• Publications
  • Influence
Effective and efficient global optimization for conceptual rainfall‐runoff models
The successful application of a conceptual rainfall-runoff (CRR) model depends on how well it is calibrated. Despite the popularity of CRR models, reports in the literature indicate that it isExpand
  • 2,718
  • 200
  • PDF
A Modified Soil Adjusted Vegetation Index
There is currently a great deal of interest in the quantitative characterization of temporal and spatial vegetation patterns with remotely sensed data for the study of earth system science and globalExpand
  • 1,724
  • 164
Status of Automatic Calibration for Hydrologic Models: Comparison with Multilevel Expert Calibration
TLDR
The usefulness of a hydrologic model depends on how well the model is calibrated. Expand
  • 1,187
  • 103
Evaluation of PERSIANN system satellite-based estimates of tropical rainfall
Abstract PERSIANN, an automated system for Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks, has been developed for the estimation of rainfall fromExpand
  • 940
  • 103
Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information
TLDR
This paper suggests that the emergence of a new and more powerful model calibration paradigm must include recognition of the inherent multiobjective nature of the problem and must explicitly recognize the role of model error. Expand
  • 1,283
  • 101
Shuffled complex evolution approach for effective and efficient global minimization
The degree of difficulty in solving a global optimization problem is in general dependent on the dimensionality of the problem and certain characteristics of the objective function. This paperExpand
  • 1,264
  • 81
A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters
Author(s): Vrugt, JA; Gupta, HV; Bouten, W; Sorooshian, S | Abstract: Markov Chain Monte Carlo (MCMC) methods have become increasingly popular for estimating the posterior probability distribution ofExpand
  • 1,114
  • 66
  • PDF
Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks
Abstract A system for Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) is under development at The University of Arizona. The current core of thisExpand
  • 767
  • 66
Optimal use of the SCE-UA global optimization method for calibrating watershed models
TLDR
A global optimization method known as the SCE-UA (shuffled complex evolution method developed at The University of Arizona) has shown promise as an effective and efficient optimization technique for calibrating watershed models. Expand
  • 1,027
  • 60
  • PDF
Dual state-parameter estimation of hydrological models using ensemble Kalman filter
TLDR
A dual state–parameter estimation approach is presented based on the Ensemble Kalman Filter (EnKF) for sequential estimation of both parameters and state variables of a hydrologic model. Expand
  • 735
  • 53
  • PDF
...
1
2
3
4
5
...