Modeling Suspended Sediment Using Artificial Neural Networks and TRMM-3B42 Version 7 Rainfall Dataset-Reference-Cited by-同舟云学术

Modeling Suspended Sediment Using Artificial Neural Networks and TRMM-3B42 Version 7 Rainfall Dataset

Published:2015-06 Issue:6 Volume:20 Page:
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Kumar Dheeraj¹,Pandey Ashish²,Sharma Nayan³,Flügel Wolfgang-Albert⁴

Affiliation:

1. Research Scholar, Water Resources Development and Management Dept., Indian Institute of Technology Roorkee, Roorkee 247 667, India (corresponding author).

2. Associate Professor, Water Resources Development and Management Dept., Indian Institute of Technology Roorkee, Roorkee 247 667, India.

3. Professor, Water Resources Development and Management Dept., Indian Institute of Technology Roorkee, Roorkee 247 667, India.

4. Professor and Head, Dept. of Geoinformatics, Hydrology and Modelling, Friedrich-Schiller Univ. Jena, Loebdergraben 32, 07743 Jena, Germany.

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Water Science and Technology,Civil and Structural Engineering,Environmental Chemistry

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29HE.1943-5584.0001082

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5. Evaluation of satellite-retrieved extreme precipitation rates across the central United States;AghaKouchak A.;J. Geophys. Res.,2011

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