Hydrologic complexity and classification: a simple data reconstruction approach
By Bellie Sivakumar, A. Jayawardena, Wai Keung Li. 2007
71 citations recorded by the source corpus.
Subfields: Environmental Engineering, Global and Planetary Change, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/eaa5d7d588ed9b600595259e7ddbd83393e7de92
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Environmental Engineering
In Global and Planetary Change
- Luciano Zunino
- M. Clark
- Osvaldo Anibal Rosso
- F. Serinaldi
- Shenglian Guo
- Vijay P. Singh
- M. Janga Reddy
- Poulomi Ganguli
In Water Science and Technology
- Luciano Zunino
- M. Clark
- Osvaldo Anibal Rosso
- F. Serinaldi
- Lauren E. Hay
- Steven Markstrom
- Jasper A. Vrugt
- Keith Beven
Citations in the corpus
- Complexity–entropy analysis of daily stream flow time series in the continental United States (2014, methodology): “The AMI is a nonlinear measure like HS and CJS: The lag plot is the plot of the pairs (xt, xt?k), it enables the detection of nonlinearities and was suggested by Sivakumar et al. (2007) and Sivakumar and Singh (2012) as a possible tool for classifying stream flow time series.”
- Towards simplification of hydrologic modeling: identification of dominant processes (2016, background): “In addition, dominant process concepts have been explored by several researchers as a way to classify watersheds and natural hydrologic systems for the purpose of simplifying DPHMs (Sivakumar and Singh, 2012; Sivakumar et al., 2007).”