ESRI's ArcToolbox includes a suite of raster hydrologic modeling tools to perform each of these functions. This page illustrates principal steps in the hydrologic modeling process, and demonstrates some strategies for designing riparian buffers to protect streams from agricultural runoff.

These analyses are almost entirely derived from an ordinary 30-meter resolution DEM. The DEM used here covers the upper Nanticoke watershed in Sussex County, Delaware. This is a particularly challenging watershed to analyze, since the terrain is very flat. If you want to try these modules out for yourself, you can download the zipped DEM and unzip it in any appropriate Arc workspace folder. This DEM is in DE State Plane NAD 1983 (meters) projection. Note that many of the images below use customized symbology, and that once I have derived the Nanticoke watershed using the BASIN module, I use it as a mask to focus the rest of the analysis on that watershed only.

Using the HILLSHADE tool in the Surface Analysis raster functions, you can create a hillshade map and overlay the DEM with 50% transparency to get a better sense of the terrain to be analyzed. (You can also create 3D views of this terrain with Arc's 3D Analyst extension and ArcScene, but that's a topic for another tutorial!)

Most DEM’s include local sinks or depressios--cells completely surrounded by higher-elevation cells--which interrupt the calculation of off-map flow directions. Use the FILL tool to create a “filled” DEM with these sinks eliminated. Use the SINK tool (or just subtract the source DEM from the filled DEM) to identify the sinks.

Use the FLOWDIRECTION tool on the filled DEM to calculate the direction of flow for each cell. The flow direction map (above right) provides the input data for most of the watershed analysis and stream inference tools discussed below.

Use the BASIN tool on the flow direction map to identify the basins that flow to each outlet point on the map edge. Use the Identify button to determine the value of the particular basin you want to analyze, and use the raster calculator to create a 0-1 raster map of just that one basin. (Note all the specious little "basins" that flow off the left edge of the map.)

In the Spatial Analyst Options you can specify this single-basin map as a mask for further analysis. To convert this basin to a vector polygon feature, select the basin cell record in the raster attribute table and then use Spatial Analyst’s Convert—Raster-to-Features. You can narrow the map extent in Spatial Analyst’s Options to cover just this basin. (Alternately, you could simply multiply the flow direction map by the 0-1 single-basin map to mask out flow direction values outside the basin.

Inferring the Stream Network

Use the FLOWLENGTH tool on the flow direction map to determine the total flow distance from each cell to the outlet point of the basin.

Use the FLOWACCUMULATION tool on the flow direction map to calculate the number of up-gradient cells that drain through each cell in the basin. You can think of this as simulating the cell-by-cell cumulative flow volumes from a uniformly-distributed one-inch rainfall over an impervious watershed surface. You can get a clearer idea of the flow accumulation if you use the raster calculator to take the natural logarithm of the flow accumulation output map. The map above shows the log of accumulation in portion of the watershed.

The inferred stream network can be derived from the flow accumulation map by using the Raster Calculator to extract the cells that exceed some threshold accumulation value. This map shows inferred principal streams where the natural logarithm of accumulation is 10 or greater. You can include progressively smaller permanent or ephemeral streams by reducing the threshold. The selected stream cells were then converted to polylines (using the Generalize Lines option).

Use the STREAMORDER tool on the stream raster map with the flow direction map to calculate the order of each segment or link in the stream network. Each stream junction combines two upstream tributary links. The links near the basin divide have no upstream tributaries, and are designated as first-order. Proceeding downstream, each successive link can be ordered as the sum of the orders of its two tributary links (Shreve method). Alternately, if both its tributaries have the same order n, the link is order n+1; otherwise if the two tributaries have orders m and n with n > m, the link is also order n (Strahler method)—this better distinguishes principal flows in the stream network. The map above shows polylines derived from STREAMORDER using the Strahler method.

Delineating Sub-Basins

Use the STREAMLINK tool on the stream raster map with the flow direction map to assign a unique ID number to each stream segment.

The stream link map can be used as input pour point targets for the WATERSHED tool. The WATERSHED tool uses the flow direction map and pour point targets to determine the sub-basins within the basin that flow to each stream link. The sub-basins can be converted to polygon features.

To obtain more detailed sub-basin delineations, use a lower flow accumulation threshold to extract a more detailed stream network, create a new stream link map (with many more links), and rerun the WATERSHED tool.

Inferring Runoff

The map below left shows 2002 land-use/land cover for the portion of the Nanticoke watershed within Sussex County, DE. The brown cells are cropland. I create a binary map of cropland (below right). I then re-run the FLOWACCUMULATION module using the binary cropland map as a Weight Raster. The output map shows how many cropland cells flow through each cell in the watershed. A portion of the logarithm of this "flow accumulation" of cropland is shown below left.

Using the Raster Calculator to take the ratio of the flow accumulation of cropland over the flow accumulation from all land yields a map showing the percentage of runoff through each cell from cropland (above right).

Multiplying this by the binary inferred stream raster shows the inferred proportion of total runoff passing through each stream cell that is from cropland. The cropland is shown in faint orange. (To fatten up the stream segments for better visibility, I created a 5x5 neighborhood maximum map with Neighborhood Statistics, which is shown below left) The red, orange and yellow stream segments would be most vulnerable to agricultural runoff.

Now we can try out some riparian buffer design strategies. We can extract buffers of any uniform width from a simple straight-line distance map to the streams (above right).

If the objective is to reduce agricultural runoff specifically, we can identify all the cropland cells within, say, 100 meters of a stream. The map below left identifies (in red) a total 902 hectares (2.256 acres) of cropland within 100 meters of streams that might be targeted for the Conservation Reserve Program in Sussex County. These riparian areas might be planted in some crop with high P uptake that would intercept much of the P runoff from up-gradient cropland.

The effectiveness of vegetative buffers is inversely related to slope (above right), which determines the speed of runoff. So we might revise the buffer design strategy to obtain wider buffers on more steeply-sloped terrain.

I used the Raster Calculator to create a "cost" map as 100/%Slope, and used this as a cost weight raster to create a cost-weighted distance vmap to the streams. I then extracted all cells with an (arbitrarily-chosen) cost-weighted distance of 10,000 or less (green) as a variable-width buffer, and all cropland cells falling within these buffers (red). This identifies 685 hectares (1,691 acres) of cropland that might be converted to vegetative buffers.

This strategy could be further refined by analyzing exiting vegetative densities in the landscape. The color-IR image above is composited from SPOT HRV satellite data recorded in early July. The SPOT image is comprised of three 20-meter resolution band files indexing reflectance of green (band1), red (band2) and near-infrared (band3). Healthy vegetation reflects near-IR and absorbs visible red to drive photosynthesis, so a ratio of IR to red provides a useful index of vegetative biomass density. The most commonly-used measure is the Normalized Difference Vegetation Index, where NDVI = (IR-red)/(IR+red).

I calculated Calc1 = 100 * (Band3 - Band2)/(Band3 + Band2) and NDVI = (Calc1>0)*Calc1 (forcing negative values to zero) to obtain the NDVI map below.

This can be used as an alternative "cost" map for calculating cost-weighted distances to streams, where each cell's "cost distance" indexes the total vegetative biomass lying between it and the nearest streambank. The green cells (above right) have an "NDVI distance" to streams of 5,000 or less. The red cells are cropland within these buffer areas.

Obviously the development of an efficient runoff management strategy requires expertise from hydrologists, soil scientists, agronomists, etc. The real challenge for the GIS analyst is translating this expertise into functional criteria that are amenable to analysis with GIS tools.