The Power of Citizen Seismology: Science and Social Impacts

The U.S. Geological Survey (USGS) “Did You Feel It?” (DYFI) system is an automatic method for rapidly collecting macroseismic intensity (MI) data from internet users’ shaking and damage reports and for generating intensity maps immediately following felt earthquakes. DYFI has been in operation for nearly two decades (1999–2019) in the United States, and for nearly 15 years globally. During that period, the amount of data collected is astounding: Over 5 million individual DYFI intensity reports—spanning all magnitude and distance ranges—have been amassed and archived. DYFI allows for macroseismic data collection at rates and quantities never before imagined, and thus high-quality MI maps can be made almost immediately, and with more complete coverage at higher resolution than in the past. DYFI also allows for valuable positive interactions of the citizenry with a Federal science agency. In essence, the widespread adoption of DYFI – along with ShakeMap—has facilitated the general acceptance of the very concept of shaking intensity, fundamentally improving our agency’s ability to communicate both hazard and risk to the population. DYFI effectively confirms the importance of reporting and inculcating the public’s understanding of intensity – in addition to magnitude – for a proper perspective of earthquake risk-related decision-making. Furthermore, the vast amount of DYFI data allows for data-rich analyses of otherwise intractable seismological, sociological, and earthquake impact studies, such as quantifying the shaking due to induced earthquakes, human response and risk perception, relating recorded shaking metrics to macroseismic effects, and the attenuation of intensity with magnitude and distance. Naturally, web-based data collection also poses challenges. After two decades of experience acquiring data with the DYFI system, we address some of these challenges by documenting refinements to our algorithmic and operational procedures that have evolved over that time. Lastly, we outline new opportune research and development directions for our DYFI approach to citizen seismology.

Nepal, located above the convergent India-Eurasia plate boundary, has repeatedly experienced devastating earthquakes. During the 2015 magnitude 7.8 Gorkha earthquake, an often-reported experience was that people were not aware of the threatening seismic hazard and had an insufficient level of preparedness. An important source of the problem is that earthquake-related topics are not part of the school curriculum. Earthquake education reaching a broad group of the population early in their lives is therefore strongly needed. We established an initiative in Nepal to introduce seismology in schools, with a focus on education and citizen seismology. We have prepared educational materials adapted to the Nepali school system, which we distributed and also share on our program’s website: http://seismoschoolnp.org. In selected schools, we also installed a low-cost seismometer to record seismicity and to allow learning-by-doing classroom activities. Our approach was very well received and we hope it will help make earthquake-safe communities across Nepal. The seismic sensor which we installed in schools is a Raspberry Shake 1D (RS1D), this was selected based on its performance in laboratory tests and suitability for the field conditions. At a test site in Switzerland we were able to record magnitude 1.0 events up to 50 km distance with a RS1D. In Nepal, 22 such seismometers installed in schools create the Nepal School Seismology Network providing online data openly. The seismometer in each school allows students to be informed of earthquakes, visualize the respective waveforms, and estimate the distance and magnitude of the event. For significant local and regional events, we provide record sections and network instrumental intensity maps on our program’s website. In 6 months of network operation, more than 194 local and teleseismic earthquakes of M ≥ 4 have been recorded. From a local and a global catalog, complemented with our own visual identifications, we have provided an earthquake wave detectability graph in distance and magnitude domain. Based on our observations, we have calibrated a new magnitude equation for Nepal, related to the epicentral distance D [km] and to the observed peak vertical ground velocity PGV_V [μm/s]. The calibration is done to best fit local catalog magnitudes, and yields the following equation: M = 1.05 × log₁₀(PGV_V) + 1.08 × log₁₀(D) + 0.75.