Merge pull request #198 from changliao1025/development

Development

paper.bib

@@ -112,19 +112,21 @@ @article{Sahr:2011
 }
 
 @article{Liao:2023b,
-author = {Liao, Chang and Zhou, Tian and Xu, Donghui and Cooper, Matthew G. and Engwirda, Darren and Li, Hong-Yi and Leung, L. Ruby},
-title = {Topological Relationship-Based Flow Direction Modeling: Mesh-Independent River Networks Representation},
+author = {Liao, Chang and Zhou, Tian and Xu, Donghui and Tan, Zeli and Bisht, Gautam and Cooper, Matthew G. and Engwirda, Darren and Li, Hong-Yi and Leung, L. Ruby},
+title = {Topological Relationship-Based Flow Direction Modeling: Stream Burning and Depression Filling},
 journal = {Journal of Advances in Modeling Earth Systems},
 volume = {15},
-number = {2},
-pages = {e2022MS003089},
-keywords = {watershed, land-river-ocean interaction, flow direction, river network, unstructured mesh, graph theory},
-doi = {https://doi.org/10.1029/2022MS003089},
-url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022MS003089},
-eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2022MS003089},
-note = {e2022MS003089 2022MS003089},
-abstract = {Abstract 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 (a) graph theory algorithms to simplify real-world vector-based river networks and assist in mesh generation; and (b) a topological relationship-based method to reconstruct conceptual river networks. The main advantages of our method are that (a) it combines the strengths of vector-based and DEM raster-based river network extraction methods; and (b) 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.},
+number = {11},
+pages = {e2022MS003487},
+keywords = {flow direction, depression filling, mesh independent, unstructured mesh, hydrology, flow routing},
+doi = {https://doi.org/10.1029/2022MS003487},
+url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022MS003487},
+eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2022MS003487},
+note = {e2022MS003487 2022MS003487},
+abstract = {Abstract Flow direction modeling consists of (a) an accurate representation of the river network and (b) 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 (a) a topological relationship-based hybrid breaching-filling method to conduct stream burning for the river network and (b) 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.},
 year = {2023}
 }
 
 
+
+

paper.md

@@ -18,7 +18,7 @@ authors:
     affiliation: 1
 
 affiliations:
- - name: Atmospheric Sciences and Global Change, Pacific Northwest National Laboratory, Richland, WA, USA
+ - name: Atmospheric, Climate, and Earth Sciences, Pacific Northwest National Laboratory, Richland, WA, USA
    index: 1 
 date: 23 Mar 2023