(HS 1) Toward Seamless Environmental Modeling: Integration of HydroShare with Server-side Methods for Exposing Large Datasets to Models


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Type: Collection
Storage: The size of this collection is 4.6 KB
Created: May 14, 2021 at 2:59 a.m.
Last updated: Jan 15, 2024 at 3:17 a.m.
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Sharing Status: Public
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Abstract

Ensuring the reproducibility of scientific studies is crucial for advancing research, with effective data management serving as a cornerstone for achieving this goal. Ensuring the reproducibility of scientific studies is crucial for advancing research, with effective data management serving as a cornerstone for achieving this goal. In hydrologic and environmental modeling, spatial data is used as model input and sharing of this spatial data is a main step in the data management process. However, by focusing only on sharing data at the file level through small files rather than providing the ability to Find, Access, Interoperate with, and directly Reuse subsets of larger datasets, online data repositories are missing an opportunity to foster more reproducible science. This leads to challenges when accommodating large files which benefit from consistent data quality and seamless geographic extent. To utilize the benefits of large datasets, the objective of this study is therefore to create and test an approach for exposing large extent spatial (LES) datasets to support catchment-scale hydrologic modeling needs. GeoServer and THREDDS Data Server connected to HydroShare were used to provide seamless access to LES datasets. The approach is demonstrated using the Regional Hydro-Ecologic Simulation System (RHESSys) for three different sized watersheds in the US. We assessed data consistency across three different data acquisition approaches: the ‘conventional’ approach, which involves sharing data at the file level through small files, as well as GeoServer, and THREDDS Data Server. This assessment is conducted using RHESSys to evaluate differences in model streamflow output. This approach provides an opportunity to serve datasets needed to create catchment models in a consistent way that can be accessed and processed to serve individual modeling needs.

This collection resource comprises 17 individual HydroShare resources (HS 2-18), each containing different datasets or workflows. These 17 HydroShare resources consist of the following: one collection resource (HS 1), three resources for three state-scale LES datasets (HS 2-4), nine resources with Jupyter notebooks for three different approaches and three different watersheds (HS 5-13), three resources for RHESSys model instances (i.e., input) of the conventional approach in three different watersheds (HS 14-16), one resource with Jupyter notebooks for automated workflows to create LES datasets (HS 17), and one resource with Jupyter notebooks for the evaluation of data consistency (HS 18). More information on each resource is provided within it.

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:
WGS84 EPSG:4326
Coordinate Units:
['Decimal degrees']
North Latitude
41.2137°
East Longitude
-73.6827°
South Latitude
32.4359°
West Longitude
-85.1501°

Collection Contents

Add Title Type Owners Sharing Status Remove
(HS 3) Large Extent Spatial Datasets in Maryland Resource Iman Maghami Public & Shareable
(HS 4) Large Extent Spatial Datasets in Virginia Resource Zhiyu/Drew Li Public & Shareable
(HS 2) Large Extent Spatial Datasets in North Carolina Resource Zhiyu/Drew Li Public & Shareable
(HS 14) RHESSys Spatial Input Data at Coweeta Subbasin18, North Carolina Resource Young-Don Choi Public & Shareable
(HS 15) RHESSys Spatial Input Data at Scotts Level Branch, Maryland Resource Young-Don Choi Public & Shareable
(HS 16) RHESSys Spatial Input Data at Spout Run, Virginia Resource Iman Maghami Public & Shareable
(HS 17) Automate Workflows using Jupyter notebook to create Large Extent Spatial Datasets Resource Jonathan Goodall Public & Shareable
(HS 6) Jupyter notebook for RHESSys modeling workflow using the GeoServer approach at Coweeta Subbasin18, NC Resource Young-Don Choi Public & Shareable
(HS 5) Jupyter notebook for RHESSys modeling workflow using the conventional approach at Coweeta Subbasin18, NC Resource Young-Don Choi Public & Shareable
(HS 7) Jupyter notebook for RHESSys modeling workflow using the THREDDS approach at Coweeta Subbasin18, NC Resource Zhiyu/Drew Li Public & Shareable
(HS 8) Jupyter notebook for RHESSys modeling workflow using the conventional approach at Scotts Level Branch, MD Resource Zhiyu/Drew Li Public & Shareable
(HS 9) Jupyter notebook for RHESSys modeling workflow using the GeoServer approach at Scotts Level Branch, MD Resource Zhiyu/Drew Li Public & Shareable
(HS 10) Jupyter notebook for RHESSys modeling workflow using the THREDDS approach at Scotts Level Branch, MD Resource Zhiyu/Drew Li Public & Shareable
(HS 11) Jupyter notebook for RHESSys modeling workflow using the conventional approach at Spout Run, VA Resource Zhiyu/Drew Li Public & Shareable
(HS 13) Jupyter notebook for RHESSys modeling workflow using the THREDDS approach at Spout Run, VA Resource Zhiyu/Drew Li Public & Shareable
(HS 18) Comparative Evaluation of Data Consistency: Conventional vs. Server-side Methods for Exposing Large Extent Spatial Datasets to Models Resource Zhiyu/Drew Li Public & Shareable
(HS 12) Jupyter notebook for RHESSys modeling workflow using the GeoServer approach at Spout Run, VA Resource Zhiyu/Drew Li Public & Shareable

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How to Cite

Choi, Y., J. Goodall, L. Band, I. Maghami, L. Lin, L. Saby, Z. Li, S. Wang, C. Calloway, M. Seul, D. Ames, D. Tarboton, H. Yi (2024). (HS 1) Toward Seamless Environmental Modeling: Integration of HydroShare with Server-side Methods for Exposing Large Datasets to Models, HydroShare, http://www.hydroshare.org/resource/afcc703d884e4f73b598c9e4b8f8a15e

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

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