Development of a Strategic-Level GIS Indicator-Based Watershed Assessment
Procedure for Assessing Cumulative Watershed Effects
Doug Lewis – Resource Practices Specialist, BC Ministry of Forests, Lands and Natural Resource Operations, Kamloops, BC
Michael Milne – Watershed Hydrologist, M.J. Mile & Associates Ltd., Vernon, BC.
Bill Grainger – Geoscientist, Grainger & Associates Ltd., Salmon Arm, BC.
1. Introduction and Background
6. Estimating Effects
The procedure developed out of the need to
understand potential cumulative watershed effects of
land use activity and natural disturbance over broad
geographic areas.
As a preliminary estimate of the likelihood of harmful changes in watershed processes, where
possible we used quantitative synthesis of the response of watershed processes and/or
aquatic organisms (benthic invertebrates, fish) to similar GIS-base metrics reported in the
published literature.
4. GIS Indicators and Model Structure
We used GIS-based indicators of inherent watershed sensitivity and land use
activity/natural disturbance to three key watershed processes: streamflow, sedimentation
and riparian function. Indicators were combined in ratings tables to provide sensitivity,
disturbance and hazard ratings(Figure 4).
The procedure builds from existing
watershed assessment procedures developed in BC
(e.g. BC MOF 1999, Carver and Utzig 2000, Green
2005). The work is now used to support strategiclevel cumulative effects assessment as part of BC’s
Cumulative Effects Framework (Lewis et al. 2015).
The procedure is intended as a first step to flag
‘higher risk’ catchments as part of a multi-step
watershed assessment approach (Figure 1).
Fig. 1. recommended multi-step approach to watershed
analysis necessary to move from strategic-level
recommendations to site-level actions
Fig 6. Quantitative synthesis of the relationship between percent agricultural (private) land and indices of biotic integrity from two published
studies (Left). Synthesized results were used to estimate the likelihood of harmful changes to watershed processes (Right).
2. Risk-based Approach
The procedure uses a risk-based approach where risk is a product of hazard and
consequence defined by the risk equation (Risk = Hazard x Consequence) and as applied
in the following matrix (Figure 2).
7. Indicator and Ratings Calibration
To further refine preliminary estimates, independent measures of impacts, collected through
targeted field-based monitoring in local catchments, are being used to calibrate indicator
measures and associated hazard ratings. The results will be used to calibrate hazard ratings in
subsequent versions and help validate model outcomes.
Fig 4. Indicators used in the watershed assessment procedure illustrating the linkages to sensitivity, disturbance and hazard ratings used
to express the likelihood of harmful changes in key watershed processes.
5. Example: Private Land Indicator
Indicators are intended to broadly capture effects of land use activities. In this example,
the potential impacts of riparian clearing on riparian function within private land are
estimated by analysing the extent of streams that overlap with private land.
Fig. 2. Risk matrix used in watershed risk analysis (adapted from Wise et al., 2004)
Fig 7. Targeted field-based assessments of stream functioning condition using BC’s Routine Riparian Effectiveness Evaluation protocol (Tripp, 2009)
were compared with GIS-based Hazard ratings and showed strong relationships to both highest hazard and riparian hazard ratings (Left). We used
Boosted Regression Tree (BRT)techniques to analyse the probability of properly functioning condition relative to indicator metrics . The percent of
total watershed stream length adjacent (<30m)from harvesting showed the strongest relationship to stream functioning condition (Right).
3. Multi-Scale Reporting Structure
We used BC Freshwater Atlas (FWA) 1:20,000 Watershed Assessment Unit (AU)
boundaries (Carver and Gray, 2010) as the base units to build a hierarchical watershed
structure for analysis and reporting hazard, consequence and risk ratings (Figure 3).
8. Conclusions
We strongly recommend that further work is required to validate model outcomes, and adjust
indicators, scores and hazard ratings accordingly. Nonetheless we have a high level of confidence
that the indicators and their application in this method give a useful first approximation of the
key hydrologic processes and watershed characteristics affecting streamflow, sediment and
riparian function. Despite our confidence, we stress that GIS-based indicators should not be
misused as management limits, but are intended to flag high risk catchments units for further
investigation by qualified professionals as part of a multi-step approach referenced in Box 1.
9. Literature Cited
Fig 5. Example illustrations of private land clearing of riparian vegetation. Red lines indicate private land boundaries. Expanded
illustrations show examples of residual riparian vegetation associated with private land logging or clearing for agriculture and urban
development.
Acknowledgments
Fig 3. A.) Several large drainages (5th order or greater) that flow into the Thompson River west of Kamloops, BC in the Kamloops Assessment Area.
B) The 6th order Deadman River Large Watershed. C) Watersheds within the Deadman River Large Watershed. D) Basins within the Criss Creek
Watershed, southeast portion of Deadman River Large Watershed. E) Sub-basins and F) Residual Units within the Criss Creek watershed.
We would like to thank a number of people for their assistance in the development of this procedure . Cam Brown of Forsite
Consultants Ltd. provided initial work on GIS indicators. In earlier versions of the work upon which this procedure is built.. We
are grateful to Sasha Lees and Graham MacGregor of BC MFLNRO for GIS support and indicator development and refinement.
Martin Carver, Rita Winkler and Russell Smith provided useful insight and helpful comments through the development of
earlier versions of this work. We would like to thank the Thompson Okanagan BC MFLNRO Integrated Monitoring Team for
assistance in field-based assessments. We would also like to thanks David Huggard for statistical analysis of monitoring results
and sampling support.
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