Timor-Leste’s economy and the livelihood of its people are dependent on groundwater. In Timor-Leste these groundwater resources are replenished by rainfall in the wet season providing storage for use throughout the year. Greater demand for groundwater in Timor-Leste from increases in population, industry and agriculture has caused a strain on this resource and its current prospectivity and sustainability is largely unknown. This study has developed a rapid national hydrogeology assessment framework for consistent groundwater system understanding that can inform future development of the resource.
This study has brought together national datasets as well as collected new data in three cases study sites. Case study locations are representative of the three principal aquifer types identified in the hydrogeology mapping. Fieldwork at each of the case study sites involved: 1) ground-truthing of aquifer characteristics, 2) ground-based electromagnetic geophysical (TEM) surveys to delineate aquifer architecture and groundwater conductivity, and 3) direct measurement of groundwater levels and hydrogeochemistry.
The hydrogeology framework was designed to simply and clearly demonstrate how existing and new datasets can be rapidly combined to produce consistent information and maps for groundwater prospectivity and vulnerability. The framework allows for limited groundwater information by using surrogate datasets for initial assessments through a system based (knowledge) approach. The framework also allows for incorporation of detailed site-specific groundwater measurements and information to the national scale (data approach). The method and datasets are transparent to permit the user to define data inputs and weightings. The framework has been applied to Timor-Leste to produce a national hydrogeological map that in turn informed an assessment of groundwater vulnerability.
Through the development of a rapid national hydrogeology assessment framework, Timor-Leste now has a consistent national hydrogeology map. This framework enables the incorporation of new knowledge and data, as it becomes available over time, and can be applied to multiple scales including continents such as Australia.