A nonparametric approach for representing interannual dependence in monthly streamflow sequences

By Ashish Sharma, R. O'Neill. 2002

108 citations recorded by the source corpus.

Subfields: Ecology, Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/21c52c8f763edbc1f40b393ec8191330384e7372

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. T. Harrold
2. Simon J. Sheather
3. Yakov A. Pachepsky
4. Walter J. Rawls
5. Attila Nemes
6. Rajeshwar Mehrotra
7. Y. P. Li
8. Y. Fan

In Global and Planetary Change

1. Rajeshwar Mehrotra
2. Ashish Sharma
3. Yakov A. Pachepsky
4. Walter J. Rawls
5. Attila Nemes
6. T. Harrold
7. Simon J. Sheather
8. Y. P. Li

In Water Science and Technology

1. T. Harrold
2. Simon J. Sheather
3. Yakov A. Pachepsky
4. Attila Nemes
5. Walter J. Rawls
6. Rajeshwar Mehrotra
7. Y. P. Li
8. Y. Fan

Citations in the corpus

• Single‐site monthly streamflow simulation using entropy theory (2011, background): “However, many streamflow records cannot be characterized by commonly assumed probability distributions [Sharma and O’Neill, 2002].”
• Use of the Nonparametric Nearest Neighbor Approach to Estimate Soil Hydraulic Properties (2006, methodology): “Examples for applications relevant to hydrologic simulation include stream flow simulation and disaggregation using nearest neighbor and kernel methods (Lall and Sharma, 1996; Sharma et al., 1997; Tarboton et al., 1998; Kumar et al., 2000; Sharma and O’Neill, 2002, Souza Filho and Lall, 2003), sim”
• A nonparametric model for stochastic generation of daily rainfall amounts (2003, methodology): “To deal with this problem, we use a variable kernel and boundary renormalization (as described by Sharma and O’Neill [2002]) near the threshold amount value of 0.”
• Maximum entropy-Gumbel-Hougaard copula method for simulation of monthly streamflow in Xiangxi river, China (2015, methodology): “For instance, Sharma and O’Neill (2002) proposed a simulation model by using a nonparametric framework to represent the probability of the observed streamflow, which was applied for monthly streamflow simulation for several rivers in Australia.”
• Conditional resampling of hydrologic time series using multiple predictor variables: A K-nearest neighbour approach (2006, background): “Both have been used extensively for a range of hydro-climatological applications [37,14,15,32,27,21,6,28,36,3,10,34,19].”
• Modeling multivariable hydrological series: Principal component analysis or independent component analysis? (2007, unknown): “Alternatively, a number of nonparametric approaches are available [e.g., Lall et al., 1996; Lall and Sharma, 1996; Sharma, 2000; Sharma and O’Neill, 2002; Sharma et al., 1997] which do not require prior assumptions on the nature of the probability distribution.”