Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations
Autor: | Dawen Yang, Bin Gao, Xueting Peng, Zhiguo Pang, Yang Jiao, Khem Sothea, Hui Lu, Wei Wang |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences Calibration (statistics) Hydrological modelling Rain Climate Change 0208 environmental biotechnology Climate change Marine and Aquatic Sciences Social Sciences lcsh:Medicine 02 engineering and technology Structural basin Research and Analysis Methods Human Geography 01 natural sciences Remote Sensing Meteorology Rivers Natural Resources Land Use lcsh:Science Asia Southeastern 0105 earth and related environmental sciences Climatology Multidisciplinary Rain gauge Geography Distributed element model Simulation and Modeling Ecology and Environmental Sciences lcsh:R Aquatic Environments Models Theoretical Bodies of Water 020801 environmental engineering Water resources Data quality Earth Sciences Water Resources Environmental science Engineering and Technology lcsh:Q Hydrology Research Article Freshwater Environments |
Zdroj: | PLoS ONE, Vol 11, Iss 3, p e0152229 (2016) PLoS ONE |
ISSN: | 1932-6203 |
Popis: | The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998–2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002–2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability. |
Databáze: | OpenAIRE |
Externí odkaz: |