Scientific Data, Journal Year: 2024, Volume and Issue: 11(1)
Published: Sept. 17, 2024
Language: Английский
Journal of Hydrology, Journal Year: 2024, Volume and Issue: 638, P. 131542 - 131542
Published: June 16, 2024
Language: Английский
Citations
5
Geoscientific model development, Journal Year: 2024, Volume and Issue: 17(8), P. 3559 - 3578
Published: May 2, 2024
Abstract. This article describes a modular ensemble-based data assimilation (DA) system which is developed for an integrated surface–subsurface hydrological model. The software environment DA the Parallel Data Assimilation Framework (PDAF), provides various algorithms like ensemble Kalman filters, non-linear 3D-Var and combinations among them. model HydroGeoSphere (HGS), physically based modelling simulation of surface variably saturated subsurface flow, as well heat mass transport. coupling capabilities are described demonstrated using idealised geologically heterogeneous alluvial river–aquifer with drinking water production via riverbank filtration. To demonstrate its modularity adaptability, both single multivariate assimilations hydraulic head soil moisture observations in combination individual joint updating multiple simulated states (i.e. heads saturation) parameters conductivity). With this framework, we have essentially hydrologically DA-wise robust toolbox developing basic operational management coupled water–groundwater resources.
Language: Английский
Citations
3
Journal of Geophysical Research Atmospheres, Journal Year: 2025, Volume and Issue: 130(3)
Published: Feb. 1, 2025
Abstract The primary objective of the GRACE Follow‐On satellite mission is to measure temporal changes in Earth's gravitational field. Distance variations between two GRACE‐FO satellites, recorded by a K‐Band Ranging system and new Laser Interferometer (LRI), are significantly influenced atmospheric mass redistribution. We investigate whether sub‐monthly water mass, precipitation, total storage during extreme flood event western Europe 2021 were sufficiently large influence gravity field measurements, if satellites would have passed directly over region. use several data sets such as weather forecasts (ICON‐D2 model), hydrological simulations (ParFlow/CLM), observations well reanalyses, showing high uncertainty different estimations considered variables: precipitable water, storage. Our estimates suggest potentially noticeable impact on satellites. Although it was globally seen rather small event, even beyond vapor, which not within de‐aliasing process, close LRI detection accuracy. This particularly relevant for future missions, will with higher sensitivity their main instrument. Sub‐monthly that is, vapor huge precipitation events should be investigated further reduce potential aliasing errors.
Language: Английский
Citations
0
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: March 7, 2025
Evapotranspiration is a key component of the hydrological cycle, influencing water and biogeochemical cycles in critical zone. Particularly, travel time evapotranspired for describing origin young contribution to evapotranspiration, but yet poorly understood. In this study, we revisited Lagrangian particle-tracking model, EcoSLIM, separate evaporation transpiration particles using mass balance approach. This separation allowed us determine distribution with different sources (i.e., rainfall, snowmelt, pre-stored groundwater) captured by transpiration. We validated against those computed physically-based ParFlow-CLM which yields expected target fluxes simulating physical processes controlling energy balances. Our results demonstrated high accuracy modified EcoSLIM closing balance, as evidenced R2 > 0.9 between tracked masses fluxes. Using further studied impact plant growth cycle vertical root on source partitioning via hillslope-scale virtual experiments. The three scenarios phenology indicated that depth state synchronicity climatic forcing timing influence times available plants contrasting ways. Finally, found show preference ages, unless deep rooting network allows extraction old ages during dry periods.
Language: Английский
Citations
0
Frontiers in Earth Science, Journal Year: 2025, Volume and Issue: 13
Published: April 1, 2025
Accurate precipitation data are crucial for many sectors and applications, like managing water resources, agriculture, or assessing the risks of hydrometeorological extreme events floods droughts, which expected to further increase with climate change. This study compares spatial temporal characteristics ten state-of-the-art, commonly used datasets, each other against reference in situ gauge observations from European Climate Assessment & Dataset (ECA&D) over Germany. The objectives evaluate whether bias adjustment is needed Centre Medium-Range Weather Forecasts (ECMWF) High Resolution (HRES) meteorological forecasting dataset, near real-time resources modeling ParFlow integrated hydrologic model, if so, assess any observation-based comparison datasets might be suitable this adjustment. Results show that HRES Reanalysis v5 (ERA5) capture patterns well, albeit deficits reproducing extremes, over- underestimation at low high altitudes, respectively. COSMO-REAnalysis (COSMO-REA6) captures less effectively but outperforms ERA5 events. HYRAS-DE-PRE (HYRAS), Radar Online Adjustment (RADOLAN), Radarklimatologie (RADKLIM) perform very showing strong accuracy potential adjustment, though their limited coverage potentially restricts use across all river catchments affecting Operational Program Exchange Information (OPERA) tends underestimate mean quantities Integrated Multi-satellite Retrievals Global Precipitation Measurement (IMERG) Final shows an improvement IMERG-Late. EUropean RADar CLIMatology (EURADCLIM) OPERA due adjustments. methodology findings may also applicable similar evaluations regions, help selection e.g., hydrological model forcing
Language: Английский
Citations
0
Hydrology and earth system sciences, Journal Year: 2025, Volume and Issue: 29(9), P. 2201 - 2218
Published: May 12, 2025
Abstract. Large-scale hydrologic modeling at the national scale is an increasingly important effort worldwide to tackle ecohydrologic issues induced by global water scarcity. In this study, a surface water–groundwater integrated platform was built using ParFlow, covering entirety of continental China with resolution 30 arcsec. This model, CONCN 1.0, offers full treatment 3D variably saturated groundwater solving Richards' equation, along shallow-water equation ground surface. The performance 1.0 rigorously evaluated both data products and observations. RSR values (the ratio root mean squared error standard deviation observations) show satisfying regard streamflow, yet streamflow lower in endorheic, Hai, Liao rivers due uncertainties potential recharge. also indicate terms table depth model. intermediate compared two models, highlighting that persist current large-scale modeling. Our work comprehensive evaluation workflow for continental-scale ParFlow could be good starting point other regions worldwide, even when different systems. More specifically, vast arid semi-arid substantial sinks (i.e., endpoints endorheic rivers) large recharge pose challenges numerical solution model performance, respectively. Incompatibilities between such as mismatch spatial resolutions models shorter, less frequent observation records, necessitate further refinement enable fast not only establishes first efficient resources management but will benefit improvement next-generation worldwide.
Language: Английский
Citations
0
ARPHA Conference Abstracts, Journal Year: 2025, Volume and Issue: 8
Published: May 28, 2025
In recent years, alternating drought and extreme precipitation events have highlighted the need for subseasonal to seasonal forecasts of terrestrial water cycle. particular, predictions impacts dry wet extremes on groundwater resources are crucial assess scarcity excess ecosystem dynamics as well provide stakeholders in agriculture, forestry, sector, other fields with information supporting sustainable use these resources. this context, we calculate four times per year probabilistic hydrological at 0.6 km resolution, from surface down 60 m depth, upcoming seven months over Germany surrounding regions (hydrological Germany). These generated using integrated, physics-based model ParFlow/CLM (Kuffour et al. 2020) setup described Belleflamme (2023), forced by 50 ensemble members SEAS5 forecast European Centre Medium-Range Weather Forecasts (ECMWF). The predicted evolution cycle is released beginning each meteorological season total subsurface storage anomaly our experimental Water Resources Bulletin (https://adapter-projekt.de/bulletin/index.html). To evaluate forecasts, evaluated six 7-months covering vegetation period (March September) years 2018 2023 a reference long-term historical time series based same setup. skill was assessed comparing climatology-based 10-member pseudo-forecast 2013–2023 (using leave-one-out method), extracted series. monthly Continuous Ranked Probability Skill Score (CRPSS), which evaluates distribution daily table depth data, indicates that outperforms most regions, except and, lesser extent, 2020 2022 (see Fig. 1). This can be attributed an under-representation extremely ensemble, combined memory effect initial conditions increasing soil depths. For example, while March started slightly below-average experienced strong leading agricultural eventually increase (i.e., depletion), 2019 already positive, less pronounced deficit during period. resulted much higher skill, because accurately simulated model. Notably, only decreases lead time, both depth. analysis Relative Operating Characteristic (ROCSS) upper quintile assesses whether positive anomalies droughts) adequately represented within ensemble. results consistent those CRPSS, showing lower 2018. Nevertheless, ROCSS overall high forecast, demonstrates no skill. means covers sufficiently wide range possible scenarios include order magnitude droughts central Europe years. conclude, evaluation confirms were captured underlining added value their potential usefulness predicting assessing impact fluctuations functioning dynamics.
Language: Английский
Citations
0
Frontiers in Water, Journal Year: 2025, Volume and Issue: 7
Published: June 5, 2025
In mid-July 2021, a quasi-stationary extratropical cyclone over parts of western Germany and eastern Belgium led to unprecedented sustained widespread precipitation, nearly doubling climatological monthly rainfall amounts in less than 72 h. This resulted extreme flooding many the Eifel-Ardennes low mountain range river catchments with loss lives, substantial damage destruction. Despite reconstructions event, open issues on underlying physical mechanisms remain. numerical laboratory approach based 52-member spatially temporally consistent high-resolution hindcast reconstruction event integrated hydrological surface-subsurface model ParFlow, this study shows prognostic capabilities ParFlow further explores event. Within ensemble, simulations can reproduce timing order magnitude flood without additional calibration or tuning. What stands out is large effective buffer capacity soil. simulations, upper soil highly affected Ahr, Erft, Kyll are able between about one third half precipitation that does not contribute immediately streamflow response leading eventually widespread, very high moisture saturation levels. case Vesdre catchment, due its initially higher water levels, buffering lower; hence more transferred into discharge.
Language: Английский
Citations
0
International Journal of Environmental Studies, Journal Year: 2024, Volume and Issue: 81(2), P. 570 - 586
Published: Feb. 28, 2024
Relationships between soil water saturation (SWS) and the accumulation of arsenic (As), cadmium (Cd), lead (Pb) in soils aboveground biomass Populus tremula Salix caprea were explored. SWS was computed with hydrological model ParFlow/CLM compared to data from field observations. Plant samples collected at main pollution sources contained highest concentrations As, Cd, Pb. S. higher Pb than P. tremula. In both species, metal(loid) leaves significantly branches. At strongly mining-affected locations, metalloid concentration trees largely reflected levels soil. remote study soil–plant transfer Cd affected by saturation: element increased moisture. Results demonstrate that coupling observations modelling is a promising approach for estimating accumulation.
Language: Английский
Citations
1
Frontiers in Water, Journal Year: 2024, Volume and Issue: 6
Published: Oct. 2, 2024
Integrated hydrological model (IHM) forecasts provide critical insights into system states, fluxes, and its evolution of water resources associated risks, essential for many sectors stakeholders in agriculture, urban planning, forestry, or ecosystem management. However, the accuracy these depends on data quality precipitation forcing data. Previous studies have utilized data-driven methods, such as deep learning (DL) during preprocessing phase to improve obtained from numerical weather prediction simulations. Nonetheless, challenges related spatiotemporal variability hourly persist, including issues with ground truth availability, imbalance training DL models, method evaluation. This study compares three (near) real-time datasets be used aforementioned IHM forecast systems: (1) 24 h by ECMWF’s 10-day HRES deterministic forecast, (2) H-SAF h61 satellite observations reference, (3) DL-based corrected using a U-Net convolutional neural network (CNN). As high-resolution data, is both reference correcting stand-alone candidate These are (~0.6 km) integrated hydrologic simulations ParFlow/CLM over central Europe April 2020 December 2022. Soil moisture (SM) diagnostic downstream variable evaluating impact The correction reduces gap between 49, 33, 12% mean error, root square Pearson correlation, respectively. comparison SM ESA CCI reveals better agreement uncorrected 24-h In conclusion, satellite-based falls short representing compared lead time forecasts. emphasizes need more reliable spatiotemporally continuous improving demonstrates potential methods near pre-processor quasi-operational forecasting workflows. preprocessor directly proportional applied observation.
Language: Английский
Citations
1