Articles | Volume 22, issue 1
https://doi.org/10.5194/hess-22-757-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-22-757-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
26 Jan 2018
Research article |
| 26 Jan 2018
A discrete wavelet spectrum approach for identifying non-monotonic trends in hydroclimate data
Yan-Fang Sang
CORRESPONDING AUTHOR
Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Department of Atmospheric Sciences, University of Washington, Seattle 98195, Washington, USA
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China
Fubao Sun
CORRESPONDING AUTHOR
Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Vijay P. Singh
Department of Biological and Agricultural Engineering and Zachry Department of Civil Engineering, Texas A&M University, 321 Scoates Hall, 2117 TAMU, College Station, Texas 77843-2117, USA
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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- Nonlinear response of runoff to atmospheric freezing level height variation based on hybrid prediction models Y. Qin et al. 10.1080/02626667.2019.1662023
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Latest update: 17 Jul 2024
