Next Article in Journal
Monitoring Groundwater Storage Changes Using the Gravity Recovery and Climate Experiment (GRACE) Satellite Mission: A Review
Previous Article in Journal
The Impact of Hurricane Maria on the Vegetation of Dominica and Puerto Rico Using Multispectral Remote Sensing
Erratum published on 10 July 2018, see Remote Sens. 2018, 10(7), 1099.
Open AccessArticle

Inter-Comparison of Gauge-Corrected Global Satellite Rainfall Estimates and Their Applicability for Effective Water Resource Management in a Transboundary River Basin: The Case of the Meghna River Basin

1
International Centre for Water Hazard and Risk Management (ICHARM), Public Works Research Institute (PWRI), Tsukuba, Ibaraki 305-8516, Japan
2
National Graduate Institute for Policy Studies (GRIPS), Tokyo 106-8677, Japan
3
Centre for Ecology & Hydrology, Maclean Building, Wallingford, Oxfordshire OX10 8BB, UK
4
IHE Delft, 2601 DA, Delft, The Netherlands
5
University of Yamanashi, Takeda, Kofu, Yamanashi 400-8510, Japan
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 828; https://doi.org/10.3390/rs10060828
Received: 29 March 2018 / Revised: 27 April 2018 / Accepted: 24 May 2018 / Published: 25 May 2018
The Meghna River basin is a transboundary basin that lies in Bangladesh (~40%) and India (~60%). Due to its terrain structure, the Bangladesh portion of the basin experiences frequent floods that cause severe human and economic losses. Bangladesh, as the downstream nation in the basin, faces challenges in receiving hydro-meteorological and water use data from India for effective water resource management. To address such issue, satellite rainfall products are recognized as an alternative. However, they are affected by biases and, thus, must be calibrated and verified using ground observations. This research compares the performance of four widely available gauge-adjusted satellite rainfall products (GSRPs) against ground rainfall observations in the Meghna basin within Bangladesh. Further biases in the GSRPs are then identified. The GSRPs have both similarities and differences in terms of producing biases. To maximize the usage of the GSRPs and to further improve their accuracy, several bias correction and merging techniques are applied to correct them. Correction factors and merging weights are calculated at the local gauge stations and are spatially distributed by adopting an interpolation method to improve the GSRPs, both inside and outside Bangladesh. Of the four bias correction methods, modified linear correction (MLC) has performed better, and partially removed the GSRPs’ systematic biases. In addition, of the three merging techniques, inverse error-variance weighting (IEVW) has provided better results than the individual GSRPs and removed significantly more biases than the MLC correction method for three of the five validation stations, whereas the two other stations that experienced heavy rainfall events, showed better results for the MLC method. Hence, the combined use of IEVW merging and MLC correction is explored. The combined method has provided the best results, thus creating an improved dataset. The applicability of this dataset is then investigated using a hydrological model to simulated streamflows at two critical locations. The results show that the dataset reproduces the hydrological responses of the basin well, as compared with the observed streamflows. Together, these results indicate that the improved dataset can overcome the limitations of poor data availability in the basin and can serve as a reference rainfall dataset for wide range of applications (e.g., flood modelling and forecasting, irrigation planning, damage and risk assessment, and climate change adaptation planning). In addition, the proposed methodology of creating a reference rainfall dataset based on the GSRPs could also be applicable to other poorly-gauged and inaccessible transboundary river basins, thus providing reliable rainfall information and effective water resource management for sustainable development. View Full-Text
Keywords: gauge-corrected satellite rainfall products (GSRPs); Meghna River; transboundary river; bias correction; merging; reference rainfall dataset; simulated streamflow gauge-corrected satellite rainfall products (GSRPs); Meghna River; transboundary river; bias correction; merging; reference rainfall dataset; simulated streamflow
Show Figures

Graphical abstract

MDPI and ACS Style

Khairul, I.M.; Mastrantonas, N.; Rasmy, M.; Koike, T.; Takeuchi, K. Inter-Comparison of Gauge-Corrected Global Satellite Rainfall Estimates and Their Applicability for Effective Water Resource Management in a Transboundary River Basin: The Case of the Meghna River Basin. Remote Sens. 2018, 10, 828.

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.

Article Access Map by Country/Region

1
Back to TopTop