HGS RESEARCH HIGHLIGHT – Three‐Dimensional Geostatistical Inverse Analyses of Transient Head and Temperature Data From a Long‐Term Heat Tracer Test
Research Highlight, HGS, Groundwater, Calibration, Numerics, Sensitivity analysis, Hydrological processes, Water Resources Management Veljko Zaric Research Highlight, HGS, Groundwater, Calibration, Numerics, Sensitivity analysis, Hydrological processes, Water Resources Management Veljko Zaric

HGS RESEARCH HIGHLIGHT – Three‐Dimensional Geostatistical Inverse Analyses of Transient Head and Temperature Data From a Long‐Term Heat Tracer Test

We’re pleased to highlight this staff research highlighted which investigates how three-dimensional geostatistical inverse modelling can improve characterization of subsurface heterogeneity in groundwater systems. This study leverages HydroGeoSphere (HGS) to simulate fully coupled groundwater flow and transport processes within a stochastic inversion framework, addressing long-standing challenges in estimating spatially distributed hydraulic conductivity fields from limited observational data.

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HGS RESEARCH HIGHLIGHT – Using High-Resolution Data to Test Parameter Sensitivity of the Distributed Hydrological Model HydroGeoSphere
Research Highlight, Case Studies, HGS, Hydrological processes, Watershed hydrology, Sensitivity analysis, Calibration, Land surface modelling, Evapotranspiration Veljko Zaric Research Highlight, Case Studies, HGS, Hydrological processes, Watershed hydrology, Sensitivity analysis, Calibration, Land surface modelling, Evapotranspiration Veljko Zaric

HGS RESEARCH HIGHLIGHT – Using High-Resolution Data to Test Parameter Sensitivity of the Distributed Hydrological Model HydroGeoSphere

By integrating HydroGeoSphere in this study, the researchers demonstrate its versatility in accommodating high-resolution data and conducting sensitivity analyses across different spatial scales. Precipitation emerges as the most sensitive input data, significantly influencing total runoff and peak flow rates. Additionally, the study highlights the importance of spatially distributed land use parameterization in accurately simulating evapotranspiration components and patterns.

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