Limpopo River Basin Digital Twin Open Data Cube Catalog
Date Issued
Date Online
Language
Type
Review Status
Access Rights
Metadata
Full item pageCitation
Afham, Abdul; Silva, Paulo; Ghosh, Surajit; Kiala, Zolo; Retief, H.; Dickens, Chris; Garcia Andarcia, Mariangel. 2024. Limpopo River Basin Digital Twin Open Data Cube Catalog. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 22p.
Permanent link to cite or share this item
External link to download this item
DOI
Abstract/Description
A Limpopo River Basin (LRB) Digital Twin, a significant technological innovation, is being developed to assist water managers to assess and manage the water resources of the basin in sustainable ways. At the core of this innovation, the LRB Digital Twin compiles and serves a variety of raster datasets with unique spatial and temporal resolutions tailored to the basin’s characteristics. These datasets include hydrological variables (e.g., precipitation), climate indicators (e.g., temperature), and land surface characteristics (e.g., vegetation cover, land use). Each data set compromises with advanced preprocessing, fusion, and calibration to ensure consistency, accuracy, and reliability, making it suitable for long-term analysis and immediate decision-making.
The Open data cube (ODC) framework was used to organize, visualize and analyze the datasets for different stakeholders of LRB effectively. Automations were built on top of the ODC stack for a smooth workflow, which include steps like creating and indexing the metadata into a database. The present report describes the structure ODC follows in cataloging raster datasets, automations in place for handling ODC tasks and implementation steps taken to get ODC and its components up and running.
The available products for the Limpopo region include comprehensive data on irrigated areas and drought index. Additionally, there are environmental flow (E-flow) warnings that provide more insights. These resources collectively support thorough understanding of the region’s water and land management dynamics.
This helps policymakers and water managers make informed decisions about resource management and agricultural planning, enabling them to respond more effectively to water-related challenges.
Author ORCID identifiers
Zolo Kiala https://orcid.org/0000-0002-5119-738X
Chris Dickens https://orcid.org/0000-0002-4251-7767
Mariangel Garcia https://orcid.org/0000-0002-4145-0847