Manitoba Co-operator - Hydrology forecasting tool drills down to field level
Farmers in the Assiniboine River basin will soon have access to a new tool designed to help them make predictions about water flow at the field level. The tool was developed by the hydrologic modelling firm Aquanty, in cooperation with the Manitoba Forage and Grasslands Association. They are able to combine their model with remote sensing data on things like soil moisture levels and real time groundwater monitoring sensors to set the initial conditions before launching a hydrologic forecast. “Combining that with insights on how water management infrastructure is maintained during floods and droughts and using cloud computing infrastructure, we can readily construct these models and deliver them via an app to your fingertips,”
HGS RESEARCH HIGHLIGHT – Sequential surface and subsurface flow modeling in a tropical aquifer under different rainfall scenarios
This paper demonstrates how HGS is flexible enough to model specific regions/domains of interest (i.e. including discrete fracture networks, but without integrated surface hydrology) and can be used in conjunction with other hydrologic modelling platforms.
HGS RESEARCH HIGHLIGHT – Analysis of drought conditions and their impacts in a headwater stream in the Central European lower mountain ranges
A new study by researchers at the University Bayreuth investigates the impact that climate change may have on drought conditions in forested catchment with riparian wetland, specifically the Lehstenbach catchment in the Fichtel Mountains of South-Eastern Germany.
HGS RESEARCH HIGHLIGHT – A hybrid approach for integrated surface and subsurface hydrologic simulation of baseflow with Iterative Ensemble Smoother
This paper introduces the development of an integrated model for the South Québec region where low-flow processes are of primary concern. In this publication, HydroGeoSphere is used with a surface water mass balance module in order to reduce computational cost, enabling the use of mathematically rigorous, ensemble-based methods to support a calibration-constrained predictive uncertainty analysis.
