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Enhancing groundwater management using aggregated-data analysis and segmented robust regression: A case study on
Jize Piao1, Seong Woo Nam2, Yeongkyoo Kim3
1Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon, South Korea.
The Science of the Total Environment
|August 12, 2023
Summary
This study highlights the importance of analyzing aggregated secondary data for groundwater quality management. The developed methods reveal diverse spatiotemporal trends, improving water resource sustainability and public health protection.
Area of Science:
- Environmental Science
- Hydrogeology
- Water Resource Management
Background:
- Effective groundwater quality management is vital for sustainable water resources and public health.
- Traditional monitoring methods face challenges with limited resources and data quality.
Purpose of the Study:
- To demonstrate the significance of secondary data analysis for spatiotemporal groundwater quality characterization.
- To develop and employ robust trend and aggregation methods for identifying groundwater quality shifts.
Main Methods:
- Development and application of a robust trend analysis method.
- Implementation of a spatiotemporal data aggregation method to identify shifts over time.
- Analysis of aggregated data across selected regions in South Korea.
Main Results:
- Diverse spatiotemporal trends and characteristics in groundwater quality were identified.
- The analysis emphasized the importance of aggregated data over individual location data.
- The methods accurately identified shifts in groundwater quality, including breakpoints.
Conclusions:
- The study contributes to more reliable and effective groundwater quality management strategies.
- Addressing gaps in traditional monitoring and data challenges is crucial.
- Future research should explore applying these methods to other regions and data sources.
Keywords:
Adaptive groundwater managementData aggregationGroundwater qualitySegmented robust regressionSmall watershedsTrend analysisMore Related Videos
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