Chandra Madramootoo, Director

Dr. Chandra Madramootoo, P.Eng., is a Distinguished James ºÚÁϲ»´òìÈ Professor in the Department of Bioresource Engineering at ºÚÁϲ»´òìÈ University, and Director of the ºÚÁϲ»´òìÈ Water Innovation Lab. With growing water scarcity and concerns about climate change, new technologies are being developed to conserve limited freshwater supplies and increase crop water productivity. Irrigation systems and techniques are being developed which can apply precise amounts of water while taking spatial field properties, crop type, and growth stage into account. Innovative technologies to predict crop water requirements and the impacts of various water management practices on greenhouse gas emissions are also being investigated. Water table management systems are being designed and field tested to reduce non-point source pollution and algal blooms/cyanobacterial contamination of rivers and lakes. 

☎ 514 398 7834

✉ chandra.madramootoo [at] mcgill.ca

 Shirley Mongeau, Administrative Coordinator

☎ 514 398 7833

✉ shirley.mongeau [at] mcgill.ca

Naresh Arumugagounder, Ph.D. Candidate

In the global urge of water conservation, new innovative methods involving water use efficiency are essential. Being a critical source of freshwater usage, agricultural industry is working on ways to increase the efficiency of the water use. An innovation in crop water stress studies is to combine satellite observatory images of ETc and soil moisture with scaled daily climatic data to generate real time prescription maps for site-specific irrigation which is applicable to thousands of hectares within irrigation/water management districts. Linking this data to a crop growth model is a powerful method of optimizing limited water supplies for maximum crop yield. The main objective of this study is to predict the irrigation water requirement of large-scale field crops using remotely sensed images using data fusion and GIS. In this research, we aim to fuse the several covariates extracted from the remotely sensed images together to generate yield prescription maps processed using the GIS. Covariate points extracted from the remotely sensed images are processed using these coupled ML models and the extracted data points from the model is processed using the GIS software to generate prescription maps.

✉ naresh.arumuga [at] mail.mcgill.ca

Tahmina Nasir Bushra, M.Sc. Candidate

Phosphorus and nitrogen are the primary drivers of eutrophication in freshwater systems. These pollutants come from both point and non-point sources; however, non-point sources are especially difficult to manage due to their diffuse nature. Agricultural fields, in particular, contribute significantly to non-point source pollution, leading to the overgrowth of aquatic plants and frequent algal blooms. My research seeks to mitigate phosphorus runoff from agricultural fields in the Holland Marsh by combining nature-based solutions, such as bioreactors, P removal structures and controlled drainage, with process-based modeling. This integrated approach aims to reduce eutrophication in Lake Simcoe and, in turn, improve its overall water quality. 

✉ tahmina.bushra [at] mail.mcgill.ca

Daniel Tamunoboma Dikio, Ph.D. Candidate

My research focuses on understanding the interaction between soil moisture and compaction, with a focus on tile drainage designs (depth and spacing) to reduce the risk of soil compaction due to machinery loads. My study site is a farm in Ontario with fields with variable drainage designs. The objective is to recommend the optimum drainage design, with particular focus on Southern Ontario and Quebec

✉ daniel.dikio [at] mail.mcgill.ca

Cody Danaher, Ph.D. Candidate

The relationships we foster, with one another and with nature, are embedded within our socio-ecological systems. Due to dynamic complexity, arising from non-linear relationships and delayed feedback processes, purposeful action in these systems often produces unexpected outcomes. In various socio-ecological systems, the implementation of nature-based solutions, such as wetland conservation and restoration efforts, to mitigate the effects of flooding has proven particularly challenging. Using participatory approaches in system dynamics modelling, my research aims to uncover the complexities and barriers to the implementation of nature-based solutions as a means of bolstering flood resilience in coastal and riverine communities.

✉ cody.danaher [at] mail.mcgill.ca

Sushree Sangita Dash, Ph.D. Candidate

Methane (CH4), a potent GHG with 28-30 times more global warming potential than carbon dioxide (CO2), contributes to 16% of total emissions, with agriculture responsible for a significant 40% of global CH4 emissions. Cattle alone contribute 77% of these emissions. Alberta is home to the largest share of Canada's beef farms, accounting for 36.8%, surpassing all other provinces. My research employs Unmanned Aerial Vehicles (UAVs) in tandem with atmospheric dispersion modeling to estimate CH4 concentrations in intensive cattle feedlots across Southern Alberta. Additionally, I am using machine learning (ML) and deep learning (DL) techniques to accurately estimate CH4 emission rates, incorporating various biophysical factors from the feedlots. This research is conducted in collaboration with scientists from Agriculture and Agri-food Canada (AAFC) in Lethbridge. This work is expected to contribute to the development of improved tools for monitoring, reporting, and verification (MRV) for effective CH4 emission management. Ultimately, my research aims to make a significant contribution to the global methane reduction pledge and Sustainable Development Goal 13 (Climate Action).

✉ sushree.dash [at] mail.mcgill.ca

Joel Z. Harms, Ph.D. candidate

Joel is a Ph.D. Student in the department of Bioresource Engineering under the supervision of Prof. Adamowski and Prof. Madramootoo working on tackling flooding in Guyana. He is interested in applying modelling to better understand and manage natural resources.

✉  joel.harms [at] mail.mcgill.ca

Farhan Ahmad, Research Assistant
MSc in Bioresource Engineering, ºÚÁϲ»´òìÈ University

My research focuses on the overexploitation of peatlands and its impact on food production, with an emphasis on greenhouse gas emissions from disturbed peatlands. The objective is to provide a comprehensive understanding of how peatland use affects greenhouse gas emissions and food security while informing policy recommendations for sustainable land management and climate change mitigation.

✉  Farhan.ahmad [at] mail.mcgill.ca

Harmanpreet Singh Grewal, Research Assistant
MSc in Bioresource Engineering, ºÚÁϲ»´òìÈ University

Phosphorus is among the key nutrients that cause eutrophication in freshwater ecosystems, primarily from diffuse sources such as agricultural fields. My research develops effective, sustainable approaches to reduce phosphorus inputs and protect water quality. By integrating machine learning and process-based modeling, I identify critical hotspots of phosphorus loading and design tailored mitigation measures. These include implementing phosphorus removal structures, optimizing land management, and evaluating best management practices. My goal is to advance our understanding of phosphorus transport mechanisms, help policymakers make informed decisions, and promote resilient freshwater ecosystems. By linking science, technology, and practice, I ensure water sustainability and resilience.

✉  harmanpreet.grewal [at] mail.mcgill.ca