# Development of a Practical Evaluation Method for Tsunami Debris and Its Accumulation
## 2 Practical Method for Evaluating Tsunami Debris Accumulation and Thickness
(**a**) An example showing the corrected positions of buildings after the removal of trees at the inundation boundary. (**b**) The corrected tsunami debris thickness distribution estimated from the difference between the DSM and DEM. Each figure from [PERSON] et al. [6]. calculated by multiplying \(DT\) by the area of the grid. If the debris thickness was less than 0.15 m (the detection accuracy of LiDAR), no debris accumulation was assumed. Each parameter was then normalized as follows: the normalized distance from the inundation boundary was defined as \(L_{*}=1-L_{\mathrm{R}}/L_{\mathrm{R0}}\); the inundation depth was defined as \(D_{*}=D/L_{\mathrm{R}}\); the normalized debris thickness was denoted by \(NDT=DT/\Sigma DT\) (where \(\Sigma DT\) is the total thickness of the debris in each area). Tsunami debris can accumulate on land, or it can be discharged into the sea. Therefore, the amount of woody debris from the tsunami that remained on land in each analysis area was estimated by comparing the volume of the buildings that had been washed away with the total accumulated debris volume. The volume of debris deposited was calculated by  
Figure 4: (**a**) Distribution of damage in the inundated area of Otsuchi area A. (**b**) A portion of the inundated area showing belt transects in relation to the tsunami inundation boundary. Each figure from [PERSON] et al. [6]. Figure 5: The definition sketch of \(SI\) evaluation. The presence or absence of buildings within a radius of 10 to 60 m, centered on an arbitrary point, is indexed within the range of 0 < \(SI\) < 2.25.  
taking into account the porosity of the debris height data. The estimated total volume of debris from destroyed or collapsed buildings was calculated as the total volume of the buildings that were washed away in the building area. On average, the proportion of the building debris produced by the tsunami that remained on the land, the residual rate, was about 50%, although it varied among the analysis areas (Table 1). The amount of debris remaining on the land depends on various factors, including tsunami size, land use, and topography. The determination of the residual rate should be evaluated in a future study. The probability of debris deposition, \(P_{\text{db}}\), was obtained by binarizing the deposition or non-deposition of debris in each belt transect and then compared with \(L^{\star}\) (Figure 6). In general, \(P_{\text{db}}\) tended to be larger closer to the inundation boundary (\(L\)\(\sim\) 1.0). Although this trend differed among the analysis areas, \(P_{\text{db}}\) never exceeded 0.5; when \(AS\) was less than 1, \(P_{\text{db}}\) increased slowly, but in some other areas, \(P_{\text{db}}\) was almost constant. Therefore, \(L\)- cannot fully explain \(P_{\text{db}}\). Moreover, \(P_{\text{db}}\) was sometimes higher at lower values of \(L\), possibly because residual foundations of washed away buildings prevented the deposition of debris. In addition to \(L\), \(AS\) and \(SI\) are candidate parameters to explain \(P_{\text{db}}\). The relationships between \(NDT\) and \(i_{\text{M}}\), \(L\), and \(D\), were examined using data from all analysis regions (Figure 7). \(NDT\) was higher when 80% \(<i_{\text{M}}<\) 100% and 0.0 \(<L\) \(<\) 0.4, and it was also higher when 25% \(<i_{\text{M}}<\) 75% and 0.4 \(<L\) \(<\) 0.8 (Figure 7a). Where \(i_{\text{M}}\) was relatively less, these higher \(NDT\) values were attributed to the accumulation of debris in residential areas. Because the analysis area is located along a \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Affected Area**} & **Total Volume of** & **Estimated Total** & **Residual Rate (\%)** \\  & **Tsunami Debris in the** & **Volume of Debris from** & **Residual Rate (\%)** \\  & **Inundation Area (m3)** & **Destroyed Buildings (m3)** & \\ \hline Yamada & 240,799 & 313,428 & 77 \\ Otsuchi & 263,278 & 546,547 & 48 \\ Kamaishi & 73,719 & 228,323 & 32 \\ \hline \hline \end{tabular}
\end{table}