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A.B. van der Veen
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Endorheic basins cover roughly 20% of Earth’s land surface but account for 50% of water-stressed regions. The Aral Sea is perhaps the most dramatic example of environmental degredation in these systems; since 1960 more than 90 % of its water volume has been lost. Although the expansion of irrigated agriculture, increasing from 47,000 km² to 83,000 km², is generally considered the primary driver of this decline, the relative contribution of climate variability remains uncertain.
This study aims to quantify the relative influence of human water use and climate variability on the Aral Sea water balance using a fully reproducible modelling workflow implemented within the eWaterCycle environment. A reproducible model chain was designed and implemented using the eWaterCycle platform, which promotes FAIR (Findable, Accessible, Interoperable, Reusable) computational hydrology. New workflow components were developed for forcing generation, spatial regridding and downscaling, bias correction, and regional model calibration, and integrated as reusable tools within eWaterCycle.
Meteorological forcing was derived from ERA5 reanalysis data (1940–2020) for historical reconstruction and CMIP6 global climate models for future scenarios (2025–2100). Catchment hydrology was simulated using PCR-GLOBWB2 (PCRaster GLOBal Water Balance model, version 2) following regional calibration against observed discharge data. Simulated discharges were subsequently used as input as inflow to an Aral Volume Balance model developed for this study.
Methodologically, the study delivers a modular and reproducible workflow enabling consistent preparation and use of climate forcing data within eWaterCycle. The developed reprocessing tools allowed CMIP6 datasets to be directly applied in PCR-GLOBWB2 simulations, while bias correction substantially reduced temperature and precipitation biases. Regional calibration improved discharge simulations from double digit negative KGE to positive values.
Hydrologically, the coupled modelling framework successfully reproduced the observed desiccation trend of the Aral Sea, and showed the effect of different models and pathways on the future of the Aral Sea. The study demonstrates that the eWaterCycle platform can be used as a robust, transparent, and reusable workflow environment. The developed tools extend the capabilities of the eWaterCycle ecosystem and enable transparent, reusable hydrological experimentation for endorheic basins and other large-scale water systems. ...
This study aims to quantify the relative influence of human water use and climate variability on the Aral Sea water balance using a fully reproducible modelling workflow implemented within the eWaterCycle environment. A reproducible model chain was designed and implemented using the eWaterCycle platform, which promotes FAIR (Findable, Accessible, Interoperable, Reusable) computational hydrology. New workflow components were developed for forcing generation, spatial regridding and downscaling, bias correction, and regional model calibration, and integrated as reusable tools within eWaterCycle.
Meteorological forcing was derived from ERA5 reanalysis data (1940–2020) for historical reconstruction and CMIP6 global climate models for future scenarios (2025–2100). Catchment hydrology was simulated using PCR-GLOBWB2 (PCRaster GLOBal Water Balance model, version 2) following regional calibration against observed discharge data. Simulated discharges were subsequently used as input as inflow to an Aral Volume Balance model developed for this study.
Methodologically, the study delivers a modular and reproducible workflow enabling consistent preparation and use of climate forcing data within eWaterCycle. The developed reprocessing tools allowed CMIP6 datasets to be directly applied in PCR-GLOBWB2 simulations, while bias correction substantially reduced temperature and precipitation biases. Regional calibration improved discharge simulations from double digit negative KGE to positive values.
Hydrologically, the coupled modelling framework successfully reproduced the observed desiccation trend of the Aral Sea, and showed the effect of different models and pathways on the future of the Aral Sea. The study demonstrates that the eWaterCycle platform can be used as a robust, transparent, and reusable workflow environment. The developed tools extend the capabilities of the eWaterCycle ecosystem and enable transparent, reusable hydrological experimentation for endorheic basins and other large-scale water systems. ...
Endorheic basins cover roughly 20% of Earth’s land surface but account for 50% of water-stressed regions. The Aral Sea is perhaps the most dramatic example of environmental degredation in these systems; since 1960 more than 90 % of its water volume has been lost. Although the expansion of irrigated agriculture, increasing from 47,000 km² to 83,000 km², is generally considered the primary driver of this decline, the relative contribution of climate variability remains uncertain.
This study aims to quantify the relative influence of human water use and climate variability on the Aral Sea water balance using a fully reproducible modelling workflow implemented within the eWaterCycle environment. A reproducible model chain was designed and implemented using the eWaterCycle platform, which promotes FAIR (Findable, Accessible, Interoperable, Reusable) computational hydrology. New workflow components were developed for forcing generation, spatial regridding and downscaling, bias correction, and regional model calibration, and integrated as reusable tools within eWaterCycle.
Meteorological forcing was derived from ERA5 reanalysis data (1940–2020) for historical reconstruction and CMIP6 global climate models for future scenarios (2025–2100). Catchment hydrology was simulated using PCR-GLOBWB2 (PCRaster GLOBal Water Balance model, version 2) following regional calibration against observed discharge data. Simulated discharges were subsequently used as input as inflow to an Aral Volume Balance model developed for this study.
Methodologically, the study delivers a modular and reproducible workflow enabling consistent preparation and use of climate forcing data within eWaterCycle. The developed reprocessing tools allowed CMIP6 datasets to be directly applied in PCR-GLOBWB2 simulations, while bias correction substantially reduced temperature and precipitation biases. Regional calibration improved discharge simulations from double digit negative KGE to positive values.
Hydrologically, the coupled modelling framework successfully reproduced the observed desiccation trend of the Aral Sea, and showed the effect of different models and pathways on the future of the Aral Sea. The study demonstrates that the eWaterCycle platform can be used as a robust, transparent, and reusable workflow environment. The developed tools extend the capabilities of the eWaterCycle ecosystem and enable transparent, reusable hydrological experimentation for endorheic basins and other large-scale water systems.
This study aims to quantify the relative influence of human water use and climate variability on the Aral Sea water balance using a fully reproducible modelling workflow implemented within the eWaterCycle environment. A reproducible model chain was designed and implemented using the eWaterCycle platform, which promotes FAIR (Findable, Accessible, Interoperable, Reusable) computational hydrology. New workflow components were developed for forcing generation, spatial regridding and downscaling, bias correction, and regional model calibration, and integrated as reusable tools within eWaterCycle.
Meteorological forcing was derived from ERA5 reanalysis data (1940–2020) for historical reconstruction and CMIP6 global climate models for future scenarios (2025–2100). Catchment hydrology was simulated using PCR-GLOBWB2 (PCRaster GLOBal Water Balance model, version 2) following regional calibration against observed discharge data. Simulated discharges were subsequently used as input as inflow to an Aral Volume Balance model developed for this study.
Methodologically, the study delivers a modular and reproducible workflow enabling consistent preparation and use of climate forcing data within eWaterCycle. The developed reprocessing tools allowed CMIP6 datasets to be directly applied in PCR-GLOBWB2 simulations, while bias correction substantially reduced temperature and precipitation biases. Regional calibration improved discharge simulations from double digit negative KGE to positive values.
Hydrologically, the coupled modelling framework successfully reproduced the observed desiccation trend of the Aral Sea, and showed the effect of different models and pathways on the future of the Aral Sea. The study demonstrates that the eWaterCycle platform can be used as a robust, transparent, and reusable workflow environment. The developed tools extend the capabilities of the eWaterCycle ecosystem and enable transparent, reusable hydrological experimentation for endorheic basins and other large-scale water systems.