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Journal articles on the topic 'ParFlow/CLM'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Zhao, Haojin, Carsten Montzka, Roland Baatz, Harry Vereecken, and Harrie-Jan Hendricks Franssen. "The Importance of Subsurface Processes in Land Surface Modeling over a Temperate Region: An Analysis with SMAP, Cosmic Ray Neutron Sensing and Triple Collocation Analysis." Remote Sensing 13, no. 16 (2021): 3068. http://dx.doi.org/10.3390/rs13163068.

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Land surface models (LSMs) simulate water and energy cycles at the atmosphere–soil interface, however, the physical processes in the subsurface are typically oversimplified and lateral water movement is neglected. Here, a cross-evaluation of land surface model results (with and without lateral flow processes), the National Aeronautics and Space Administration (NASA) Soil Moisture Active/Passive (SMAP) mission soil moisture product, and cosmic-ray neutron sensor (CRNS) measurements is carried out over a temperate climate region with cropland and forests over western Germany. Besides a tradition

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2

Naz, Bibi S., Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet. "Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe." Geoscientific Model Development 16, no. 6 (2023): 1617–39. http://dx.doi.org/10.5194/gmd-16-1617-2023.

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Abstract. High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications, including water resource management. However, many of the existing global- to continental-scale hydrological models are applied at coarse resolution and neglect more complex processes such as lateral surface and groundwater flow, thereby not capturing smaller-scale hydrologic processes. Applications of high-resolution and physically based integrated hydrological models are often limited to watershed scales, neglecting the mesoscale climate effects on the water cycl

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3

Shrestha, P., M. Sulis, M. Masbou, S. Kollet, and C. Simmer. "A Scale-Consistent Terrestrial Systems Modeling Platform Based on COSMO, CLM, and ParFlow." Monthly Weather Review 142, no. 9 (2014): 3466–83. http://dx.doi.org/10.1175/mwr-d-14-00029.1.

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A highly modular and scale-consistent Terrestrial Systems Modeling Platform (TerrSysMP) is presented. The modeling platform consists of an atmospheric model (Consortium for Small-Scale Modeling; COSMO), a land surface model (the NCAR Community Land Model, version 3.5; CLM3.5), and a 3D variably saturated groundwater flow model (ParFlow). An external coupler (Ocean Atmosphere Sea Ice Soil, version 3.0; OASIS3) with multiple executable approaches is employed to couple the three independently developed component models, which intrinsically allows for a separation of temporal–spatial modeling scal

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4

Xu, Zexuan, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman. "Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin." Hydrology and Earth System Sciences 27, no. 9 (2023): 1771–89. http://dx.doi.org/10.5194/hess-27-1771-2023.

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Abstract. Mountain hydrology is controlled by interacting processes extending from the atmosphere through the bedrock. Integrated process models (IPMs), one of the main tools needed to interpret observations and refine conceptual models of the mountainous water cycle, require meteorological forcing that simulates the atmospheric process to predict hydroclimate then subsequently impacts surface–subsurface hydrology. Complex terrain and extreme spatial heterogeneity in mountainous environments drive uncertainty in several key considerations in IPM configurations and require further quantificatio

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5

Hein, Annette, Laura Condon, and Reed Maxwell. "Evaluating the relative importance of precipitation, temperature and land-cover change in the hydrologic response to extreme meteorological drought conditions over the North American High Plains." Hydrology and Earth System Sciences 23, no. 4 (2019): 1931–50. http://dx.doi.org/10.5194/hess-23-1931-2019.

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Abstract. Drought is a natural disaster that may become more common in the future under climate change. It involves changes to temperature, precipitation and/or land cover, but the relative contributions of each of these factors to overall drought severity is not clear. Here we apply a high-resolution integrated hydrologic model of the High Plains to explore the individual importance of each of these factors and the feedbacks between them. The model was constructed using ParFlow-CLM, which represents surface and subsurface processes in detail with physically based equations. Numerical experime

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6

Belleflamme, Alexandre, Suad Hammoudeh, Klaus Goergen, and Stefan Kollet. "Assessment of the skill of seasonal probabilistic water table depth forecasts with the hydrological model ParFlow/CLM over central Europe." ARPHA Conference Abstracts 8 (May 28, 2025): e151700. https://doi.org/10.3897/aca.8.e151700.

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In recent years, alternating drought and extreme precipitation events have highlighted the need for subseasonal to seasonal forecasts of the terrestrial water cycle. In particular, predictions of the impacts of dry and wet extremes on groundwater resources are crucial to assess the impacts of groundwater scarcity and excess on ecosystem dynamics as well as to provide stakeholders in agriculture, forestry, the water sector, and other fields with information supporting the sustainable use of these resources.In this context, we calculate four times per year seasonal probabilistic hydrological for

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7

Gupta, Aniket, Alix Reverdy, Jean-Martial Cohard, et al. "Impact of distributed meteorological forcing on simulated snow cover and hydrological fluxes over a mid-elevation alpine micro-scale catchment." Hydrology and Earth System Sciences 27, no. 1 (2023): 191–212. http://dx.doi.org/10.5194/hess-27-191-2023.

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Abstract. From the micro- to the mesoscale, water and energy budgets of mountainous catchments are largely driven by topographic features such as terrain orientation, slope, steepness, and elevation, together with associated meteorological forcings such as precipitation, solar radiation, and wind speed. Those topographic features govern the snow deposition, melting, and transport, which further impacts the overall water cycle. However, this microscale variability is not well represented in Earth system models due to coarse resolutions. This study explores the impact of precipitation, shortwave

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8

Hinderer, J., B. Hector, U. Riccardi, et al. "A study of the monsoonal hydrology contribution using a 8-yr record (2010–2018) from superconducting gravimeter OSG-060 at Djougou (Benin, West Africa)." Geophysical Journal International 221, no. 1 (2020): 431–39. http://dx.doi.org/10.1093/gji/ggaa027.

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SUMMARY We analyse a nearly 8-yr record (2010–2018) of the superconducting gravimeter OSG-060 located at Djougou (Benin, West Africa). After tidal analysis removing all solid Earth and ocean loading tidal contributions and correcting for the long-term instrumental drift and atmospheric loading, we obtain a gravity residual signal which is essentially a hydrological signal due to the monsoon. This signal is first compared to several global hydrology models (ERA, GLDAS and MERRA). Our superconducting gravimeter residual signal is also superimposed onto episodic absolute gravity measurements and

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9

Jefferson, Jennifer L., Reed M. Maxwell, and Paul G. Constantine. "Exploring the Sensitivity of Photosynthesis and Stomatal Resistance Parameters in a Land Surface Model." Journal of Hydrometeorology 18, no. 3 (2017): 897–915. http://dx.doi.org/10.1175/jhm-d-16-0053.1.

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Abstract Land surface models, like the Common Land Model component of the ParFlow integrated hydrologic model (PF-CLM), are used to estimate transpiration from vegetated surfaces. Transpiration rates quantify how much water moves from the subsurface through the plant and into the atmosphere. This rate is controlled by the stomatal resistance term in land surface models. The Ball–Berry stomatal resistance parameterization relies, in part, on the rate of photosynthesis, and together these equations require the specification of 20 input parameters. Here, the active subspace method is applied to 2

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10

O'Neill, Mary M. F., Danielle T. Tijerina, Laura E. Condon, and Reed M. Maxwell. "Assessment of the ParFlow–CLM CONUS 1.0 integrated hydrologic model: evaluation of hyper-resolution water balance components across the contiguous United States." Geoscientific Model Development 14, no. 12 (2021): 7223–54. http://dx.doi.org/10.5194/gmd-14-7223-2021.

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Abstract. Recent advancements in computational efficiency and Earth system modeling have awarded hydrologists with increasingly high-resolution models of terrestrial hydrology, which are paramount to understanding and predicting complex fluxes of moisture and energy. Continental-scale hydrologic simulations are, in particular, of interest to the hydrologic community for numerous societal, scientific, and operational benefits. The coupled hydrology–land surface model ParFlow–CLM configured over the continental United States (PFCONUS) has been employed in previous literature to study scale-depen

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11

Gilbert, James M., and Reed M. Maxwell. "Examining regional groundwater–surface water dynamics using an integrated hydrologic model of the San Joaquin River basin." Hydrology and Earth System Sciences 21, no. 2 (2017): 923–47. http://dx.doi.org/10.5194/hess-21-923-2017.

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Abstract. Widespread irrigated agriculture and a growing population depend on the complex hydrology of the San Joaquin River basin in California. The challenge of managing this complex hydrology hinges, in part, on understanding and quantifying how processes interact to support the groundwater and surface water systems. Here, we use the integrated hydrologic platform ParFlow-CLM to simulate hourly 1 km gridded hydrology over 1 year to study un-impacted groundwater–surface water dynamics in the basin. Comparisons of simulated results to observations show the model accurately captures important

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12

Soltani, Samira Sadat, Marwan Fahs, Ahmad Al Bitar, and Behzad Ataie-Ashtiani. "Improvement of soil moisture and groundwater level estimations using a scale‐consistent river parameterization for the coupled ParFlow-CLM hydrological model: A case study of the Upper Rhine Basin." Journal of Hydrology 610 (July 2022): 127991. http://dx.doi.org/10.1016/j.jhydrol.2022.127991.

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13

Schalge, Bernd, Gabriele Baroni, Barbara Haese, et al. "Presentation and discussion of the high-resolution atmosphere–land-surface–subsurface simulation dataset of the simulated Neckar catchment for the period 2007–2015." Earth System Science Data 13, no. 9 (2021): 4437–64. http://dx.doi.org/10.5194/essd-13-4437-2021.

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Abstract. Coupled numerical models, which simulate water and energy fluxes in the subsurface–land-surface–atmosphere system in a physically consistent way, are a prerequisite for the analysis and a better understanding of heat and matter exchange fluxes at compartmental boundaries and interdependencies of states across these boundaries. Complete state evolutions generated by such models may be regarded as a proxy of the real world, provided they are run at sufficiently high resolution and incorporate the most important processes. Such a simulated reality can be used to test hypotheses on the f

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14

Hector, Basile, Jean-Martial Cohard, Luc Séguis, Sylvie Galle, and Christophe Peugeot. "Hydrological functioning of western African inland valleys explored with a critical zone model." Hydrology and Earth System Sciences 22, no. 11 (2018): 5867–88. http://dx.doi.org/10.5194/hess-22-5867-2018.

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Abstract. Inland valleys are seasonally waterlogged headwater wetlands, widespread across western Africa. Their role in the hydrological cycle in the humid, hard-rock-dominated Sudanian savanna is not yet well understood. Thus, while in the region recurrent floods are a major issue, and hydropower has been recognized as an important development pathway, the scientific community lacks precise knowledge of streamflow (Q) generation processes and how they could be affected by the presence of inland valleys. Furthermore, inland valleys carry an important agronomic potential, and with the strong de

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15

Reed, M. Maxwell, J. Kollet Stefan, G. Smith Steven, et al. "ParFlow a6c81a763c058d551dc60a032e8ceeba0ae94fc6." May 25, 2020. https://doi.org/10.5281/zenodo.4008861.

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ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR co

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16

Zhao, Haojin, Carsten Montzka, Johannes Keller, Fang Li, Harry Vereecken, and Harrie‐Jan Hendricks Franssen. "How Does Assimilating SMAP Soil Moisture Improve Characterization of the Terrestrial Water Cycle in an Integrated Land Surface‐Subsurface Model?" Water Resources Research 61, no. 6 (2025). https://doi.org/10.1029/2024wr038647.

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AbstractLand surface modeling combined with data assimilation can yield highly accurate soil moisture estimates on regional and global scales. However, most land surface models often neglect lateral surface and subsurface flows, which are crucial for water redistribution and soil moisture. This study applies the Community Land Model (CLM) and the coupled CLM‐ParFlow model over a 22,500 area in western Germany. Soil moisture retrievals from the Soil Moisture Active Passive mission are assimilated with the Localized Ensemble Kalman Filter (with and without parameter estimation). The simulated so

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17

Naz, Bibi S. "3 km ParFlow-CLM model simulations over EU-CORDEX." Geoscientific Model Development, March 10, 2023. https://doi.org/10.5281/zenodo.7716900.

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This dataset consists of a 10 years (1997–2006) high-resolution ParFlow-CLM model outputs over Europe. This dataset was created by running the integrated land surface and groundwater ParFlow-CLM model at 3 km resolution over a pan-European domain. For model validation, we performed an extensive evaluation of this datasets by comparing with in-situ and satellite data. This dataset can serve as a reference for future studies of climate change impact projections and for hydrological forecasting. Detail description of the model evaluation is given in https://doi.org/10.5194/gmd-2022-173

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18

Leonarduzzi, Elena, Hoang Tran, Vineet Bansal, et al. "Training machine learning with physics-based simulations to predict 2D soil moisture fields in a changing climate." Frontiers in Water 4 (October 11, 2022). http://dx.doi.org/10.3389/frwa.2022.927113.

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The water content in the soil regulates exchanges between soil and atmosphere, impacts plant livelihood, and determines the antecedent condition for several natural hazards. Accurate soil moisture estimates are key to applications such as natural hazard prediction, agriculture, and water management. We explore how to best predict soil moisture at a high resolution in the context of a changing climate. Physics-based hydrological models are promising as they provide distributed soil moisture estimates and allow prediction outside the range of prior observations. This is particularly important co

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19

Belleflamme, Alexandre, Klaus Goergen, Niklas Wagner, et al. "Hydrological forecasting at impact scale: the integrated ParFlow hydrological model at 0.6 km for climate resilient water resource management over Germany." Frontiers in Water 5 (May 30, 2023). http://dx.doi.org/10.3389/frwa.2023.1183642.

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In the context of the repeated droughts that have affected central Europe over the last years (2018–2020, 2022), climate-resilient management of water resources, based on timely information about the current state of the terrestrial water cycle and forecasts of its evolution, has gained an increasing importance. To achieve this, we propose a new setup for simulations of the terrestrial water cycle using the integrated hydrological model ParFlow/CLM at high spatial and temporal resolution (i.e., 0.611 km, hourly time step) over Germany and the neighboring regions. We show that this setup can be

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20

Tran, Hoang, Jun Zhang, Mary Michael O’Neill, Anna Ryken, Laura E. Condon, and Reed M. Maxwell. "A hydrological simulation dataset of the Upper Colorado River Basin from 1983 to 2019." Scientific Data 9, no. 1 (2022). http://dx.doi.org/10.1038/s41597-022-01123-w.

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AbstractThis article presents a hydrological reconstruction of the Upper Colorado River Basin with an hourly temporal resolution, and 1-km spatial resolution from October 1982 to September 2019. The validated dataset includes a suite of hydrologic variables including streamflow, water table depth, snow water equivalent (SWE) and evapotranspiration (ET) simulated by an integrated hydrological model, ParFlow-CLM. The dataset was validated over the period with a combination of point observations and remotely sensed products. These datasets provide a long-term, natural-flow, simulation for one of

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21

Belleflamme, Alexandre, Suad Hammoudeh, Klaus Goergen, and Stefan Kollet. "Assessment of the skill of seasonal probabilistic water table depth forecasts with the hydrological model ParFlow/CLM over central Europe." ARPHA Conference Abstracts 8 (May 28, 2025). https://doi.org/10.3897/aca.8.e151700.

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In recent years, alternating drought and extreme precipitation events have highlighted the need for subseasonal to seasonal forecasts of the terrestrial water cycle. In particular, predictions of the impacts of dry and wet extremes on groundwater resources are crucial to assess the impacts of groundwater scarcity and excess on ecosystem dynamics as well as to provide stakeholders in agriculture, forestry, the water sector, and other fields with information supporting the sustainable use of these resources. In this context, we calculate four times per year seasonal probabilistic hydrological fo

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22

Bennett, Andrew, Hoang Tran, Luis De la Fuente, et al. "Spatio‐Temporal Machine Learning for Regional to Continental Scale Terrestrial Hydrology." Journal of Advances in Modeling Earth Systems 16, no. 6 (2024). http://dx.doi.org/10.1029/2023ms004095.

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AbstractIntegrated hydrologic models can simulate coupled surface and subsurface processes but are computationally expensive to run at high resolutions over large domains. Here we develop a novel deep learning model to emulate subsurface flows simulated by the integrated ParFlow‐CLM model across the contiguous US. We compare convolutional neural networks like ResNet and UNet run autoregressively against our novel architecture called the Forced SpatioTemporal RNN (FSTR). The FSTR model incorporates separate encoding of initial conditions, static parameters, and meteorological forcings, which ar

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23

Kracheletz, Magdalena, Ziyu Liu, Anne Springer, Jürgen Kusche, and Petra Friederichs. "Would the 2021 Western Europe Flood Event Be Visible in Satellite Gravimetry?" Journal of Geophysical Research: Atmospheres 130, no. 3 (2025). https://doi.org/10.1029/2024jd042190.

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AbstractThe primary objective of the GRACE Follow‐On satellite mission is to measure temporal changes in the Earth's gravitational field. Distance variations between the two GRACE‐FO satellites, recorded by a K‐Band Ranging system and a new Laser Ranging Interferometer (LRI), are significantly influenced by atmospheric mass redistribution. We investigate whether the sub‐monthly variations in atmospheric water mass, precipitation, and changes in total water storage during the extreme flood event in western Europe in 2021 were sufficiently large to influence the satellite gravity field measureme

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24

Thiros, Nicholas E., Erica R. Woodburn, W. Payton Gardner, James P. Dennedy‐Frank, and Kenneth H. Williams. "Matrix Diffusion Controls Mountain Hillslope Groundwater Ages and Inferred Storage Dynamics." Groundwater, March 29, 2025. https://doi.org/10.1111/gwat.13475.

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AbstractGroundwater age distributions provide fundamental insights on coupled water and biogeochemical processes in mountain watersheds. Field‐based studies have found mixtures of young and old‐aged groundwater in mountain catchments underlain by bedrock; yet, the processes that dictate these groundwater age distributions are poorly understood. In this work, we use the coupled ParFlow‐CLM integrated hydrologic and EcoSLIM particle tracking models to simulate groundwater age distributions on a lower montane hillslope in the East River Watershed, Colorado (USA). We develop a convolution‐based ap

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25

Patakchi Yousefi, Kaveh, Alexandre Belleflamme, Klaus Goergen, and Stefan Kollet. "Impact of deep learning-driven precipitation corrected data using near real-time satellite-based observations and model forecast in an integrated hydrological model." Frontiers in Water 6 (October 2, 2024). http://dx.doi.org/10.3389/frwa.2024.1439906.

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Integrated hydrological model (IHM) forecasts provide critical insights into hydrological system states, fluxes, and its evolution of water resources and associated risks, essential for many sectors and stakeholders in agriculture, urban planning, forestry, or ecosystem management. However, the accuracy of these forecasts depends on the data quality of the precipitation forcing data. Previous studies have utilized data-driven methods, such as deep learning (DL) during the preprocessing phase to improve precipitation forcing data obtained from numerical weather prediction simulations. Nonethele

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