Free Online Tool Lets You Assess Dam Projects Around the World
By Claire Salisbury
For example, high quantities of greenhouse gases are released from submerged soil and rotting vegetation, and from turbines and spillways, especially in the tropics, meaning that dam projects are often not the environmentally-friendly option they seem. But assessing the various impacts of dams, alongside their economic viability, is a complex task, and the decision-making process behind a dam is rarely transparent.
Now, a new tool has been developed with the aim of making this kind of assessment more open and available to all. The free HydroCalculator tool, developed by the NGO Conservation Strategy Fund (CSF), is accessible online and is easy to use. The tool's developers, CSF founder John Reid and CSF researcher Thaís Vilela, hope it will allow "a broad group of citizens, researchers and policymakers, to foresee and monitor the economic and environmental consequences of hydropower projects."
The HydroCalculator's end output offers a clear presentation of the net economic value of the dam under consideration, with and without the cost of greenhouse gas emissions factored in; the number of years required before the project generates a profit; and the number of years until net carbon emissions become negative.
Thousand Island Lake in China, the result of a dam built in the 1950s on the Xin'an River.Bryan Ong / Flickr
Reid was inspired to develop the HydroCalculator tool after carrying out numerous cost-benefit analyses of dams, and finding that many such projects "threatened ecosystems and didn't deliver much economic benefit," he said. "I wanted to make it easy for other people to do this sort of analysis.
"For too long, environmentalists had tacitly accepted that it was none of their business to weigh in on the economic merits of big construction projects. That's nonsense," he continued. "The tool is part of a bigger effort to make nature's advocates real players in large public investment decisions."
Vilela said the number of projects which aren't financially feasible "is surprising," and that "transparency in the decision-making process is our main goal."
To use the tool, accessed via CSF's website, the user inputs key project data, including the size of the area to be flooded, the vegetation types that will be submerged, projected costs, dam generating capacity and the price at which the electricity will be sold.
Default values for several factors, such as vegetation carbon content, the wholesale price of energy, and the energy discount rate, are available online if specific details are unknown. All of the dam project analyses that have previously been carried out can also be consulted on the website.
A graphic depiction of major factors influencing greenhouse gas emissions from hydroelectric dams.Vilela and Reid (2017) under a CC BY 4.0 license
Reid and Vilela validated the tool against in-depth, peer-reviewed studies of Amazonian dam impacts, and found that their simplified methodology produced comparable results. Although the precise results varied, the relative costs and benefits of different existing Amazon dams, and their economic feasibility, was similar. The inclusion of the cost of greenhouse gas emissions had both positive and negative effects on the economic feasibility of different dams, they found, but did not change the overall feasibility for any of them.
Recent scientific studies have shown how important hydropower dams are as a source of methane, something largely overlooked in dam impact assessments. Methane is far more potent than CO2, but it also degrades more quickly: over 100 years, methane has an effect more than 30 times stronger than CO2, but this increases to 86 times stronger when considered over a period of 20 years. This shorter timeframe is what really counts, scientists say, given the urgency with which CO2 emissions need to be curbed to prevent catastrophic global warming.
As a result, the incorporation of accurate greenhouse gas emissions estimates was key to the creation of the HyroCalculator. That "required installing a global map of carbon density, figuring out the emissions from each country's electricity mix, and finding a formula for reservoir-based emissions that can work for any project," said Reid. "The difficulty with emissions points to the central challenge with any web-based analytical tool: precision versus practicality."
The Tucuruí dam spillway on Brazil's Tocantins River. International Rivers / Flickr
In the name of practicality and ease of use, the Hydrocalculator does make some minor concessions to accuracy. Emissions from turbines and spillways, for example, were excluded from this version of the tool, because there's greater uncertainty around these sources, said Vilela. As a result, the calculator's emission estimates will be conservative, for now, but CSF is planning to add these additional sources into future versions.
The HydroCalculator has been well tested. It has been used by CSF for some time, and other organizations, including a development bank and International Rivers, an environmental NGO, have also employed the tool in their research.
Sarah Bardeen, of International Rivers, said their staff has "found the HydroCalculator to be useful in assessing a [dam's] economic viability when we have limited information about a project."
"The HydroCalculator shows that hydropower is far from carbon-neutral, and helps users calculate a ballpark estimate of greenhouse gas emissions from a dam's reservoir," Bardeen added. "This is important, because it puts information about reservoir emissions into the hands of affected communities, who are often shut out of the opaque planning processes around hydropower projects."
The Santo Antônio dam on the Madeira River in Brazil, part of the Madeira Hydroelectric Complex.Brazil's Growth Acceleration Program / Flickr
Both Bardeen and the CSF team emphasize that the tool should not be used in isolation, but as part of a broader assessment process. "Hydropower is a notoriously complex and risky power source to build, and there really isn't a tool that can capture and show all the environmental, social and economic consequences of building a dam," Bardeen explained.
Assessing the tradeoffs of hydropower development should be done through "deep analysis of primary data and listening to the people who would be affected," agreed Reid. "The HydroCalculator just lets you take a first step along that path."
Major environmental risks of dams—such as the direct and indirect impacts to biodiversity, effects on aquatic and terrestrial wildlife connectivity, and reduction in a waterway's nutrient and sediment flow—along with the consequences to local communities, must all be carefully weighed against the benefits of a proposed dam. Though, at present, none of these risks are tallied by the Hydrocalculator. Still, the tool goes a long way toward empowering dam project-impacted communities, the experts said.
Belo Monte dam under construction in 2015.Pascalg622 under a CC BY 3.0 license
In the Amazon, where mega-dam projects are slated for many of the basin's rivers, scientists fear that harm from dams will be irreversible. There, Indigenous people and traditional river communities are fighting to protect their sacred lands and livelihoods. And untold numbers of species still not described by science are at risk.
"Communities protecting their lands and waters need all the help they can get to evaluate the impacts of proposed hydropower projects. In the Amazonian context, this tool is another arrow in their quiver," Bardeen said. "But bad hydropower projects go forward for many reasons—and in Brazil, corruption, graft and authoritarianism have the tendency to steamroll reason and science."
The global debate around hydropower "is likely to intensify as pressure grows to meet expanding electricity demand and rein in greenhouse gas emissions," Reid and Vilela concluded in their paper. Tools such as the HydroCalculator can help provide the knowledge needed to navigate that debate.
Reposted with permission from our media associate Mongabay.
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By Eric Tate and Christopher Emrich
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Mapping Social Vulnerability<p>Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6237.8402002" target="_blank"><em>Cutter et al.</em></a> . Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.</p>
Fig. 1. (a) Social vulnerability across the United States at the census tract scale is mapped here following the Social Vulnerability Index (SoVI). Red and pink hues indicate high social vulnerability. (b) This bivariate map depicts social vulnerability (blue hues) and annualized per capita hazard losses (pink hues) for U.S. counties from 2010 to 2019.<p>Many current indexes in the United States and abroad are direct or conceptual offshoots of SoVI, which has been widely replicated [e.g., <a href="https://link.springer.com/article/10.1007/s13753-016-0090-9" target="_blank"><em>de Loyola Hummell et al.</em></a>, 2016]. The U.S. Centers for Disease Control and Prevention (CDC) <a href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html" target="_blank">has also developed</a> a commonly used social vulnerability index intended to help local officials identify communities that may need support before, during, and after disasters.</p><p>The first modeling and mapping efforts, starting around the mid-2000s, largely focused on describing spatial distributions of social vulnerability at varying geographic scales. Over time, research in this area came to emphasize spatial comparisons between social vulnerability and physical hazards [<a href="https://doi.org/10.1007/s11069-009-9376-1" target="_blank"><em>Wood et al.</em></a>, 2010], modeling population dynamics following disasters [<a href="https://link.springer.com/article/10.1007%2Fs11111-008-0072-y" target="_blank" rel="noopener noreferrer"><em>Myers et al.</em></a>, 2008], and quantifying the robustness of social vulnerability measures [<a href="https://doi.org/10.1007/s11069-012-0152-2" target="_blank" rel="noopener noreferrer"><em>Tate</em></a>, 2012].</p><p>More recent work is beginning to dissolve barriers between social vulnerability and environmental justice scholarship [<a href="https://doi.org/10.2105/AJPH.2018.304846" target="_blank" rel="noopener noreferrer"><em>Chakraborty et al.</em></a>, 2019], which has traditionally focused on root causes of exposure to pollution hazards. Another prominent new research direction involves deeper interrogation of social vulnerability drivers in specific hazard contexts and disaster phases (e.g., before, during, after). Such work has revealed that interactions among drivers are important, but existing case studies are ill suited to guiding development of new indicators [<a href="https://doi.org/10.1016/j.ijdrr.2015.09.013" target="_blank" rel="noopener noreferrer"><em>Rufat et al.</em></a>, 2015].</p><p>Advances in geostatistical analyses have enabled researchers to characterize interactions more accurately among social vulnerability and hazard outcomes. Figure 1b depicts social vulnerability and annualized per capita hazard losses for U.S. counties from 2010 to 2019, facilitating visualization of the spatial coincidence of pre‑event susceptibilities and hazard impacts. Places ranked high in both dimensions may be priority locations for management interventions. Further, such analysis provides invaluable comparisons between places as well as information summarizing state and regional conditions.</p><p>In Figure 2, we take the analysis of interactions a step further, dividing counties into two categories: those experiencing annual per capita losses above or below the national average from 2010 to 2019. The differences among individual race, ethnicity, and poverty variables between the two county groups are small. But expressing race together with poverty (poverty attenuated by race) produces quite different results: Counties with high hazard losses have higher percentages of both impoverished Black populations and impoverished white populations than counties with low hazard losses. These county differences are most pronounced for impoverished Black populations.</p>
Fig. 2. Differences in population percentages between counties experiencing annual per capita losses above or below the national average from 2010 to 2019 for individual and compound social vulnerability indicators (race and poverty).<p>Our current work focuses on social vulnerability to floods using geostatistical modeling and mapping. The research directions are twofold. The first is to develop hazard-specific indicators of social vulnerability to aid in mitigation planning [<a href="https://doi.org/10.1007/s11069-020-04470-2" target="_blank" rel="noopener noreferrer"><em>Tate et al.</em></a>, 2021]. Because natural hazards differ in their innate characteristics (e.g., rate of onset, spatial extent), causal processes (e.g., urbanization, meteorology), and programmatic responses by government, manifestations of social vulnerability vary across hazards.</p><p>The second is to assess the degree to which socially vulnerable populations benefit from the leading disaster recovery programs [<a href="https://doi.org/10.1080/17477891.2019.1675578" target="_blank" rel="noopener noreferrer"><em>Emrich et al.</em></a>, 2020], such as the Federal Emergency Management Agency's (FEMA) <a href="https://www.fema.gov/individual-disaster-assistance" target="_blank" rel="noopener noreferrer">Individual Assistance</a> program and the U.S. Department of Housing and Urban Development's Community Development Block Grant (CDBG) <a href="https://www.hudexchange.info/programs/cdbg-dr/" target="_blank" rel="noopener noreferrer">Disaster Recovery</a> program. Both research directions posit social vulnerability indicators as potential measures of social equity.</p>
Social Vulnerability as a Measure of Equity<p>Given their focus on social marginalization and economic barriers, social vulnerability indicators are attracting growing scientific interest as measures of inequity resulting from disasters. Indeed, social vulnerability and inequity are related concepts. Social vulnerability research explores the differential susceptibilities and capacities of disaster-affected populations, whereas social equity analyses tend to focus on population disparities in the allocation of resources for hazard mitigation and disaster recovery. Interventions with an equity focus emphasize full and equal resource access for all people with unmet disaster needs.</p><p>Yet newer studies of inequity in disaster programs have documented troubling disparities in income, race, and home ownership among those who <a href="https://eos.org/articles/equity-concerns-raised-in-federal-flood-property-buyouts" target="_blank">participate in flood buyout programs</a>, are <a href="https://www.eenews.net/stories/1063477407" target="_blank" rel="noopener noreferrer">eligible for postdisaster loans</a>, receive short-term recovery assistance [<a href="https://doi.org/10.1016/j.ijdrr.2020.102010" target="_blank" rel="noopener noreferrer"><em>Drakes et al.</em></a>, 2021], and have <a href="https://www.texastribune.org/2020/08/25/texas-natural-disasters--mental-health/" target="_blank" rel="noopener noreferrer">access to mental health services</a>. For example, a recent analysis of federal flood buyouts found racial privilege to be infused at multiple program stages and geographic scales, resulting in resources that disproportionately benefit whiter and more urban counties and neighborhoods [<a href="https://doi.org/10.1177/2378023120905439" target="_blank" rel="noopener noreferrer"><em>Elliott et al.</em></a>, 2020].</p><p>Investments in disaster risk reduction are largely prioritized on the basis of hazard modeling, historical impacts, and economic risk. Social equity, meanwhile, has been far less integrated into the considerations of public agencies for hazard and disaster management. But this situation may be beginning to shift. Following the adage of "what gets measured gets managed," social equity metrics are increasingly being inserted into disaster management.</p><p>At the national level, FEMA has <a href="https://www.fema.gov/news-release/20200220/fema-releases-affordability-framework-national-flood-insurance-program" target="_blank">developed options</a> to increase the affordability of flood insurance [Federal Emergency Management Agency, 2018]. At the subnational scale, Puerto Rico has integrated social vulnerability into its CDBG Mitigation Action Plan, expanding its considerations of risk beyond only economic factors. At the local level, Harris County, Texas, has begun using social vulnerability indicators alongside traditional measures of flood risk to introduce equity into the prioritization of flood mitigation projects [<a href="https://www.hcfcd.org/Portals/62/Resilience/Bond-Program/Prioritization-Framework/final_prioritization-framework-report_20190827.pdf?ver=2019-09-19-092535-743" target="_blank" rel="noopener noreferrer"><em>Harris County Flood Control District</em></a>, 2019].</p><p>Unfortunately, many existing measures of disaster equity fall short. They may be unidimensional, using single indicators such as income in places where underlying vulnerability processes suggest that a multidimensional measure like racialized poverty (Figure 2) would be more valid. And criteria presumed to be objective and neutral for determining resource allocation, such as economic loss and cost-benefit ratios, prioritize asset value over social equity. For example, following the <a href="http://www.cedar-rapids.org/discover_cedar_rapids/flood_of_2008/2008_flood_facts.php" target="_blank" rel="noopener noreferrer">2008 flooding</a> in Cedar Rapids, Iowa, cost-benefit criteria supported new flood protections for the city's central business district on the east side of the Cedar River but not for vulnerable populations and workforce housing on the west side.</p><p>Furthermore, many equity measures are aspatial or ahistorical, even though the roots of marginalization may lie in systemic and spatially explicit processes that originated long ago like redlining and urban renewal. More research is thus needed to understand which measures are most suitable for which social equity analyses.</p>
Challenges for Disaster Equity Analysis<p>Across studies that quantify, map, and analyze social vulnerability to natural hazards, modelers have faced recurrent measurement challenges, many of which also apply in measuring disaster equity (Table 1). The first is clearly establishing the purpose of an equity analysis by defining characteristics such as the end user and intended use, the type of hazard, and the disaster stage (i.e., mitigation, response, or recovery). Analyses using generalized indicators like the CDC Social Vulnerability Index may be appropriate for identifying broad areas of concern, whereas more detailed analyses are ideal for high-stakes decisions about budget allocations and project prioritization.</p>
By Jessica Corbett
Sen. Bernie Sanders on Tuesday was the lone progressive to vote against Tom Vilsack reprising his role as secretary of agriculture, citing concerns that progressive advocacy groups have been raising since even before President Joe Biden officially nominated the former Obama administration appointee.