This study targeted 13 geological regions in four areas that experienced landslides due to heavy rains between 2014 and 2019. LiDAR topography data before and after the disasters were used to estimate the differences in the elevation values of the source areas of the landslides so that the landslide volumes could be estimated. Next, the α and γ parameters of an equation used to estimate the landslide volume were calculated and modeled for each region. The parameters were incorporated into equation (1), which is the functional form of Simonett’s equation (Simonett, 1967), to estimate the landslide volume. The aim of this study was to improve the formula itself and clarify its compatibility with actual measured values. When the relationship between the α value, which corresponds to the intercept of V = α A^γ , and values obtained for standardized cumulative rainfall, we found that the R² value was the highest for the 48-hour cumulative rainfall at 0.518. There was a strong negative correlation between the γ and α values, with an R² value of 0.844; the γ value can be estimated from the α value. After examining the factors that statistically affect the α value, the standardized 48-hour cumulative rainfall (R² =0.518) and slope (R² =0.309) were selected. Since both of these two factors could be approximated by linear equations, we modeled the α value using a basic general linear model (GLM) and obtained α” =0.686－1.747 x₁+0.013 x₂” (R² =0.53, p=0.02, x₁ is the standardized 48-hour cumulative rainfall, and x₂ is the slope). We improved the formula for estimating the landslide volume using three factors: cumulative landslide area and rainfall, slope. When we investigated the applicability of the improved estimation formula and found that the calculated values were concentrated in a fairly close range on the 1 : 1 line for all geology types. When the actual cumulative values of landslide volume, they was 101.7 % for granites and 96.0 % for rhyolites. It is therefore considered that the improved estimation formula could be applied to the geological features included in the model dataset (such as granites and rhyolites).

On July 1, 15, and 25, 2024 in the Katsuyamadani River, which flows through the southwestern foothills of Mt. Ibuki in eastern Shiga Prefecture, debris flows occurred three times in a row, causing damage by sediment flooding houses, prefectural roads, and municipal roads in the downstream Ibuki district. These debris flows occurred despite low rainfall that had not occurred in previous decades in the Katusyamadani River. In order to clarify the cause of the repeated occurrence of debris flows due to such not very strong rainfall, I examined the mechanism of the occurrence of these debris flows from field surveys and interpretation of satellite images at different measurement times. As a result, soil erosion occurred due to the impoverished vegetation grazed by Sika Deer (Cervus Nippon) on the southern slope of Mt. Ibuki, and the amount of surface flow and runoff sediment increased, flowing into the depression in the Middle Katuyamadani River Basin through the gullies. It was clarified that the overflowing water from this depression flowed into the Lower Katsuyamadani River, and the increase in the flow rate of the Lower Katsuyamadani River caused erosion of the valley bed and the valley bank, resulting in debris flows. Until now, there have been no reports of debris flows caused by deer eating damage in Japan, causing damage to houses downstream, and this is considered to be the first case in Japan.

To discuss disaster countermeasures caused by the inflow of sediment and water from tributaries into the mainstream due to large-scale landslides and debris flows, a quantitative prediction of the impact of water and sediment inflow from tributaries on the flow conditions of the main river is required. In this study, a flume experiment was conducted assuming a 45°confluence angle between the main river and the tributary. Through comparison with the results of previous experimental studies the impact of different confluence angles on the flow conditions of the main river due to water and sediment inflow from the tributary was evaluated and discussed. We have found that the planar distribution position of the boundary between the main river and tributary flows exhibited a positive correlation with the flow rate ratio at each time point, with a higher coefficient of determination when riverbed changes were minimal at the 45° confluence angle.