This report assessed the climate impacts on the hydropower plants in 13 Latin American countries between 2020 and 2100, comparing the results with the values of the baseline period from 1970 to 2000. The baseline period was selected reflecting the maximum availability of historical climate records.

The assessment focuses on 13 Latin American countries with the largest installed capacity of hydropower. The selected countries consist of four groups reflecting their climatic characteristics: Central America and Mexico (Mexico, Costa Rica, Panama and Guatemala), Andean region (Colombia, Ecuador and Peru), Southern South America (Argentina and Chile) and the rest of South America (Brazil, Venezuela, Paraguay, and Uruguay).

The total hydropower installed capacity in these 13 countries is over 193 000 MW, which accounts for 98% of total installed capacity in Latin America (IHA, 2020). Brazil takes up over 55% of the total hydropower installed capacity, followed by Venezuela, Mexico, Colombia and Argentina.

Around 90% of selected hydropower plants are impoundment facilities with reservoirs. Around 10% of selected plants are mostly diversion (run-of-river) facilities with a small fraction of pumped hydropower storage. Each hydropower plant assessed in the study has a different level of capacity factors during the baseline period, depending on its location, size, type and other conditions. To present an integrated analysis of climate impacts on different hydropower plants, the study uses only relative values (% of changes compared to the baseline).

High-resolution (15’’x 15’’) global monthly discharge maps are developed by combining low-resolution (0.5˚x 0.5˚) monthly runoff data from each ensemble of General Circulation Models (GCM), Global Hydrological Models (GHM) and Representative Concentration Pathways (RCP) with high-resolution (15’’x 15’’) area accumulation and drainage direction maps available from the HydroSHEDS project (ISIMIP, Database; Gernaat et al., 2017; Lehner et al., 2008), and a low-resolution (0.5˚ x 0.5˚) map of monthly runoff.

The discharge maps were used to extract the design discharge and design load factors per hydropower plant (Gernaat, 2019). By ordering the discharge of a selected hydropower plant from the lowest to the highest month of discharge, a flow duration curve was generated. The value of the fourth-highest discharge month is called the design discharge and determines turbine capacity. The capacity factor is, by design, 100% for the four wettest months and less than 100% for the remaining eight drier months.

To analyse climate impacts on Latin American hydropower, this report examined as many combinations of models as possible to enhance the reliability of results. It compared 60 different ensembles of five GCMs, four GHMs, and three RCPs to minimise the probability of misleading outcome and distortion by outliers. Since outliers are often difficult to avoid due to the complexity of the climate system and the different assumptions within each model, this report compared and aggregated outcomes from various GCMs, GHMs and RCPs, and presented average annual and monthly capacity factors. Further studies using downscaled GCMs to regional or local levels and then combining GHMs could advance the accuracy of results (Maceira, M.E.P. et al., 2018).

General Circulation Models (GCM)

GFDL-ESM2M was developed by scientists at the Geophysical Fluid Dynamics Laboratory to make projections of the behaviour of the atmosphere, the oceans and climate, using super-computer and data storage resources. The Laboratory has contributed to each assessment of the IPCC since 1990.

HadGEM2 stands for the Hadley Centre Global Environment Model version 2. The HadGEM2 family of models includes a coupled atmosphere-ocean configuration, with or without a vertical extension in the atmosphere to include a well-resolved stratosphere, and an Earth-System configuration which includes dynamic vegetation, ocean biology and atmospheric chemistry. Members of the HadGEM2 family were used in the IPCC Fifth Assessment Report.

IPSL-CM5 model is a full earth system model and the last version of the Institut Pierre Simon Laplace (IPSL) that is a consortium of nine research laboratories on climate and the global environment. Based on a physical atmosphere-land-ocean-sea ice model, it also includes a representation of the carbon cycle, the stratospheric chemistry and the tropospheric chemistry with aerosols. The IPSL-CM5 model contributed to the modelling for the IPCC Fifth Assessment Report.

MIROC-ESM was developed by the Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (The University of Tokyo), and National Institute for Environmental Studies.

NorESM1 is the first version of the Norwegian earth system model. It has been applied with medium spatial resolution to provide results for the modelling for IPCC Fifth Assessment Report. It provides complementary results to the evaluation of possible anthropogenic climate change.

Global Hydrological Models (GHM)

H08 is a grid-cell based global hydrological model developed by the National Institute for Environmental Studies of Japan. It consists of six sub-models, namely land surface hydrology, river routing, reservoir operation, crop growth, environmental flow and water abstraction.

LPJmL is a dynamic global vegetation model with managed land use and river routing. It is managed by the Potsdam Institute for Climate Impact Research. It is designed to simulate vegetation composition and distribution as well as stocks and land-atmosphere exchange flows of carbon and water, for both natural and agricultural ecosystems.

MPI-HM is a global hydrological model developed by the Max Planck Institute to investigate hydrological research questions mostly related to high resolution river routing. While hydrological processes are implemented in similar complexity as in full land surface models, the MPI-HM does not compute any energy-related fluxes.

PCR-GLOBWB is a grid-based global hydrology and water resources model developed at Utrecht University. The computational grid covers all continents except Greenland and Antarctica. It simulates moisture storage in two vertically stacked upper soil layers, as well as the water exchange between the soil, the atmosphere and the underlying groundwater reservoir. The exchange with the atmosphere comprises precipitation, evaporation from soils, open water, snow and soils and plant transpiration, while the model also simulates snow accumulation, snowmelt and glacier melt. 

Representative Concentration Pathways (RCP)

The IPCC Fifth Assessment Report defines RCPs as scenarios that include time series of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover (Moss et al., 2008). The word representative signifies that each RCP provides only one of many possible scenarios that leads to the specific radiative forcing characteristics. In the IPCC Fifth Assessment Report, four RCPs are presented: RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5. The RCPs show various representative GHG concentration trajectories and the impact of each level of GHG concentration on the future climate.

In the forthcoming IPCC Sixth Assessment Report will use Shared Socioeconomic Pathways (SSPs) which show how societal choices will affect GHG emissions and how the climate goals of the Paris Agreement could be met. SSPs are expected to fill the missing piece of socioeconomic narratives in RCPs, looking at five different ways in which the world might evolve in the absence of climate policy and how different levels of climate change mitigation could be achieved when the mitigation targets of RCPs are combined with the SSPs. Although this report decided to use RCPs instead of SSPs, given that still more data resources are available for RCPs rather than SSPs across various GCMs and GHMs. This impact assessment could be updated soon reflecting the new trajectories of SSPs.

This report developed three scenarios based on three different RCPs. Each of them leads to a different global average temperature outcome: Below 2°C, Below 3°C and Above 4°C, respectively. By comparing these three scenarios, the report aims to present how greenhouse gas (GHG) concentrations are likely to affect hydropower generation in Latin America.

The Below 2°C scenario is based on the projections of the RCP 2.6 that assumes a radiative forcing value of around 2.6 W/m2 in the year 2100. Under the Below 2°C scenario the rise in global annual mean temperature stays below 2°C by 2100 compared to pre-industrial times (1850‑1900). For the period 2080 to 2100, the global annual mean temperature increases by 1.6 (±0.4) °C above the level of 1850‑1900. The Below 2°C scenario assumes an early peak in global GHG emission trends followed by a drastic decline.

The Below 3°C scenario follows the trajectory of the RCP 4.5 which assumes a radiative forcing value of around 4.5 W/m² in the year 2100. The Below 3°C scenario is associated with a rise by 2.4 (±0.5) °C in global annual mean temperature for the period 2080 to 2100 compared to the pre-industrial level. The Below 3°C scenario assumes a peak in global GHG emission trends by mid-century and a subsequent decline.

The Above 4°C scenario is based on the high-emission trajectory, RCP 8.5, which assumes the absence of additional effort to mitigate GHG emissions. The Above 4°C scenario is associated with a radiative forcing value of around 8.5 W/m² in the year 2100 and a rise by 4.3 (±0.7) °C in global annual mean temperature for the period 2080 to 2100 compared to the pre-industrial level. Under the Above 4°C scenario, global GHG emission does not reach its peak before 2100.

Alarcón, A. (2020), ‘Blog: Hydro modernisation in South America requires better financing and regulation’, International Hydropower Association, https://www.hydropower.org/blog/blog-hydro-modernisation-in-south-america-requires-better-financing-and-regulation/.

Andritz Hydro GmbH, “Bring Back to Life”, https://www.andritz.com/hydro-en/hydronews/hn32/callahuanca-peru.

Andritz Hydro GmbH (2019), New Life for Hydro Assets, Andritz Group, Vienna, https://www.andritz.com/resource/blob/31840/5cab6294379100be61fdd75aa590769f/hydro-service-rehab-en-data.pdf.

Argonne National Laboratory (2012), Resilience: Theory and Applications, Argonne National Laboratory, Oak Ridge, https://publications.anl.gov/anlpubs/2012/02/72218.pdf.

Bellfield, H. (2015), Water, Energy and Food Security Nexus in Latin America and the Caribbean, Global Canopy Programme, https://iwa-network.org/wp-content/uploads/2017/03/The-Water-Energy-Food-Nexus-in-LAC-April-2015-lower-res.pdf.

Berga, L. (2016), The Role of Hydropower in Climate Change Mitigation and Adaptation: A Review, Engineering Volume 2, Issue 3, https://doi.org/10.1016/J.ENG.2016.03.004.

Business Wire, (2020), “Emerson to Modernise Hydroelectric Power Complex Ensuring Renewable Energy Supply in Latin America”, https://www.businesswire.com/news/home/20200922005199/en/Emerson-to-Modernize-Hydroelectric-Power-Complex-Ensuring-Renewable-Energy-Supply-in-Latin-America (accessed on October 14th 2020).

Centre for Southern Hemisphere Oceans Research (CSHOR) (2019), Understanding ENSO in a Changing Climate, ENSO Science Symposium; Hobart, Tasmania, Australia, 29–31 January 2019, https://eos.org/meeting-reports/understanding-enso-in-a-changing-climate.

CONELSUR (2018), “Reconstrucción de la subestación Callahuanca 220/60 kV fortalecerá el sistema de transmisión eléctrico del país”, https://www.conelsur.com/reconstruccion-de-subestacion-callahuanca-220-60-kv-fortalecera-el-sistema-de-transmision-electrico-del-pais/.

Cook, A., Watkins, A. B., Trewin, B., and C. Ganter (2016), El Niño is over, but has left its mark across the world, The Conversation France, https://theconversation.com/el-nino-is-over-but-has-left-its-mark-across-the-world-59993/.

Cook, B. I., Mankin, J. S., Marvel, K., Williams, A. P., Smerdon, J. E., and K. J. Anchukaitis (2020), Twenty‐First Century Drought Projections in the CMIP6 Forcing Scenarios, Earth’s Future, Vol. 8, Issue 6, https://doi.org/10.1029/2019EF001461/.

Cristina F, (2015), El Niño Phenomenon in Latin America: Economic impacts, https://www.bbva.com/en/climate-impacts-of-el-nino-phenomenon-in-latin-america/.

Department for International Development (DFID) (2008), Water storage and hydropower: supporting growth, resilience and low carbon development: a DFID evidence-into-action paper, London, https://reliefweb.int/sites/reliefweb.int/files/resources/40F3E613CFE321F1492576FC0023DE59-water-strge-hydropow-supp-grwth.pdf.

DFID (2011), Defining Disaster Resilience: A DFID Approach Paper, https://www.gov.uk/government/publications/defining-disaster-resilience-a-dfid-approach-paper.

European Commission (2013), A Europe-South America Network for Climate Change Assessment and Impact Studies, European Commission, https://cordis.europa.eu/project/id/1454/.

European Commission (2019), A Europe-South America Network for Climate Change Assessment and Impact Studies in La Plata Basin, European Commission CORDIS EU research results, https://cordis.europa.eu/project/id/212492/.

Fasullo, J., Otto-Bliesner, B. and Stevenson, S., (2018), ENSO’s changing influence on temperature, precipitation, and wildfire in a warming climate, Geophysical Research Letters, Vol. 45, pp. 9216–9225, https://doi.org/10.1029/2018GL079022.

Geophysical Fluid Dynamics Laboratory (GFDL) (2013), GFDL-ESM2M, general circulation model, GFDL, Princeton, https://www.gfdl.noaa.gov/.

Gernaat, D.E.H.J. (2019), The role of renewable energy in long-term energy and climate scenarios, Utrecht University, https://dspace.library.uu.nl/handle/1874/381146.

Gernaat, D.E.H.J., et al. (2017), High-resolution assessment of global technical and economic hydropower potential, Nature Energy, Vol. 2, pp. 821–828.

Global Environment Facility (GEF) (2017), Introduction to Green Finance, GEF, http://documents1.worldbank.org/curated/en/405891487108066678/text/112831-WP-PUBLIC-Introduction-to-Green-Finance.txt/.

Gnos, P. (2018), Bring Back to Life: Callahuanca, Peru, Hydro News, Andritz Group, Issue 32 Vienna, https://www.andritz.com/hydro-en/hydronews/hn32/callahuanca-peru/.

Godoy, E. (2020), Mexico’s Plan to Upgrade Hydropower Plants Faces Hurdles, IPSNews, http://www.ipsnews.net/2020/03/mexicos-plan-upgrade-hydropower-plants-faces-hurdles/.

Goldberg, J. and O. Espeseth Lier (2011), Rehabilitation of Hydropower: An Introduction to Economic and Technical Issues, Water papers, World Bank, Washington D.C., http://hdl.handle.net/10986/17251/.

Government of Chile (2015), Plan Nacional de Adaptación al Cambio Climático https://www4.unfccc.int/sites/NAPC/Documents/Parties/Chile%20NAP%20including%20sectoral%20plans%20Spanish.pdf. 

Government of Colombia (2016), Plan Nacional de Adaptación al Cambio Climático (PNACC), https://www4.unfccc.int/sites/NAPC/Documents/Parties/Colombia%20NAP%20Spanish.pdf.

Government of Guatemala (Plan de Acción Nacional de Cambio Climático, https://www4.unfccc.int/sites/NAPC/Documents/Parties/Guatemala%20NAP%20small.pdf.

Hausfather, Z. (2018), Explainer: How ‘Shared Socioeconomic Pathways’ explore future climate change, Carbon Brief, https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future-climate-change/.

Hydroreview (2018), Mexico’s new energy plan places strong emphasis on hydroelectric generation, https://www.hydroreview.com/2018/12/12/mexico-s-new-energy-plan-places-strong-emphasis-on-hydroelectric-generation/#gref

IDB Invest, Ituango Hydroelectric Project, Inter-American Investment Corporation, https://www.idbinvest.org/en/projects/ituango-hydroelectric-project/.

International Energy Agency (IEA) (2020a), Countries and Regions, https://www.iea.org/countries/.

IEA (2020b), World Energy Outlook 2020, IEA, Paris, https://www.iea.org/reports/world-energy-outlook-2020/.

IEA (2020c), Power Systems in Transition, IEA, Paris, https://www.iea.org/reports/power-systems-in-transition.

IEA (2020d), Renewables 2020, IEA, Paris, https://www.iea.org/reports/renewables-2020.

IEA (2016), Energy, Climate Change and Environment: 2016 Insights, https://www.iea.org/reports/energy-climatechange-and-environment-2016-insights.

IEA Hydro (2019), Flexible hydropower providing value to renewable energy integration, https://www.ieahydro.org/media/51145259/IEAHydroTCP_AnnexIX_White%20Paper_Oct2019.pdf.

IHA (International Hydropower Association) (2019a), Hydropower Sector Climate Resilience Guide, https://www.hydropower.org/publications/hydropower-sector-climateresilience-guide.

IHA (2019b), Hydropower Status Report 2019, https://archive.hydropower.org/status2019.

IHA (2020a), Hydropower Status Report 2020, https://www.hydropower.org/publications/2020-hydropower-status-report.

IHA (2020b), Blog: Hydro modernisation in South America requires better financing and regulation, https://www.hydropower.org/blog/blog-hydro-modernisation-in-south-america-requires-better-financing-and-regulation.

Institut Pierre Simon Laplace (IPSL) (2010), IPSL-CM5, full earth system model, IPSL Climate Modelling Centre, https://cmc.ipsl.fr/ipsl-climate-models/.

Inter-American Development Bank (IDB) (2011), Brazil refurbishes two hydroelectric power plants with IDB funding, IDB News, https://www.iadb.org/en/news/news-releases/2011-07-28/brazil-refurbishes-two-hydroelectric-power-plants%2C9481.html/.

IDB (2016), “Executive Summary”, Vulnerability to Climate Change of Hydroelectric Production Systems in Central America and their Adaptation Options, IDB, https://publications.iadb.org/publications/english/document/Vulnerability-to-Climate-Change-of-Hydroelectric-Production-Systems-in-Central-America-and-their-Adaptation-Options-Executive-Summary.pdf.

IDB (2018), “IDB supports program in Paraguay to modernize the Acaray hydroelectric power plant”, IDB News Release, https://www.iadb.org/en/news/idb-supports-program-paraguay-modernize-acaray-hydroelectric-power-plant.

IDB and IHA (2020), Blog: Hydropower for the 21st century in Latin America and the Caribbean, https://www.hydropower.org/blog/blog-hydropower-for-the-21st-century-in-latin-america-and-the-caribbean.

Intergovernmental Panel on Climate Change (IPCC) (2011), “Hydropower”, IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation, Cambridge University Press, Cambridge, and New York, https://www.ipcc.ch/site/assets/uploads/2018/03/Chapter-5-Hydropower-1.pdf.

IPCC (2012), “Changes in climate extremes and their impacts on the natural physical environment”, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, Cambridge University Press, Cambridge, and New York, pp. 109-230, https://www.ipcc.ch/site/assets/uploads/2018/03/SREX-Chap3_FINAL-1.pdf.

IPCC (2013), Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge and New York, https://www.ipcc.ch/report/ar5/wg1/.

IPCC (2014), Climate Change 2014: Impacts, Adaptation, and Vulnerability, Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, and New York, https://www.ipcc.ch/report/ar5/wg2/.

IPCC (2015), AR5 Synthesis Report: Climate Change 2014, https://www.ipcc.ch/report/ar5/syr/.

Iversen, T., Bentsen, M., Bethke, I., Debernard, J. B., Kirkevåg, A., Seland, Ø., Drange, H., Kristjansson, J. E., Medhaug, I., Sand, M. and I. A. Seierstad (2013), NorESM1, earth system model, Geoscientific Model Development, https://gmd.copernicus.org/articles/6/389/2013/gmd-6-389-2013.pdf.

Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (The University of Tokyo), and National Institute for Environmental Studies (2011), MIROC-ESM, earth system model, Geoscientific Model Development, Vol. 4, pp. 845-872, https://www.jamstec.go.jp/es-repository/meta-bin/mt-pdetail.cgi?tlang=0&cd=00004783/.

Lehner, B., K. Verdin and A. Jarvis (2008), New global hydrography derived from spaceborne elevation data, Eos, Vol. 89, No. 10, pp. 93–94. https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2008EO100001.

Lucena, A.F.P. et al. (2018), Interactions between climate change mitigation and adaptation: The case of hydropower in Brazil, Energy, Volume 164, https://doi.org/10.1016/j.energy.2018.09.005.

Lucena, A.F.P. et al. (2009), The vulnerability of renewable energy to climate change in Brazil, Energy Policy, Volume 37, Issue 3, https://doi.org/10.1016/j.enpol.2008.10.029.

Maceira, M.E.P. et al. (2018), Análise dos Efeitos das Mudanças Climáticas no Setor Elétrico Brasileiro em Termos de Mitigação e Adaptação, XIV Symposium of Specialists in Electric Operational and Expansion Planning, http://www.cepel.br/pt_br/produtos/mudclima-avaliacao-e-efeito-das-mudancas-climaticas-no-setor-eletrico.htm.

Maceira, M. E. P., Melo, A. C. G. and Zimmermann, M. P. (2016), "Application of stochastic programming and probabilistic analyses as key parameters for real decision-making regarding implementing or not energy rationing - a case study for the Brazilian hydrothermal interconnected system," 2016 Power Systems Computation Conference (PSCC), Genoa.

Max Planck Institute for Meteorology, MPI-HM, global hydrological model, Max Planck Institute, https://mpimet.mpg.de/en/science/the-land-in-the-earth-system/working-groups/former-group-terrestrial-hydrology/hd-model/.

Met Office, HadGEM2, general circulation model, Met Office Hadley Technical Centre, Exeter https://www.metoffice.gov.uk/research/approach/modelling-systems/unified-model/climate-models/hadgem2/.

Ministry of Environment, Brazil (2016) National Adaptation Plan to Climate Change. https://www4.unfccc.int/sites/NAPC/Documents/Parties/Brazil%20NAP%20English.pdf

Moss, R. et al. (2008), Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts, and Response Strategies, Intergovernmental Panel on Climate Change, https://www.researchgate.net/publication/236487152_Towards_New_Scenarios_for_Analysis_of_Emissions_Climate_Change_Impacts_and_Response_Strategies_Technical_Summary.

National Institute for Environmental Studies of Japan (2013), H08, grid-cell based global hydrological model, National Institute for Environmental Studies of Japan, https://h08.nies.go.jp/.

Organisation for Economic Co-operation and Development (OECD) (2018), Climate-Resilient Infrastructure, http://www.oecd.org/environment/cc/policy-perspectives-climateresilient-infrastructure.pdf.

Organización Latinoamericana de Energía (OLADE) (2020), Vulnerability to climate change and adaptation measures of the hydroelectric systems of the Andean countries, Olade, Quito, http://www.olade.org/en/vulnerability-to-climate-change-and-adaptation-measures-of-the-hydroelectric-systems-of-the-andean-countries/.

Pelto M.S., North Cascade Glacier Climate Project, https://glaciers.nichols.edu/glacier-runoff-hydropower/.

Government of Peru (2015), Nationally Determined Contribution (NDC), https://www4.unfccc.int/sites/ndcstaging/PublishedDocuments/Peru%20First/iNDC%20Per%C3%BA%20english.pdf.

Potsdam Institute for Climate Impact Research, LPJmL, dynamic global vegetation model, Potsdam Institute for Climate Impact Research, https://www.pik-potsdam.de/en/institute/departments/activities/biosphere-water-modelling/lpjml/.

PowerTechnology (2018), Why drought could limit hydropower’s role in the energy mix, PowerTechnology, https://www.power-technology.com/features/drought-limit-hydropowers-role-energy-mix/.

Rabatel, A. et al. (2013), “Current state of glaciers in the tropical Andes: a multi-century perspective on glacier evolution and climate change”, The Cryosphere, 7, https://doi.org/10.5194/tc-7-81-2013, 2013.

Rodríguez-de-Francisco et al. (2019), “Payment for Ecosystem Services and the Water-Energy-Food Nexus: Securing Resource Flows for the Affluent?” Water, https://www.mdpi.com/2073-4441/11/6/1143/pdf.

The Hydro Group of Clarion Energy (2018), Mexico’s new energy plan places strong emphasis on hydroelectric generation, Hydro Review, https://www.hydroreview.com/2018/12/12/mexico-s-new-energy-plan-places-strong-emphasis-on-hydroelectric-generation/#gref/.

Treistman, F., Maceira, M.E.P., Penna, D.D.J. et al. (2020), Synthetic scenario generation of monthly streamflows conditioned to the El Niño–Southern Oscillation: application to operation planning of hydrothermal systems. Stoch Environ Res Risk Assess 34, https://doi.org/10.1007/s00477-019-01763-2.

USAID (2017), Climate Risk profile Colombia, USAID Climate Change Integration Support, https://www.climatelinks.org/resources/climate-risk-profile-colombia.

US EIA (US Energy Information Administration) (2019), Hydropower explained, https://www.eia.gov/.

Utrecht University (2018), PCR-CLOBWB, grid-based global hydrology and water resources model, Earth Surface Hydrology group at Utrecht University, http://www.globalhydrology.nl/models/pcr-globwb-2-0/.

WBCSD (2014), Building a Resilient Power Sector. https://www.wbcsd.org/Programs/Climate-and-Energy/Climate/Resources/Building-a-Resilient-Power-Sector.

Weather World 2020 (WW2010) (2010), Atmospheric Consequences of El Niño, Department of Atmospheric Sciences at the University of Illinois at Urbana-Champaign, Champaign, http://ww2010.atmos.uiuc.edu/%28Gh%29/guides/mtr/eln/atms.rxml/.

Wheeler, B. (2012), “Hydro Powers Latin America”, https://www.renewableenergyworld.com/2012/06/21/hydro-powers-latin-america/#gref (accessed on October 14th 2020).

World Meteorological Organization (WMO), Climate Rationale for GCF Project Design, https://unfccc.int/sites/default/files/resource/0.9WMOCli.

World Bank (2011), “Rehabilitation of hydropower – an introduction to economic and technical issues”, Water Papers, http://documents1.worldbank.org/curated/en/518271468336607781/pdf/717280WP0Box370power0for0publishing.pdf.

World Bank (2016), European Commission and World Bank Sign Agreement on Catastrophe Risk Insurance for Caribbean and Central American countries, The World Bank Group, Washington D.C., https://www.worldbank.org/en/news/press-release/2016/04/15/catastrophe-risk-insurance-for-caribbean-and-central-american-countries/.

World Bank (2019), Lifelines: The Resilient Infrastructure Opportunity, http://hdl.handle.net/10986/31805.

World Bank (2020a), Latin America Climate Data Projections, Climate Change Knowledge Portal, https://climateknowledgeportal.worldbank.org/region/latin-america/climate-data-projections (accessed on September 27th 2020).

World Bank (2020b), Brazil Climate Data Projections, Climate Change Knowledge Portal, https://climateknowledgeportal.worldbank.org/country/brazil/climate-data-projections (accessed on September 24th 2020).

WWAP (United Nations World Water Assessment Programme) (2014), The United Nations World Water Development Report 2014: Water and Energy, UNESCO, Paris, http://www.unesco.org/new/en/natural-sciences/environment/water/wwap/wwdr/2014-water-and-energy/.

World Meteorological Organization (WMO) (2015), El Niño Expected to Strengthen Further: High Impacts, Unprecedented Preparation, https://public.wmo.int/en/media/press-release/el-ni%C3%B1o-expected-strengthen-further-high-impacts-unprecedented-preparation.