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A global distributed basin morphometric dataset.
Shen, Xinyi; Anagnostou, Emmanouil N; Mei, Yiwen; Hong, Yang.
Afiliação
  • Shen X; Department of Civil &Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269-3037, USA.
  • Anagnostou EN; Department of Civil &Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269-3037, USA.
  • Mei Y; Department of Civil &Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269-3037, USA.
  • Hong Y; Advanced Radar Research Center, National Weather Center, University of Oklahoma, Norman, Oklahoma 73072, USA.
Sci Data ; 4: 160124, 2017 Jan 05.
Article em En | MEDLINE | ID: mdl-28055032
ABSTRACT
Basin morphometry is vital information for relating storms to hydrologic hazards, such as landslides and floods. In this paper we present the first comprehensive global dataset of distributed basin morphometry at 30 arc seconds resolution. The dataset includes nine prime morphometric variables; in addition we present formulas for generating twenty-one additional morphometric variables based on combination of the prime variables. The dataset can aid different applications including studies of land-atmosphere interaction, and modelling of floods and droughts for sustainable water management. The validity of the dataset has been consolidated by successfully repeating the Hack's law.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Data Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Data Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos