Application of Land Cover Data to Assess Pollution Potential

In addition to being used to conduct change analysis as a measure of landscape dynamics, land cover data has been used to assess pollution potential. (Subra and Waters, 1993; Newell et al., 1992; Harbor, 1994). The Carmans River area was used as a test case in the Reserve for developing an application of the C-CAP land cover data in pollution potential assessment. Information presented here on Carmans River is summarized in part, from Orlando (1997).

Carmans River Study Area Delineation

A combination of factors was used to determine the bounds of the study area. Land parcels falling within a half-mile distance to water provided the first rough study area boundary. Additional parcels were added to the study area, using nearest roads to complete the boundary in order to reduce the jagged, irregular shape that parcel boundaries alone had created. Parcels alone were used when no nearby roads could be selected.

Creating the Land Cover Image

Using the study boundary, the area was masked from the C-CAP database (Figure 3, Map 1). The C-CAP developed category was segregated from the other land cover classes and refined into three new developed categories: high intensity developed, medium intensity developed, and low intensity developed. The high intensity developed class contains pixels which are nearly 100 percent impervious such as major roads and parking lots. The medium intensity developed class contains pixels where impervious surfaces are the dominant physical feature, but vegetation or other cover types are also included within the 25 square meter pixel area. The low intensity developed class includes impervious surfaces consistent with 1/4 acre residential development and a mix of other cover types.

Distance to Water Criterion

A second data set was developed to provide a rough approximation of topography by buffering 10 distance zones from the landward edge of a combined 1:24000 hydrology and wetlands coverage. Wetlands were combined with the water coverage based on their direct hydrologic connection and low topographic relief. The resulting distance buffers were compared to 1:24000 topography and found to be a useful substitution for topography data. A better data source would have been a digital elevation model, however no digital elevation model of adequate resolution was available. Buffer zones were used in the model to reduce pollution potential as distance from water increased. Sites with high pollution potential nearest to water are emphasized using this approach.

Relating Land Cover to Natural Resource Conservation Service Curve Numbers

The amount of runoff that results from storm rainfall can be estimated using runoff curve numbers. Curve numbers are used to calculate the amount of runoff according to the amount of rainfall, the potential maximum retention of water after runoff begins, and initial abstraction (water retained in surface depressions, and intercepted by vegetation, evaporation, and infiltration).

Curve numbers were developed to estimate runoff and peak discharges using a simplified procedure referred to as the TR-55 model (Soil Conservation Service, 1986). Determination of curve numbers depends on soil and cover conditions, which are represented by soil group, cover type, surface treatment, and hydrologic condition. Land cover classes from C-CAP were compared to corresponding cover types for hydrologic soil group A to determine appropriate assignment of curve numbers to each C-CAP class. Use of a single hydrologic soil group was based on general soils information for Long Island which classified most soils as group A.

There are eleven C-CAP land cover categories present in the Carmans River study area: (1) Bare, (2) Cultivated, (3) High intensity urban, (4) Medium intensity urban, (5) Low intensity urban, (6) Grassland, (7) Water, (8) Estuarine emergent wetland, (9) Wooded land, (10) Palustrine emergent wetland, and (11) Palustrine wooded wetland.

Bare ground in the C-CAP database was equated to fallow, bare soil. Cultivated Land is similar to straight row crops with good hydrologic conditions; the land classified as cultivated land in the C-CAP database primarily consists of such straight row crops. Good hydrologic conditions reflect factors such as (a) density and canopy of vegetative areas, (b) amount of year-round cover, (c) amount of grass or close-seeded legumes in rotations, (d) percent of residue on the land surface (good >= 20%), and (e) degree of surface roughness which encourage average and better than average infiltration, and tend to decrease runoff.

High intensity developed is comprised entirely of impervious surfaces equating to the curve number for impervious areas including paved parking lots, roofs, and driveways. The medium intensity developed category includes impervious surfaces as the dominant land cover (>50%) with the remainder in vegetated open space. This developed cover class corresponds to the commercial and business urban districts category. Low intensity developed includes a mixed cover class with between 30 and 50 percent impervious surface and the remainder in vegetated open space. This land cover class is comparable to the NRCS Residential Districts by average lot size of 1/4 acre (38 percent impervious) based on the 25 meter resolution of the land cover data. Residential uses often include pixels of low density development, depending on the amount of developed land on a parcel. Since the land cover pixel size is 25 square meters, or approximately 1/6 acre, development on larger lot sizes are represented by a mix of different land cover types. Residential lots larger than 1/3 acre are classified in 1/6 acre units as the land cover physically present, which typically includes low intensity developed land, grassland, or wooded land classes. Development on lots of 1/6 acre or smaller are classified as either a uniform low density developed class or a higher density developed class based on the amount of impervious surface in each pixel.

Grassland in the C-CAP classification related to the NRCS Open Space category for open space in good condition (grass cover of over 75%) and included lawns, parks, golf courses, and cemeteries. C-CAP's Wooded land category is comparable to NRCS Woods category for woods with good hydrologic condition (woods which are protected from grazing, and where litter and brush adequately cover the soil). There are no curve numbers for water or wetlands. Water and wetland are 100% permeable and have a curve number of 0.

Generating Surface Runoff Potential Maps

Curve numbers for hydrologic soil group A corresponding to C-CAP land covers and distance to water buffers were used to generate a preliminary pollution potential map which was presented to South Shore Estuary Reserve members in October, 1996. The results of that meeting suggested that hydrologic soils group may be a significant factor and should be included in assessing pollution potential. Soils are categorized as either group A, B, C, or D, according to the water infiltration and transmission rates for saturated soils. Group A soils have high infiltration rates when thoroughly wet and a high rates of water transmission. These soils consist mainly of deep, well drained to excessively drained sands or gravely sands. Group D soils have high runoff potential with very low infiltration rates when thoroughly wetted. Natural Resource and Conservation Service (NRCS) staff provided appropriate soils information which was digitized according to hydrologic soils group for inclusion in the Carmans River area (B. Zimmerman, pers.communication).

The NRCS model protocol provides curve numbers for land uses and land cover for each soil group. Land cover and hydrologic soils group data was compared against appropriate categories to assign curve numbers (Table 5) in order to determine the significance of all four soil groups on estimates of nonpoint source pollution potential.

Results from the Carmans River Test Area

Information developed under the Carmans River study measures runoff potential at each point in the study area, without consideration of adjacent land cover, adjacent soils or surface drainage systems. Regardless, an increase in curve number indicates an increase in the amount of runoff entering existing drainage, filtration or detention systems. Total surface runoff directly reaching coastal waters would increase to the extent that existing conditions could not intercept and retain the additional runoff.

One way to measure contribution of hydrologic soils group information to pollution potential assessment is to compare weighted average curve numbers between calculations based on group A soils alone and all four soil groups. The weighted average curve number for the study area was 43.4 under the assumption that only hydrologic soils group A was present.

The study area was comprised of hydrologic soil groups as follows: group A - 36%; group B - 48%; group C- 1%; and group D - 7% (Figure 3, Map 2). Factoring the four soil groups into the spatial model calculations results in a weighted average curve number of 56.6. The represents an increase of 13.2 in the curve number due to soil type alone. The influence of soil type is largest for grassland and woodland classes. Bare ground, cultivated, and low intensity development also change with soil type, but to a lesser degree (Table 5). The difference in curve numbers is important, since the relationship between runoff and curve number is not linear.

In addition to measuring the relative contribution soils data, a visual representation was output from the spatial model which indicates the distribution and concentration of potential sources of stormwater runoff (Figure 3, Map 3). The final pollution potential map integrates land cover, hydrologic soil group and distance to water. The distance to water criterion accentuates the importance of sources located closer to water.

Curve number for each land cover is determined based on the plant cover, amount of impervious areas, interception and surface storage for each hydrological soil group A, B, C, and D (Soil Conservation Service, 1986).

Reserve-wide estimates

Although soils data was found to be a significant determinate of runoff potential in the Carmans River study area, incorporating soils data in larger areas such as the entire Reserve was not practical in the initial phases of this work. Curve numbers for hydrologic soil group A corresponding to C-CAP land cover classes were used in a reserve-wide assessment of pollution potential. Curve numbers for soil group A and distance to water criteria were used to generate a pollution potential map for the entire Reserve (Figure 4).

As in the case of the Carmans River study, in addition to a graphic representation of pollution potential, weighted average curve numbers were calculated for the reserve. Since soils information was not included in this part of the work, the amount of potential runoff would be underestimated if Group A curve numbers were used alone, particularly for grasslands, woodland and low density developed classes occurring over other soil types. Calculations for the entire Reserve were done for both soil group A and B to compensate for the affect of soils by providing a range of potential runoff values more likely to encompass actual runoff. Hydrologic soil groups C and D are not considered in the reserve-wide examples based on the lower amount of these soil groups in the study area, their relatively localized occurrence, and the extent that these soils types occur in wetlands which are not included in this analysis . The second estimate of runoff potential assumes that the Reserve is uniformly comprised of Group B soils. Using Group A curve numbers, the weighted average curve number is 55, while for Group B, the weighted average curve number is 71. As in the Carmans River example, these estimates illustrate the importance of including hydrologic soils group in an evaluation of potential surface runoff. Both reserve-wide weighted average curve numbers are higher than in the Carmans River example, reflecting the generally higher amount of developed classes throughout the reserve.

In addition to characterizing total surface runoff, the relative importance of different sources of potential runoff were compared for both soil groups. (Figure 6). Runoff for each cover type was calculated from the following equation (Soil Conservation Service, 1986):

where Q is the runoff depth in inches, P is rainfall in inches, and CN is the curve number. The curve number is related to potential maximum soil retention after runoff begins (S) according to the following equation: S = (1000/CN) - 10. Potential maximum soil retention depends on soil type and cover parameters.

A two inch rainfall amount was used for the precipitation value in the illustration provided. Depth of runoff was calculated for each of the land cover classes and then multiplied by the corresponding land cover's reserve-wide area to arrive at potential runoff volume by land cover class. Figures 5 and 6 indicate the relative importance of land cover class for hydrologic soil groups A and B.

Comparison among land cover classes indicates that high density development dominates runoff potential under either soil group A or B assumptions. Runoff potential for low density development strongly depends on soil group, but in either case represent the second largest potential runoff source. Runoff associated with low density development probably fall closest to the soil group B assumption, based on disturbance of soil profiles associated with development. Bare ground, due to its high runoff potential, also plays a relatively large role in potential runoff. Both woodland and grassland cover areas contribute little to runoff potential in comparison to other cover classes.

Changing rainfall values change the relative contribution of each cover type to pollution potential. Decreasing the rainfall amount increases the relative importance of high density development. Increasing the rainfall amount will increase the relative contribution for all cover classes other than high density development.

Application of pollution potential assessment to the Reserve

Land cover data provides a means to characterize runoff potential, particularly when used in association with hydrologic soils group data. The next step in evaluating surface runoff potential would be to incorporate soils information for specific areas of interest, or for all of the reserve. This would improve estimates of surface runoff potential, and is a data set that would be required in any other methods used to assess surface runoff.

In addition to addressing reserve-wide characterizations, a town-based assessment can be conducted by subsetting land cover data by town. A town-based surface runoff potential analysis could be modified to more accurately reflect local conditions and reduce generalizations used in the reserve-wide assessment. The value of completing a town-based analysis would be to provide better estimates of runoff volumes, allow comparison of relative importance of sources within a town, and identify specific areas which are likely to be significant sources of surface runoff. This town-based approach also allows comparison of the analysis to town management practices and land use issues. An alternative strategy would be to perform subsetted analyses by water management zones (Nassau-Suffolk Regional Planning Board, 1978) or by watersheds.

Loading estimates can also be made for pollutants which are related to land cover such as total suspended solids, total nitrogen, total phosphorus, biochemical oxygen demand, oil and grease, fecal coliforms, and pesticides (Newell et al., 1992). Estimates of these pollutants should be completed using land cover in combination with hydrologic soils data. Soluble pollutants would be segregated between surface and groundwater flows. Results of this effort would be used to further focus attention on specific areas which appear to be significant contributors of pollutants and the importance of these areas relative to other sources. Although previous modeling efforts, notably the 208 study (Nassau-Suffolk Regional Planning Board, 1978), have provided valuable information regarding total loading estimates, the land cover approach adds greater spatial and quantitative information which can be used to identify potential sources of pollutants.

Change in pollution potential for the period 1984 to 1994 can also be assessed based on the land cover change analysis presented in this report. The distribution of, and increase in, runoff quantity associated with the 12,000 acres of new development detected through land cover change merits investigation to estimate the increased runoff load to the south shore estuary. Results of this effort would be useful in describing the magnitude of the nonpoint source pollution problem based on known changes in development.

Measuring the effects of land use development through build-out projections are needed to understand the potential magnitude of water quality changes due to development. Accurate land use and zoning data by parcel is needed to identify land available for development. Once developable parcels are identified, projected change in land use and land cover can be derived. The change in runoff potential and pollutant loading can be calculated from projected land cover and soils data to estimate the magnitude of potential water quality impact under current development scenarios. Results of this approach can indicate the magnitude of the nonpoint pollution problem that awaits the south shore estuary depending on how development occurs.