Many natural and anthropogenic processes occurring within a lake’s watershed directly affect lake water quality (Soranno et al., 2015). As such, delineating the bounds of a lake’s watershed is often the first step towards identifying factors driving changes in water quality over time. This critical step can be achieved with the help of Arc Hydro, which provides a data model, a toolset, and workflows directly pertaining to water resources applications (Esri, 2019). The workflow below details the steps executed in my research, that focuses on changes in water quality across a 40-year period within a set of Halifax-area lakes in Nova Scotia.  The delineation process for Lake Major (Fig. 1) is illustrated throughout this piece.

Inputs and Data Preparation

The following data were required:

An enhanced 20m DEM for the province was accessed from the Nova Scotia Department of Natural Resources and Renewables website, and the Provincial Hydrographic Network (containing the stream network) was accessed from Nova Scotia’s Geographic Data Directory. Lake outfall locations were determined by viewing lake bathymetry maps and cross checking with the National Hydrographic Network, whenever possible, and were marked with a “Pour Point” (Fig. 1).

To improve processing speeds, both the stream layer and DEM were subset to an area several times larger than the anticipated size of the watershed. Additionally, all layers were projected to the same projected coordinate system as per the Arc Hydro Technical Guide (Esri, 2011).  

A map showing streams and a lake, superimposed over a digital elevation model layer.
Figure 1. Lake Major, which supplies water to the city of Halifax, is indicated in blue (black outline). Input data is depicted, including the 20m NS DEM (background), the Provincial Hydrographic Network (blue lines), and the Pour Point or outfall location of Lake Major (green point).

Although the NS DEM asserts that it is “hydrologically correct,” the following preprocessing steps were taken to ensure it was hydrologically conditioned (i.e., it correctly models the flow of water across the surface) (Djokic, 2015).

  1. DEM Reconditioning “burns” your stream network into your DEM and requires that you first convert your stream network into a raster (Fig. 2b). (Burning is the process of decreasing the elevation of a DEM along a linear feature to enforce the proper drainage across the surface). The tool allows the user to manipulate the “buffer,” which is the horizontal distance in cells away from the stream, the “smooth drop,” which is the vertical drop at each unit of the buffer, and the “sharp drop,” which is the vertical depth of the line itself (Fig. 2a).
  1. The Fill Sinks tool identifies cells having values lower than their surrounding cells and are often errors that result from the resolution of the dataset (Esri, n.d.). The tool aims to correct these cell values as their presence in the surface can interrupt the derived drainage network (Esri, n.d.) (output shown in Fig. 2c).
A series of three screenshots showing the parameters in the dialog for the DEM Reconditioning geoprocessing tool, and before/after views of a digital elevation model layer that has been processed by the tool.
Figure 2.  A) Depicts the inputs used for the DEM Reconditioning Tool, B) depicts the new DEM raster output with the streams “burned” in surrounding Lake Major, and C) depicts the output from the Fill Sinks tool.

Terrain Processing

  1. Once a hydrologically conditioned DEM has been obtained, the Flow Direction tool can be applied. This tool scans the elevation of each cell to identify the direction of steepest decent and assigns values to the output raster which indicate which neighboring cell water would flow into (Fig. 3a).
  1. The Flow Direction output can then subsequently be used by the Flow Accumulation tool to create a raster output where each cell contains the value of upstream cells draining into the focal cell (Fig. 3b). The stream network is easily distinguishable in the output, and the directionality becomes clear as well since the values increase as you move farther downstream (Fig. 3b).
  1. This Flow Accumulation output can then be used by the Stream Definition tool, to produce a new stream raster where only cells that receive enough flow from upstream cells are recognized; all other cells that are not recognized by the process are assigned as “No Data” cells (Fig. 3c). This intermediate step is intended to speed up point delineation and, therefore, the output does not need to match the original stream network (Esri, 2011). The recommended threshold for stream determination is 1% of the maximum flow accumulation and appears as the default number of cells that will define a stream (Esri, 2011).  Selecting too small of a threshold will create a denser stream network which could negatively impact delineation performance (Esri, 2011).  
A series of three raster maps showing flow direction classification, flow accumulation output, and stream definition/lake polygons.
Figure 3. A) Depicts the Flow Direction output raster where cell colour corresponds to the direction of flow, B) depicts the Flow Accumulation output where lightly coloured cells accumulate the least amount of water, and dark blue cells accumulate the most, and C) depicts the Stream Definition output (black lines) with the lake polygons layered on top (blue), and Lake Major highlighted in light blue.

Sub-catchment polygons were generated over the following three steps (Fig. 4).

  1. First, the new stream raster is divided into individual stream segments with the help of the Flow Direction raster by the Stream Segmentation tool (Fig. 4a).
  1. The Catchment Grid Delineation tool then identifies the area draining into each stream segment (again, with the help of the Flow Direction raster) and assigns a unique value to the cells within each sub-catchment, as shown in Figure 4b.
  1. Finally, this raster is converted to a polygon layer through the Catchment Polygon Processing tool (Fig. 4c).
A series of three maps showing the outputs from stream segmentation, catchment grid delineation (with areas classified into different sub-catchments), and sub-catchment polygon boundaries in a map showing the lakes within the catchments.
Figure 4. A) Depicts the output of the Stream Segmentation tool, where different colours indicate different segments, B) depicts the output of the Catchment Grid Delineation tool, and C) depicts the vector output from the Catchment Polygon Processing tool. Lake Major is selected and outlined in light blue in B) and C).
  1. Returning to the output from the Stream Segmentation tool, the Drain Line Processing tool converts the raster to a vector line layer (Fig. 5a). This step also assigns information to each feature regarding connections to downstream features and the catchment it belongs within.
  1. The Adjoint Catchment tool aggregates sub-catchment polygons from the Catchment Polygon Processing output that drain to the same point based on the Drain Line Processing output and stores them in a new polygon feature layer (Fig. 5b). This step aims to speed up the point delineation process.
Two map views showing the vector lines produced by the drain line processing tool, and the new polygon features generated by the adjoint catchment process.
Figure 5. A) Depicts the output from the Drain Line Processing tool (red lines) overlaying the polygon feature layer generated by the Catchment Polygon Processing tool, and B) depicts the new polygon feature layer generated by the Adjoint Catchment Processing tool. Lake Major is selected and outlined in light blue in A) and B). 
  1. The Drain Point Processing tool also makes use of the Catchment Polygon Processing output, as well as the Flow Accumulation output (which had not been used up to this point). A new point feature layer is created, and points are placed at the lowest (farthest downstream) point of each sub-catchment (Fig. 6a).
Two maps, one showing a zoomed-in subset of the first, displaying the results of the drain point analysis, identifying the locations where each sub-catchment drains to.
Figure 6. A) Depicts the output of the Drain Point Processing tool (red points), and B) shows an enlarged view of the lake outfall location (green point). Red lines indicate the Drain Line Processing tool output, beige polygons belong to the Adjoint Catchment output, and Lake Major is selected and outlined in light blue.
  1. Finally, the Point Delineation tool creates a polygon indicating the bounds of the watershed, based on the location of the Pour Point. The resulting watershed delineation for Lake Major is depicted in Figure 7.  
A map (with overview inset map) showing Lake Major, with its catchment boundary.
Figure 7. Map depicting Lake Major’s watershed derived through Arc Hydro in ArcGIS Pro. Inset depicts the location of Lake Major within the Halifax Regional Municipality. Projection: NAD 1983 UTM Zone 20. Data Sources: hydrographic network (Nova Scotia Geographic Data Directory, 2020); DEM (Nova Scotia Department of Natural Resources and Renewables, 2006); Halifax Regional Municipality boundary (Nova Scotia Geographic Data Directory, 2020); Basemap courtesy of Esri.

Due to the urban nature of many of the lakes within this dataset, manual adjustments were often required to account for storm water infrastructure, which interrupts the natural flow of water across the landscape. The watersheds derived from this workflow will be used to quantify watershed characteristics such as road densities which may, in turn, reveal connections between changes in lake water quality and the natural and anthropogenic processes within each watershed.


Djokic, Dean. (2015). Creating a Hydrologically Conditioned DEM. Esri User Conference. Technical Workshop. Retrieved from:

Esri. (2019). Arc Hydro: Project Development Best Practices. An Esri White Paper.  Retrieved from:

Esri. (2011). Arc Hydro Tools – Tutorial. Version 2.0 – October 2011. Retrieved from:

Esri. (n.d.). How Fill Works. Retrieved from:

Soranno, P. A., Cheruvelil, K. S., Wagner, T., Webster, K. E., & Bremigan, M. T. (2015). Effects of land use on lake nutrients: the importance of scale, hydrologic connectivity, and region. PloS one10(8), e0135454.