Next Article in Journal
A New Soil Moisture Agricultural Drought Index (SMADI) Integrating MODIS and SMOS Products: A Case of Study over the Iberian Peninsula
Previous Article in Journal
Hyperspectral Anomaly Detection Based on Low-Rank Representation and Learned Dictionary
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2016, 8(4), 279; doi:10.3390/rs8040279

Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin

1
Faculty of Civil Engineering and Geosciences, Department of Water Management, Delft University of Technology, Stevinweg 1, Delft 2628 CN, The Netherlands
2
FutureWater, Costerweg 1V, Wageningen 6702 AA, The Netherlands
3
UNESCO-IHE, Westvest 7, Delft 2611 AX, The Netherlands
4
Faculty of Hydrology and Water Resources, Thuy Loi University, 175 Tay Son, Dong Da, Ha Noi, Vietnam
5
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, USA
6
Hydrology and Remote Sensing Labaratory, USDA-ARS, Beltsville, MD 20705, USA
7
USGS EROS Center, North Central Climate Science Center, Colorado State University, Fort Collins, CO 80523, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Magaly Koch and Prasad S. Thenkabail
Received: 14 January 2016 / Revised: 14 March 2016 / Accepted: 21 March 2016 / Published: 28 March 2016
View Full-Text   |   Download PDF [8767 KB, uploaded 28 March 2016]   |  

Abstract

With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P) and land use/land cover (LULC) is currently being expanded with the application of actual evapotranspiration (ETact) algorithms on the global scale. We demonstrate how global remotely sensed P and ETact datasets can be merged to examine hydrological processes such as storage changes and streamflow prior to applying a numerical simulation model. The study area is the Red River Basin in China in Vietnam, a generally challenging basin for remotely sensed information due to frequent cloud cover. Over this region, several satellite-based P and ETact products are compared, and performance is evaluated using rain gauge records and longer-term averaged streamflow. A method is presented for fusing multiple satellite-derived ETact estimates to generate an ensemble product that may be less susceptible, on a global basis, to errors in individual modeling approaches. Subsequently, monthly satellite-derived rainfall and ETact are combined to assess the water balance for individual subcatchments and types of land use, defined using a global land use classification improved based on auxiliary satellite data. It was found that a combination of TRMM rainfall and the ensemble ETact product is consistent with streamflow records in both space and time. It is concluded that monthly storage changes, multi-annual streamflow and water yield per LULC type in the Red River Basin can be successfully assessed based on currently available global satellite-derived products. View Full-Text
Keywords: global satellite-derived data; intercomparison; evapotranspiration; Red River Basin; hydrological modeling; water accounting global satellite-derived data; intercomparison; evapotranspiration; Red River Basin; hydrological modeling; water accounting
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Simons, G.; Bastiaanssen, W.; Ngô, L.A.; Hain, C.R.; Anderson, M.; Senay, G. Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin. Remote Sens. 2016, 8, 279.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top