A comprehensive assessment of water storage dynamics and hydroclimatic extremes in the Chao Phraya River Basin during 2002-2020

被引:50
作者
Abhishek [1 ]
Kinouchi, Tsuyoshi [1 ]
Sayama, Takahiro [2 ]
机构
[1] Tokyo Inst Technol, Sch Environm & Soc, Yokohama, Kanagawa 2268503, Japan
[2] Kyoto Univ, Disaster Prevent Res Inst, Uji, Kyoto 6110011, Japan
关键词
GRACE-Follow On; Terrestrial water storage; Artificial neural network; Floods; Drought Potential Index; Hydrological fluxes; GRACE; FLOOD; DROUGHT; RUNOFF; MODELS; RISK;
D O I
10.1016/j.jhydrol.2021.126868
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A holistic assessment of the hydroclimatic extremes, which have caused tremendous environmental, societal, and economic losses globally, is imperative for the highly vulnerable Chao Phraya River Basin. In this study, the water storage dynamics and extremes in the basin during 2002-2020 were quantified, for the first time, using GRACE (Follow-On) based terrestrial water storage anomaly (TWSA) with the help of a novel artificial neural network-based model for the data gap filling. TWSA showed a linear trend of -1.12 +/- 0.05 cm yr(-1) (equivalent to a volumetric trend of -1.79 +/- 0.08 km(3) yr(-1)) in the basin, and segregation of the constituent components of TWS revealed that the groundwater storage is a significant contributor (45%) to TWS with a linear trend of -0.51 +/- 0.06 cm yr(-1) (-0.82 +/- 0.10 km(3) yr(-1)) followed by surface water storage (i,e., cumulative of the water storage in the reservoirs, flood inundation, and rivers) (36%) and soil moisture storage (19%). The hydroclimatic extremes detected in TWSA are primarily triggered by the variations in precipitation during the monsoon season (May to October) and further amplified by the subsequent water storage and abstraction. TWSA attained a maximum of 42.86 cm in October 2011 during severe floods of 2011 (similar to 95% increase in net precipitation during 2010 and 2011) and a minimum of -31.81 cm during the drought of May 2020 (similar to 82% decrease in net precipitation during 2019 and 2020). All other flood and drought events in some years, e.g., 2006, 2010, 2015, 2016, are also well recorded in TWSA, albeit with a lag time of up to a maximum of two months from precipitation. Further, the basin's increasing potential of severe drought, as assessed by the effective water-storagebased novel drought potential index (DPI), underscored the need for multifaceted water management essentially focused on the demand side rather than the supply side in the basin. The proposed framework can be utilized for policymaking for adequate and equitable water allocation, developing the early warning systems for the droughts and floods, and employing the optimal adaptation measures in the Chao Phraya River Basin and other data-scarce river basins globally.
引用
收藏
页数:13
相关论文
共 72 条
  • [1] Synergetic application of GRACE gravity data, global hydrological model, and in-situ observations to quantify water storage dynamics over Peninsular India during 2002-2017
    Abhishek
    Kinouchi, Tsuyoshi
    [J]. JOURNAL OF HYDROLOGY, 2021, 596
  • [2] Remotely sensed ensembles of the terrestrial water budget over major global river basins: An assessment of three closure techniques
    Abolafia-Rosenzweig, R.
    Pan, M.
    Zeng, J. L.
    Livneh, B.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2021, 252
  • [3] Anthropogenic Drought: Definition, Challenges, and Opportunities
    AghaKouchak, Amir
    Mirchi, Ali
    Madani, Kaveh
    Di Baldassarre, Giuliano
    Nazemi, Ali
    Alborzi, Aneseh
    Anjileli, Hassan
    Azarderakhsh, Marzi
    Chiang, Felicia
    Hassanzadeh, Elmira
    Huning, Laurie S.
    Mallakpour, Iman
    Martinez, Alexandre
    Mazdiyasni, Omid
    Moftakhari, Hamed
    Norouzi, Hamid
    Sadegh, Mojtaba
    Sadeqi, Dalal
    Van Loon, Anne F.
    Wanders, Niko
    [J]. REVIEWS OF GEOPHYSICS, 2021, 59 (02)
  • [4] Projection of near-future climate change and agricultural drought in Mainland Southeast Asia under RCP8.5
    Amnuaylojaroen, Teerachai
    Chanvichit, Pavinee
    [J]. CLIMATIC CHANGE, 2019, 155 (02) : 175 - 193
  • [5] Babel M. S., 2006, International Review for Environmental Strategies, V6, P307
  • [6] Beaudoing H., 2020, GLDAS Noah Land Surface Model L4 monthly 0.25 x 0.25 degree V2.1, DOI DOI 10.5067/SXAVCZFAQLNO
  • [7] Long-term groundwater storage variations estimated in the Songhua River Basin by using GRACE products, land surface models, and in-situ observations
    Chen, Hao
    Zhang, Wanchang
    Nie, Ning
    Guo, Yuedong
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 649 : 372 - 387
  • [8] The 2009 exceptional Amazon flood and interannual terrestrial water storage change observed by GRACE
    Chen, J. L.
    Wilson, C. R.
    Tapley, B. D.
    [J]. WATER RESOURCES RESEARCH, 2010, 46
  • [9] Basin-Scale River Runoff Estimation From GRACE Gravity Satellites, Climate Models, and In Situ Observations: A Case Study in the Amazon Basin
    Chen, Jianli
    Tapley, Byron
    Rodell, Matt
    Seo, Ki-Weon
    Wilson, Clark
    Scanlon, Bridget R.
    Pokhrel, Yadu
    [J]. WATER RESOURCES RESEARCH, 2020, 56 (10)
  • [10] Improved modeling of snow and glacier melting by a progressive two-stage calibration strategy with GRACE and multisource data: How snow and glacier meltwater contributes to the runoff of the Upper Brahmaputra River basin?
    Chen, Xi
    Long, Di
    Hong, Yang
    Zeng, Chao
    Yan, Denghua
    [J]. WATER RESOURCES RESEARCH, 2017, 53 (03) : 2431 - 2466