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What motivates our group
Accurate prediction of the stream hydrograph [and stream water quality] implies adequate modeling of sources, pathways and residence time of water and solutes
[Hewlett and Troendle, 1975].
Decades after Hewlett and Troendle's writing, we still know little about the sources, pathways and residence time of water and solutes within headwaters and their parent watersheds. This lack of scientific knowledge has limited the ability to sufficiently predict the impacts of climate variability and land-use alteration on the quality and quantity of stream water. HydroGeoscience for Watershed Management (HG-WM) research group advances the scientific knowledge on the quantification of sources, pathways and residence time of water and solutes to inform watershed management, under changing climate and land-use. In doing so, we use physically-based and conceptual hydrologic models as well as we develop new physics-informed machine learning and statistical models.
Accurate prediction of the stream hydrograph [and stream water quality] implies adequate modeling of sources, pathways and residence time of water and solutes
[Hewlett and Troendle, 1975].
Decades after Hewlett and Troendle's writing, we still know little about the sources, pathways and residence time of water and solutes within headwaters and their parent watersheds. This lack of scientific knowledge has limited the ability to sufficiently predict the impacts of climate variability and land-use alteration on the quality and quantity of stream water. HydroGeoscience for Watershed Management (HG-WM) research group advances the scientific knowledge on the quantification of sources, pathways and residence time of water and solutes to inform watershed management, under changing climate and land-use. In doing so, we use physically-based and conceptual hydrologic models as well as we develop new physics-informed machine learning and statistical models.
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ALI AMELI (Director)
I am a hydrologist interested in exploring how water and solutes move and react within watersheds, how these movements and reactions change with climate variability and land-use alteration, and ultimately, how these changes impact terrestrial and aquatic ecosystems. I currently lead national and international projects on the development of interdisciplinary approaches for water security assessments and watershed management in collaboration with geochemists, ecologists, agricultural and forestry scientists, as well as water conservation and protection agencies. Through this work, we are developing science-based evidence on the interaction amongst hydrological, geochemical, and ecological processes to inform watershed management, planning, and engineering designs for the end-goal of managing the environmental impacts of climate variability and land-use alteration on groundwater and surface water resources. |
RESEARCH GROUP
UBC's HydroGeoscience for Watershed Management (HG-WM) research group combines different environmental and statistical science disciplines in order to scientifically manage the environmental impacts of climate and land-use changes. In particular, HG-WM (1) advances the knowledge on materiel (water & solute) transport below and above the land surface, to (2) inform science-based watershed management strategies and land-use planing, and to (3) design engineered groundwater and surface water protection and purification systems. For the details of our current projects, please see the research section. The research group members receive full support from HG-WM director to obtain high-level professional development and to achieve their career goals and dreams. Our group members have already received prestigious scholarships and fellowships. In addition, our group alumnus have already landed high-level jobs in environmental and statistical agencies, or continued their graduate studies in top-ranked Universities. |
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RESEARCH INTERESTS:
Groundwater Ecohydrology Hydro-geological Engineering Watershed Management Applied Hydro-geochemistry Groundwater - Surfacewater & Land Interaction Water Resources Engineering Statistical Machine Learning Functional Data Analysis |
NSERC SUBJECTS:
4504 Groundwater 1007 Water Resources and Supply 1501 Water Quality 4501 Hydrogeochemistry 1006 Hydrologic Engineering 2203 Modeling, Simulation |
