Staff Research Highlight - Application of Different Weighting Schemes and Stochastic Simulations to Parameterization Processes Considering Observation Error

Staff Research Highlight - Application of Different Weighting Schemes and Stochastic Simulations to Parameterization Processes Considering Observation Error

In this paper co-authored by Aquanty personnel, researchers explore how different weighting schemes and stochastic simulations can enhance the accuracy of parameter estimation processes, ultimately reducing uncertainty in climate change impact assessments.

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Staff Research Highlight - Spatiotemporal estimation of groundwater and surface water conditions by integrating deep learning and physics-based watershed models

Staff Research Highlight - Spatiotemporal estimation of groundwater and surface water conditions by integrating deep learning and physics-based watershed models

We’re pleased to highlight this publication, co-authored by Aquanty’s senior scientist, Hyoun-Tae Hwang, which focuses on the integration of deep learning (DL) models with physics-based hydrological models to enhance the efficiency of estimating spatiotemporal groundwater and surface water conditions.

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Staff Research Highlight - Effects of soil heterogeneity and preferential flow on the water flow and isotope transport in an experimental hillslope

Staff Research Highlight - Effects of soil heterogeneity and preferential flow on the water flow and isotope transport in an experimental hillslope

We’re pleased to highlight this publication, co-authored by Aquanty’s senior scientist, Hyoun-Tae Hwang, which examines the water sources and threshold behaviours of streamflow generation in a mountain headwater catchment.

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Staff Research Highlight - Assessment of hydraulic and thermal properties of the Antarctic active layer: Insights from laboratory column experiments and inverse modelling

Staff Research Highlight - Assessment of hydraulic and thermal properties of the Antarctic active layer: Insights from laboratory column experiments and inverse modelling

We’re pleased to highlight this publication, co-authored by Aquanty’s senior scientist, Hyoun-Tae Hwang, which investigates the hydraulic and thermal properties of the Antarctic active layer using laboratory column experiments and HydroGeoSphere (HGS) for inverse modeling.

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HGS RESEARCH HIGHLIGHT – Evaluation of Hydraulic Conductivity Estimates from Various Approaches with Groundwater Flow Models

HGS RESEARCH HIGHLIGHT – Evaluation of Hydraulic Conductivity Estimates from Various Approaches with Groundwater Flow Models

Over several decades a wide variety of techniques have been used to estimate the hydraulic flow properties of the subsurface. Here the authors have produced heterogeneous hydraulic conductivity (K) distributions at a heavily instrumented research site using 6 distinct techniques (slight variations in some tests resulted in 9 distinct K distributions):.

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HGS RESEARCH HIGHLIGHT – Impacts of Climate Change and Different Crop Rotation Scenarios on Groundwater Nitrate Concentrations in a Sandy Aquifer

HGS RESEARCH HIGHLIGHT – Impacts of Climate Change and Different Crop Rotation Scenarios on Groundwater Nitrate Concentrations in a Sandy Aquifer

This study by researchers at the University of Guelph investigated the impacts of various crop rotation scenarios and climate change on groundwater nitrate concentrations in a 155 sq-km agricultural sub-watershed in Norfolk County, Ontario.  

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HGS RESEARCH HIGHLIGHT – An adaptive zone-based refinement method for characterizing a highly complex aquifer system model

HGS RESEARCH HIGHLIGHT – An adaptive zone-based refinement method for characterizing a highly complex aquifer system model

This new paper by Aquanty senior scientist Hyoun-Tae Hwang introduces an innovative new method to iteratively refine model meshes based on model sensitivity and uncertainty, as calculated by PEST. The paper presents an initial proof-of-concept for this new method, based on the K-COSEM test site located in Eumseong-gun, South Korea.

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