Model for Prioritizing Catchments for Terrestrial Liming in NS
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Presentation for Marley Geddes' third term project, AGEO COGS.
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Model for Prioritizing Catchments for Terrestrial Liming in NS
- 1. A Model for Prioritizing Catchments for Terrestrial Liming in Nova Scotia Marley Geddes Gold River, Nova Scotia AGEO Third Term Project, COGS
- 2. Overview Key definitions Background Project Objectives Project components Model details Model issues Conclusions & Future work Questions West River, Nova Scotia
- 3. Key definitions Catchment: Drainage area for a stream, or tributary, where any drop of water will eventually flow into the tributary. Watershed: The complete drainage area for an entire river network. Pour Point: The point of highest flow accumulation. All water of a drainage area will flow through this point.
- 4. Background: Acidification is still a major issue in Nova Scotia & it’s threatening the Atlantic salmon (Salmo salar) populations Freshwater acidification is a persistent issue in Nova Scotia (NS) (Clair et al., 2007). Acidification is the most serious threat to local Atlantic salmon populations which have declined from 88% to 99% since the 1980’s (DFO, 2013). More positively, the probability of salmon extirpation is greatly reduced with habitat quality improvements. Natural recovery is not predicted to occur for another 60 years (Clair et al., 2004). Southern Upland (SU) salmon declines due to chronic acidification
- 5. Rationale: Terrestrial liming is a viable mitigation option but we don’t know where to focus liming efforts Liming, the addition of base cations to an acidified system, is the only mitigation method for acidification. Whole catchment terrestrial liming, the addition of base cations to the entire catchment of an acidified river, targets toxic aluminum mobilization and is thought to be a more sustainable and cost-effective method compared to other liming methods. The effectiveness of terrestrial liming varies by location A terrestrial liming catchment selection framework for NS was developed last year (Geddes, 2015) but it was difficult to use and replicate. (MTRI, 2014)
- 6. Catchment Selection Project Objectives 1. Create a workflow to prioritize catchments that have the most promise for effective response in water quality with terrestrial liming that will best support local salmon. 2. Provide an easy-to-use decision tool for prioritizing catchments by offering: Simple models to automate the watershed delineation, suitability analysis and prioritization tasks A comprehensive user guide to support the use and modification of the project components.
- 7. Catchment Selection Project: Components Provides a complete package for the user User friendly model interface(s) and comprehensive user guide support a user friendly experience Model to Generate NS Flowline and Input Data Preprocessing Model are supplementary models that should not be used unless changes are made to the input Catchment Selection Project Input Data Preprocessing Model Catchment Selection Model Model to Generate NS Flowline Project Geodatabase User Guide
- 8. Spatial Scope: Nova Scotia Watersheds
- 9. Software and Data Requirements Name Description Year last update Source NS Watershed Boundaries Watershed boundaries for major NS watersheds and remaining residual watersheds 2014 Nova Scotia Watershed Assessment Program (NSWAP) geodatabase Digital Elevation Model (DEM) Hydrologically correct 20m resolution DEM of NS 2006 Province of NS Pour Points Point feature class containing the pour points for the candidate liming catchments n/a User created Road Network Road Network for NS 2004 Nova Scotia Topographic Database (NSTBD) – Province of NS Lakes NS lakes n/a Nova Scotia Hydrologic Network derived from the NSTBD Wetlands NS wetlands 2006 Nova Scotia Department of Natural Resources Forestry Layer* Forestry inventory layer showing forest attributes for stands across NS 2015 Crown Land Crown owned land in NS 2016 Wet Area Mapping (WAM)* WAM layer shows the depth to water table for all areas of NS 2012 Acid Rock Drainage (ARD) Potential* ARD Potential layer shows areas of ARD risk primarily in South Western Nova Scotia. 2013 Acidification ANC Layer Gran titration Acid Neutralization Capacity (ANC) interpolated raster from NS stream measurements 2007 Thomas A. Clair, Environment Canada *Layer is preprocessed in the Data Input Preprocessing Model and resulting output is input for the Catchment Selection Model Software: ArcMap with ArcGIS Spatial Analyst Extension Data Layers Used:
- 10. Project Geodatabase Included in the geodatabase: all input layers required Includes the output layers from the Input Data Preprocessing and Generate NS Flowline Models that are inputs in the Catchment Selection Model Toolbox contains the three models and a script tool used in the Catchment Selection Model
- 11. Supplementary Models Model to Generate NS Flowline Generates a provincial flowline from an input DEM Flowline is referenced when creating the catchment pour points Intended for use if default DEM is changed. Input Data Preprocessing Model Automates the time-intensive geoprocessing workflow for three input layers Output layers are used as inputs in the Catchment Selection Model Allows the Catchment Selection model to run more efficiently
- 12. Catchment Selection Model The model objective is to prioritize user-defined catchments within a target watershed to identify the best catchment(s) for terrestrial liming. Model is composed of three sections: 1. Target watershed selection and catchment delineation 2. Selection criteria analysis and ranking 3. Criteria weighting and suitability scoring
- 13. Selection Criteria Summary Name Description Priority Input Output Suitable forest Stands that have a mean crown height greater than 10m or a stand total merchantable volume of 50m3/ha are considered suitable. Higher percentage Forest Inventory layer Percent suitable forest field Wetlands The percentage of area within the catchment. Lower percentage Wetlands layer Percent wetlands field Crownland The percentage of crownland within the catchment. Higher percentage Crownland layer Percent Crownland Field Acid Rock Drainage (ARD) Potential The percentage of catchment at risk to ARD. Lower percentage ARD Potential Percent high ARD potential field Connectivity Length from each catchment pour points to the target watershed outlet pour point calculated as a straight line distance. Less distance to mouth of the target watershed Catchment pour points Target Watershed Outlet point Connectivity field with length from pour point to outlet Accessibility The length from each catchment pour point to the nearest road. Less distance to nearest road Catchment pour points Road Network Accessibility field with length from pour point to nearest road Depth to Water Table The percentage of catchment with a depth of less than 2 meters to the water table. Higher percentage WAM layer Percent of area with < 2m depth to water table Acid Neutralization Capacity (ANCG) The mean ANCG (mg/L-1) Not included in suitability score ANCG interpolated raster layer Mean ANCG value per catchment Criteria that support effective liming, salmon populations and accessibility Used to assess catchment suitability for terrestrial liming Determined through stakeholder consultation
- 14. Catchment Selection Model Steps User selects the target watershed Catchments delineated based on input pour point layer and logical check deletes erroneous catchments Selection Criteria are analyzed and the key field joined to the catchment feature class. Rank script tool is used to rank catchments based on each criteria. Suitability score is calculated as the sum of the weighted ranks for each catchment.
- 15. Rank Catchments Script Tool Objective of this tool is to create a rank field for each criterion and populate it with catchment ranks. Each criterion is sorted ascending or descending based on if higher or lower values are of priority. Rank the catchments based on order; ranked 1 to n where n is the total. Account for multiple zero values or all zero values appropriately Add a weight field to be populated in the model.
- 16. Results Example: West River liming catchments Catchment feature class attribute table Criteria Analysis Ranks Weights Suitability Score
- 17. Results Example: West River liming catchments Catchment feature class attribute table Criteria Analysis Ranks Weights Suitability Score
- 18. Results Example: Gold River liming catchments Catchment feature class attribute table Criteria Analysis Ranks Weights Suitability Score
- 19. Model Interface: Simple with descriptions for each input
- 20. Comprehensive User Guide Developed to help community groups and other non- GIS experts in implementing the model as a decision- making tool. Easy-to-use guide with simple terminology and references to additional resources. Provides step-by-step instructions with visuals describing how to add and delete selection criteria Describes how to solve common model errors
- 21. Catchment Selection Model Issues 1. Pour point creation and catchment delineation when using different DEMs 2. Calculating connectivity 3. Incorporating the Rank Catchment Script Tool in the Catchment Selection Model
- 22. Catchment Selection Model Issues 1. Pour point creation and catchment delineation when using different DEMs 2. Calculating connectivity 3. Incorporating the Rank Catchment Script Tool in the Catchment Selection Model
- 23. Catchment Selection Model Issues 1. Pour point creation and catchment delineation when using different DEMs 2. Calculating connectivity 3. Incorporating the Rank Catchment Script Tool in the Catchment Selection Model
- 24. Conclusions & Suggestions Complete package for the prioritization of catchments for terrestrial liming in Nova Scotia Improves the catchment selection framework proposed by Geddes (2015) by automating the workflow and providing a simple user guide Suggestions for future work: Comparative analysis of different watershed delineation methods using a variety of DEM’s to determine which most accurately represents Nova Scotia’s hydrologic network. Bridge the data limitations and gaps More experimental liming studies are required to better understand liming dynamics in NS (National Geographic)
- 25. Thank you! • David MacLean, Jim Verran and Mark Hebert with the Centre of Geographic Sciences (COGS) • Dr. Shannon Sterling and Dr. Tom Clair with the Dalhousie Hydrology Research Group • The Bluenose Coastal Action Foundation (BCAF) • Ross Claytor, Shane O’Neil and Alex Levy with DFO • Southern Upland Collaborative Projects Working Group and Southern Upland Acid Mitigation Committee Gold River, Nova Scotia
- 26. References Clair, T. A., Dennis, I. F., Amiro, P. G. and Cosby, B.J. (2004). Past and future chemistry changes in acidified Nova Scotian Atlantic salmon (Salmo salar) rivers: A dynamic modeling approach. Canadian Journal of Fisheries and Aquatic Sciences, 61(10), 1965-1975. Clair, T. A., Dennis, I. F., Scruton, D. A. and Gilliss, M. (2007). Freshwater acidification research in Atlantic Canada: A review of results and predictions for the future. Environmental Reviews, 15(1), 153- 167. doi:10.1139/A07-004 Clair, T. A. and Hindar, A. (2005). Liming for the mitigation of acid rain effects in freshwaters: A review of recent results. Environmental Reviews, 13(3), 91-128. doi:10.1139/A05-009 DFO, D. o. (2013). Recovery potential assessment for Southern Upland Atlantic Salmon. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2013/009. Geddes, M. (2015). A New Method for Prioritizing Catchments for Terrestrial Liming in Nova Scotia. Dalhousie University Environmental Science Undergraduate Honors Thesis. Olem, H. (1991). Liming acidic surface waters. Chelsea, Mich.: Lewis Publishers. Sterling, S., Angelidis, C., Armstrong, M., Biagi, K., Clair, T., Jackson, N., and Breen, A. (2014-a). Terrestrial liming to promote Atlantic salmon recovery in Nova Scotia–approaches needed and knowledge gained after a trial application. Hydrology and Earth System Sciences Discussions, 11(9), 10117-10156. Sterling, S. M., Garroway, K., Guan, Y., Ambrose, S. M., Horne, P., and Kennedy, G. W. (2014-b). A new watershed assessment framework for Nova Scotia: A high-level, integrated approach for regions without a dense network of monitoring stations. Journal of Hydrology, 519, Part C(0), 2596-2612. doi:http://dx.doi.org/10.1016/j.jhydrol.2014.07.063
- 27. Questions? (National Geographic) BCAF Gold River, Nova Scotia
Editor's Notes
- -Describe the work briefly -Describe an outline of the presentation: Key definitions Background information for context Project objectives Project components More in-depth into one of the models which involved the bulk of the project Issues Conclusions / future work
- A drainage area is the total surface area, upstream of a point on a stream, where the water from rain, snowmelt, or irrigation which is not absorbed into the ground flows over the ground surface, back into streams, to finally reach that point.
- Chronic freshwater acidification is an issue in NS. We are known as the tail pipe of North America as we receive large amounts of acid deposition caused by the burning of fossil fuels in more industrialized regions in central north America. Acid deposition is a particular issue in NS because of the low Acid Neutralizing Capacity (ANC; which is the bedrock and soils ability to buffer acidic inputs; see map where ANC is lowest). Freshwater acidification reduces aquatic and terrestrial productivity by lowering pH, stripping base cations and nutrients from the soils, increases metal concentrations and lowering calcium concentrations. Despite the reduction in emissions with the US Clean Air Act in the early 1990’s, water quality in NS has not improved and recovery is not predicted for another 60 years.
- Liming, the addition of base cations to an acidified system, is the only mitigation method for acidification. There are two main methods of liming, in stream liming ( which is the addition of base cations directly to the waters of an acidified stream) and terrestrial liming, the addition of base cations to the drainage area of an acidified stream. Terrestrial liming increases freshwater and terrestrial productivity by increasing pH and nutrients and decreasing metal concentrations. The federal government and community groups (who would be leading the liming initiatives) are interested in terrestrial liming because it is a more sustainable and potentially more cost effective method. Terrestrial liming is more sustainable because you can apply the lime to the catchment and walk away without the need for expensive maintenance. European studies show that one terrestrial liming application can improve water quality for decades but that the effectiveness varies greatly by location (i.e. Yan et al., 1995; Hindar et al., 2003). Selecting a catchment that supports effective liming is key in NS because of: limited resources the urgency to improve habitat quality for salmon populations Widespread nature of the problem. A terrestrial liming catchment prioritization framework for NS was developed last year (Geddes, 2015) but it was difficult to use and replicate.
- The overarching objective of this project is to decrease the probability of extirpation of Nova Scotia salmon by increasing the effectiveness of terrestrial liming by providing an information tool for identifying locations that best support effective liming and a positive increase in local salmon populations.
- The catchment selection project components include: A project geodatabase that will contain all necessary input layers Three models, two of which (the model to generate NS flowline and the input data preprocessing model), are used to create inputs for the Catchment Selection Model. And a comprehensive user guide to support the models use and modification by non-expert users.
- Considers 245 major watersheds in Nova Scotia and does not consider the residual drainage area
- This project requires ArcMap with ArcGIS Spatial Analyst extension. The data layers listed in this table are provided within the project geodatabase. The three support the watershed delineation process while the remaining eight are used to assess catchment suitability. One layer to make note of is the pour point layer, which is created by the user. The pour point layer is used in the delineation of the catchments that will be prioritized.
- The file provided to groups will contain the project file geodatabase. The file geodatabase contains all input layers for the three models. In addition it includes the output layer from the Input Data Preprocessing Model and the Model to Generate NS Flowline that are inputs to the Catchment Selection Model. The toolbox contains the three models and the Rank Catchments Script tool. In addition to what you see here the python script source for the script tool, a map to which the results will be displayed and a user guide will be provided.
- The model to generate NS flowline generates a provincial river network from an input DEM. The river network referenced when creating the catchment pour point file MUST BE THE RIVER NETWORK GENERATED FROM THE DEM USED FOR THE CATCHMENT DELINEATION or the pour points may not be located correctly and the delineation will fail. This model is only intended to be used if the user is going to change the DEM. I have already ran this model, which takes ~3 hours, so the river network provided with the project is derived from the input DEM. The Data Input Preprocessing Model automates some time-intensive geoprocessing of layers that are used in the Catchment Selection Model. This model takes approximately 15 minutes to run and is separated from the main Catchment Selection Model to allow it to run more smoothly. These output layers are already provided in the project geodatabase therefore this model should not have to run unless the input layers are updated.
- Describe what the user inputs are and expected output. Inputs include a watershed layer that allows the user to select the target watershed, pour points (defined by the user) that supports the delineation of the candidate catchments and the selection criteria layers that are either the raw unprocessed layers or the output from the input data preprocessing model (e.g. forestry layers and crownland). The output of the catchment selection model is a catchment layer containing information about the selection criteria, ranks, weights and total suitability score for each of the catchments. A lyr file is used to ensure that a simple gradient scheme is used o identify the more suitable catchments as a dark green and the least suitable catchments as red (examples of the output will be shown later).
- The selection criteria listed here are used to assess the catchments suitability for terrestrial liming The criteria are selected if they support effective liming, the salmon population or accessibility for water quality monitoring. Higher priority is given to catchments that have: Higher proportions of suitable forest which uptake less base cations which supports more effective water quality improvements. Lower proportions of wetlands which are naturally acidic and can be damaged from terrestrial liming. Higher proportions of crownland in which permission for liming in more easily granted. Lower proportion of area at risk to Acid Rock Drainage (ARD) which are areas underlain by bedrock containing sulphide minerals that will leach sulphuric acid when exposed to air or water. Catchments closer to the mouth of the main river are of higher priority. This is because salmon are anadromous meaning that they travel up the stream from the ocean to breed in freshwater rivers therefore catchments closer to the mouth of the river are more accessibility to salmon and are of higher priority. Accessibility to the pour point of the liming catchment is important for monitoring water quality within the catchment. Areas with less depth to the water table is ideal for terrestrial liming as it supports a more immediate change in water quality. I also looked at the Acid Neutralization Capacity (ANC) for each catchment. ANC measures how well the bedrock and soils can buffer, or offset, acidic inputs. Thus catchments with low ANC are likely more acidic. This was not used directly in the suitability analysis because the interpolated raster layer has a poor resolution of 250 meters and the differences in ANC between catchments at this scale are not significant.
- The catchment selection model is quite large so it’s impossible to show via power point with any sort of clarity so I’ve created this flow chart to show the logic of the model. I’ve split the model into six logical steps, each step is listed in blue on the left and the tools used are listed on the right. I’m going to walk you through each of these steps: The user will select the target watershed from the watershed boundary layer containing 245 watersheds. The watershed is buffered (to account for errors in the watershed boundary layer) and the DEM is clipped to the target watershed. The candidate liming catchments are delineated using Spatial Analyst Hydrology tools The candidate liming catchment pour point layer, created prior to running the model, is the input pour points for the delineation A logical error check will select catchments with an area less than 10,000 m2 and will delete the catchment. Catchments less than 10,000 m2 are not suitable for liming and are likely to be delineated from errors in the pour point placement. Seven selection criteria are analyzed. Most of the selection criteria involve similar geoprocessing to calculate the percentage of the catchment that is suitable according to that criteria and that field is joined to the catchment feature class (this involves the tools in the first two lines). Two selection criteria, connectivity and accessibility, use the near tool to identify the distance from the catchment pour point to the main river outlet and the distance from the catchment pour point to the nearest road, respectively. The end result of the selection criterion analysis is the addition of seven criteria fields to the catchment feature class attribute table The catchments are then ranked based on each of the selection criteria. Unfortunately there are no simple geoprocessing tools in ArcMap to do this processing so I created a Rank Catchment Script tool to do this processing. I go through the details of this script tool on the next slide. The output from this is the addition of 14 new fields, 7 contain populated ranks based on each of the criterion and the other 7 contain empty criteria weight fields. The criteria weights are determined by user input based on the importance of each weight in determining catchment suitability for terrestrial liming. Lastly the total suitability for each catchment is calculated as the sum of the weighted ranks. The catchments with a higher suitability score are of higher priority. Selection criteria are analyzed and the key field joined to the catchment feature class
- This flow chart describes the workflow of the rank catchment script tool. The input to the tool is the catchment feature class layer with the selection criterion fields. It is easiest to explain the script workflow by walking through an example using the suitable forest criterion. So the input is the catchment feature class layer with the selection criteria fields including the percent of suitable forest field. First the a rank field for suitable forest is added to the catchment feature class layer The catchment feature class is sorted ASCENDING based on the percent of suitable of forest (catchments lower percentages of suitable forest to catchments with more suitable forests) Populate the forest rank field in order assigning 1 to n IF the criterion field has multiple zeros or all zeros, then account for that appropriately. Add a weight field for the criterion to be populated later in the model Move on to the next criterion. Account for multiple zero values or all zero values appropriately IF there are multiple zeros then the zero values would be assigned the same rank value and all other rank values would be reduced by 1. IF there are all zeros, then assign the whole rank field a value of 0 so it will not be used for prioritization. After this script tool is ran the criterion weight fields are populated based on user-input and the suitability score is calculated as the sum of the weighted criterion.
- Example with equal weights
- Example with UNequal weights
- Example with UNequal weights
- Using different DEMs can generate different flowlines. Although the flowlines are not vastly different, the differences are significant at the catchment level and when creating catchment pour points. As you can see from the picture, the pour point created in reference to the original DEM would not properly delineate the intended catchment if the reconditioned DEM is used in the Catchment Selection Model. To avoid this issue the flowline referenced when creating the pour points must be the same as the DEM used in the model. The Model to Generate NS Flowline was created to help non-expert users create a flowlines easily for different DEMs.
- The connectivity of a catchment is typically measured as the length of stream from the catchment pour point to the outlet of the main river. Although this length could quickly be calculated using Network Analyst, I am assuming that the local community groups do not have the Network Analyst license. In an attempt to provide the most accurate results I attempted to create a script tool to measure connectivity. The logic of the script tool involved the calculation of the stream segments from the outlet point to each of the pour points and then storing that information in the associated catchments attribute table. Although this logic seems simple, after a day of attempting to write this script it turned out to be a lot harder then thought. Instead I used the near tool as a proxy for connectivity but this does not always provide accurate results. In this example you can see that the relative connectivity of pour point B and C are not consistent between the two measures of connectivity. Because of this I suggest a lower weight for the connectivity measurement or that the user calculate this by hand to support more accurate results.
- The Rank Catchment Script Tool was difficult to incorporate into the Catchment Selection Model. The Script Tool did not originally have an output feature layer and therefore it could not be set as a precondition for the calculation of the selection criteria weights. The Rank Catchment Script Tool has to be ran prior to the calculate criteria weights because this process calculates fields created in the script tool. To solve this problem I created a ‘dummy’ output to allow the setting of preconditions.
- Data limitations: Update the invasive species database DFO has an invasive species database but it only contains ~ 250 records of small mouth bass and chain pickerel sightings by the public dating back to the 1950’s. Unverified and clearly outdated. Critical salmon habitat in NS More recent and accurate provincial wide water quality data Improve understanding of terrestrial liming in NS:\ How do different environmental factors impact the effectiveness of terrestrial liming. Examination of aluminum dynamics in NS to pinpoint Critical Source Areas for toxic aluminum?