Extreme Rainfall vs Dam Safety: A Study on Dam Failures in India

Dam failures pose significant risks to life, property, and nature. Overtopping is the most frequent cause of dam failure, typically triggered by extreme rainfall events. The increasing frequency and magnitudes of such events, driven by climate change, further amplify these risks. This study investigates the effect of extreme rainfall patterns on 20 Dam Failure (DF) cases in India. Daily rainfall data are obtained from the India Meteorological Department, Pune, for 120 years and divided into four 30-year periods, i.e., ‘Epoch’ (Epoch-1: 1901–1930, Epoch-2: 1931–1960, Epoch-3: 1961–1990, Epoch-4: 1991–2020). The location-specisfic rainfall data is computed using the Inverse Distance Weighted interpolation method. The dates of DFs are sourced from the Central Water Commission, State Water Resources Departments, and other literature.First, the 5-day Accumulated Rainfall (ACR5) prior to the date of DF is computed, and compared with the ACR5 of other years prior to DF during the same dates. Interestingly, none of the value exceeds the ACR5 of DF year in most of the locations. It denotes that these dams failed due to the accumulated effect of consecutive heavy rainfall events, which were not anticipated by the respective dam authority to prepare for safeguarding the dam through suitable operations.Second, the trends in the rainfall distribution over each epoch are analyzed by computing the normal rainfall (30-year averaged annual rainfall). The severity of ACR5 with respect to normal rainfall (respective epoch in which DF occurred) is examined. It is noticed that the proportion of ACR5 with that of normal rainfall varied between 30%-90%. This means a huge magnitude of rainfall occurred in just 5 days. Therefore, it is indicated that the ACR5 played a crucial role in the failure of most of the dams considered in this study.Third, the study also introduced the Efficiency Factor (EF), defined as the ratio of maximum daily rainfall to Probable Maximum Precipitation (PMP). The value of EF above 0.85 poses a severe threat to dams and could result in DF. The vital conclusion from this study is that the dam owners will be notified at least 5 days prior to the dam failure, which is sufficient to take suitable measures for safe reservoir operations. The major limitation of this study is that the date of DF is not known for existing dam locations. However, the advanced weather forecasting models are providing reliable information for 5 to 7-day rainfall estimates, which will enable us to know the critical ACR5. Moreover, the systematic analysis offers a data-driven approach to improve dam safety protocols and enhance resilience against extreme rainfall events. The findings are particularly relevant for professionals in dam engineering, supporting informed decision-making in dam design, operation, and management.