Irena CreedFaculty of Science

Techniques

Remote Sensing | Digital Terrain Analysis & GIS | Modelling | Laboratory & Field | Scenario Analysis

Remote Sensing
"Remote sensing from satellite and airborne platforms, along with many other sources of hydrological data such as wireless sensor arrays and ground-based radar networks, is playing and will continue to play a vital role in better understanding the hydrosphere by providing the next generation of datasets to the hydrological community. Remote sensing systems are planetary macroscopes that allow the study of ecosystems from a completely new vantage point, facilitating a holistic perspective like viewing the Earth does for astronauts.

Remote sensing allows us to (1) view large geographic areas instantaneously; (2) spatially integrate over heterogeneous surfaces at a range of resolutions; (3) be totally unobtrusive; and (4) be cost effective compared to ground-based approaches. While there are challenges relating remote sensing data recorded in radiance or backscatter to variables of interest, and remote sensing systems have poor temporal resolution compared to ground-based measurement devices, remote sensing and spatial analytical techniques such as digital terrain analysis and distributed hydrological modeling embedded in Geographic Information Systems have allowed hydrologists to better understand the movement of water across a landscape" (Sass and Creed, 2011).

Lake Naivasha DEM

A satellite image of Lake Naivasha, Kenya, overlain on a digital elevation model

Selected Publications:
Sass GZ, Aldred DA, Wheatley M, Gould J, Creed IF. 2012. Protected areas: a hydrological approach for defining boundaries based on archived radar imagery. Biological Conservation 147: 143-152. [PDF]

Gala TS, Aldred DA, Carlyle S, Creed IF. 2011. Improved performance of models for predicting soil moisture using physically-based spatially averaging of synthetic aperture radar data. Remote Sensing of Environment. 115: 3507-3516. [PDF]

Sass GZ, Creed IF. 2011. Bird’s eye view of forest hydrology: Novel approaches using remote sensing techniques.  In DF Levia, DE Carlyle-Moses, T Tanaka (Eds. Forest Hydrology and Biogeochemistry: Synthesis of Research and Future Directions. Ecological Studies Series, No. 216, Springer-Verlag, Heidelberg, Germany.  Invited Book Chapter [PDF]

Clark RB, Sass GZ, Creed IF. 2009. Mapping hydrologically sensitive areas on the Boreal Plain: a multitemporal analysis of ERS synthetic aperture radar data. International Journal of Remote Sensing 30: 2619-2635. [PDF]

Digital Terrain Analysis and Geographic Information Systems
"Digital terrain analysis comprises a set of tools that use digital elevation models to model earth surface processes at a range of scales .... The ubiquity of digital terrain models in the hydrologist’s toolkit has led to the widespread use of terrain attributes such as slope and upslope contributing area to characterize the way water and associated nutrients move across landscapes. Algorithms to compute terrain attributes are now programmed into all commercial Geographic Information System software (e.g., ArcGIS, Idrisi) and with a push of the button users can map patterns of potential surface hydrological flows" (Creed and Sass, 2011).

Hydrologic Profiling

Digital elevation models (A), topographic feature maps (B), and global warming potential maps (C) from three sites in the Prairie Pothole Region of Saskatchewan (Creed et al. Submitted).

Selected Publications:
Webster KL, Creed IF, Beall FD, Bourbonniere RA. 2011. A topographic template for estimating soil carbon pools in forested landscapes. Geoderma 160: 457-467. [PDF]

Creed IF, Sass GZ. 2011. Digital terrain analysis approaches for tracking hydrological and biogeochemical pathways and processes in forested landscapes.  In DF Levia, DE Carlyle-Moses, T Tanaka (Eds. Forest Hydrology and Biogeochemistry: Synthesis of Research and Future Directions. Ecological Studies Series, No. 216, Springer-Verlag, Heidelberg, Germany.  Invited Book Chapter [PDF]

Creed IF, Beall FD. 2009. Distributed topographic indicators for predicting nitrogen export from headwater catchments. Water Resources Research 45: W10407. [PDF]

Modelling
Simulation models can be used to recreate natural systems in the laboratory and test the responsiveness of ecological systems. Statistical models, such as wavelet analyses and cross-correlation techniques, can be used to account for temporal variability in indicators of ecosystem services.

The Budyko Curve

How long-term ecological research sites fit with the Budyko curve (Jones et al. 2012).

Selected Publications:
Jones JA, Creed IF, Hatcher K, Warren R, Benson M, Boose E, Brown W, Campbell J, Covich A, Clow D, Dahm C, Elder K, Ford C, Grimm N, Henshaw D, Larson K, Miles E, Moore K, Sebestyen S, Stone A, Vose J, Williams M. 2012. Water supply sensitivity and ecosystem resilience to land use change, climate change, and climate variability at long-term ecological research sites. Bioscience 62: 390-404. Invited contribution to Special Issue on the US Long-Term Ecological Research Network. [PDF]

Laboratory and Field Research
Active research is being conducted in the laboratory at Western (in the Catchment Research Facility and the Biotron) and in the field around the world (including the Turkey Lakes Watershed of Ontario, the Boreal Plains of Alberta, and Lake Naivasha in Kenya) to both inform and ground-truth results from desktop studies.

Eric in the Field

Eric's N2O sampling experimental setup at Turkey Lakes.

Selected Publications:
Creed IF, Webster KL, Braun GL, Bourbonniere RA, Beall FD. In Press. Topographically regulated traps of dissolved organic carbon create hotspots of carbon dioxide efflux from forest soils. Biogeochemistry. [PDF]

Webster KL, Creed IF, Beall FD, Bourbonniere RA. 2011. A topographic template for estimating soil carbon pools in forested landscapes. Geoderma 160: 457-467. [PDF]

Scenario Analysis
Scenarios are stories about the future. Scenario analysis is not about prediction, but rather scenario logic, characteristics and storylines. It explors different assumptions about how causal relationships work and result in different outcomes. Scenario analysis is a structured process involving four fundamental steps: (1) identify the driving forces that influence a system; (2) define the critical uncertainties within the system; (3) describe the major characteristics of four alternative scenarios; and (4) develop logical policy paths that would be required to move towards the desired future and provide a set of indicators that can help recognize movement towards a different scenario or to a different stage along a scenario path.

Scenario Analysis Framework

Steps of scenario analysis (image adapted from presentation to the Forest Futures working group by A. Brummell 2008)