Publications

Influence of plateau, slope, and valley on soil hydrology during the dry season in a Central Amazon old‐growth forest

Published in Vadose Zone Journal, 2026

Soil moisture regulates plant water supply and drought sensitivity in tropical forests, yet its vertical and topographic variation remains poorly characterized. We combined high-frequency time-domain reflectometry measurements from 5 to 100 cm across plateau, slope, and valley landforms at the Zona Florestal 2 research site north of Manaus, Central Amazonia, to quantify how soil moisture memory, timing of responses to rainfall, dry-down rates (τ), and soil–water depletion vary across these contrasting landforms. Landform-specific soil moisture calibration curves ensured accurate volumetric water content estimates in these highly weathered soils. During the 2023 dry-to-wet transition (August–November), soil moisture memory showed strong topographic contrasts, with valley profiles increasing from ∼47 h at 5 cm to ∼154 h at 100 cm, while plateaus exhibited higher near-surface persistence (∼124 h at 5 cm) but weaker memory at depth. Dry-down behavior reinforced these differences as valley soils exhibited τ values exceeding ∼200 h, more than double the characteristic τ of plateau soils (∼90 h). Rainfall–soil moisture correlations indicated immediate responses at shallow depths in valleys and progressively longer lags with depth on plateaus and slopes. These hydrologic patterns were mirrored in depletion profiles, which declined sharply below 30 cm on plateaus but remained high and sustained throughout the upper meter in slopes and valleys. Together, these findings provide the first depth-resolved field measurements of soil moisture memory, rainfall coupling, dry-down constants, and depletion dynamics across major upland landforms in Central Amazonia and offer clear observational benchmarks for improving land-surface and ecosystem model representations of soil–water processes.

Recommended citation: Negron-Juarez, R., Wright, C., Ferreira, S., Hirai, K., Kobayashi, M., Warren, J. M., Oliveira, R., Liao, C., Leung, L. R., deSouza, C. A. S., Chambers, J. Q., Lima, A., & Higuchi, N. (2026). Influence of plateau, slope, and valley on soil hydrology during the dry season in a Central Amazon old-growth forest. Vadose Zone Journal, 25, e70095. https://doi.org/10.1002/vzj2.70095 http://changliao.github.io/files/2026/soil_moisture_hillslope2026.pdf

Systematic evaluation of atmospheric forcing, surface datasets, and mesh effects on Kilometer-Scale land surface and river modeling

Published in Journal of Hydrology', 2026

Earth system models are advancing toward kilometer-scale resolution to capture local climate impacts and extremes. High-resolution land and river modeling depends on multiple factors, including mesh, surface datasets, and atmospheric forcing, but their relative effects at kilometer scales remain unquantified. We evaluated five Energy Exascale Earth System Model land and river configurations over the Mid-Atlantic region using two mesh (1/8° structured versus variable-resolution unstructured mesh), two surface datasets (default versus newly developed), and three atmospheric forcings (NLDAS2, MSWX, GSWP). Evaluation against satellite, reanalysis, and in situ benchmarks across water, energy, and carbon cycles quantifies how these factors affect model performance. Forcing selection produces the largest bias reductions (12–99% across variables), followed by surface datasets (7–75%) and mesh (up to 21%). Forcing effects vary by variable, with MSWX reducing biases for snow water equivalent, evapotranspiration, albedo, temperature, and gross primary productivity, GSWP for snow cover and runoff, and NLDAS for soil moisture and streamflow. The use of newly developed surface datasets improves gross primary productivity (58% bias reduction) and evapotranspiration but increase soil moisture and albedo biases due to current modeling limitations. Variable-resolution unstructured mesh improves the simulation of small-basin streamflow through better capturing drainage networks, though mesh minimally affects other land variables. These findings provide important guidance for high-resolution modeling development and actionable science.

Recommended citation: Li, L., Bisht, G., Xu, D., Hao, D., Liao, C., Feng, D., ... & Leung, L. R. (2026). Systematic evaluation of atmospheric forcing, surface datasets, and mesh effects on Kilometer-Scale land surface and river modeling. Journal of Hydrology, 135500. http://changliao.github.io/files/2026/lsmevaluation2026.pdf

ELM-MOSART-DOC: A Large-Scale Riverine Dissolved Organic Carbon Model and Its Application Over the United States

Published in Journal of Advances in Modeling Earth Systems', 2026

Riverine dissolved organic carbon (DOC), primarily sourced from soil organic carbon (SOC), plays a crucial role in regional and global carbon cycles. However, the complexities of the underlying mechanisms and limited observations present significant challenges for predictive understanding of DOC at regional or larger scales. Recently, we developed a machine learning-based (ML) map of DOC transformation rates, bridging the gap between SOC and DOC leaching flux and simplifying terrestrial DOC representation. Building on this advancement, we introduce ELM-MOSART-DOC, a DOC module integrated into the riverine component of the Energy Exascale Earth System Model (E3SM)—the Model for Scale Adaptive River Transport (MOSART). ELM-MOSART-DOC simulates DOC transport and transformation across both headwater streams and river networks, including those managed. Model validation demonstrates the ability of ELM-MOSART-DOC to accurately capture long-term average DOC concentrations, with Kling-Gupta Efficiency (KGE) scores of 0.58 and 0.76 at large and local stations, respectively. We further assess the impact of reservoirs through different simulation schemes, revealing that reservoirs significantly alter DOC fluxes by regulating streamflow patterns and promoting DOC mineralization. Model simulations indicate that reservoirs reduce total DOC flux from the Mississippi River into the ocean by 7.5%, with the long-term average annual export decreasing from 3.34 to 3.14 teragrams (Tg) per year. ELM-MOSART-DOC integrates process-based modeling with ML parameterization to enhance the predictive understanding of riverine biogeochemical processes. This approach reduces uncertainties in modeling regional and global carbon cycle ESMs and provides new insights into carbon cycling and its implications for global environmental change.

Recommended citation: Li, L., Li, H.-Y., Abeshu, G., Yang, X., Tang, J., Tan, Z., et al. (2026). ELM-MOSART-DOC: A large-scale riverine dissolved organic carbon model and its application over the United States. Journal of Advances in Modeling Earth Systems, 18, e2025MS005307. https://doi.org/10.1029/2025MS005307 http://changliao.github.io/files/2026/mosartdoc2026.pdf

Improving the representation of plant water stress and water use in Earth System Models

Published in New Phytologist, 2025

Projections of terrestrial climate feedbacks from Earth System Models (ESMs) depend on simulated carbon and water dynamics of vegetation, and their credibility depends on realistic representation of water stress responses. Here, we discuss how models simulate plant hydraulic processes and identify opportunities to improve confidence in model outputs. We focus on the vegetation sub-models that represent plant physiology and hydrodynamics, and also on groundwater flow models, which could influence water availability. Recently implemented plant hydrodynamic frameworks allow ESMs to represent water transport through plants but depend on crudely estimated fixed trait values. Few data are available for parameterizing, assessing, and validating these models across landscapes and at large scales. Furthermore, global models do not account for fine-scale soil water and groundwater flow patterns that influence growth and mortality. We encourage the development of model-compatible databases that include vetted data on plant hydraulic traits, states, and responses to drought. We also encourage efficient model representation of sub-grid variation in slopes, soil depths, and groundwater accessibility. Finally, we recommend using physically informed artificial intelligence approaches to integrate knowledge from process-based models and data from field observations, experiments, and remote-sensing products toward better prediction of ecosystem dynamics under water stress at large scales.

Recommended citation: Dukes, J.S., Xu, C., Liao, C., Novick, K.A., Phillips, R.P., Beverly, D.P., Fang, Y., Jacobs, E.M., McAdam, S.A.M., Paudel, I., Rimer, I.M. and Robbins, Z.J. (2025), Improving the representation of plant water stress and water use in Earth System Models. New Phytol. https://doi.org/10.1111/nph.70687 http://changliao.github.io/files/2025/waterstress2025.pdf

Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model

Published in Natural Hazards and Earth System Sciences, 2025

Compound riverine and coastal flooding is usually driven by complex interactions among meteorological, hydrological, and ocean extremes. However, existing efforts to model this phenomenon often do not integrate hydrological processes across atmosphere–land–river–ocean systems, leading to substantial uncertainties that have not been fully examined. To bridge this gap, we leverage the new capabilities of the Energy Exascale Earth System Model (E3SM) that enable a multi-component framework that integrates coastally refined atmospheric, terrestrial, and oceanic components. We evaluate compound uncertainties arising from two-way land–river–ocean coupling in E3SM and track the cascading meteorological and hydrological uncertainties through ensemble simulations over the Delaware River basin and estuary during Hurricane Irene (2011). Our findings highlight the importance of two-way river–ocean coupling to compound flood modeling and demonstrate E3SMs capability in capturing compound flood extent near the coast, with a hit rate over 0.75. Our study shows the growing uncertainties that transition from atmospheric forcings to flood distribution and severity. Furthermore, an analysis based on artificial neural networks is used to assess the roles of hydrological drivers, such as infiltration and soil moisture, in the generation of compound flooding. The response of compound floods to tropical cyclones (TCs) is found to be susceptible to these often overlooked drivers. For instance, the flooded area could increase more than 2-fold (∼2.4) if Hurricane Irene were preceded by an extreme antecedent soil moisture condition (AMC). The results not only support the use of a multi-component framework for interactive flooding processes, but also underscore the necessity of broader definitions of compound flooding that encompass the simultaneous occurrence of intense precipitation, storm surge, and high AMC during TCs.

Recommended citation: Feng, D., Tan, Z., Engwirda, D., Wolfe, J. D., Xu, D., Liao, C., Bisht, G., Benedict, J. J., Zhou, T., Deb, M., Li, H.-Y., and Leung, L. R.: Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model, Nat. Hazards Earth Syst. Sci., 25, 3619–3639, https://doi.org/10.5194/nhess-25-3619-2025, 2025. http://changliao.github.io/files/2025/compoundflood2025.pdf

Representing Lateral Groundwater Flow from Land to River in Earth System Models

Published in Geoscientific Model Development, 2025

Lateral groundwater flow (LGF) is an important hydrologic process in controlling water table dynamics. Due to the relatively coarse spatial resolutions of land surface models, the representation of this process is often overlooked or overly simplified. In this study, we developed a hillslope-based lateral groundwater flow model. Specifically, we first developed a hillslope definition model based on an existing watershed delineation model to represent the subgrid spatial variability in topography. Building upon this hillslope definition, we then developed a physical-based lateral groundwater flow using Darcy’s equation. This model explicitly considers the relationships between the groundwater table along the hillslope and the river water table levels. We coupled this intra-grid model to the land component (ELM) and river component (MOSART) of the Energy Exascale Earth System Model (E3SM). We tested both the hillslope definition model and the lateral groundwater flow model and performed sensitivity experiments using different configurations. Simulations for a single grid cell at 0.5° × 0.5° within the Amazon basin show that the definition of hillslope is the key to modeling lateral flow processes and the runoff partition between surface and subsurface can be dramatically changed using the hillslope approach. Although our method provides a pathway to improve the lateral flow process, future improvements are needed to better capture the subgrid structure to account for the spatial variability in hillslopes within the simulated grid of land surface models.

Recommended citation: Liao, C., Leung, L. R., Fang, Y., Tesfa, T., and Negron-Juarez, R.: Representing lateral groundwater flow from land to river in Earth system models, Geosci. Model Dev., 18, 4601–4624, https://doi.org/10.5194/gmd-18-4601-2025, 2025. http://changliao.github.io/files/2025/hillslope_gmd2025.pdf

Evaluation of flow routing on the unstructured Voronoi meshes in Earth system modeling

Published in Journal of Advances in Modeling Earth Systems, 2025

Flow routing is a fundamental process of Earth System Models (ESMs) river component. Traditional flow routing models rely on Cartesian rectangular meshes, which exhibit limitations, particularly when coupled with unstructured mesh-based ocean components. They also lack the support for regionally refined models (RRMs). While previous studies have highlighted the potential benefits of unstructured meshes for flow routing, their widespread application and comprehensive evaluation within ESMs remain limited. This study extends the river component of the Energy Exascale Earth System Model (E3SM) to unstructured Voronoi meshes. We evaluated the models performance in simulating river discharge and water depth across three watersheds spanning the Arctic, temperate, and tropical regions. The results show that while providing several benefits, unstructured mesh-based flow routing can achieve comparable performance to structured mesh-based routing, and their difference is often less than 10%. Although the unstructured mesh-based method could address several existing limitations, this research also shows that additional improvements in the numerical method are needed to fully exploit the advantages of unstructured mesh for hydrologic and ESMs.

Recommended citation: Liao, C., Donghui Xu, G Cooper, M, Tian Zhou, Darren Engwirda, Gautam Bisht, Hong-yi Li, Lingcheng Li, Dongyu Feng, L Ruby Leung. Evaluation of flow routing on the unstructured Voronoi meshes in Earth system modeling. Journal of Advances in Modeling Earth Systems. http://changliao.github.io/files/2025/mpas_mosart2025.pdf

Deriving a Transformation Rate Map of Dissolved Organic Carbon over the Contiguous U.S.

Published in Earth System Science Data, 2025

Riverine dissolved organic carbon (DOC) plays a vital role in regional and global carbon cycles. However, the processes of DOC conversion from soil organic carbon (SOC) and leaching into rivers are insufficiently understood, inconsistently represented, and poorly parameterized, particularly in land surface and earth system models. As a first attempt to fill this gap, we propose a generic formula that directly connects SOC concentration with DOC concentration in headwater streams, where a single parameter, the transformation rate from SOC in the soil to DOC leaching flux, Pr, accounts for the overall processes governing SOC conversion to DOC and leaching from soils (along with runoff) into headwater streams. We then derive a high-resolution Pr map over the contiguous U.S. (CONUS) in five major steps: 1) selecting 2595 headwater catchments where observed riverine DOC data are available with reasonable quality; 2) estimating catchment-average SOC for the 2595 catchments based on high-resolution SOC data; 3) estimating the Pr values for these catchments based on the generic formula and catchment-average SOC; 4) developing a predictive model of Pr with machine learning (ML) techniques and catchment-scale climate, hydrology, geology, and other attributes; and 5) deriving a national map of Pr, based on the ML model. For evaluation, we compare the DOC concentration derived using the Pr map and the observed DOC concentration values at another 3210 headwater gauges. The resulting mean absolute scaled error and coefficient of determination are 0.73 and 0.47, respectively, suggesting the effectiveness of the overall methodology. Efforts to constrain uncertainty and evaluate the sensitivity of Pr to different factors are discussed. To illustrate the use of such a map, we derive a riverine DOC concentration reanalysis dataset for more than two million small catchments over CONUS. The map, robustly derived and empirically validated, lays a critical cornerstone for better simulating the terrestrial carbon cycle in land surface and earth system models. Our findings not only set a foundation for improving our predictive understanding of the terrestrial carbon cycle at the regional and global scales but also hold promises for informing policy decisions related to decarbonization and climate change mitigation.

Recommended citation: Li, L., Li, H.-Y., Abeshu, G., Tang, J., Leung, L. R., Liao, C., Tan, Z., Tian, H., Thornton, P., and Yang, X.: Deriving a Transformation Rate Map of Dissolved Organic Carbon over the Contiguous U.S., Earth Syst. Sci. Data, https://doi.org/10.5194/essd-2024-43, 2025 http://changliao.github.io/files/2025/essddoc2025.pdf

Discrete Global Grid System-based Flow Routing Datasets in the Amazon and Yukon Basins

Published in Earth System Science Data, 2025

Discrete Global Grid systems (DGGs) are emerging spatial data structures widely used to organize geospatial datasets across scales. While DGGs have found applications in various scientific disciplines, including atmospheric science and ecology, their integration into physically based hydrologic models and Earth System Models (ESMs) has been hindered by the lack of flow-routing datasets based on DGGs. In response to this gap, this study pioneers the development of new flow routing datasets using Icosahedral Snyder Equal Area (ISEA) DGGs and a novel mesh-independent flow direction model. We present flow routing datasets for two large basins, the tropical Amazon River Basin and the Arctic Yukon River Basin. These datasets demonstrate the potential of DGGs-based flow routing datasets to enhance the performance of hydrologic models and provide observationally-based flow routing inputs for immediate application to the Amazon and Yukon River Basins. The data are available at https://doi.org/10.5281/zenodo.8377765 (Liao, 2023).

Recommended citation: Liao, C., Engwirda, D., Cooper, M., Li, M., and Fang, Y.: Discrete Global Grid System-based Flow Routing Datasets in the Amazon and Yukon Basins, Earth Syst. Sci. Data. https://doi.org/10.5194/essd-2023-398 http://changliao.github.io/files/2025/hexwatersheddggs2025.pdf

Changes in soil water content and lateral flow exert large effects on soil thermal dynamics across Alaskan landscapes

Published in Environmental Research Letters, 2025

Both lateral surface and subsurface water flow affect soil moisture dynamics, yet most land surface models only solve subsurface water movement vertically. Here we use a 3-D ecosystem model that considers both land surface and subsurface hydrologic processes to simulate soil moisture, which is then used to drive a 1-D vertical soil thermal model to simulate the soil moisture effects on soil thermal dynamics in central Alaska. Our coupled model improves soil temperature estimates by 43.5% in comparison with observational data. Soil moisture has little effect on soil temperature during the wet season (-1.5 %) and a substantial influence during the dry season (60%). Spatially, water lateral flow has significant impacts on both soil moisture and soil temperature, causing model estimates for thawed areas in the transition season to increase by ~10% in the study area. Our results highlight the importance of considering dynamical soil moisture, as well as lateral flow effects, on soil thermal dynamics in permafrost regions.

Recommended citation: Liu, X., Zhuang, Q., Liao, C., & Jorgenson, M. T. (2025). Changes in soil water content and lateral flow exert large effects on soil thermal dynamics across Alaskan landscapes. Environmental Research Letters. https://doi.org/10.1088/1748-9326/adaa05 http://changliao.github.io/files/2025/lateralflow2025.pdf

A Multi-algorithm Approach for Modeling Coastal Wetland Ecogeomorphology

Published in Frontiers in Earth Science, 2024

Coastal wetlands play an important role in the global water and biogeochemical cycles. Climate change is making them more difficult to adapt to the fluctuation of sea levels and other environment changes. Given the importance of eco-geomorphological processes for coastal wetland resilience, many eco-geomorphology models differing in complexity and numerical schemes have been developed in recent decades. But their divergent estimates on the response of coastal wetlands to climate change indicate that substantial structural uncertainties exist in these models. To investigate the structural uncertainty of coastal wetland eco-geomorphology models, we developed a multi-algorithm model framework of eco-geomorphological processes, such as mineral accretion and organic matter accretion, within a single hydrodynamics model. The framework is designed to explore possible ways to represent coastal wetland eco-geomorphology in Earth system models and reduce the related uncertainties in global applications. We tested this model framework at three representative coastal wetland sites: two saltmarsh wetland (Venice Lagoon and Plum Island Estuary) and a mangrove wetland (Hunter Estuary). Through the model-data comparison, we showed the importance to use a multi-algorithm ensemble approach for more robust predictions of the evolution of coastal wetlands. We also find that more observations of mineral and organic matter accretion at different elevations of coastal wetlands and evaluation of the coastal wetland models at different sites of diverse environments can help reduce the model uncertainty.

Recommended citation: Tan, Z., Leung, L. R., Liao, C., Luca Carniiello, Jose F. Rodriguez, Patricia M. Saco, Steven Sandi Rojas, J. Patrick Megonigal, Vanessa L. Bailey. A Multi-algorithm Approach for Modeling Coastal Wetland Ecogeomorphology. Frontiers in Earth Science. https://doi.org/10.3389/feart.2024.1421265 http://changliao.github.io/files/2024/coastal_wetland.pdf

Simulation of Compound Flooding Using River-Ocean Two-Way Coupled E3SM Ensemble on Variable-Resolution Meshes

Published in Journal of Advances in Modeling Earth Systems, 2024

Coastal zone compound flooding (CF) can be caused by the interactive fluvial and oceanic processes, particularly when coastal backwater propagates upstream and interacts with high river discharge. The modeling of CF is limited in existing Earth System Models (ESMs) due to coarse mesh resolutions and one-way coupled river-ocean components. In this study, we present a novel multi-scale coupling framework within the Energy Exascale Earth System Model (E3SM), integrating global atmosphere and land with interactively coupled river and ocean models using different meshes with refined resolutions near the coastline. To evaluate this framework, we conducted ensemble simulations of a CF event (Hurricane Irene in 2011) in a Mid-Atlantic estuary. The results demonstrate that the novel E3SM configuration can reasonably reproduce river discharge and sea surface height variations. The two-way river-ocean coupling improves the representation of coastal backwater effects at the terrestrial-aquatic interface that are caused by the combined actions of tide and storm surge during the CF event, thus providing a valuable modeling tool for better understanding the river-estuary-ocean dynamics in extreme events under climate change. Notably, our results show that the most significant CF impacts occur when the highest storm surge generated by a tropical cyclone meets with a moderate river discharge. This study highlights the state-of-the-art advancements developed within E3SM for simulating multi-scale coastal processes..

Recommended citation: Feng, D., Tan, Z., Engwirda, D., Wolfe, J. D., Xu, D., Liao, C., et al. (2024). Simulation of compound flooding using river-ocean two-way coupled E3SM ensemble on variable-resolution meshes. Journal of Advances in Modeling Earth Systems, 16, e2023MS004054. https://doi.org/10.1029/2023MS004054 http://changliao.github.io/files/2024/riverocean_james.pdf

Pyflowline: a mesh-independent river network generator for hydrologic models

Published in The Journal of Open Source Software, 2023

River networks are crucial in hydrologic and Earth system models. Accurately representing river networks in hydrologic models requires considering the model spatial resolution and computational mesh. However, current river network representation methods often have several limitations: (1) vector-based; (2) they perform poorly at coarse resolution (3) they do not support unstructured meshes. To overcome these limitations, we developed PyFlowline, a Python package that generates mesh-independent river networks. With PyFlowline, hydrologic modelers can generate conceptual river networks at various spatial resolutions for both structured and unstructured computational meshes. The generated river network datasets can be used by hydrologic models across scales.

Recommended citation: Liao et al., (2023). pyflowline: a mesh-independent river network generator for hydrologic models. Journal of Open Source Software, 8(91), 5446, https://doi.org/10.21105/joss.05446 http://changliao.github.io/files/2023/pyflowline_joss.pdf

Disentangling the Hydrological and Hydraulic Controls on Streamflow Variability in E3SM V2 – A Case Study in the Pantanal Region

Published in Geoscientific Model Development, 2023

Streamflow variability plays a crucial role in shaping the dynamics and sustainability of Earth’s ecosystems, which can be simulated and projected by a river routing model coupled with a land surface model. However, the simulation of streamflow at large scales is subject to considerable uncertainties, primarily arising from two related processes: runoff generation (hydrological process) and river routing (hydraulic process). While both processes have impacts on streamflow variability, previous studies only calibrated one of the two processes to reduce biases in the simulated streamflow. Calibration focusing only on one process can result in unrealistic parameter values to compensate for the bias resulting from the other process; thus other water-related variables remain poorly simulated. In this study, we performed several experiments with the land and river components of the Energy Exascale Earth System Model (E3SM) over the Pantanal region to disentangle the hydrological and hydraulic controls on streamflow variability in coupled land–river simulations. Our results show that the generation of subsurface runoff is the most important factor for streamflow variability contributed by the runoff generation process, while floodplain storage effect and main-channel roughness have significant impacts on streamflow variability through the river routing process. We further propose a two-step procedure to robustly calibrate the two processes together. The impacts of runoff generation and river routing on streamflow are appropriately addressed with the two-step calibration, which may be adopted by developers of land surface and earth system models to improve the modeling of streamflow.

Recommended citation: Xu, D., Bisht, G., Tan, Z., Liao, C., Zhou, T., Li, H.-Y., and Leung, L. R.: Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region, Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, 2024. http://changliao.github.io/files/2023/river_disentangle_gmd.pdf

Topological relationship-based flow direction modeling: stream burning and depression filling

Published in Journal of Advances in Modeling Earth Systems, 2023

Flow direction modeling consists of (1) an accurate representation of the river network and (2) digital elevation model (DEM) processing to preserve characteristics with hydrological significance. In part 1 of our study, we presented a mesh-independent approach to representing river networks on different types of meshes. This follow-up part 2 study presents a novel DEM processing approach for flow direction modeling. This approach consists of (1) a topological relationship-based hybrid breaching-filling method to conduct stream burning for the river network and (2) a modified depression removal method for rivers and hillslopes. Our methods reduce modifications to surface elevations and provide a robust two-step procedure to remove local depressions in DEM. They are mesh-independent and can be applied to both structured and unstructured meshes. We applied our new methods with different model configurations to the Susquehanna River Basin. The results show that topological relationship-based stream burning and depression-filling methods can reproduce the correct river networks, providing high-quality flow direction and other characteristics for hydrologic and Earth system models.

Recommended citation: Liao, C., Zhou, T., Xu, D., Tan, Z., Bisht, G., G Cooper, M., Engwirda, D, Hongyi Li, L Ruby Leung.Topological relationship-based flow direction modeling: stream burning and depression filling. Journal of Advances in Modeling Earth Systems. https://doi.org/10.1029/2022MS003487 http://changliao.github.io/files/2023/hexwatershed_james.pdf

Topological relationship-based flow direction modeling: Mesh-independent river networks representation

Published in Journal of Advances in Modeling Earth Systems, 2023

River networks are important features in surface hydrology. However, accurately representing river networks in spatially distributed hydrologic and Earth system models is often sensitive to the model’s spatial resolution. Specifically, river networks are often misrepresented because of the mismatch between the model’s spatial resolution and river network details, resulting in significant uncertainty in the projected flow direction. In this study, we developed a topological relationship-based river network representation method for spatially distributed hydrologic models. This novel method uses (1) graph theory algorithms to simplify real-world vector-based river networks and assist in mesh generation; and (2) a topological relationship-based method to reconstruct conceptual river networks. The main advantages of our method are that (1) it combines the strengths of vector-based and DEM raster-based river network extraction methods; and (2) it is mesh-independent and can be applied to both structured and unstructured meshes. This method paves a path for advanced terrain analysis and hydrologic modeling across different scales.

Recommended citation: Liao, C., Zhou, T., Xu, D., Cooper, M. G., Engwirda, D., Li, H.-Y., & Leung, L. R. (2023). Topological relationship-based flow direction modeling: Mesh-independent river networks representation. Journal of Advances in Modeling Earth Systems, 15, e2022MS003089. https://doi.org/10.1029/2022MS003089 http://changliao.github.io/files/2023/pyflowline_james.pdf

Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh

Published in Hydrology and Earth System Sciences Discussion, 2022

Coastal backwater effects are caused by the downstream water level increase as the result of elevated sea level, high river discharge and their compounding influence. Such effects have crucial impacts on floods in densely populated regions but have not been well represented in large-scale river models used in Earth System Models (ESMs), partly due to model mesh deficiency and oversimplifications of river hydrodynamics. Using two mid-Atlantic river basins as a testbed, we perform the first attempt to simulate the backwater effects comprehensively over a coastal region using the MOSART river transport model under an Earth system model framework i.e., Energy Exascale Earth System Model (E3SM) configured on a regionally-refined unstructured mesh, with a focus on understanding the backwater drivers and their long-term variations. By including sea level variations at the river downstream boundary, the model performance in capturing backwaters is greatly improved. We also propose a new flood event selection scheme to facilitate the decomposition of backwater drivers into different components. Our results show that while storm surge is a key driver, the influence of extreme discharge cannot be neglected, particularly when the river drains to a narrow river-like estuary. Compound flooding, while not necessarily increasing the flood peaks, exacerbates the flood risk by extending the duration of multiple coastal and fluvial processes. Furthermore, our simulations and analysis highlight the increasing strength of backwater effects due to sea level rise and more frequent storm surge during 1990–2019. Thus, backwaters need to be properly represented in ESMs for improving predictive understanding of coastal flooding.

Recommended citation: Feng, D., Tan, Z., Engwirda, D., Liao, C., Xu, D., Bisht, G., Zhou, T., Li, H.-Y., and Leung, R.: Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2022-251, in review, 2022. http://changliao.github.io/files/2022/backwater_hess.pdf

Using a surrogate assisted Bayesian framework to calibrate the runoff generation scheme in the Energy Exascale Earth System Model E3SM v1

Published in Geoscientific Model Development, 2022

Runoff is a critical component of the terrestrial water cycle, and Earth system models (ESMs) are essential tools to study its spatiotemporal variability. Runoff schemes in ESMs typically include many parameters so that model calibration is necessary to improve the accuracy of simulated runoff. However, runoff calibration at a global scale is challenging because of the high computational cost and the lack of reliable observational datasets. In this study, we calibrated 11 runoff relevant parameters in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) using a surrogate-assisted Bayesian framework. First, the polynomial chaos expansion machinery with Bayesian compressed sensing is used to construct computationally inexpensive surrogate models for ELM-simulated runoff at 0.5 × 0.5 for 1991–2010. The error metric between the ELM simulations and the benchmark data is selected to construct the surrogates, which facilitates efficient calibration and avoids the more conventional, but challenging, construction of high-dimensional surrogates for the ELM simulated runoff. Second, the Sobol index sensitivity analysis is performed using the surrogate models to identify the most sensitive parameters, and our results show that, in most regions, ELM-simulated runoff is strongly sensitive to 3 of the 11 uncertain parameters. Third, a Bayesian method is used to infer the optimal values of the most sensitive parameters using an observation based global runoff dataset as the benchmark. Our results show that model performance is significantly improved with the inferred parameter values. Although the parametric uncertainty of simulated runoff is reduced after the parameter inference, it remains comparable to the multimodel ensemble uncertainty represented by the global hydrological models in ISMIP2a. Additionally, the annual global runoff trend during the simulation period is not well constrained by the inferred parameter values, suggesting the importance of including parametric uncertainty in future runoff projections.

Recommended citation: Xu, D., Bisht, G., Sargsyan, K., Liao, C., and Leung, L. R.: Using a surrogate-assisted Bayesian framework to calibrate the runoff-generation scheme in the Energy Exascale Earth System Model (E3SM) v1, Geosci. Model Dev., 15, 5021–5043, https://doi.org/10.5194/gmd-15-5021-2022, 2022. http://changliao.github.io/files/2022/uqtk_gmd.pdf

Advances in hexagon mesh based flow direction modeling

Published in Advances in Water Resources, 2021

Watershed delineation and flow direction representation are the foundations of streamflow routing in spatially distributed hydrologic modeling. A recent study showed that hexagon-based watershed discretization has several advantages compared to the traditional Cartesian (latitude-longitude) discretization, such as uniform connectivity and compatibility with other Earth system model components based on unstructured mesh systems (e.g., oceanic models). Despite these advantages, hexagon-based discretization has not been widely adopted by the current generation of hydrologic models. One major reason is that there is no existing model that can delineate hexagon-based watersheds while maintaining accurate representations of flow direction across various spatial resolutions. In this study, we explored approaches such as spatial resampling and hybrid breaching-filling stream burning techniques to improve watershed delineation and flow direction representation using a newly developed hexagonal mesh watershed delineation model (HexWatershed). We applied these improvements to the Columbia River basin and performed 16 simulations with different configurations. The results show that (1) spatial resampling modulates flow direction around headwaters and provides an opportunity to extract subgrid information; and (2) stream burning corrects the flow directions in mountainous areas with complex terrain features.

Recommended citation: Chang Liao, Tian Zhou, Donghui Xu, Richard Barnes, Gautam Bisht, Hong-Yi Li, Zeli Tan, Teklu Tesfa, Zhuoran Duan, Darren Engwirda, and L. Ruby Leung. Advances in hexagon mesh based flow direction modeling. Advances in Water Resources (2021). https://doi.org/10.1016/j.advwatres.2021.104099 http://changliao.github.io/files/2022/hexwatershed_awr.pdf

Unified Laguerre Power Meshes for Coupled Earth System Modelling

Published in 29th International Meshing Roundtable (IMR), 2021

The representation of physical processes in earth system models is often constrained and simplified by details of the underlying numerical model. Ocean, atmosphere, ice, land and river dynamics are typically discretised over incompatible computational grids, and are coupled together via lossy interpolation schemes. In this work, we describe an alternative unified approach, in which components are represented on a common multi-scale unstructured mesh, and employ compatible numerical formulations and interpolation-free coupling across embedded boundaries. This unified strategy is built on an unstructured primal-dual meshing workflow, in which a global surface mesh conforming to various coastline, river network and land process boundaries is formed as a restricted Laguerre Power tessellation. This mesh layout enables coupled physics to be discretised over the set of staggered edge-, triangle- and cell-based control volumes, leading to a conforming representation. Key to this process is the use of restricted triangulations to approximate complex boundaries and constraints in a multi-scale manner, enabling a transition from high-resolution regional representations to coarser global scales. Initial work on the unified representation is reported here, focusing on development of the restricted triangulation kernels, and subsequent staggered Laguerre-Power mesh optimisation techniques.

Recommended citation: Engwirda, Darren, Liao, Chang. (2021, October 9). Unified Laguerre Power Meshes for Coupled Earth System Modelling. 29th International Meshing Roundtable (IMR), Virtual Conference. https://doi.org/10.5281/zenodo.5558988 http://changliao.github.io/files/2021/jigsaw_zenodo.pdf

Watershed Delineation On A Hexagonal Mesh Grid

Published in Environmental Modelling Software, 2020

Spatial discretization is the cornerstone of all spatially-distributed numerical simulations including watershed hydrology. Traditional square grid spatial discretization has several limitations including inability to represent adjacency uniformly. In this study, we developed a watershed delineation model (HexWatershed) based on the hexagon grid spatial discretization. We applied this model to two different types of watershed in the US and we evaluated its performance against the traditional method. The comparisons show that the hexagon grid spatial discretization exhibits many advantages over the tradition method. We propose that spatially distributed hydrologic simulations should consider using a hexagon grid spatial discretization.

Recommended citation: Liao, Chang, Teklu Tesfa, Zhuoran Duan, and L. Ruby Leung. Watershed delineation on a hexagonal mesh grid. Environmental Modelling & Software (2020) 104702. http://changliao.github.io/files/hexwatershed2020.pdf

Quantifying Dissolved Organic Carbon Dynamics Using a Three‐Dimensional Terrestrial Ecosystem Model at High Spatial‐Temporal Resolutions

Published in Journal of Advances in Modeling Earth Systems, 2019

Arctic terrestrial ecosystems are very sensitive to the global climate change due to the large storage of soil organic carbon and the presence of snow, glacier, and permafrost, which respond directly to near surface air temperature that has warmed in the Arctic by almost twice as much as the global average. These ecosystems play a significant role in affecting regional and global carbon cycling, which have been traditionally quantified using biogeochemical models that have not explicitly considered the loss of carbon due to lateral flow of water from land to aquatic ecosystems. Building upon an extant spatially distributed hydrological model and a process‐based biogeochemical model, we have developed a three‐dimensional terrestrial ecosystem model to elucidate how lateral water flow has impacted the regional dissolved organic carbon (DOC) dynamics in the Tanana Flats Basin in central Alaska. The model explicitly simulates the production, consumption, and transport of DOC. Both in situ observational data and remote sensing‐based products were used to calibrate and validate the model. Our simulations show that (1) plant litter DOC leaching exerts significant controls on soil DOC concentration during precipitation and snowmelt events, (2) lateral transport plays an important role in affecting regional DOC dynamics, and (3) DOC export to the Tanana River is approximately 9.6 × 106 kg C year−1. This study provides a modeling framework to adequately quantify the Arctic land ecosystem carbon budget by considering the lateral transport of carbon affected by permafrost degradation. The quantification of the lateral carbon fluxes will also improve future carbon cycle modeling for Arctic aquatic ecosystems.

Recommended citation: Liao, C., Zhuang, Q., Leung, L. R., & Guo, L. (2019). Quantifying dissolved organic carbon dynamics using a three‐dimensional terrestrial ecosystem model at high spatial‐temporal resolutions. Journal of Advances in Modeling Earth Systems, 11, 4489– 4512. https://doi.org/10.1029/2019MS001792 http://changliao.github.io/files/2019/eco3d_james.pdf

Quantifying the role of snowmelt in stream discharge in an Alaskan watershed: an analysis using a spatially distributed surface hydrology model

Published in JGR: Earth Surface, 2017

This study uses a spatially distributed surface hydrology model to investigate the role of snowmelt in stream discharge for the Tanana Flats Basin in interior Alaska. The Parameter ESTimation code is used to calibrate the model with observed stream discharge data. The model was further evaluated using remote sensing‐based snow cover product and in situ snowpack water equivalent (SWE) observations. A 36 year (1980–2015) U.S. Geological Survey Precipitation‐Runoff Modeling System simulation shows (1) the monthly stream discharge from the Tanana Flats Basin in April decreased by 44%; (2) snow cover area at high altitudes (above 2000 m) decreased in summer, both SWE and snowmelt also decreased significantly, especially in spring; (3) the timings of snowmelt onset and ending shifted by 2 (earlier) and 5 (later) days per decade, respectively; and (4) snowmelt accounts for 40% of the annual stream discharge. This study provides a quantitative tool to investigating hydrological systems considering the impacts of snow dynamics in cold regions. This study also suggests that future warming will further decrease snow coverage, advance snow melting time, and hereafter change the stream discharge dynamics in the Arctic.

Recommended citation: Liao, C., & Zhuang, Q. (2017). Quantifying the role of snowmelt in stream discharge in an Alaskan watershed: An analysis using a spatially distributed surface hydrology model.Journal of Geophysical Research: Earth Surface, 122, 2183– 2195. https://doi.org/10.1002/2017JF004214 http://changliao.github.io/files/2017/prms_jgres.pdf

Quantifying the role of permafrost distribution in groundwater and surface water interactions using a three-dimensional hydrological model

Published in Arctic, Antarctic, and Alpine Research, 2017

This study uses a three-dimensional groundwater flow model to investigate groundwater dynamics and groundwater—surface water (GW-SW) interactions considering the effects of permafrost distribution for the Tanana Flats Basin in interior Alaska. The Parameter ESTimation (PEST) code is used to calibrate the model with observed stream discharge data. A 36-year MODLFOW-USG regional simulation shows the following. (1) Permafrost impedes groundwater movement in all directions and through taliks provides a major pathway to connect the groundwater and surface water systems. More than 80% of the vertical groundwater flow occurs within the permafrost-free zones. (2) Permafrost holds a significant amount of water that cannot be easily released through groundwater movements; however, water above the permafrost table has much higher renewal rates than deep groundwater. (3) Groundwater upwelling supports the base flow for the Tanana River and its tributaries throughout the year and feeds water to the wetland ecosystems at the Tanana Flats through unfrozen zones. Stream leakage is also highly correlated with stream discharge. Our study suggests that cold regional hydrological cycle studies should consider the effects of permafrost distribution under future warming conditions. This study provides a robust three-dimensional hydrological modeling tool that can be applied for the regions underlain with either continuous or discontinuous permafrost.

Recommended citation: Liao, Chang, and Qianlai Zhuang. "Quantifying the role of permafrost distribution in groundwater and surface water interactions using a three-dimensional hydrological model." Arctic, Antarctic, and Alpine Research 49, no. 1 (2017): 81-100. http://changliao.github.io/files/2017/modflow_aaar.pdf

Reduction of global plant production due to droughts from 2001 to 2010: An analysis with a process-based global terrestrial ecosystem model

Published in AMS Earth Interactions, 2010

Droughts dramatically affect plant production of global terrestrial ecosystems. To date, quantification of this impact remains a challenge because of the complex plant physiological and biochemical processes associated with drought. Here, this study incorporates a drought index into an existing process-based terrestrial ecosystem model to estimate the drought impact on global plant production for the period 2001–10. Global Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data products are used to constrain model parameters and verify the model algorithms. The verified model is then applied to evaluate the drought impact. The study indicates that droughts will reduce GPP by 9.8 g C m−2 month−1 during the study period. On average, drought reduces GPP by 10% globally. As a result, the global GPP decreased from 106.4 to 95.9 Pg C yr−1 while the global net primary production (NPP) decreased from 54.9 to 49.9 Pg C yr−1. This study revises the estimation of the global NPP and suggests that the future quantification of the global carbon budget of terrestrial ecosystems should take the drought impact into account.

Recommended citation: Liao, C., and Q. Zhuang, 2015: Reduction of Global Plant Production due to Droughts from 2001 to 2010: An Analysis with a Process-Based Global Terrestrial Ecosystem Model. Earth Interact., 19, 1–21, https://doi.org/10.1175/EI-D-14-0030.1. http://changliao.github.io/files/2015/tem_ei.pdf