Anthropogenic pollutants and biomarkers for the identification of 2011 Tohoku-oki tsunami deposits (Japan)

<p>Organic geochemistry is commonly used in environmental studies. In tsunami research, however, its application is in its infancy and rarely used. Tsunami deposits may also be able to be characterized by organic-geochemical parameters as tsunami transports not only particulate sedimentary material from marine to terrestrial areas (and vice versa), but also associated organic material. Recently, more attention has been given to the usage of natural organic substances (biomarkers) for tsunami identification. We present results of biomarkers and anthropogenic markers detected in deposits of the 2011 Tohoku-oki tsunami on the Sendai Plain, Japan (Bellanova et al., 2020). As the tsunami inundated the coastal lowland up to 4.85 km inland, sediments from various sources were eroded, transported and deposited across the area. This led to the distribution of biomarkers from different sources across the Sendai Plain creating a unique geochemical signature in the tsunami deposits. The tsunami also caused destruction along the Sendai coastline, leading to the release of large quantities of environmental pollutants (e.g., fossil fuels, tarmac, pesticides, plastics, etc.) that were distributed across the inundated area. Corresponding anthropogenic markers, represented by three main compound groups (polycyclic aromatic hydrocarbons, pesticides, and halogenated compounds), were preserved in tsunami deposits (at least until 2013, prior to land clearing). Organic compounds from the tsunami deposits (Tohoku-oki tsunami) were extracted from tsunami sediment and compared with the organic signature of unaffected pre-tsunami samples using gas chromatography-mass spectrometry (GS/MS) based analyses. Their concentrations differed significantly from the pre- and post-tsunami background contamination levels. Organic proxy concentrations differ also for sandy and muddy tsunami deposits due to various factors (e.g., preservation, dilution, microbial alteration).</p><p>As tsunami research advanced over the last decades so did the methods used to gain more and more information on the past events. Developing new methods for the identification and characterization of tsunami deposits for recent, historic or paleo events is crucial. Every piece of additional information we gain from event deposits leads us a step further to a better understanding of mechanisms acting during a tsunami. This will help to improve countermeasures and relief efforts. Anthropogenic markers and biomarkers, because of their high source specificity and good preservation potential, have the potential to be a valuable proxy in future studies of tsunami deposits and provide information about sediment sources and transport pathways.</p>

Factors Affecting the Installation Potential of Ground Source Heat Pump Systems: A Comparative Study for the Sendai Plain and Aizu Basin, Japan

Evaluating the installation potential of ground source heat pump (GSHP) systems based on the hydrogeological condition of an area is important for the installation and sustainable use of the system. This work is the first to have compared the distributions of heat exchange rate in the Sendai Plain and Aizu Basin (Japan) in terms of topographical and hydrogeological conditions. A regional groundwater flow and heat transport model was constructed for the Sendai Plain. Suitability assessment was conducted for an identical closed-loop system by preparing the distribution maps of heat exchange rate for space heating for the plain and basin. For both locations, the upstream area showed a higher heat exchange rate than the downstream area. Multiple regression analysis was conducted using heat exchange rate as a response variable. Average groundwater flow velocity and average subsurface temperature were considered as explanatory variables. The heat exchange rate for the plain, whose Péclet number ranged from 3.5 × 10−3–7.3 × 10−2, was affected by groundwater flow velocity and subsurface temperature. The exchange rate for the basin, whose Péclet number ranged from 8.5 × 10−2–5.8 × 10−1, was affected by groundwater flow velocity. Inland basins are likely to be more suitable for GSHP system installation utilizing groundwater flow than coastal plains in terms of inclination of slope. This study showed that multiple regression analysis can reveal factors affecting the heat exchange rate as well as the degree to which they affect it.

Probabilistic Tsunami Loss Estimation Methodology: Stochastic Earthquake Scenario Approach

This study develops a probabilistic tsunami loss estimation methodology for enhancing community resilience against tsunami disasters. The method is based on novel stochastic earthquake source modeling and state-of-the-art tsunami fragility modeling. It facilitates the quantitative evaluation of tsunami loss for coastal community by accounting for uncertainties of earthquake occurrence and rupture characteristics. A case study is set up to illustrate an application of the developed method to the Sendai Plain area by focusing on possible tsunami events in the Tohoku region of Japan. The quantitative tsunami hazard as well as risk assessment results serve as effective means to make decisions regarding tsunami disaster risk reduction.

QUANTIFYING NUMERICAL MODEL ACCURACY AND VARIABILITY

On March 11, 2011 the Tohoku tsunami event caused the death of thousands of people and generated billions of dollars in damages. Following this and previous tsunami events, there has been an effort to improve tsunami risk mitigation for coastal communities. Currently, numerical models are being used in a state-of-the-art methodology to estimate tsunami risk from near and far field sources. Model predictions are essential for the development of Tsunami Hazard Assessments (THA). By better understanding model bias and uncertainties and if possible minimizing them, a more accurate and reliable THA will result. In this study we compare runup height, inundation lines and flow velocity field measurements between GeoClaw and the Method Of Splitting Tsunami (MOST) predictions in the Sendai plain. Runup elevation and average inundation distance was in general over predicted by the models. However, both models agree relatively well with each other when predicting maximum sea surface elevation and maximum flow velocities. Model predictions show that the flow velocity increases as the tsunami wave front reaches the shoreline and makes its way inland for a couple of kilometers, contrary to what it is generally assumed. The tsunami models used in this study show much more variability when predicting flow velocity than predicting runup elevations and inundation lines. The results provided in this study will help understand the uncertainties in model predictions and locate possible sources of errors within a model.