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Supporting Information: Practical data-driven flood forecasting based on dynamical systems theory

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Created:	Feb 12, 2020 at 9:36 a.m.
Last updated:	Sep 21, 2020 at 8:40 a.m.
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Abstract

This document provides an overview of the accompanying data files used in the manuscript entitled "Practical data-driven flood forecasting based on dynamical systems theory: Case studies from Japan."

db_kagetsu.csv:
Past hourly data on Kagetsu gauging station and 4 precipitation stations (Tsurukochi, Kagetsu, Yokohata, and Mikuma) downloaded from the website of the Water Information System (http://www1.river.go.jp/).

db_hiwatashi.csv
Past hourly data on 5 gauging stations (Takeshita, Otobou, Hirose, Ohjibashi, and Hiwatashi) and 14 precipitation stations (Sunoura, Nojiri, Kensetsutakaharu, Shika, Sano, Kirishima, Miike, Hiwatashi, Aoidake, Mimata, Kabayama, Takeshita, Hisokino, and Sueyoshi) downloaded from the website of the Water Information System (http://www1.river.go.jp/).

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The content of this resource is derived from

Water Information System: http://www1.river.go.jp/

How to Cite

Okuno, S., K. Ikeuchi, K. Aihara (2020). Supporting Information: Practical data-driven flood forecasting based on dynamical systems theory, HydroShare, http://www.hydroshare.org/resource/dfcea9afcba94976a2df14f42a5d1a97

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/

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