Natural recharge in crystalline hard rock is affected by multiple parameters such as magnitude and intensity of rainfall, lithological characteristics, temperature, evaporation, land management, etc. and hence turns to be one of the most complex nonlinear dynamic hydrogeological process with large scale spatial variability. This new article introduces an inversion scheme to couple such multiple hydrogeophysical parameters and constrained interpolation for the improved prediction of natural recharge with spatio-temporal distribution in a highly heterogeneous natural geological system. Natural recharge was coupled with soil resistivity, vadose zone thickness and rainfall, eventually leading to the proposition of the Lithologically Constrained Recharge (LCR) recharge methods applied in crystalline hard rocks. The spatio-temporal recharge by this method provides estimates that are more realistic in heterogeneous media. Once lithological parameters are known, it can be applied to estimate natural recharge for ±100 years or so by inputting annual precipitation.
Figure: (a) LCR recharge contours map without LCI constrained interpolation that observed unrealistic high recharge contours over hills; (b) data integration and laterally constrained - slope and curvature interpolation responses; (c) LLCR recharge contours map with optimal joint slope and curvature LCI constrained interpolation that improves spatial distribution of natural recharge.
Citation: Chandra, S., Jacobsen, B.H., Christensen, N.B. et al. Multiparametric coupling and constrained interpolation to improve natural recharge estimation. J Earth Syst Sci 129, 8 (2020). https://doi.org/10.1007/s12040-019-1253-z