Run-off and Land Use Change

Photo: Landslide on Riverside Ave 2019 By the UVM Spatial Analysis Lab

This project involved building a first approximation of expected rainfall runoff as a function of rainfall events, runoff estimates, and mapped land use changes over three intervals for Burlington, VT.

Runoff and Land Use Changes

Fig. 1: 1998 Orthophoto of Burlington and Winooski, VT. The five lot plot used for this exercise is located in red. Provided by Paul Bierman.

Fig. 2: 2018 Orthophoto of Burlington, Vt. The same five lot plot is shown in red. Provided by Paul Bierman

Fig. 3: Comparison of the 1998 and 2018 lots from Fig 1 & 2. Note the lower resolution of the 1998 orthophoto results in a wider image for comparison

Method, Data, and Error

For this project five adjacent residential lots were documented for land use changes over two dates of orthophotography (Fig 1-3). For self consistency between projects, an area was chosen with visible, but moderate changes on N Willard Ave, 3 blocks from from the intersection of Riverside Ave and Intervale Rd.

These adjacent plots were scaled to nearly the same size and imported into a 1mm x 1mm grid system in Inskscape. Land use was color coded into six categories: Houses/Roofs, Sidewalks, Parking (paved), Parking (dirt), Lawn/Trees, and Fences/Walls. Summed grid coverage by land use type was normalized by total image area to derive relative land use percentages (Fig. 4)

Each of these land use types was categorized by land type according to Urban Hydrology for Small Watersheds (1986) with a corresponding runoff estimate percent (curve numbers) based on this land use classification, as follows:

Lawn/Trees - Open Space Good Condition (75%+ grass) Group A
Houses/Roofs - Parking Lots, Roofs, Driveways
Sidewalks - Streets/Roads (paved)
Parking (paved) - Parking Lots, Roofs, Driveways
Parking (dirt) - Dirt Road, Group D
Fences/Walls (compact soil) - Open Area Poor Condition (50%- grass)

Weighted averages for runoff percentage were calculated for each time-frame's land use of the study area, with an assumed full cover of wooded area in 1600CE. These were then scaled by 2 year, 1 hour, 100 year 1 hour, 2 year 24 hour, and 100 year 24 hour expected rainfall events (US. Department of Commerce and Weather Bureau, 1959) (See Runoff Calculation Spreadsheet). The results are displayed in Fig. 5. Note the extrapolation from trends derived from n=3 data points are necessarily approximate, confidence intervals are displayed to illustrate better expected ranges of runoff over the projection.

Sources of error include estimates of runoff percent (Urban Hydrology, 1986), poor estimations of land use type or soil quality, extrapolation of 100 year rainfall estimates (USDC & WB, 1959), not diverting roof rainfall percent to the slope adjacent land use it would naturally drain to, and not extending the site margins to include 1/2 of the roads for land use percentage calculations.

Fig. 4: Spacial land use analysis from orthophotos. An arbitrarily small grid system (1mm) was used for snap fits of land use distribution, and relative rates of land use were calculated. Note due to resolution differences, the 1998 image zoom created a slightly wider image. Created using Inkscape.

Fig. 5: Expected runoff estimates for each of the four rainfall events by year - based on land use analysis. Fully wooded area was assumed for 1600 CE, while land use maps dictated runoff for 1998 and 2018. Linear regressions show increases in runoff over time (via development, and should be compared to area population on the right hand axis in future studies). Shaded areas show the 95% confidence interval. Very few (n=3<20) data points per event led to obvious extrapolation of the interval (1600-1998). Created using JMP.

Discussion

Water infiltration and surface run off both depend on ground porosity and the interconnectedness of those pores, which in turn have defining factors such as mineral composition, animal and root paths, plant uptake, density and compaction. As humans tend to cultivate their surroundings for specific purposes, our land use has a large impact on water infiltration. As populations grow, and the density of these populations do as well, development of housing and parking addresses these needs, but usually at a cost of natural green spaces. These green spaces - forests, woods, grassland, even lawns - have high rates of water infiltration, whereas compact dirt, gravel, or paved areas are rather impermeable and drive surface runoff which leads to saturation, erosion, and landslides.

In comparing the development of of the 5 adjacent lots from 1998 and 2018, we can see a few trends in the land use. Paved and unpaved parking are universally expanded at the expense of green space and roofs (especially those that appear to be carports), which results in a 6.5% increase in rainfall runoff over this area (See Runoff Calculation Spreadsheet).

In contrast, we can also see the relatively stable levels of runoff generated ~1600CE assuming a fully wooded area in precolonial times. The development of roads (which should have a larger land use impact than measured), and buildings grow with settled permanent population. A more expansive study should show Fig. 5 with the additional axis of population growth in the Burlington area for comparison to a non-linear regression of rainfall runoff trend. In all the 1998 calculated estimated runoff is 2.25 times higher than assumed preindustrial/precolonial amount, while the 2018 calculated estimate of runoff is 2.39 times higher than from 1600.

This higher runoff is especially worrisome due to the increased parking that is used. Vehicles can leak small amounts of complex chemical compounds while functioning, and larger amounts when encountering issues. The increased runoff in Burlington drains either to the Winooski, or directly into Lake Champlain.

Citations

Urban Hydrology for Small Watersheds. (1986). Chapter 2: Estimating Runoff. Technical Release 55. Second Ed., June.
US. Department of Commerce and Weather Bureau. Rainfall Intensity-Frequency Regime. (1959). Part 4 - Northeastern United States. Technical Paper no. 29. U.S. Government Printing Office, Washington 25, D.C. May.

Page updated

Google Sites

Report abuse