Posts by Collection
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/tem2015.pdf
Published in Zenodo, 2017
Anusplin_pro is a C++ program to run the Anusplin program in batch mode.
Recommended citation: Chang Liao. (2020, July 5). A C++ program to generate grid-based climate data (Version 1.0.0). Zenodo. http://doi.org/10.5281/zenodo.3930590 http://changliao.github.io/files/anusplin2017.pdf
Published in Journal of Open Source Software, 2017
HexWatershed is a C++ program to run watershed delineation on a hexagon mesh grid.
Recommended citation: Liao, C., (2020). HexWatershed: A watershed delineation model based on hexagon mesh grid. Journal of Open Source Software, 5(54), 2751. https://doi.org/10.21105/joss.02751 http://changliao.github.io/files/hexwatershed_joss2020.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/modflow2017.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/prms2017.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/eco3d2019.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
GIS, PNNL, 2020
An advanced automated spatial data processing library for GIS/RS datasets (IDL and ESRI ArcObject).
Ecosystem, PNNL, 2020
A three-dimensional water and carbon cycle ecosystem model (ECO3D) (C++ and OpenMP, documented by Doxygen).
Compute Graphic, PNNL, 2020
An advanced publication-ready cartography graphics library (IDL, 90% of figures in my publications were directly produced using this library).
Hydrology, PNNL, 2020
A global scale river routing model based on HexWatershed (The first global river network using hexagonal mesh).
Hydrology, PNNL, 2020
A hexagonal grid-based surface watershed delineation model, HexWatershed (The first watershed scale model using hexagonal mesh; C++, based on DGGRID and RichDEM, documented by Doxygen).
Hydrology, PNNL, 2020
A USGS Modular Finite-Difference Ground-Water Flow Model (MODFLOW) model preparation system (IDL and Python).
Hydrology, PNNL, 2020
A USGS Precipitation Runoff Modeling System (PRMS) model preparation system (IDL and Python).