Implementation of the methodology for climate change assessment for stormwater management in the Barcelona case study

Transcription

1 Implementation of the methodology for climate change assessment for stormwater management in the Barcelona case study Xavier Aldea, CETaqua Beniamino Russo, CLABSA Marc Velasco, CETaqua David Sunyer, CLABSA Teresa Kersting, CETaqua

2 Introduction about Barcelona Case Study General information: Barcelona is located in Mediterranean area (NE Spain) 1,621,000 inhabitants Area of Km 2 Climate: Mediterranean, with cool winters and hot summers Density of 15,980 inhab./ Km 2 (19,200 inhab./ Km 2 not considering Collserola mountain) High slopes in the mountain and nearly flat on the coast High density of population and land imperviousness Heavy rainfall with high intensities (flash flood events). Average annual precipitation 600 mm Maximum intensity in 5 min is 205 mm/h for a 10 yr return period 50% of annual precipitation can occur in only 2 or 3 events

3 Introduction about Barcelona Case Study Raval District Spot susceptible to flooding as demonstrated by historical data inh./km 2 High social and economical vulnerability Traditional 1D sewer models do not detect flooding problems

4 Model setup 1D/2D coupled model through Infoworks ICM software 5 catchments (aprox. 44 Km 2 ) involved with 241 Km of pipes with 3826 manholes 38 sluices (fixed and variable) 27 weirs and 3 flap valves 6 storage tanks with a storage volume of more than 170,000 m 3

5 Model setup Creation of 1D/2D detailed coupled model with secondary network and microcatchments inside the Raval District for the hydraulic characterization of surface drainage structures Definition of the Rainfall-Runoff transformation model (losses and routing models) for the building area Definition of 338 2D infiltration zones in the 2D mesh (more than cells). Hydrological characterization of pervious and the impervious areas using the hydrological model of the cells (new feature of the last version of ICM).

6 Model setup 1D/2D approach Rainfall directly falls on cells characterized by a hydrological model 1D and 2D models are coupled through Node Type 2D (manholes) or Node Type Gully2D (inlets) Gully2D nodes were hydraulically characterized using experimental expressions achieved for the most common inlets of Spain, in order to take into account flow entering into the network and surcharged overflows.

7 Calibration of the 1D/2D coupled model Calibration process Selection of 3 calibration events and 1 validation event. Due to the recent significant changes of the Barcelona sewer system, rainfall events were selected in the year This year was characterized by several heavy rainfall events Date event Cumulative rainfall Maximum rainfall intensity in 20 minutes Maximum rainfall intensity in 5 minutes (mm) (mm/h) (mm/h) Function of the event 15/03/ Calibration 07/06/ Calibration 19/07/ Calibration 30/07/ Verification Processing of rainfall data from 11 rain gauge, flow depth time series from 27 limnimeters and time series of 12 variable sluices Collection of field data (reports of policemen, firemen, municipality authorities, etc.) concerning selected events Selection and adjustment of the calibration model parameters Calibration related to surface flooded areas, pressured pipes and manholes with overflows Results verification

8 Calibration of the 1D/2D coupled model Sewer system calibration (Flow depths time series in pipes, manholes and storage tanks) Situation for a monitored manhole (P-AV65) in Parallel Street Measured Simulated

9 Calibration of the 1D/2D coupled model Surface flow validation Sant Pau Street: Comparison between flow depths provided by model simulations and youtube video recorded during the event of 30/07/2011

10 Calibration of the 1D/2D coupled model Surface flow validation Diagonal Avenue with Casanova Street: Analysis of sewer profile focusing on the surcharged manholes. Comparison with a photo taken during the event of 30/07/2011

11 Vulnerability methodology Vulnerability is essential to assess flood risk Damages types Risk = Hazard Exposure Vulnerability Vulnerability is defined as the susceptibility of the Tangible Intangible exposed structures/people at contact with the damaging natural event. This factor Physical measures damage the to extent to which the Direct subject matter could be Fatalities, injuries assets affected by the hazard Indirect Loss of production, traffic disruption Psychological trauma, increased vulnerability of survivors

12 Vulnerability methodology To obtain direct tangible damages the following are needed: depth damage curves flood depth maps land use maps The methodology proposed follows these steps: Simulation of three flood events to obtain the flood depths in the area Assign a water depth to each building Interpolate this value in the depth damage curve to obtain the relative cost Multiply the relative cost by the area, obtaining the total damage value per each block Sum of all the blocks damages to obtain the total damages of each event Calculation of the EAD by weighting the damages of each event with its probability

13 Depth damage curves Buildings Calibration and validation of the curves has been undertaken using: Surveys of the event occurred in 30/07/2011 to validate some qualitative features of the curves Actual damage data from the Spanish reassurance (CCS) has been collected to undertake a spatial and quanititive validation Prepared enabling Contents change

14 Flood maps Post processing of flood maps is required Conversion of the 1D-2D model outputs From depths in the streets to depths in the buildings

15 Land use maps Catastro (National land-registry) Geoportal (Municipal spatial database) Information at a block size Number of floors Land-use area of each type per floor

16 Scenarios Combinations of changes in climate and adaptive capacity level are considered in the follwoing scenarios Socioeconomic scenario is kept constant in order to properly assess the results of the CBA Combined scenario Climate scenario Socioeconomic scenario Adaptive capacity Baseline (2010) Pessimistic None None Optimistic (2050) Optimistic Medium None Pessimistic (2050) Pessimistic Medium None Adaptation (2050) Pessimistic Medium High

17 Scenarios Climate data coming from SW0801 project has been used to obtain uplift factors for the year 2050 Pessimistic scenarios will use the maximum uplift factors for each return period Representing the worst case scenario Optimistic scenarios will use the minimum uplift factors for each return period Representing the minimum adaptation needed Pessimistic scenario Optimistic scenario Return periods 1 year 10 years 100 years

18 Scenarios Socio-economic scenarios Baseline High growth Medium growth Low growth Growth rate Growth rate Growth rate GVA (billion, 2005 prices) % % % Employment (thousands) % % % Population (15-64 years, thousands) % % % Population (total, thousands) % % % Ratio of exposed assets in the Raval National level scenarios for Spain. Sources: SSP-Database, IIASA, 2012; Eurostat, 2012; INE, Growth trends ( ) and future scenarios ( ) for GVA (left) and employment (right) for Catalonia.

19 Scenarios Adaptation strategies will be implemented to cope with the impacts of climate change Adaptation scenario is defined by several structural strategies affecting the drainage network New retention tank in the Raval district Improvement of the hydraulic capacity of the sewer network in the upstream basins redesigning several pipes

20 Results Expected Anual Damage For the four simulated scenarios Return period (years) Probability EAD Damages baseline (2010) 78,846 1,615,738 19,156,196 1,697,300 Damages optimistic (2050) 131,654 2,718,048 32,400,065 2,862,681 Damages pessimistic (2050) 211,846 8,369,323 45,642,494 6,292,058 Damages adaptation (2050) 7, ,258 10,478, ,915

21 Results Cost benefit analysis In order to be able to compare costs and benefits of the adaptation measures, the CBA is based on annual equivalent costs and benefits EAD is used to express the annual benefits Total cost of adaptation is annualized through its useful life Scenario Total cost of adaptation Equivalent annual cost of adaptation EAD (2050) Annual benefit (2050) Annual net benefit of adaptation (2050) Pessimistic M - - Adaptation 78.00M 5.65M 0.61M 5.68M 29,123

22 Conclusions A 1D/2D coupled model was developed and the interface between the two drainage layers was characterized through empirical expressions related to hydraulic performance of surface drainage systems Calibration and validation of the model were based on the data related to 4 heavy storm events occurred in The obtained results show that it is possible to reproduce the effects of urban floods in the Raval District in a more realistic way than traditional 1D sewer flow simulations. DDC have been created for the case study area Calibration and validation process has lead to a set of curves that are able to accurately represent the damages of the area

23 Conclusions The methodology followed is able to determine the EAD of the area in a straightforward way The EAD of the several scenarios is easily obtained once these are simulated The comparison of baseline and future scenarios highlights the need for the implementation of adaptation strategies The structural strategies implemented are able to reduce flood damages in a cost effective way

24 Xavier Aldea Beniamino Russo Marc Velasco David Sunyer Teresa Kersting