Technical Learning Exchange on groundwater data in decision support tools

The document details technical improvements to the BWDSS, including the development of a PostgreSQL timeseries provider, the creation of maintenance scripts to optimize database size, and a guide for operationalizing FEFLOW groundwater models. It identifies performance bottlenecks in specific jobs and recommends the implementation of regular maintenance tasks and improved error handling in Python scripts to enhance system resilience.

• The BWDSS database contains several large tables that could be reduced in size through maintenance; specifically, the 'blob' table is 3,214 MB and the 'change_log' table contains almost 5 million records that are rarely used.
• Current Python scripts in the system lack sufficient error handling and progress logging, which makes it difficult to determine the root cause of errors when jobs fail.
• DHI developed a MIKE Workbench timeseries provider as a .Net assembly (dll) to allow the BWDSS to access data stored in the dbo PostgreSQL schema without needing local copies of the data.
• To support the integration of groundwater resources, it is recommended that the City of Cape Town create a new database schema to store real-time timeseries from approximately 400 groundwater boreholes.
• While steady-state FEFLOW groundwater models for the Cape Flats and Steenbras Nardouw aquifers were successfully registered, the report notes that transient models are required for the operational goal of simulating and forecasting groundwater levels.

APA

WWF South Africa (2022). Technical Learning Exchange on groundwater data in decision support tools. https://wwfafrica.awsassets.panda.org/downloads/5_annexure_5_learning_exchange_partnering_with_dhi.pdf

Chicago

WWF South Africa. Technical Learning Exchange on groundwater data in decision support tools. 2022. https://wwfafrica.awsassets.panda.org/downloads/5_annexure_5_learning_exchange_partnering_with_dhi.pdf.

Wikipedia

{{cite report |author=WWF South Africa |title=Technical Learning Exchange on groundwater data in decision support tools |date=4 May 2022 |url=https://wwfafrica.awsassets.panda.org/downloads/5_annexure_5_learning_exchange_partnering_with_dhi.pdf |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{wwfsouthafrica2022technical, author = {{WWF South Africa}}, title = {{Technical Learning Exchange on groundwater data in decision support tools}}, institution = {WWF South Africa}, year = {2022}, month = may, url = {https://wwfafrica.awsassets.panda.org/downloads/5_annexure_5_learning_exchange_partnering_with_dhi.pdf}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }