Snowmelt and runoff analysis in landslide areas using a time-series statistical model based on monitoring and meteorological data

Abstract

In this study, to analyze the hydrological behavior of landslide areas in snowy cold regions, we developed a state-space model by integrating Sugawara’s snowmelt analysis model with a groundwater tank model. The target area was the Obuchi district of Ani, Akita Prefecture, and the analysis utilized landslide moni- toring data from June 2018 to May 2022, along with meteorological data from the Ani AMeDAS station. The integrated model enabled the estimation of daily snowmelt-equivalent rainfall, taking into account both snowfall and snowmelt, which was then input into the groundwater tank model to analyze the time series of runoff and groundwater storage. Model parameters were estimated using Bayesian inference with the Markov Chain Monte Carlo (MCMC) method.

As a result of verifying the consistency of the estimated values, the variations in snow depth and runoff during the snowfall and snowmelt periods were generally reproduced, indicating successful modeling of hydrological processes in snowy cold regions. The mean squared error between the observed and estimated (median) values was 10.4 cm for snow depth and 203 m³/s for runoff.