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利用卫星观测和建模来了解湄公河下游流域的径流变化。

Satellite observations and modeling to understand the Lower Mekong River basin streamflow variability.

作者信息

Mohammed Ibrahim Nourein, Bolten John D, Srinivasan Raghavan, Lakshmi Venkat

机构信息

Science Applications International Corporation, Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Mail Code 617.0, Greenbelt, MD 20771, USA.

Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Mail Code 617, Greenbelt, MD 20771, USA.

出版信息

J Hydrol (Amst). 2018 Sep;564:559-573. doi: 10.1016/j.jhydrol.2018.07.030. Epub 2018 Jul 24.

Abstract

In this work, we have used the Soil & Water Assessment Tool (SWAT) to examine streamflow variability of the Lower Mekong River Basin (LMRB) associated with changes in the Upper Mekong River Basin (UMRB) inflows. Two hypothetical experiments were formulated and evaluated for the LMRB, where we conducted runoff simulations with multiple inflow changes that include upstream runoff yield increase and decrease scenarios. Streamflow variability of the LMRB was quantified by two streamflow metrics that explain flow variability and predictability, and high flow disturbance. The model experiments were performed for the Lower Mekong River Basin with identical climate, soil, and other watershed characteristics data. Remote sensing precipitation (Tropical Rainfall Measurement Mission, TRMM, and Global Precipitation Measurement mission, GPM), meteorological data as well as spatial data that include a digital elevation model, newly developed soil information (Harmonized World Soil Database, HWSD), and land use and land cover were processed as input to the LMRB model simulations. Observed daily streamflow data along the Lower Mekong River from Chiang Sean, Thailand to Kratie, Cambodia were used for calibration and validation. Our work results suggest that the Lower Mekong River streamflow is highly variable and has a low predictability (Colwell index of about 32%). We found that releasing more water from upstream Mekong during rainfall months by 30% would result in a reduction in the Lower Mekong streamflow predictability by about 21%. This reduction in predictability is mainly attributed to a decrease in the Contingency index. Our work shows that the ability to predict floods/droughts at the Lower Mekong River would be reduced if there is any anticipated change (i.e., increase/decrease) from UMRB releases. Our results also show that releasing more flows from the upstream Mekong would also affect flood duration and the frequency of flood occurrences downstream. The results of this work thus help to quantify the sensitivity of streamflow variability at the Lower Mekong River Basin to upstream anthropogenic changes.

摘要

在本研究中,我们使用土壤与水评估工具(SWAT)来研究湄公河流域下游(LMRB)的径流变化与湄公河流域上游(UMRB)入流变化之间的关系。针对湄公河流域下游设计并评估了两个假设实验,在实验中我们进行了多次入流变化的径流模拟,其中包括上游径流量增加和减少的情景。通过两个径流指标对湄公河流域下游的径流变化进行了量化,这两个指标解释了流量变化和可预测性以及高流量扰动。针对湄公河流域下游进行了模型实验,使用了相同的气候、土壤和其他流域特征数据。将遥感降水数据(热带降雨测量任务卫星,TRMM,以及全球降水测量任务卫星,GPM)、气象数据以及包括数字高程模型、新开发的土壤信息(统一世界土壤数据库,HWSD)和土地利用与土地覆盖的空间数据作为输入,用于湄公河流域下游的模型模拟。泰国清盛至柬埔寨桔井沿湄公河下游的实测日径流数据用于模型校准和验证。我们的研究结果表明,湄公河下游的径流变化很大且可预测性较低(科尔韦尔指数约为32%)。我们发现,在降雨月份从湄公河上游多放水30%会导致湄公河下游径流可预测性降低约21%。可预测性的这种降低主要归因于偶然性指数的下降。我们的研究表明,如果湄公河上游放水有任何预期变化(即增加/减少),那么预测湄公河下游洪水/干旱的能力将会降低。我们的结果还表明,从湄公河上游多放水也会影响下游洪水持续时间和洪水发生频率。因此,本研究结果有助于量化湄公河流域下游径流变化对上游人为变化的敏感性。

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