Anatomy of a Catastrophe: Reconstructing the 1936 Rock Fall and Tsunami Event in Lake Lovatnet, Western Norway

Abstract

Rock falls and landslides plunging into lakes or small reservoirs can result in tsunamis with extreme wave run-ups. The occurrence of these natural hazards in populated areas have encouraged a recent sharp increase of studies that aim to mitigate their impact on human lives and assess infrastructure lost. This paper amalgamates in a novel fashion and at an unprecedented detail in situ historic measurements, geological data and numerical modeling of a rock fall event and associated tsunami wave that occurred in Lake Lovatnet (western Norway) in September 1936. Historical records report an event that released ca. 1 million m3 of rocks and debris from Ramnefjellet Mountain at an altitude of 800 m above Lake Lovatnet. The fragmented material plunged into the lake, causing a tsunami that reached a maximum run-up of 74 m and killed 74 people. In fact, the settlements of Bødal and Nesdal were wiped out as a result of the catastrophic wave. Sediments resulting from the 1936 rock fall and associated tsunami were identified in the subsurface of Lake Lovatnet by shallow geophysical investigations and were retrieved using gravity coring equipment. A set of high resolution physical and geochemical measurements were carried out on the cores with the aim of reproducing a highly detailed reconstruction of this catastrophic event in order to better understand and learn about the processes involved. The cores were retrieved in the northwestern sub-basin of the lake and its chronology was constrained by 210Pb and radiocarbon dating. A specially tailored physically based mathematical model was applied to better understand the tsunami event. Integration of the geophysical record, the sedimentological data and numerical modeling provide a comprehensive background to better understand the effects of such event in a deep fjord-like lacustrine basin and to generate information for better mitigation of similar events elsewhere.