A Robust Strategy to Account for Data Sampling Variability in the Development of Hydrological Models

Time to Update the Split‐Sample Approach in Hydrological Model Calibration

(2022) Hongren Shen et al.   WATER RESOURCES RESEARCH

Achieving Robust and Transferable Performance for Conservation‐Based Models of Dynamical Physical Systems

(2022) Feifei Zheng et al.   WATER RESOURCES RESEARCH

Formulation of Wavelet Based Multi‐Scale Multi‐Objective Performance Evaluation (WMMPE) Metric for Improved Calibration of Hydrological Models

(2022) Velpuri Manikanta et al.   WATER RESOURCES RESEARCH

Improved data splitting methods for data-driven hydrological model development based on a large number of catchment samples

(2022) Junyi Chen et al.   JOURNAL OF HYDROLOGY

Understanding the Information Content in the Hierarchy of Model Development Decisions: Learning from data

(2021) Shervan Gharari et al.   WATER RESOURCES RESEARCH

On the Robustness of Conceptual Rainfall‐Runoff Models to Calibration and Evaluation Data Set Splits Selection: A Large Sample Investigation

(2020) Danlu Guo et al.   WATER RESOURCES RESEARCH

Towards quick parameter estimation of hydrological models with large number of computational units

(2020) Vamsi Krishna Vema et al.   JOURNAL OF HYDROLOGY

Potential and Challenges of Investigating Intrinsic Uncertainty of Hydrological Models with Stochastic, Time‐Dependent Parameters

(2020) Peter Reichert et al.   WATER RESOURCES RESEARCH

Stochastic Gradient Descent and Its Variants in Machine Learning

(2019) Praneeth Netrapalli   JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE

Reducing the uncertainty of time-varying hydrological model parameters using spatial coherence within a hierarchical Bayesian framework

(2019) Zhengke Pan et al.   JOURNAL OF HYDROLOGY

Reliable Accuracy Estimates from k-Fold Cross Validation

(2019) Tzu-Tsung Wong et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Latent Factor-Based Recommenders Relying on Extended Stochastic Gradient Descent Algorithms

(2019) Xin Luo et al.   IEEE Transactions on Systems Man Cybernetics-Systems

On Lack of Robustness in Hydrological Model Development Due to Absence of Guidelines for Selecting Calibration and Evaluation Data: Demonstration for Data-Driven Models

(2018) Feifei Zheng et al.   WATER RESOURCES RESEARCH

Assessing the potential robustness of conceptual rainfall-runoff models under a changing climate

(2018) Danlu Guo et al.   WATER RESOURCES RESEARCH

The hazards of split-sample validation in hydrological model calibration

(2018) Richard Arsenault et al.   JOURNAL OF HYDROLOGY

A trans-disciplinary review of deep learning research and its relevance for water resources scientists

(2018) Chaopeng Shen   WATER RESOURCES RESEARCH

Introductory overview: Optimization using evolutionary algorithms and other metaheuristics

(2018) H.R. Maier et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Modeling of daily runoff from a small agricultural watershed using artificial neural network with resampling techniques

(2015) Gurjeet Singh et al.   JOURNAL OF HYDROINFORMATICS

Modeling residual hydrologic errors with Bayesian inference

(2015) Tyler Smith et al.   JOURNAL OF HYDROLOGY

Multi-model approach to assess the impact of climate change on runoff

(2015) J. Dams et al.   JOURNAL OF HYDROLOGY

Flood hazard risk assessment model based on random forest

(2015) Zhaoli Wang et al.   JOURNAL OF HYDROLOGY

Data-driven input variable selection for rainfall–runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines

(2015) Riccardo Taormina et al.   JOURNAL OF HYDROLOGY

A scalable bootstrap for massive data

(2014) Ariel Kleiner et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Comparison of joint versus postprocessor approaches for hydrological uncertainty estimation accounting for error autocorrelation and heteroscedasticity

(2014) Guillaume Evin et al.   WATER RESOURCES RESEARCH

A benchmarking approach for comparing data splitting methods for modeling water resources parameters using artificial neural networks

(2013) Wenyan Wu et al.   WATER RESOURCES RESEARCH

Pitfalls and improvements in the joint inference of heteroscedasticity and autocorrelation in hydrological model calibration

(2013) Guillaume Evin et al.   WATER RESOURCES RESEARCH

Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios

(2012) Harald Kling et al.   JOURNAL OF HYDROLOGY

Towards a comprehensive assessment of model structural adequacy

(2012) Hoshin V. Gupta et al.   WATER RESOURCES RESEARCH

Towards improved criteria for hydrological model calibration: theoretical analysis of distance- and weak form-based functions

(2011) V. Guinot et al.   JOURNAL OF HYDROLOGY

On typical range, sensitivity, and normalization of Mean Squared Error and Nash-Sutcliffe Efficiency type metrics

(2011) Hoshin Vijai Gupta et al.   WATER RESOURCES RESEARCH

Improving robustness of hydrologic parameter estimation by the use of moving block bootstrap resampling

(2010) Mohammad Ebtehaj et al.   WATER RESOURCES RESEARCH

Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling

(2009) Hoshin V. Gupta et al.   JOURNAL OF HYDROLOGY

Uncertainty assessment and ensemble flood forecasting using bootstrap based artificial neural networks (BANNs)

(2009) Mukesh Kumar Tiwari et al.   JOURNAL OF HYDROLOGY

Data splitting for artificial neural networks using SOM-based stratified sampling

(2009) R.J. May et al.   NEURAL NETWORKS

Estimation of prediction error by using K-fold cross-validation

(2009) Tadayoshi Fushiki   STATISTICS AND COMPUTING

Informal likelihood measures in model assessment: Theoretic development and investigation

(2008) Paul Smith et al.   ADVANCES IN WATER RESOURCES

Reconciling theory with observations: elements of a diagnostic approach to model evaluation

(2008) Hoshin V. Gupta et al.   HYDROLOGICAL PROCESSES