Evaluation of driftwood generation in the Northern Kyushu heavy rain in 2017 by logistic regression

Takahiro Shogaki, Akiyoshi Tsusue, Shinichiro Yano, Kiyonobu Kasama

Research output: Contribution to conferencePaperpeer-review

Abstract

We tried to develop a model to calculate the amount of driftwood generation from a given watershed area in a specific heavy rain event. In this research, slope failure dataset in the Northern Kyushu Heavy Rain in 2017 was used for the logistic regression model to estimate the possibility of slope failure generation. In this model, C-X band radar precipitation, geographical data, geological data, and land use data were adapted. As a result of the present research, it is found that the best model can express the slope failure in the heavy rain with very high accuracy. In addition, the model can estimate the driftwood generation from 10 rivers with 20% of accuracy the model.

Original languageEnglish
Publication statusPublished - 2020
Event22nd Congress of the International Association for Hydro-Environment Engineering and Research-Asia Pacific Division: Creating Resilience to Water-Related Challenges, IAHR-APD 2020 - Sapporo, Virtual, Japan
Duration: Sep 14 2020Sep 17 2020

Conference

Conference22nd Congress of the International Association for Hydro-Environment Engineering and Research-Asia Pacific Division: Creating Resilience to Water-Related Challenges, IAHR-APD 2020
CountryJapan
CitySapporo, Virtual
Period9/14/209/17/20

All Science Journal Classification (ASJC) codes

  • Ecology
  • Environmental Engineering

Fingerprint Dive into the research topics of 'Evaluation of driftwood generation in the Northern Kyushu heavy rain in 2017 by logistic regression'. Together they form a unique fingerprint.

Cite this