Articles | Volume 15, issue 1
https://doi.org/10.5194/esd-15-75-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-15-75-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Jan 2024
Research article |
| 29 Jan 2024
| 29 Jan 2024
Historical and projected future runoff over the Mekong River basin
Chao Wang
School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
Stephen Leisz
Department of Anthropology and Geography, Colorado State University, Fort Collins, CO 80523, USA
College of Arts and Sciences, VinUniversity, Ocean Park, Hanoi, Vietnam
Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA 16802, USA
Xiaoying Shi
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Jiafu Mao
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
Department of Biology, Colorado State University, Fort Collins, CO 80523, USA
Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO 80523, USA
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We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and multilayer) by merging a wide range of data sources, including in situ and satellite observations, reanalysis, offline land surface model simulations, and Earth system model simulations. Given the great value of long-term, multilayer, gap-free soil moisture products to climate research and applications, we believe this paper and the presented datasets would be of interest to many different communities.
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Short summary
Climate change can significantly impact river runoff; however, predicting future runoff is challenging. Using historical runoff gauge data to evaluate model performances in runoff simulations for the Mekong River, we quantify future runoff changes in the Mekong River with the best simulation combination. Results suggest a significant increase in the annual runoff, along with varied seasonal distributions, thus heightening the need for adapted water resource management measures.
Climate change can significantly impact river runoff; however, predicting future runoff is...
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