Cai Mingyong, Yang Shengtian, Zhao Changsen, Zhou Qiuwen, Hou Lipeng
Satellite Environment Center of MEP, Beijing, China.
College of Water Sciences, Beijing Normal University, Beijing, China.
PLoS One. 2017 May 9;12(5):e0176813. doi: 10.1371/journal.pone.0176813. eCollection 2017.
Regional hydrological modeling in ungauged regions has attracted growing attention in water resources research. The southern Tibetan Plateau often suffers from data scarcity in watershed hydrological simulation and water resources assessment. This hinders further research characterizing the water cycle and solving international water resource issues in the area. In this study, a multi-spatial data based Distributed Time-Variant Gain Model (MS-DTVGM) is applied to the Yarlung Zangbo River basin, an important international river basin in the southern Tibetan Plateau with limited meteorological data. This model is driven purely by spatial data from multiple sources and is independent of traditional meteorological data. Based on the methods presented in this study, daily snow cover and potential evapotranspiration data in the Yarlung Zangbo River basin in 2050 are obtained. Future (2050) climatic data (precipitation and air temperature) from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR5) are used to study the hydrological response to climate change. The result shows that river runoff will increase due to precipitation and air temperature changes by 2050. Few differences are found between daily runoff simulations from different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5) for 2050. Historical station observations (1960-2000) at Nuxia and model simulations for two periods (2006-2009 and 2050) are combined to study inter-annual and intra-annual runoff distribution and variability. The inter-annual runoff variation is stable and the coefficient of variation (CV) varies from 0.21 to 0.27. In contrast, the intra-annual runoff varies significantly with runoff in summer and autumn accounting for more than 80% of the total amount. Compared to the historical period (1960-2000), the present period (2006-2009) has a slightly uneven intra-annual runoff temporal distribution, and becomes more balanced in the future (2050).
无资料地区的区域水文模型在水资源研究中受到越来越多的关注。青藏高原南部在流域水文模拟和水资源评估方面常常面临数据匮乏的问题。这阻碍了对该地区水循环特征的进一步研究以及国际水资源问题的解决。在本研究中，一种基于多空间数据的分布式时变增益模型（MS-DTVGM）被应用于雅鲁藏布江流域，该流域是青藏高原南部一个重要的国际流域，气象数据有限。该模型完全由来自多个来源的空间数据驱动，且独立于传统气象数据。基于本研究提出的方法，获取了雅鲁藏布江流域2050年的日积雪覆盖和潜在蒸散数据。利用政府间气候变化专门委员会第五次评估报告（IPCC-AR5）中的未来（2050年）气候数据（降水和气温）来研究对气候变化的水文响应。结果表明，到2050年，由于降水和气温变化，河流径流将会增加。2050年不同代表性浓度路径（RCP）情景（RCP2.6、RCP4.5和RCP8.5）的日径流模拟结果差异不大。结合奴下的历史站点观测数据（1960 - 2000年）以及两个时期（2006 - 2009年和2050年）的模型模拟结果，研究年际和年内径流分布及变异性。年际径流变化较为稳定，变异系数（CV）在0.21至0.27之间变化。相比之下，年内径流变化显著，夏季和秋季径流占总量的80%以上。与历史时期（1960 - 2000年）相比，当前时期（2006 - 2009年）年内径流时间分布略显不均，而在未来（2050年）将变得更加均衡。
