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

Abhishek, Abhishek; Kinouchi, Tsuyoshi; Sayama, Takahiro

doi:10.1016/j.jhydrol.2021.126868

Cited by 58 publications

(10 citation statements)

References 62 publications

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“…A multi-source dataset of P, ET, R, and ∆S from in situ observations, remote sensing satellites, and reanalysis output, as listed in table S1 (available online at stacks.iop.org/ERL/17/064006/mmedia), was comprehensively collected to ensure the reliability of our results by employing the ensemble approach to minimize the biases associated with any single dataset (Abhishek and Sayama 2021). Various datasets with their salient features are described in detail below.…”

Section: Datamentioning

confidence: 99%

“…Although the abovementioned studies have summarized the changes in RCs over many river basins, most of them merely focused on a limited size of watersheds, and a global assessment is still lacking due to the constraints of rainfall and runoff data (Ares et al 2020, He et al 2022. For instanse, the number of global hydrological and meteorological stations is decreasing due to substantial financial and material cost, causing interrupted time intervals, uneven spatial distribution, and sparse spatial coverage of precipitation and runoff measurements (Abhishek and Sayama 2021). Despite this, the effect of alternative hydrological fluxes (i.e.…”

Section: Introductionmentioning

confidence: 99%

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Annual runoff coefficient variation in a changing environment: a global perspective

Xiong

Yin

Guo

et al. 2022

Environ. Res. Lett.

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Assessing variations in the annual runoff coefficient (RC) on a basin scale is crucial for understanding the hydrological cycle under natural and anthropogenic changes, yet a systematic global assessment remains unexamined from a water-balance perspective. Here, we combine observation-based runoff and precipitation datasets to quantify basin-averaged RC changes in 433 major global river basins during the period 1985–2014. Thereafter, the ratios of terrestrial water storage changes and evaporation to precipitation (SC and EC, respectively) are obtained to evaluate the factors driving the RC changes. The results show that 12.93% of the basins experience significant decreasing trends in RC, with slopes ranging from −0.55 ± 0.17% yr−1 to −0.05 ± 0.02% yr−1, while 6.47% basins show increasing RCs with slopes ranging from 0.09 ± 0.04% yr−1 to 0.56 ± 0.17% yr−1. A higher percentage (62.95%) of basins reveal decreasing RCs for the regions with considerable human intervention compared to those (58.24%) with dominant natural variability. Changes in EC dominate the RC changes over 79.68% of the basins for both increasing and decreasing trends, with a maximum contribution (53.65%) from transpiration, among other partitioned components. Corroborated inferences from explicit investigation in the Yangtze River basin highlight the robustness of our results for global water managers and policymakers.

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Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Annual runoff coefficient variation in a changing environment: a global perspective

Xiong

Yin

Guo

et al. 2022

Environ. Res. Lett.

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“…In this study, we further propose a new normalized daily flood potential index (NDFPI) with reference to Reager and Famiglietti (2009) and Abhishek et al (2021). Compared to the original flood potential index, the NDFPI can not only provide useful information on the early signs of the region's transition from a normal state to a flood-prone situation, but also effectively detect the flood events at sub-monthly timescales, which is calculated via the following steps:…”

Section: Daily Flood Potential Indexmentioning

confidence: 99%

Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data

Xie

Xu²,

Yu³

et al. 2022

Hydrol. Earth Syst. Sci.

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Abstract. Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-on (GRACE-FO) satellite provide terrestrial water storage anomaly (TWSA) estimates globally that can be used to monitor flood in various regions at monthly intervals. However, the coarse temporal resolution of GRACE and GRACE-FO satellite data has been limiting their applications at finer temporal scales. In this study, TWSA estimates have been reconstructed and then temporally downscaled into daily values based on three different learning-based models, namely a multi-layer perceptron (MLP) model, a long-short term memory (LSTM) model and a multiple linear regression (MLR) model. Furthermore, a new index incorporating temporally downscaled TWSA estimates combined with daily average precipitation anomalies is proposed to monitor the severe flood events at sub-monthly timescales for the Yangtze River basin (YRB), China. The results indicated that (1) the MLP model shows the best performance in reconstructing the monthly TWSA with root mean square error (RMSE) = 10.9 mm per month and Nash–Sutcliffe efficiency (NSE) = 0.89 during the validation period; (2) the MLP model can be useful in temporally downscaling monthly TWSA estimates into daily values; (3) the proposed normalized daily flood potential index (NDFPI) facilitates robust and reliable characterization of severe flood events at sub-monthly timescales; (4) the flood events can be monitored by the proposed NDFPI earlier than traditional streamflow observations with respect to the YRB and its individual subbasins. All these findings can provide new opportunities for applying GRACE and GRACE-FO satellite data to investigations of sub-monthly signals and have important implications for flood hazard prevention and mitigation in the study region.

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“…A few indexes like the standardised soil moisture index (SSI), standardised groundwater index (SGI), and standardised runoff index (SRI), however, focus on a single aspect of the water cycle and do not describe the integrated status of the terrestrial water storage (TWS) (AghaKouchak, 2014;Wu et al, 2018;Guo et al, 2021). In the coupled human-natural systems, where the synergistic impacts of natural and anthropogenic drivers are exceedingly difficult to disentangle, an integrated representation of the land systems is of paramount importance for policymakers (Abhishek et al, 2021;Rodell et al, 2018). TWS, consisting of water storage in surface water, soil moisture, groundwater, snow and ice, and canopies, can physically provide integrated information about the overall status of the land, whose changes are closely linked to the terrestrial wetting and drying tendency (Tapley et al, 2019;Pokhrel et al, 2021).…”

mentioning

confidence: 99%

“…Apart from the societal and economic importance, TWS plays a vital role in Earth system processes, including climate, weather, and biogeochemical cycles (Abhishek et al, 2021, Seyoum andMilewski, 2017). Therefore, understanding the past and future TWS trends dynamics is not only essential for human life but also crucial for assessing the water cycle, planning, policymaking, and other management strategies for water resources in a changing climate and for a continuously increasing population (Abhishek et al, 2021). There are several studies dealing with TWS or derived indicators to assess freshwater availability (Rodell et al, 2018), water storage dynamics (Abhishek et al, 2021, Scanlon et al, 2018, droughts and floods monitoring https://doi.org/10.…”

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confidence: 99%

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Guo

2022

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

Cited by 58 publications

References 62 publications

Annual runoff coefficient variation in a changing environment: a global perspective

Annual runoff coefficient variation in a changing environment: a global perspective

Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data

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