[HTML][HTML] An overview of approaches for reducing uncertainties in hydrological forecasting: Progress and challenges
Uncertainty plays a key role in hydrological modeling and forecasting, which can have
tremendous environmental, economic, and social impacts. Therefore, it is crucial to …
tremendous environmental, economic, and social impacts. Therefore, it is crucial to …
A factorial ecologically-extended input-output model for analyzing urban GHG emissions metabolism system
Increasing urbanization in the world brings tremendous social, economic and environmental
challenges. It is essential to fully analyze urban GHG emissions metabolism systems to …
challenges. It is essential to fully analyze urban GHG emissions metabolism systems to …
Robust and efficient uncertainty quantification for extreme events that deviate significantly from the training dataset using polynomial chaos-kriging
This study presents the strengths of polynomial chaos-kriging (PCK), a new surrogate model
that merges polynomial chaos extension (PCE) and Gaussian process with kriging variance …
that merges polynomial chaos extension (PCE) and Gaussian process with kriging variance …
Development of a stochastic hydrological modeling system for improving ensemble streamflow prediction
Streamflow prediction plays a crucial role in water resources systems planning and the
mitigation of hydrological extremes such as floods and droughts. Since a variety of …
mitigation of hydrological extremes such as floods and droughts. Since a variety of …
Improving robustness of hydrologic ensemble predictions through probabilistic pre‐and post‐processing in sequential data assimilation
Data assimilation using the ensemble Kalman filter (EnKF) has been increasingly
recognized as a promising tool for probabilistic hydrologic predictions. However, little effort …
recognized as a promising tool for probabilistic hydrologic predictions. However, little effort …
Development of a disaggregated multi-level factorial hydrologic data assimilation model
A disaggregated multi-level factorial hydrologic data assimilation model (FHDA) is proposed
for exploring not only the direct effects from individual uncertainties but also, more …
for exploring not only the direct effects from individual uncertainties but also, more …
Rivers' temporal sustainability through the evaluation of predictive runoff methods
JL Molina, S Zazo, AM Martín-Casado… - Sustainability, 2020 - mdpi.com
The concept of sustainability is assumed for this research from a temporal perspective.
Rivers represent natural systems with an inherent internal memory on their runoff and, by …
Rivers represent natural systems with an inherent internal memory on their runoff and, by …
Nonlinear and periodic dynamics of chaotic hydro-thermal process of Skokomish river
H Ruskeepää, LN Ferreira, MA Ghorbani… - … Research and Risk …, 2023 - Springer
This paper investigates the dynamics of the time-series of water temperature of the
Skokomish River (2019–2020) at hourly time scale by employing well-known nonlinear …
Skokomish River (2019–2020) at hourly time scale by employing well-known nonlinear …
A novel modeling framework for computationally efficient and accurate real‐time ensemble flood forecasting with uncertainty quantification
A novel modeling framework that simultaneously improves accuracy, predictability, and
computational efficiency is presented. It embraces the benefits of three modeling techniques …
computational efficiency is presented. It embraces the benefits of three modeling techniques …
Parameter uncertainty of a hydrologic model calibrated with remotely sensed evapotranspiration and soil moisture
Remotely sensed (RS) observations are becoming prevalent for hydrological model
calibration in sparsely monitored regions. In this study, the parameter uncertainty associated …
calibration in sparsely monitored regions. In this study, the parameter uncertainty associated …