Xanthos – A Global Hydrologic Model

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad; Link, Robert; Feng, Leyang; Liu, Yaling; Rauchenstein, Lynn T.

doi:10.5334/jors.181

Cited by 24 publications

(19 citation statements)

References 10 publications

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“…We have released the version of the specific HE v1.0.0 referenced in this paper at https: //github.com/JGCRI/hydro-emulator/releases/tag/v1.0.0, where the source code (written in Matlab), all related inputs, calibrated parameters and outputs for each of the global 235 basins as well as the user manual are available. In addition, the HE documented here has been translated into Python and is being incorporated into Xanthos (Li et al, 2017), which is an open-source global hydrologic model that allows users to run different combinations of evapotranspiration, runoff, and routing models. The HE will be the default runoff model used in Xanthos 2.0 and will be available on GitHub (https://github.com/JGCRI/xanthos).…”

Section: Resultsmentioning

confidence: 99%

A hydrological emulator for global applications – HE v1.0.0

Liu

Hejazi

et al. 2018

Geosci. Model Dev.

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Abstract. While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluated in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean KlingGupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.

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Section: Resultsmentioning

confidence: 99%

A hydrological emulator for global applications – HE v1.0.0

Liu

Hejazi

et al. 2018

Geosci. Model Dev.

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“…We calculate each of these impacts by using downscaled and bias-corrected climate data from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) 51 . The global hydrologic model, Xanthos [52][53][54] , calculates climate derived changes to renewable water supply at the GCAM 235-basin scale using necessary GCM outputs. Climate derived impacts to crop yield changes 55 , hydropower availability 56 , and building energy demands 57 are calculated from the same set of ISI-MIP models and the climate varying impacts are added to the SSP2 scenario.…”

Section: Methodsmentioning

confidence: 99%

Future changes in the trading of virtual water

et al. 2020

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Water stressed regions rely heavily on the import of water-intensive goods to offset insufficient food production driven by socioeconomic and environmental factors. The water embedded in these traded commodities, virtual water, has received increasing interest in the scientific community. However, comprehensive future projections of virtual water trading remain absent. Here we show, for the first time, changes over the 21 st century in the amount of various water types required to meet international agricultural demands. Accounting for evolution in socioeconomic and climatic conditions, we estimate future interregional virtual water trading and find trading of renewable water sources may triple by 2100 while nonrenewable groundwater trading may at least double. Basins in North America, and the La Plata and Nile Rivers are found to contribute extensively to virtual water exports, while much of Africa, India, and the Middle East relies heavily on virtual water imports by the end of the century.

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“…This function is designed to be used with specific open-source downscaling models (Xanthos [18], Demeter [19], and Tethys [20]) that downscale GCAM data to the grid level. The function takes outputs from these various models and processes them into the format required for providing input to the metis.mapsProcess.R function.…”

Section: Metisprepgridrmentioning

confidence: 99%

Metis – A Tool to Harmonize and Analyze Multi-Sectoral Data and Linkages at Variable Spatial Scales

Khan¹,

Wild²,

Vernon³

et al. 2020

JORS

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Metis was developed to allow users to analyze regional and sub-regional multi-sector dynamics by providing a platform to harmonize and amalgamate data from different models and stakeholders operating at variable spatial scales. Metis is an open-source R package hosted on GitHub. Metis functions collectively allow users to compare, manipulate, and harmonize multi-sector data at user-specified spatial scales, and to identify and quantify sectoral inter-linkages. Each Metis function can also be used independently to support an array of other research applications, such as spatial analysis and data visualization.

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Xanthos – A Global Hydrologic Model

Cited by 24 publications

References 10 publications

A hydrological emulator for global applications – HE v1.0.0

A hydrological emulator for global applications – HE v1.0.0

Future changes in the trading of virtual water

Metis – A Tool to Harmonize and Analyze Multi-Sectoral Data and Linkages at Variable Spatial Scales

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