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Research Interests
Water resources management:
Inclusiveness of stakeholder engagement processes and empowering marginalized communities (e.g., Indigenous communities) in water resources management
‘Serious games’ and stakeholder collaboration, social learning, and knowledge co-creation in water resources management
Water resources vulnerability and management in the Arctic
Ecosystem services in a water resources management context
Water resources modeling:
Artificial intelligence (i.e., machine learning, deep learning) and wavelet transform based approaches in hydrological forecasting (e.g., floods, droughts), as well as urban water supply system forecasting
Participatory coupled human-water systems modeling approaches, including stakeholder-friendly dynamic coupling of stakeholder built system dynamics models with physically based models
Hydro-meteorological trend estimation (e.g., streamflow, precipitation), and linking dominant periodicities with climate indices (e.g., PDO, NAO, ENSO)
Groundwater contamination and remediation modeling
Sustainable agriculture; water and food security; renewable energy:
Agro-ecological food web modeling
Smallholder agriculture
Irrigation forecasting; optimizing agricultural water use; supplemental irrigation
Grassland degradation and restoration in the Qinghai-Tibetan Plateau
Effects of land use and agricultural practices on soil carbon storage
Tillage implements and soil structure
Solar and wind energy prediction
Research project locations:
Canada (Quebec, Ontario, Arctic); USA; Mexico; Guatemala; Brazil; Cuba; Germany; Cyprus; Poland; Italy; Hungary; Spain; United Kingdom; Egypt; Jordan; Israel; Algeria; Iran; Saudi Arabia; India; Nepal; Mongolia; Kyrgyzstan; Georgia; Pakistan; Ethiopia; Cameroon; Ivory Coast; Nigeria; Australia; Japan; South Korea; China.
Water resources management:
Inclusiveness of stakeholder engagement processes and empowering marginalized communities (e.g., Indigenous communities) in water resources management
‘Serious games’ and stakeholder collaboration, social learning, and knowledge co-creation in water resources management
Water resources vulnerability and management in the Arctic
Ecosystem services in a water resources management context
Water resources modeling:
Artificial intelligence (i.e., machine learning, deep learning) and wavelet transform based approaches in hydrological forecasting (e.g., floods, droughts), as well as urban water supply system forecasting
Participatory coupled human-water systems modeling approaches, including stakeholder-friendly dynamic coupling of stakeholder built system dynamics models with physically based models
Hydro-meteorological trend estimation (e.g., streamflow, precipitation), and linking dominant periodicities with climate indices (e.g., PDO, NAO, ENSO)
Groundwater contamination and remediation modeling
Sustainable agriculture; water and food security; renewable energy:
Agro-ecological food web modeling
Smallholder agriculture
Irrigation forecasting; optimizing agricultural water use; supplemental irrigation
Grassland degradation and restoration in the Qinghai-Tibetan Plateau
Effects of land use and agricultural practices on soil carbon storage
Tillage implements and soil structure
Solar and wind energy prediction
Research project locations:
Canada (Quebec, Ontario, Arctic); USA; Mexico; Guatemala; Brazil; Cuba; Germany; Cyprus; Poland; Italy; Hungary; Spain; United Kingdom; Egypt; Jordan; Israel; Algeria; Iran; Saudi Arabia; India; Nepal; Mongolia; Kyrgyzstan; Georgia; Pakistan; Ethiopia; Cameroon; Ivory Coast; Nigeria; Australia; Japan; South Korea; China.
研究兴趣
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GEO-EXTREME 2021: INFRASTRUCTURE RESILIENCE, BIG DATA, AND RISK (2021): 343-351
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