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Land data assimilation: Harmonizing theory and data in land surface process studies
Data assimilation plays a dual role in advancing the “scientific” understanding and serving
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …
Recent advances and new frontiers in riverine and coastal flood modeling
Over the past decades, the scientific community has made significant efforts to simulate
flooding conditions using a variety of complex physically based models. Despite all …
flooding conditions using a variety of complex physically based models. Despite all …
Generating ensemble streamflow forecasts: A review of methods and approaches over the past 40 years
M Troin, R Arsenault, AW Wood, F Brissette, JL Martel - 2021 - Wiley Online Library
Ensemble forecasting applied to the field of hydrology is currently an established area of
research embracing a broad spectrum of operational situations. This work catalogs the …
research embracing a broad spectrum of operational situations. This work catalogs the …
Continental drought monitoring using satellite soil moisture, data assimilation and an integrated drought index
Satellite remote sensing provides unprecedented information on near-surface soil moisture
at a global scale, enabling a wide range of studies such as drought monitoring and …
at a global scale, enabling a wide range of studies such as drought monitoring and …
Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities
Data assimilation (DA) holds considerable potential for improving hydrologic predictions as
demonstrated in numerous research studies. However, advances in hydrologic DA research …
demonstrated in numerous research studies. However, advances in hydrologic DA research …
[HTML][HTML] The role of satellite-based remote sensing in improving simulated streamflow: A review
D Jiang, K Wang - Water, 2019 - mdpi.com
A hydrological model is a useful tool to study the effects of human activities and climate
change on hydrology. Accordingly, the performance of hydrological modeling is vitally …
change on hydrology. Accordingly, the performance of hydrological modeling is vitally …
Evolution of ensemble data assimilation for uncertainty quantification using the particle filter‐Markov chain Monte Carlo method
Particle filters (PFs) have become popular for assimilation of a wide range of hydrologic
variables in recent years. With this increased use, it has become necessary to increase the …
variables in recent years. With this increased use, it has become necessary to increase the …
Bayesian flood forecasting methods: A review
Over the past few decades, floods have been seen as one of the most common and largely
distributed natural disasters in the world. If floods could be accurately forecasted in advance …
distributed natural disasters in the world. If floods could be accurately forecasted in advance …
Hydrologic data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications
During the past decades much progress has been made in the development of computer
based methods for parameter and predictive uncertainty estimation of hydrologic models …
based methods for parameter and predictive uncertainty estimation of hydrologic models …
Multivariate remotely sensed and in-situ data assimilation for enhancing community WRF-Hydro model forecasting
Flood is one of the most catastrophic natural disasters in the United States, particularly in the
Southeast states where hurricanes and tropical storms are most prevalent, causing billions …
Southeast states where hurricanes and tropical storms are most prevalent, causing billions …