2023
DOI: 10.1016/j.gsd.2023.100953
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Quantifying basin-scale changes in groundwater storage using GRACE and one-way coupled hydrological and groundwater flow model in the data-scarce Bandung groundwater Basin, Indonesia

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Cited by 10 publications
(4 citation statements)
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“…We use (a) SoilGrids database (Hengl et al, 2017) for soil-related parameters estimation, (b) Monthly Leaf Area Index climatology for daily interception calculation (Gash, 1979), (c) MERIT-DEM dataset (Yamazaki et al, 2017) for river network delineation (Eilander et al, 2020), and (d) vito land use map (Buchhorn et al, 2020) for deriving land-use related parameters. The M axLeakage parameter is calibrated by optimizing the KGE value between the observed and the simulated discharge (Rusli et al, 2023a).…”
Section: Bias Adjustment and Statistical Downscaling Methods Of Isimip3bmentioning
confidence: 99%
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“…We use (a) SoilGrids database (Hengl et al, 2017) for soil-related parameters estimation, (b) Monthly Leaf Area Index climatology for daily interception calculation (Gash, 1979), (c) MERIT-DEM dataset (Yamazaki et al, 2017) for river network delineation (Eilander et al, 2020), and (d) vito land use map (Buchhorn et al, 2020) for deriving land-use related parameters. The M axLeakage parameter is calibrated by optimizing the KGE value between the observed and the simulated discharge (Rusli et al, 2023a).…”
Section: Bias Adjustment and Statistical Downscaling Methods Of Isimip3bmentioning
confidence: 99%
“…For the groundwater abstraction projection, we consider three diverging scenarios where the groundwater abstraction (a) increases, (b) stays constant, and (c) decreases in the future. Meanwhile, the groundwater abstraction during the baseline period is set according to estimates from our previous studies (Rusli et al, 2023a), increasing annually from 300 Mm 3 per year in 2005 to 495 Mm 3 per year in 2020. For all boundary conditions, the groundwater abstraction is distributed horizontally based on land use and vertically based on domestic/industrial water demand classification.…”
Section: Groundwater Abstraction Scenariosmentioning
confidence: 99%
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