Research Interests

Canadian Prairie Agrohydrology

Hydrological processes are incredibly complex in the sub-humid cold climate of the Canadian Prairies and define agricultural production. With a drive to improve understanding ag-water interactions of this region key processes of interest include snow accumulation and redistribution, snowmelt, frozen and unfrozen soil infiltration, soil water retention and transmission, evaporation from soils and wetlands, transpiration from crops, and runoff generation. Additional interests include the scaling of these processes from point to watershed scales and their interactions with agricultural management practices. These interests are investigates utilizing field based observations and modelling with specific work on:

  • Improving understanding of crop water use efficiency in contemporary agricultural production systems from field based observations.

  • Quantifying water balances of agricultural systems to understand the importance of different cold and warm season hydrological processes and interactions with agricultural practices.

  • Developing frameworks to identify and quantify opportunities to improve crop water availability and increase agricultural resilience to weather and climate extremes with optimization of land management practices such as stubble and crop residue management.

  • Developing modelling tools that integrate crop growth and hydrological processes that are appropriate to the cold-water limited climate of the Canadian prairies.

Energy and Water Balance Observation Station at the Livestock and Forage Centre for Excellence near Clavet SK
Snow Accumulation and Wheat Stubble Interactions near Rosthern SK

Improving representations of prairie hydrology in precision agriculture

Water underlies all aspects of agronomy with implications on yield potential, nutrient use efficiency, and carbon sequestration to name a few buzzwords. Growing capabilities of sensor networks and modelling tools to quantify weather and soil moisture at the field level and adoption of precision ag technologies to manage production provide many opportunities improve understanding of production risks and improve efficiencies. Multiple objectives can be supported with improved understanding and tools to quantify water dynamics underlying crop production in the cold water-limited prairies. Development of decision support tools that incorporate appropriate agrohydrology interactions is an ongoing interest to support (but not limited to):

  • 4R nutrient management to optimize nutrient management to support economic and environmental goals
  • Variable rate management based on spatial and temporal variability in crop available water
  • Optimization of stubble and residue management to maximize crop water availability accounting for variability in soils, climate and antecedent moisture conditions.
Spatial variability of crop growth was highly correlated to crop water availability in 2021 drought at Livestock and Forage Centre for Excellence near Clavet SK

Drone based remote sensing

The development of drone based remote sensing in the last decade offers an unprecedented ability to quantify the spatial variability of the land surface and associated hydrological processes. This interest spans sensor development, flight operations, data processing, and translation to scientific understandings with hundreds of hours of operations and terabytes of data generation across western Canada from the Prairies to the Rockies.

Specific interests include mapping the spatial variability of:

  • Snow:
    • Snow depth in open and forested environments from lidar and structure from motion techniques.
    • Snow water eEquivalent with gamma ray spectroscopy
    • Snow surface properties such as albedo and surface temperature from multi/hyperspectral and thermal sensors to resolve the snow surface energy balance.
  • Crop Growth
    • Physical structure such as height and LAI from lidar
    • Stress with multispectral indices such as NDVI
    • Surface temperature from thermal sensors to resolve water stress
    • Integration of drone based observations, insitu meteorological observations, and energy balance modeling to quantify the spatial variability of crop water use.
  • Elevation
    • A basic component of hydrological process understanding on landscape regular mapping of research site elevation utilizes both lidar and structure from motion techniques
    • Have supported varied research efforts ranging from predictive soil mapping, glacier change monitoring, and estimation of snow storage chemical loading.

Drone based research is possible with involvement in the Smart Water System Laboratory and research supports of the Centre for Hydrology, the Global Institute for Water Security, and the Transformative Sensor Technologies and Smart Watersheds project.

Drone lidar mapping of snow depth in the Canadian Rockies
Mapping spatial variability of crop growth and water with an integrated lidar, multispectral and thermal drone system near Broderick SK
Drone lidar elevation map of the University of Saskatchewan Kernen Research Farm

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