+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Assessing data assimilation frameworks for using multi-mission satellite products in a hydrological context

Assessing data assimilation frameworks for using multi-mission satellite products in a hydrological context

Science of the Total Environment 647: 1031-1043

With a growing number of available datasets especially from satellite remote sensing, there is a great opportunity to improve our knowledge of the state of the hydrological processes via data assimilation. Observations can be assimilated into numerical models using dynamics and data-driven approaches. The present study aims to assess these assimilation frameworks for integrating different sets of satellite measurements in a hydrological context. To this end, we implement a traditional data assimilation system based on the Square Root Analysis (SQRA) filtering scheme and the newly developed data-driven Kalman-Takens technique to update the water components of a hydrological model with the Gravity Recovery And Climate Experiment (GRACE) terrestrial water storage (TWS), and soil moisture products from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and Soil Moisture and Ocean Salinity (SMOS) in a 5-day temporal scale. While SQRA relies on a physical model for forecasting, the Kalman-Takens only requires a trajectory of the system based on past data. We are particularly interested in testing both methods for assimilating different combination of the satellite data. In most of the cases, simultaneous assimilation of the satellite data by either standard SQRA or Kalman-Takens achieves the largest improvements in the hydrological state, in terms of the agreement with independent in-situ measurements. Furthermore, the Kalman-Takens approach performs comparably well to dynamical method at a fraction of the computational cost.

Please choose payment method:

(PDF emailed within 0-6 h: $19.90)

Accession: 065701860

Download citation: RISBibTeXText

PMID: 30180311

DOI: 10.1016/j.scitotenv.2018.08.032

Related references

The application of multi-mission satellite data assimilation for studying water storage changes over South America. Science of the Total Environment 647: 1557-1572, 2019

Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll- a data. Remote Sensing of Environment 203: 139-151, 2017

Evaluation of hydrological circulation over Asia using fine resolution four dimensional data assimilation products (GAME reanalysis); an impact study of satellite snow information. Kyoto Daigaku Bosai Kenkyujo Nenpo = Disaster Prevention Research Institute Annuals 45, B: 141-148, 2002

Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model. Advances in Water Resources 107: 301-316, 2017

Development of multi-mission satellite data systems at the German Remote Sensing Data Centre. Advances in Space Research 22(11): 1573-1576, 1998

Statistical and hydrological evaluation of TRMM-based Multi-satellite Precipitation Analysis over the Wangchu Basin of Bhutan Are the latest satellite precipitation products 3B42V7 ready for use in ungauged basins?. Journal of Hydrology 499: 91-99, 2013

Data assimilation of satellite-based actual evapotranspiration in a distributed hydrological model of a controlled water system. International Journal of Applied Earth Observation and Geoinformation 57: 123-135, 2017

Assessing parameter, precipitation, and predictive uncertainty in a distributed hydrological model using sequential data assimilation with the particle filter. Journal of Hydrology 376(3-4): 428-442, 2009

A cloud-detection scheme for use with satellite sounding radiances in the context of data assimilation for numerical weather prediction. Quarterly Journal of the Royal Meteorological Society 125(559): 2359-2378, 1999

Modeling and analysis of lake water storage changes on the Tibetan Plateau using multi-mission satellite data. Remote Sensing of Environment 135: 25-35, 2013

Recent dynamics of alpine lakes on the endorheic Changtang Plateau from multi-mission satellite data. Journal of Hydrology 552: 633-645, 2017

Multi-variable calibration of a semi-distributed hydrological model using streamflow data and satellite-based evapotranspiration. Journal of Hydrology 505: 276-290, 2013

Transitioning Satellite Products, Modeling & Data Assimilation Techniques, and Nowcasting Tools to Operations. Meteorological Technology International 2016: 32-36, 2016

A study of Bangladesh's sub-surface water storages using satellite products and data assimilation scheme. Science of the Total Environment 625: 963-977, 2018

A study of Bangladesh's sub-surface water storages using satellite products and data assimilation scheme. Science of Total Environment 625: 963-977, 2018