The tool calculates the net present value (NPV - definition and explanation) on a hydroelectric dam investment based on costs and benefits over a 50-year period. Many dams last longer than that, but their NPV is not significantly influenced by cash flows in the distant future. The tool assumes that dams begin operation in the first year after construction is complete. Annual operation and maintenance costs are calculated as 4% of construction costs and there are no significant reinvestment costs included once the dam is operational. Future costs and benefits are discounted at an economic discount rate entered by users.

In this first release of the model, financial and economic prices are assumed to be the same. In other words the financial to economic conversion factors are assumed to be equal to 1. This simplification may bias results substantially if either the prices of inputs or the price of energy is distorted. Future releases will have more precise conversion factors. User suggestions on reliable and country-specific sources for conversion factors are welcome.

The tool calculates carbon dioxide emissions based on global average carbon content for different vegetation types. Carbon dioxide equivalent is calculated using the Biome Carbon Loss model, which considers methane and carbon dioxide emissions from the reservoir's surface. It does not include emissions of methane "gasified" when methane hits turbines and downstream structures. These emissions can be 50% or more of the total but are omitted in the HydroCalculator due to their extreme variability. The model calculates net emissions, equal to the dam's emissions minus greenhouse gases from alternative sources of an equivalent amount of electricity. These sources represent the short-term mix of sources in each of the countries for which we have information. Net emissions can be negative for dams with large powerplants relative to their reservoir size and/or sparse vegetation covering the flooded land. Negative net emissions are also more likely where the alternative source of electricity is a plant burning fossil fuels.

The people displaced and land area flooded per MW is a simple ratio of the user-provided values. More detailed accounting of environmental and social costs is beyond the scope of the model.

Read an abstract of a speech about environmental impacts of hydroelectric dams in the Amazon.
Read an article titled Unlearned Lessons for Hydroelectric Development in Amazonia.

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HydroCalculator Input Methodology

As noted, the HydroCalculator calculates net greenhouse gas emissions, equal to the dam's emissions minus greenhouse gases from alternative sources of an equivalent amount of electricity (sources of electricity other than the dam in question). Central to this calculation is a parameter describing the magnitude of greenhouse gas emissions produced for every MWh of electricity generated from these alternative sources (tCO2e/MWh). This statistic varies by country and over time, as electricity generation mixes change, altering the relative environmental effects of adding hydropower.

General Procedure For Finding a Country's tCO2e/MWh Value:

-Find the country’s electricity generation mix for the year in question, the magnitude of each source’s annual production in MWh/year.
-Find the emission factors for the country’s electricity generation sources in TCO2e/MWh. If country-specific emissions factors are not available, use regional emission factors.
-Multiply the previous two numbers to obtain TCO2e/year (the year in question). Sum the values obtained for each production source.
-Divide total TCO2e/year (just found) by country’s total electric production for that year to get the weighted average of the country’s electricity production emissions in TCO2/MWh.

General Sources Used in Calculating This Statistic:

• IEA Energy Statistics Database

• CIA Economic Statistics Database

• UN Energy Statistics Database

• Emissions Factors (Coal, Oil, and Natural Gas)

• Emissions Factor (Geothermal)

Bases for Individual Countries' Current/Projected tCO2e/MWh In the Coming Decades:

AFRICA

Burundi:
• Current energy mix was found from CIA economic statistics database; future hydropower projections based on historical hydro production data from the UN Energy Statistics Database.
• Because of lack of data on the specific composition of thermal production, an emissions factor found by averaging coal, oil, and gas values was applied to the known total thermal production value in order to get TCO2e/year from thermal.
• Used continental Africa emissions factor values.

Democratic Republic of Congo:
• Current energy mix was found from IEA energy statistics database; future hydropower projections based on historical hydro production data from the UN Energy Statistics Database.
• Assuming hydro production will grow at constant rate until projected value is reached in 2030.
• Used DRC-specific emissions factor for oil and gas.

Kenya:
• Current energy mix was found from IEA energy statistics database; future projections based on Kenya’s electricity generation goals for 2030 (Glopolis: Renewable Energy Sources in Kenya-pdf).
• Goals include values for total fossil fuels, coal, hydro, wind, geothermal, and ‘other sources’ and were listed in terms of targeted MW of installed capacity.
• To get from targeted installed MW to likely actual MWh of production: multiplied MW by 8760 (8760 hours in one year), then again by percent utilization of installed capacity for that individual source. Percent utilization of installed capacity values were found using historical production data from the UN Energy Statistics Database.
• Made the assumption that total thermal for 2030 does not include natural gas (only coal and oil), since Kenya does not currently generate electricity from natural gas or explicitly name it as a targeted source.
• Used Kenya-specific oil emissions factor, general geothermal emissions factor.

Rwanda:
• Current energy mix was found from CIA economic statistics database; future projections based on Rwanda’s targeted MW of installed capacity for coal, hydro, geothermal, and solar electricity production. Assuming these targets will be achieved by 2030.
• Because of lack of data on the specific composition of thermal production, an averaged thermal emissions factor was applied to the known total thermal production value in order to get TCO2e/year from thermal.
• To get from targeted installed MW to likely actual MWh of production: multiplied MW by 8760 (8760 hours in one year), then again by percent utilization of installed capacity for that individual source. Percent utilization of installed capacity values were found using historical production data from the UN Energy Statistics Database.
• Used continental Africa and general geothermal emissions factor values.

Sudan:
• Current energy mix was found from IEA energy statistics database; future thermal projections based on historical thermal production data from the UN Energy Statistics Database.
• Assuming thermal production will grow at constant rate until projected value is reached in 2030. -Assuming Sudan’s thermal production will continue to consist entirely of generation from oil.
• Used Sudan-specific emissions factor for oil.

Tanzania:
• Current energy mix was found from IEA energy statistics database; future hydropower projections based on historical hydro production data from the UN Energy Statistics Database.
• Used Tanzania-specific emissions factor values.

Uganda:
• Current energy mix was found from IEA energy statistics database; future projections based on Ugandan government’s electricity generation goals (http://www.rea.or.ug/userfiles/RENEWABLE%20ENERGY%20POLIC9-11-07.pdf).
• Targeted figures for 2017, via 2012, were listed in MW of installed capacity. To get from targeted installed MW to likely actual MWh of production: multiplied MW by 8760 (8760 hours in one year), then again by percent utilization of installed capacity for that individual source. Percent utilization of installed capacity values were found using historical production data from the UN Energy Statistics Database
• Used continental Africa and general geothermal emissions factor values.

LATIN AMERICA

Argentina
• Current energy mix was found from IEA energy statistics database.
• Used Argentina-specific emissions factors.

Chile
• Current energy mix was found from IEA energy statistics database.
• Used Latin America emissions factors.

Costa Rica
• Current energy mix was found from IEA energy statistics database.
• Used Costa Rica-specific emissions factors for oil, Latin America emissions factors for coal and gas, and general emissions factor for geothermal.

Guatemala
• Current energy mix was found from IEA energy statistics database.
• Used Guatemala-specific emissions factors.

Honduras
• Current energy mix was found from IEA energy statistics database; future projections (through 2015) based Honduras government electricity generation goals (ENEE Expansion Plan/World Bank 2007, via Wikipedia: Honduras Electricity Sector).
• 2015 targets were listed in MW of planned installed capacity. To get from targeted installed MW to likely actual MWh of production: multiplied MW by 8760 (8760 hours in one year), then again by percent utilization of installed capacity for that individual source. Percent utilization of installed capacity values were found using historical production data from the UN Energy Statistics Database.
• Used Honduras-specific (oil) emissions factor.

Mexico
• Current energy mix was found from IEA energy statistics database; projections through 2025 based on Mexican government electricity generation goals (http://www.ccap.org/docs/fck/file/Mexico's%20Renewable%20Energy%20Program%2010-11-11.pdf).
• 2025 targets were listed in MW of planned installed capacity. To get from targeted installed MW to likely actual MWh of production: multiplied MW by 8760 (8760 hours in one year), then again by percent utilization of installed capacity for that individual source. Percent utilization of installed capacity values were found using historical production data from the UN Energy Statistics Database.
• Used Mexico-specific emissions factors for thermal production and general geothermal emissions factor.

Nicaragua
• Current energy mix was found from IEA energy statistics database; projections through 2017 based on Nicaragua Government’s planned addition of renewable electricity generation installed capacity (http://delsurnewsonline.com/1677/nicaragua-energy-plan-2010-2017/).
• 2017 additions were listed in MW of planned additional installed capacity (hydro, geothermal, and wind). To get from targeted installed MW to likely actual MWh of production: multiplied MW by 8760 (8760 hours in one year), then again by percent utilization of installed capacity for that individual source. Percent utilization of installed capacity values were found using historical production data from the UN Energy Statistics Database.
• Assumed unnamed sources would remain constant through 2017.
• Used Nicaragua-specific (oil) emissions factor and general geothermal emissions factor.

Panama
• Current energy mix was found from IEA energy statistics database.
• Used Panama-specific (oil) emissions factor.

ASIA

Bhutan
• Current energy mix was found using electricity generating source percentages (Overview of Energy Policies of Bhutan-pdf) and total production data from CIA economic statistics database.
• Used continental Asia emissions factors.

Cambodia
• Current energy mix was found form IEA energy statistics database; projections through 2020 based on Cambodia government electricity generation expansion plans (http://cambodia.usembassy.gov/media2/pdf/cambodian_power_development_pla...).
• Assuming all electricity generation sources that are not named in expansion plan will remain constant through 2020 (that is, generation from coal, oil, biofuels, wind, geothermal, solar, and nuclear).
• 2015/2020 targets were listed in MW of planned installed capacity. To get from targeted installed MW to likely actual MWh of production: multiplied MW by 8760 (8760 hours in one year), then again by percent utilization of installed capacity for that individual source. Percent utilization of installed capacity values were found using historical production data from the UN Energy Statistics Database.
• Used Cambodia-specific (oil) emissions factor.

China
• Current energy mix was found from IEA energy statistics database.
• Used China-specific emissions factors for thermal production and general geothermal emissions factor.

India
• Current energy mix was found from IEA energy statistics database; projections through 2020 based on IEA report on India Electricity (India Electricity-pdf).
• Assuming constant growth from present to 2020.
• 1,800,000 MWh of planned ‘other renewables’ assumed to have emissions factors of zero.
• Used India-specific emissions factors.

Laos
• Current energy mix was found from CIA economy statistics database.
• Because of lack of data on the specific composition of thermal production, an averaged thermal emissions factor was applied to the known total thermal production value in order to get TCO2e/year from thermal.

Nepal
• Current energy mix was found from IEA energy statistics database.
• Used Nepal-specific (oil) emissions factor.

Pakistan
• Current energy mix was found from IEA energy statistics database; projections through 2030 based on Pakistan government 2030 energy mix goals (A New Energy Mix for Pakistan-ppt).
• Goals were presented in terms of target percentage of electricity generation from each source; paired those with forecasted total production for 2030 based on historical data of total electricity production from the UN Energy Statistics Database to get likely 2030 energy mix in MWh.
• Assumed constant growth from present through 2030.
• Assumed the noted ‘renewable’ electricity generation to have emissions factor of zero.
• Used Pakistan-specific emissions factors.

Thailand
• Current energy mix found from IEA energy statistics database.
• Used Thailand-specific emissions factors for thermal production and general geothermal emissions factor.

Vietnam
• Current energy mix was found from IEA energy statistics database; projections through 2030 based on Vietnam government energy development plan (http://www.mondaq.com/x/144632/Renewables/Vietnam+Power+Development+Plan...).
• Assumed constant growth from present through 2020 and from 2020 through 2030.
• 2020/2030 targets were presented in terms of MW of planned installed capacity. To get from targeted installed MW to likely actual MWh of production: multiplied MW by 8760 (8760 hours in one year), then again by percent utilization of installed capacity for that individual source. Percent utilization of installed capacity values were found using historical production data from the UN Energy Statistics Database.
• Used Vietnam-specific emissions factors.