<p>Underground water zoning remains limited due to sparse hydrogeological data in Chikwawa District, Malawi. This paper integrated the geophysical and hydrogeological approaches to delineate shallow aquifers in this district. Using the gravity data, the residual gravity anomalies were derived by removing regional trends employing a high-order polynomial surface fitting technique, and the resulting anomalies were spatially interpolated across the study area. The borehole datasets were extracted at corresponding locations to examine their relationship with the residual gravity field. The statistical analyses were employed to evaluate these relationships, including Pearson correlation and linear regression. Furthermore, K-means clustering was applied to group boreholes into zones exhibiting similar geophysical and hydrogeological characteristics. The results indicated weak but statistically significant correlations between residual gravity and borehole parameters, suggesting a limited direct relationship. However, the clustering analysis identified three distinct zones that reflected coherent spatial patterns, potentially linked to variations in groundwater availability. While the correlation between gravity anomalies and borehole data is modest, the findings demonstrate that the combined use of gravity analysis and unsupervised clustering offers a valuable framework for identifying areas of groundwater potential. The study underscores the value of integrating geophysical and hydrogeological data, recommending field validation to support sustainable groundwater management.</p>

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Geophysical delineation of groundwater zones in Chikwawa District based on residual gravity anomalies

  • Robert Galatiya Suya,
  • John Bosco Ogwang,
  • Rosemary Nyamwera,
  • Charles Chisha Kapachika,
  • Mwayi Michael Taulo,
  • Samson Mazonde Banda

摘要

Underground water zoning remains limited due to sparse hydrogeological data in Chikwawa District, Malawi. This paper integrated the geophysical and hydrogeological approaches to delineate shallow aquifers in this district. Using the gravity data, the residual gravity anomalies were derived by removing regional trends employing a high-order polynomial surface fitting technique, and the resulting anomalies were spatially interpolated across the study area. The borehole datasets were extracted at corresponding locations to examine their relationship with the residual gravity field. The statistical analyses were employed to evaluate these relationships, including Pearson correlation and linear regression. Furthermore, K-means clustering was applied to group boreholes into zones exhibiting similar geophysical and hydrogeological characteristics. The results indicated weak but statistically significant correlations between residual gravity and borehole parameters, suggesting a limited direct relationship. However, the clustering analysis identified three distinct zones that reflected coherent spatial patterns, potentially linked to variations in groundwater availability. While the correlation between gravity anomalies and borehole data is modest, the findings demonstrate that the combined use of gravity analysis and unsupervised clustering offers a valuable framework for identifying areas of groundwater potential. The study underscores the value of integrating geophysical and hydrogeological data, recommending field validation to support sustainable groundwater management.