Application of Soil Water Index to landslide prediction in snowy regions: sensitivity analysis in Japan and preliminary results from Tomsk, Russia

Abstract

Soil Water Index (SWI) represents the conceptual water stored in the soil and is calculated using a three-layer tank model with hourly precipitation. In Japan, landslide disasters are likely to occur when SWI in an event exceeds the maximum value of the past 10 years; however, snowmelt-driven landslide disasters have not been considered yet. Using the tank model that simultaneously calculates SWI and runoff, we implemented the snowfall-accumulation-snowmelt processes into the original SWI and applied the modified SWI to meteorological data in Tomsk, Russia, in spring 2010 when severe flood and landslide disasters had occurred. We conducted a sensitivity analysis of hourly precipitation in snowy region in Japan considering that meteorological data in Russia are available every 3 h. When we input the average of the three-hourly accumulated precipitation to calculate SWI, the result was almost identical to that of the observed hourly precipitation being given. We then estimated the hourly temperature by linearly interpolating the data every 3 h, and set the threshold of liquid/solid precipitation. The degree-hour method was employed to calculate the snowmelt. The modified SWI predicted the occurrence of snowmelt-driven landslide disasters in Japan when the calculated SWI exceeded the maximum value in the snowmelt season (March–May) for the past 10 years. When applied to meteorological data in Tomsk, the modified SWI and calculated runoff captured the timing of snowmelt-driven flood and landslide disasters in spring 2010. We demonstrated that by focusing on the maximum value of SWI in the snowmelt season for the past 10 years, we can predict snowmelt-driven landslide disasters.

An Analytical Study on Soil Water Index (SWI), Landslide Prediction and Other Related Factors Using XRAIN Data during the July 2018 Heavy Rain Disasters in Hiroshima, Japan

“…Although originally designed for river discharge analysis and warning systems, SWI calculation is also used for the case of soil water content in failure-prone slopes and consequent landslide disasters [7,14,16,28]. In Japan, the government uses SWI calculations along 60-min cumulative rainfall for a nationwide early-warning system for landslide disasters since March 2007.…”

“…The system uses Radial Basis Function Network methods to analyze past records of SWI values and occurrence or non-occurrence of landslides, determining the lowest limit of SWI, known as the critical line, above which landslide occurrence is considered likely, and thus evacuation is advised [14]. These values are distributed in a 1-km mesh all throughout the Japanese territory and are found on the JMA website [28]. The critical SWI value for the study area of this research, at the time of the July 2018 disasters, was 124 mm.…”

Aplicação do Tank Model como Ferramenta de Gestão na Bacia do Rio Perdizes – Cambará do Sul/RS

“…A aplicação de índices derivados do Tank Model como indicadores conceituais do armazenamento de água no solo já é amplamente utilizada no Japão para avaliar a predisposição de ocorrência de inundações ou deslizamentos. Matsuyama et al (2021) aplicaram 2 índices derivados do Tank (SWI e SWI-modificado) em uma bacia hidrográfica na Rússia para previsão de deslizamentos acarretados por neve, com bons resultados. Outros trabalhos também foram bemsucedidos na estimativa deslizamentos (Lin et al, 2020) e estabilidade de encostas (Matlan et al, 2018).…”

Relationship between landslides and long-term rainfall trends

“…Although the SWI and three-layer tank model are conceptual models, they are used in the Japanese sediment disaster warning system (Osanai et al 2010). Moreover, studies of the occurrence of landslides induced by heavy rainfall have demonstrated their effectiveness (Chen et al 2017;Matsuyama et al 2021;Saito et al 2010a;Shuin et al 2020).…”