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shi_dataset_cdmx's Introduction

Socio-hydrological resilience dataset Mexico city and Metropolitan Area

Original Publish Date: 26 May, 2021
Updated on: 01 Jun, 2021

This page describes the technical specifications of the Socio-hydrological resilience dataset for Mexico city and its Metropolitan Area. The data is presented as geometric polygon features representing administrative areas.

Methodology

This research project was developed by the British Geological Survey, the Architectural Association, the Centre for Advanced Spatial Analysis and Fluxus. For more information about the project and methodology visit the project website.

General description

The dataset comprises a set of variables that describe socio-hydrological vulnerability and the effects of building constructed wetlands for geographic areas called Colonias (n = 2785). Additionally, the effects of constructed wetlands are summarised at larger administrative areas called Alcaldias (n = ). The variables represent a description of the baseline (no constructed wetlands) for the actual 2020 and future 2050 situations and the estimation of the impacts of 4 budget schemes. Socio-hydrological vulnerability is represented by a Socio-hydrological index (SHI) which is the quotient between the Water Stress index (WSI) and the Adaptive Capacity index (ACI).

The impact of Constructed Wetlands (CW) in each Colonia is presented as the total amount of CW measured in square meters, and measured as total budget when this variable is aggregated to Alcaldias. Finally, the indexes and effects of CW (SHI, WSI, ACI and CW) are calculated for 3 world-views scenarios; Stakeholder, Environmental and Social. As illustrated in the data-cube figure below the combination of these parameters make up 120 variables for Colonias and 30 variables for Alcaldias (budget 0 variables for CW should be removed as this budget produces no impact making a final total of 114 and 24 variables)

Codebook

The name of the variables is created from a string of the different parameters according to the following table. For example, the variable "ACI_c_w1_b1" corresponds to Adaptive Capacity index for 2020, Stakeholder weighting and budget 1

Variable name Variable description
ID_Colonia unique numeric identifier for Colonia
Municipality Name of Alcaldia (similar to Borough)
Colonia Name of Colonia (similar to LSOA)
pop Total population (by Colonia)
SHI Socio-hydrological vulnerability index
WSI Water Stress index
ACI Adaptive Capacity index
CW_sqm Constructed Wetlands in square metres
CW_perc Percentage of homes with CW
c current 2020
f future 2050
w1 Stakeholder (weighting)
w2 Environmental (weighting)
w3 Social (weighting)
b0 no constructed wetlands
b1 10,000 constructed wetlands
b2 100,000 constructed wetlands
b3 500,000 constructed wetlands
b4 maximum constructed wetlands
cl class. The index (SHI, WSI, ACI) reclassified into levels
budget Total budget invested in CW by Alcaldia

Indices classes (or levels) & colour schemes

The values of all indices (SHI, WSI and ACI) are categorised and organised according to the following tables of value breaks, classes and colours

SHI

Value Class Colour
0.0 - 0.6 Little to no #003496
0.6 - 0.8 Little to no #567bbb
0.8 - 1.0 Little to no #adc3e0
1.0 - 1.2 Moderate #fef9e4
1.2 - 1.4 Moderate #fee2a4
1.4 - 1.6 Moderate #fdca65
1.6 - 1.8 Moderate #fdb225
1.8 - 2.0 Moderate #ee8311
2.0 - 2.2 Significant #d4411e
2.2 - 2.4 Significant #bd1a21
2.4 - 2.6 Significant #ab1319
2.6 - 2.8 Significant #990d10
2.8 - 3.0 Significant #870608
3.0 - 8.0 Extreme #750000

WSI

Value Class Colour
0.0 - 0.1 Very low #ffffff
0.1 - 0.2 Very low #ffffff
0.2 - 0.3 Low #ffffff
0.3 - 0.4 Low #ffffff
0.4 - 0.5 Moderate #ffffff
0.5 - 0.6 Moderate #dff6fa
0.6 - 0.7 High #87cce1
0.7 - 0.8 High #2fa2c7
0.8 - 0.9 Very high #01568b
0.9 - 1.0 Very high #00316b

ACI

Value Class Colour
0.0 - 0.1 Very low #00403F
0.1 - 0.2 Very low #005651
0.2 - 0.3 Low #006D64
0.3 - 0.4 Low #008476
0.4 - 0.5 Moderate #009B89
0.5 - 0.6 Moderate #19B09E
0.6 - 0.7 High #4CC2B6
0.7 - 0.8 High #7FD5CE
0.8 - 0.9 Very high #B2E7E6
0.9 - 1.0 Very high #E5FAFE

The interactive mock-up shows the map legends for SHI, WSI and ACI maps. This mock-up also shows the information included in Tooltips.

This interactive maps shows calculations of CW at Alcaldia level. The budget values come from the following formula

Budget Formula
Budget (pesos) CW_sqm * 18000

CW colour scheme

The breaks for the CW maps are created with the natural break or "jenks" algorithm. The table shows the breaks and corresponding colour from lower (1) t higher (10)

Break Colour
1 #EAEBB2
2 #D6D996
3 #C3C87B
4 #B0B760
5 #9CA645
6 #889334
7 #727F2E
8 #5D6A28
9 #475522
10 #32411C

The 10 breaks in the previous table have the following values for ALCALDIAS (pesos) and COLONIAS (sqm) - (this requires testing to highlight Colonias that have an impact from CW across budgets, particularly for the smallest tiers)

ALCALDIA - Value (pesos) COLONIA - Value (sqm) Colour
0 - 72000 0 - 286 #EAEBB2
72000 - 426384000 286 - 918 #D6D996
426384000 - 1038780000 918 - 1822 #C3C87B
1038780000 - 1726308000 1822 - 3134 #B0B760
1726308000 - 2561544000 3134 - 4986 #9CA645
2561544000 - 3516336000 4986 - 7960 #889334
3516336000 - 4961268000 7960 - 12620 #727F2E
4961268000 - 6366888000 12620 - 20796 #5D6A28
6366888000 - 9068724000 20796 - 41446 #475522
9068724000 - 10000000000 41446 - 50000 #32411C

Files

The files containing the data are detailed below

Name Description Download URL
colonias_all_nc.geojson 2785 features with 142 fields and geometry type Polygon. This file doesn't have a class descriptor for indices (nc- no class) https://raw.githubusercontent.com/npalomin/shi_dataset_cdmx/master/colonias_all_nc.geojson
colonias_all_wc.geojson 2785 features with 232 fields and geometry type Polygon (90 additional fields with 'class' variable). This file has a class descriptor for indices (wc- with class) https://raw.githubusercontent.com/npalomin/shi_dataset_cdmx/master/colonias_all_wc.geojson
alcaldias.geojson 23 features and 25 fields and geometry type MultiPolygon https://raw.githubusercontent.com/npalomin/shi_dataset_cdmx/main/alcaldias.geojson
cdmx.geojson 1 feature showing administrative boundary of Mexico City https://raw.githubusercontent.com/npalomin/shi_dataset_cdmx/main/cdmx.geojson

Benefits variables

The impacts of the CW is shown as a series of benefits variables (on a side summary panel). These can be calculated from the CW_sqm and CW_perc variables according to the following table.

Benefit Formula
Population impacted CW_perc * pop
Homes impacted CW_sqm / 2
Water filtered yearly (lt) CW_sqm * 18000
Rain filtered yearly (lt) CW_sqm * 6000
Cattail plants yearly CW_sqm * 3
Arum lilies yearly CW_sqm * 32
Maintenance jobs CW_sqm * 0.0625
Manufacture jobs CW_sqm * 0.0115

This interactive map shows the benefit variables for each Colonia in the corresponding tooltip

Weightings and scenario descriptions

WSI

Scenario Water Variation (WV) Water Scarcity (WS) Water Exploitation (WE) Water Pollution (WP)
w1_stakeholder scenario 0.15 0.27 0.39 0.19
w2_environmental scenario 0.17 0.5 0.14 0.19
w3_social scenario 0.13 0.55 0.23 0.09

ACI

Scenario Natural Capacity (NC) Physical Capacity (PC) Human Capacity (HC) Economic Capacity (EC)
w1_stakeholder scenario 0.26 0.17 0.31 0.16
w2_environmental scenario 0.4 0.41 0.1 0.09
w3_social scenario 0.08 0.12 0.39 0.41

Scenario descriptions

Scenario Description
w1_stakeholder scenario derived from surveys with different authorities of the CDMX that are experts in related topics, including authorities from the Secretaría de Protección Civil, Fondo para la Comunicación y Educación Ambiental, Isla Urbana and Loreto y Peña Ecological Park. 
w2_environmental scenario environmental scientist who believes that water scarcity is the most important factor of water stress and that the natural and physical capacities of an area are essential for it to be able to face climate change. 
w3_social scenario expert who believes that equal access to water is fundamental for water security and that improving social aspects related to economic and human resource capacities is key to facing climate change.

NA values

Occasionally some variables show NA values. This occurs when it was not possible to compute the value due to missing data or when there is no constructed wetland built.

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