m		16
M	Societal memory of floods					0	0

*Floodplain density is normalized between 0 and 1 using an estimated maximum GDP in floodplain areas based on the current GDP per capita of India and China.

**Floodplain density is normalized between 0 and 1 using an estimated maximum population in floodplain areas based on expert judgement.

Figure 1. Testing consistency between the outcomes of the socio-hydrological model and real-world data: People’s Republic of Bangladesh (example of green systems, left column) and Rome (example of technological systems, right column). Data are depicted in black.

Table 2. Time-invariant parameters of the dynamic model and values used in the experiment and reference for the two case studies: the People’s Republic of Bangladesh (BGD) and Rome.

			Values
Parameter	Description	Unit	BGD	Rome
αH	Parameter related to relationship between flood water levels and relative damage (vulnerability)	[L]	1000	30
ξH	Proportion of flood level enhancement due to presence of levees		–	0
ρD	Mean relative growth rate	[T^−1]	0.011 year^−1	0.003 year^−1
κT	Protection level decay rate		–	0
αD	Ratio preparedness/awareness		10	20
εT	Safety factor for levee heightening		–	1.1
μS	Memory loss rate (half-life)	[T^−1]	0.06 year^−1 (11.5 years)	0.06 year^−1 (11.5 years)

Figure 2. Levee height (H), population density (D) and risk (R) dynamics of green (left) and technological (centre, right) systems according to high (α_H = 0.25) and low (α_H = 10) vulnerability conditions. The lighter the line colour, the lower the vulnerability. The centre and right pictures show risk dynamics in technological systems for two different values of levee decay rate k_T, equal to 2 × 10^–5 (centre) and 2 × 10^–3 (right).

Figure 3. Each box contains two bars relating to average losses per event in green (G) and technological (T) systems. The risk-taking attitude increases for decreasing values of α_D (i.e. 50, 10, 3), while the awareness-raising attitude increases for decreasing values of µ_S (i.e. 0.9, 0.22, 0.05).

Figure 4. Recovery time frequencies for green (G) and technological (T) systems. Each group of bars refers to high (H, green), medium (M, orange) and low (L, red) resilience. The fourth bar (NR, grey) indicates frequency of non-resilient responses, namely cases of no recovery. The risk-taking attitude increases for decreasing values of α_D (i.e. 50, 10, 3), while the awareness-raising attitude increases for decreasing values of µ_S (i.e. 0.9, 0.22, 0.05).