2020-12-10 AGU hydrology highlight: AGU Hydrology Highlight.
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2021-12-09 HexWatershed workshop “Variable-resolution flow routing in Earth System Models: An introduction to HexWatershed” was accepted by AGU Frontiers in Hydrology Meeting 2022. AGU FIHM.
2022-07-28 Our study using results from HexWatershed to investigate the river-ocean interactions was published in HESS: Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh.
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
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
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 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
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
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
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
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
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
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
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
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
Ecosystem, PNNL, 2020
A three-dimensional water and carbon cycle ecosystem model (ECO3D) (C++ and OpenMP, documented by Doxygen).
Hydrology, PNNL, 2020
HexWatershed: a mesh independent flow direction model for hydrologic models.
Earth scence, PNNL, 2022
PyEarth is a lightweight Python package to support various Earth science tasks. It is designed to be a general-purpose library as it is inspired by the popular IDL Coyote library (http://www.idlcoyote.com/).
Hydrology, PNNL, 2022
Pyflowline: a mesh-independent river network generator for hydrologic models.
PNNL mini conference 2023.