Assessment of the suitability of rainfall–runoff models by coupling performance statistics and sensitivity analysis

Skip Nav Destination

Hydrology Research (2017) 48 (5): 1192–1213.

This article has been cited by the following articles in journals that are participating in CrossRef Cited-by Linking.

Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil

Louise Akemi Kuana
Arlan Scortegagna Almeida
Emílio Graciliano Ferreira Mercuri
Steffen Manfred Noe

Hydrology and Earth System Sciences (2024) 28 (14): 3367.

Ensemble flood predictions for River Thames under climate change

Yurui Fan

National Science Open (2024) 3 (1): 20230027.

Evaluating the dynamics of hydroclimate and streamflow for data-scarce areas using MIKE11-NAM model in Bilate river basin, Ethiopia

Abera Shigute Nannawo
Tarun Kumar Lohani
Abunu Atlabachew Eshete
Melkamu Teshome Ayana

Modeling Earth Systems and Environment (2022) 8 (4): 4563.

Towards reliable uncertainty quantification for hydrologic predictions, Part I: Development of a particle copula Metropolis Hastings method

Y.R. Fan
X. Shi
Q.Y. Duan
L. Yu

Journal of Hydrology (2022) 612: 128163.

Assessment of global reanalysis precipitation for hydrological modelling in data-scarce regions: A case study of Kenya

Maureen A. Wanzala
Andrea Ficchi
Hannah L. Cloke
Elisabeth M. Stephens
Heou M. Badjana
David A. Lavers

Journal of Hydrology: Regional Studies (2022) 41: 101105.

Using a global sensitivity analysis to estimate the appropriate length of calibration period in the presence of high hydrological model uncertainty

Mun-Ju Shin
Yong Jung

Journal of Hydrology (2022) 607: 127546.

A comprehensive intercomparison study between a lumped and a fully distributed hydrological model across a set of 50 catchments in the United Kingdom

Sumit Sinha
Anthony Hammond
Helen Smith

Hydrological Processes (2022) 36 (3)

Component Combination Test to Investigate Improvement of the IHACRES and GR4J Rainfall–Runoff Models

Mun-Ju Shin
Chung-Soo Kim

Water (2021) 13 (15): 2126.

Technical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspective

Paul C. Astagneau
Guillaume Thirel
Olivier Delaigue
Joseph H. A. Guillaume
Juraj Parajka
Claudia C. Brauer
Alberto Viglione
Wouter Buytaert
Keith J. Beven

Hydrology and Earth System Sciences (2021) 25 (7): 3937.

What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling

Thorsten Wagener
Francesca Pianosi

Earth-Science Reviews (2019) 194: 1.

Sensitivity Analysis to Investigate the Reliability of the Grid-Based Rainfall-Runoff Model

Mun-Ju Shin
Yun Seok Choi

Water (2018) 10 (12): 1839.

Combining an R-Based Evolutionary Algorithm and Hydrological Model for Effective Parameter Calibration

Mun-Ju Shin
Yun Seok Choi

Water (2018) 10 (10): 1339.

Integration of a Parsimonious Hydrological Model with Recurrent Neural Networks for Improved Streamflow Forecasting

Ye Tian
Yue-Ping Xu
Zongliang Yang
Guoqing Wang
Qian Zhu

Water (2018) 10 (11): 1655.

Evaluating the Temporal Dynamics of Uncertainty Contribution from Satellite Precipitation Input in Rainfall-Runoff Modeling Using the Variance Decomposition Method

Qiumei Ma
Lihua Xiong
Dedi Liu
Chong-Yu Xu
Shenglian Guo

Remote Sensing (2018) 10 (12): 1876.

Preliminary Study of Computational Time Steps in a Physically Based Distributed Rainfall–Runoff Model

Yun Seok Choi
Mun-Ju Shin
Kyung Tak Kim

Water (2018) 10 (9): 1269.

Assessment of the suitability of rainfall–runoff models by coupling performance statistics and sensitivity analysis

This Feature Is Available To Subscribers Only