India has the third greatest number of large dams in the world with more than 5,700 either existing or under construction. These dams provide important services for the population of India, including flood mitigation, water supply, fisheries, recreation, and more. But as the of dams age, there is an increased need for maintenance, upgrades, and inspections to help reduce risks to downstream populations and economic sectors. These challenges are not unique to India – globally, aging dams require upgrades and rehabilitation. In the United States, an estimated $23 billion is required to rehabilitate high-hazard dams, most of which is for the larger collection of non-Federal dams.
In support of the proposed World Bank-funded Second Dam Rehabilitation and Improvement Project (DRIP-2) in India, RTI utilized components of our analytical Rapid Risk Suite to assess components of a portion of India's dam portfolio and develop initial metrics of potential risk at a portfolio scale. This project was unique for several reasons including the scale, process, and application of these rapid risk tools that demonstrates the scalability for larger portfolio assessments within a risk-informed paradigm.
Why Rapid Risk Assessment?
Full quantitative risk-assessment (QRA) investigations require detailed site-specific data, healthy budgets, and sufficient time for completion. More simplified analyses, such as Indexing methods, are affordable and rapid but do not provide measures of risk, only relative risk scores. There's a need for a solution between these extremes that uses quantitative approaches for initial estimation of risk. RTI's Rapid Risk Suite is a collection of tools scalable to portfolios for efficient and affordable risk estimation.
For this study, RTI utilized the following tools to assess potential risk at 100 dams:
- RTI WxGen: Precipitation frequency estimation for each watershed using global data sources
- RTI QFreq: Multiple hydrologic model generation and inflow frequency estimation
- RTI Breach: 2D breach modeling for flood wave estimation
- RTI Impacts: Consequence estimation including estimates of populations at risk
Although different components of the probabilistic risk analysis process are available throughout the industry, this study was unique in bringing them together into a single probabilistic rapid risk assessment process.
Hydrologic models account for the runoff, streamflow, and reservoir routing upstream of a dam given some precipitation event. These models were run not just with different precipitation storm depths, but with collections of precipitation templates, used during repeated sampling to scale various storm spatial and temporal patterns. Starting soil moisture conditions were sampled using estimates from satellite remotely sensed products. Upstream reservoir levels were sampled from seasonal guide curves. Despite its many components, the entire process was considered 'rapid', as we were able to complete 100 dams in a few weeks’ time, while including many of the components used in full-scale quantitative risk analyses that can typically take months to years for a single dam.