Bias evaluation and minimization for estuarine total dissolved solids (TDS) patterns constructed using spatial interpolation techniques.

This study evaluated and minimized bias in estuarine total dissolved solids (TDS) patterns predicted using geostatistical approaches. The acquired TDS data was divided into three parts: 29 points (60 %) for predicting TDS patterns with spatial interpolation techniques, 12 points (25 %) for validation and bias correction, and 7 points (37 %) for testing the corrected bias. Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Universal Kriging (UK) and Regression Kriging (RK) were applied to map TDS patterns. R-square and Relative Error of Mean showed significant discrepancies between observed and predicted TDS levels. The Mean field bias (MFB) correction technique was applied to minimize bias in TDS patterns. After correcting bias, the TDS values predicted by IDW, OK, UK and RK at random locations deviated from measured values by -2.85 %, 0.71 %, 4.66 %, and - 6.03 % respectively. At the test locations, these values deviated by -1.45 %, 1.41 %, 2.11 %, and - 2.65 % respectively.