detecting potential erosion threats to the coastal zone: st. john,...
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Detecting potential erosion threats to the coastal zone:St. John, UsviJohn Radke a ba Departments of Landscape Architecture and Environmental Planning, City and RegionalPlanning, University of California, Berkeley, California, USAb College of Environmental Design, University of California, 202 Wurster Hall, Berkeley, CA,94720–2000, USA E-mail:
Version of record first published: 10 Jan 2009.
To cite this article: John Radke (1997): Detecting potential erosion threats to the coastal zone: St. John, Usvi, MarineGeodesy, 20:2-3, 235-254
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Detecting Potential Erosion Threats to theCoastal Zone: St. John, USVI
JOHN RADKE
Departments of Landscape Architecture and Environmental Planning,City and Regional PlanningUniversity of CaliforniaBerkeley, California, USA
Islands, by definition, contain more coastal zone than mainland coastal regions ofsimilar area, yet island coastal zone management (CZM) plans are typically adaptedfrom existing mainland plans, which often results in narrowly defined and inadequateisland coastal zones. Typically, these zones are threatened as much by land usepractices employed in adjoining upland watersheds as by practices within the coastalzones themselves. The U.S. Virgin Islands (USVI) are no exception.
This research identifies areas with high erosion potential in the upland watershedsof St. John, USVI, given current development trends, land management policy, andland use control. To characterize erosion hazard, an erosion model, integrating therevised universal soil loss equation (RUSLE) with a digital terrain model (DTM) isbuilt within a geographic information system (GIS). Using quantitative multivariateanalysis in the model, a hierarchical assessment of potential soil erosion on devel-opment sites that lie outside, yet threaten the coastal zone environment, is produced.More resilient areas, those that can safely be maintained under existing or proposedland uses, are also mapped. This method can be applied to other regions that facesimilar development and erosion problems.
Keywords coastal zone management, GIS, land use planning, RUSLE soil erosion
By definition, islands have larger perimeter-to-area ratios, usually translating to morecoastal zone, than mainland regions of similar size. Tropical island coastal zones, withtheir lush vegetation, sandy beaches, and rich coral reefs, comprise some of the mostdiverse bioregions on earth. The coastline attracts great species diversity. Of all species,humans have the power to dominate—to preserve or destroy—the coastal zone. Humans
Received 30 November 1995; accepted 21 February 1996.I gratefully acknowledge the support and insightful comments on an earier draft of this work
by Maria Cacho and Mintai Kim and comments on a later draft by Laurie Newman Osher and JonBerger. I have benefited from discussions with Keith Richards, Director of the Department ofPlanning and Natural Resources within the Division of Comprehensive and Coastal Zone. LenGaydos, John Parks, and David Greenlee of the U.S. Geological Survey helped acquire the hyp-sography layer of St. John. I acknowledge Walt Bunter, State of California Agronomist, and RobGriffith, regional soil scientist at the U.S. Forest Service office in San Francisco, for their insightsinto the estimates of A and its relationship to sediment delivery and mass wasting events. Thisarticle is based on research supported by a COR grant from the University of California. Manuscriptpreparation was partially supported by a grant from the Beatrice Farrand Fund of the University ofCalifornia, Landscape Architecture Department.
Address correspondence to Dr. John Radke, College of Environmental Design, University ofCalifornia, 202 Wurster Hall, Berkeley, CA 94720-2000, USA. E-mail: [email protected]
235Marine Geodesy, 20:235-254, 1997Copyright © 1997 Taylor & Francis
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have become the custodians of this unique ecotone. Even with the best intentions, it isdifficult for humans to set foot near the coastline without causing some negative impact.
The key to sustaining tropical island coastal ecosystems is our ability and willingnessto undertake sound environmental land use planning and management within a context ofeconomic growth (Griffith & Ashe, 1993, p. 270). Sustainable development can beachieved when the needs of the present can be met without compromising the future(Cicin-Sain, 1993, p. 15). This can be achieved within the framework of a coastal zonemanagement (CZM) plan when a continuous decision-making process is in place (Cicin-Sain, 1993).
The land within the coastal zone may be regulated and managed as an integratedunit, but its fate is intimately linked with both the physical and socioeconomic worldbeyond its boundaries (Thia-Eng, 1993, p. 91). In order to insure the protection of thecoastal zone and to maintain an environmentally sound community, planners and man-agers must be able to identify those lands most at risk to erosion. The main objective ofthis research is to develop a method which identifies and measures land that has a highpotential for erosion and destruction given the current development trends, regulations,and CZM plan. A secondary objective is to build a spatially sensitive soil erosion modelwhich can map variations in potential soil loss across basins of complex terrain. Such amodel will aid landscape planners in locating properties which have a high potential forsoil erosion and which may have gone undetected using traditional basin-wide methodsof estimating soil loss.
This work was inspired by the destruction caused by Hurricane Hugo,1 and thepotential destruction of future hurricanes if poor land use practices continue. The extensivedamage to personal property and to the natural environment was blamed solely on Hugo,with little regard for the poor land use practices and conditions in place outside the definedcoastal zone.
Coastal Zones
Cendrero (1989, p. 367) synthesizes a number of definitions of coastal zone, and suggeststhat it at least includes the "inner part of the continental shelf, the coastline and ahinterland a few kilometers in width." Thia-Eng (1993, p. 83) defines it as the interfacebetween the land and the sea where humans interact with the terrestrial and marineenvironments. Many suggest it is a place of instability and conflict, which have increasedwith human intervention (Griffith & Ashe, 1993, p. 270; Verstappen, 1988). All agree itis a region that is not only attractive but essential for a healthy marine environment.
Mangrove swamps are an important component of the coastal zone ecosystem. Densenetworks of mangrove roots filter runoff and over time build islands by anchoring sedimentand acting as a buffer between the fresh water on one side and the salt and waves on theother. During all but the most powerful storms, sediment from uphill erosion will havelittle effect on the shoreline and offshore coral reefs due to the the efficiency of themangroves and turtle grass meadows in trapping sediment.
The coral reefs are dependent on the mangroves in a myriad of ways but perhapsmost importantly for the filtering of sediment (Milliman, 1973; Williams, 1988; Hubbard,1987). Coral colonies cannot exist without light for the photosynthetic species and a freshsupply of clean water to provide a rich supply of oxygen. Coral growth averages only
'Hurricane Hugo was a category 4 hurricane, which devastated the USVI in September 1989(Case & Mayfield, 1990).
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Detecting Potential Erosion Threats 237
2-10 cm per year, depending on species and water conditions (Glynn, 1973, p. 305).Increases in turbidity retard coral growth and accelerate reef decline. A single deposit ofsediment several centimeters thick, as was deposited by Hurricane Hugo, can kill anentire shallow reef in only a few days (Johannes, 1978).
Upland Management and the Coastal Zone
Humans are powerful geomorphological agents (Goudie, 1993), and our contribution tosoil erosion is one of the most serious mechanisms of land degradation in the tropics. Inhis studies on the effects of agriculture reducing the productivity of mangrove swamps,fisheris, and reefs, El-Swaify (1990) emphasizes the need for protective land uses in thetropics to mitigate devastation from soil erosion. Extreme rainfall and runoff during ahurricane exacerbates the problem (White, 1990) of soil losses, which occur regularlyduring a dozen or so smaller storms a year (Sheng, 1990).
The sediment form deforested upland sites is carried rapidly down the narrow valleys,where it cuts away more of the soil to form eroded valleys also known as "guts." Thesenarrow intermittent stream beds carry runoff and sediment to the coastal areas and threatenthe health of the mangrove wetlands, seagrass beds, and coral reefs, which are consideredone of the most biologically productive and taxonomically divese regions on earth (Griffith& Ashe, 1993, p. 271). The combination of land clearing, dredging, and the destructionof the mangroves leads to increased sedimentation and the eventual death of the reefcommunity, not to mention the tourist economy. If the reefs are removed, the coastalzone is left vulnerable to storm damage, and the process of destruction is enhanced(Towle, 1985, p. 648).
The Study Site: St. John, USVI
A Brief History
The Virgin Islands are approximately latitude 18° North and longitude 64° West. Theywere discovered by Western civilization during the voyages of Columbus nearly 500 yearsago. At that time Carob and Arawak tribes inhabited them, and subsisted on fish andnative fruits. Most of the land was densely covered by tropical vegetation, supported bylateritic and calcareous soils. Through all but the most violent storms, the soils wereprotected from heavy rains and held in place by the native plants. Subtropical forests,like those found on St. John, are structurally less complex than tropical forests (Teytaud,1988). They are highly resilient and return to their predisturbance condition quickly afterhurricanes (Reilly, 1991). Little is known of the original plant ecology prior to the arrivalof Westerners. During the colonial plantation years of the eighteenth and nineteenthcenturies, approximately 90% of the land was cleared, principally for sugar cane andcotton production. It is estimated that an enormous amount of topsoil was lost from thesteep slopes which dominate the islands (Reilly et al., 1990). At that time it is likely thatmuch of the coral reef was under stress from sedimentation. By the twentieth century theplantations had been abandoned for a variety of reasons, soil loss among them. Thesechanges in land use and vegetation during the last four centuries have irreversibly changedthe island forests, coastlines, and coral reefs.
There are approximately 50 cays and islands that make up the USVL. The threelargest and main islands are: St. Croix (218 km2), St. Thomas (83 km2), and St. John(50 km2). The islands are underlain by cretaceous volcanic bedrock (Rivera et al., 1966)
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238 J. Radke
and covered by a thin layer of soils (Rivera et al., 1970) with a mean depth to bedrockof 39.5 cm in the upland area (Mount et al., 1994), where they are highly susceptible toerosion when exposed. The islands support a variety of human cultures as well as adiverse and complex ecosystem (Ewel & Whitmore, 1973). Tourism has emerged as thesingle most significant industry and accounts for half of the gross territorial product.Although seen as a blessing to the local economy, which now boasts the highest per-capita income in the Carribbean, tourism has contributed to an overtaxed infrastructureand the degradation of the territory's ecosystem. There currently exists a conflict betweenthose who want more economic growth and those who want to conserve the naturalecosystem (Gilliard-Payne, 1988).
Development Pressures and the Coastal Zone
At first glance the USVI is truly one of the most attractive island habitats in the world.A closer look reveals the signs of stress due to a lack of a comprehensive plan coupledwith poor development practices and an unorganized management scheme. A coastal zonemanagement (CZM) plan, modeled after the plan implemented for the State of Florida(NOAA, 1981), was put in place in the USVI in 1978 (Towle, 1985, p. 659). Using theparameters from the Florida plan, the CZM for the USVI delineated a relatively narrowzone along the coastline. In order to attain sound land management practices on thesesmall islands, it may be appropriate to define the entire island as coastal zone.
Figure 1 delineates the land within the St. John coastal zone2 as defined by the CZMplan, which consolidated the local permitting process for developments in the coastalzone. Although the plan contains stringent regulations, local criticism suggests that severalfactors critical to coastal ecosystem health are given little weight or overlooked entirelyin the regulations (Towle, 1985, p. 661; Richards, 1992). While many of the plants andshorelines of Florida are similar to those of the USVI, the topography, soils, and theinteraction of the land and marine life are quite different. Management of the USVIecosystem must be consistent with that of an island community and not the mainland. Anintegrated coastal management plan must include lands that have the potential for directimpact on the delineated coastal zone itself. The current stress on the existing infractruc-ture in the USVI now dictates that there is little room for error in this effort.
St. John differs from the rest of the USVI in that it is dominated by a national parkgifted to the government in 1956 by Laurance Rockefeller. The remaining 30% is underintense pressure from developers and private landowners seeking to build vacation homesand holiday resorts. The island is characterized by extreme rugged mountainous terrainwith slopes greater than 30% (CH2M Hill, 1979) descending steeply into small coves andbays defined by rocky points. It appears that any erosion inland will certainly threatenthe coastal ecosystems by destroying plant communities and endangering the adjacentcoral reef.
Hurricanes impose a constant threat to the Caribbean islands each year between Juneand November. During hurricanes, the coastal zone areas receive considerable damagefrom wind and wave action, yet the greatest threat comes from the sediments that areeroded in the uplands and deposited in the wetlands, mangrove swamps, and coral reefsduring these catastrophic events. The greatest amount of soil loss and subsequent depo-sition down slope comes during these heavy storms, due to the torrential rains, saturatedsoils, and steep slopes (Sheng, 1990, p. 158). Although Hurricane Hugo was the last
2CoastaI Zone Management Map of St. John, USVI, produced by Department of Planning andNatural Resources, Coastal Zone Management Program, NOAA.
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Detecting Potential Erosion Threats 239
Coastal Zone Management Plan
• National Park • Unprotected Land
£1 Coastal Zone Management 0 2 Km
Figure 1. Land protected by coastal zone management and the national park.
great storm to cause havoc on St. John, the chronology of major and memorable floodsin Table 1 indicates that these catalystic events are not uncommon.
In theory, the CZM plan in place on St. John protects the costal zone, which includesthe mangrove swamps. In practice, however, a great many of these mangrove protectivebarriers have been removed and replaced with resort developments (Towle, 1985, p. 650).The watershed above the area delineated by the CZM plan is undergoing rapid develop-ment (Richards, 1992). The hillsides are undergoing regarding to accommodate infrastruc-ture to support the new development. Natural vegetative communities are being replacedwith ornamental landscaped gardens most often not designed to mitigate erosion. It isspeculated that the intensive development in the upper watersheds has increased thepotential of flash flooding and massive soil erosion (Towle, 1985, p. 648). Figure 2illustrates the problem where single-family residential development is occurring abovethe area protected by the CZM plan.
The coastal zone on St. John is at risk. The upland watershed is a key physical unitwhich must be considered in any management scheme to protect the coastal zone. Towle(1985, p. 665) suggests that the definition of the coastal zone is flawed in the USVI andthat a more appropriate definition should include all of the island territory. This wouldessentially equate the watershed and the coastal zone. In its current state, manageabletasks within the coastal zone quickly become unmanageable in the face of externalpressure from development activity in upland areas.
Method
The method developed here fuels a revised universal soil loss equation (RUSLE) (Moore& Wilson, 1992) with sensitive surface model information derived from a digital terrain
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Table 1Chronology of major storms and other memorable floods in
St. John, U.S. Virgin Islands, 1960-1989
Date Description
8 May 1960 Slow-moving, low-pressure trough. Maximum wind speed 104mi/h, maximum 3-day rainfall 14.6 in. on St. Thomas. Damage,$700,000.
7 Oct. 1970 Slow-moving tropical depression. Maximum 24-h rainfall 9.6 in.on St. Thomas. Damage, $6 million.
12 Nov. 1974 Intense rainfall (6 in. in 4 h) on St. Thomas; declared majordisaster area. Also on St. John and St. Croix. Deaths, 1; propertydamage, $6 million.
8 Oct. 1977 Tropical wave interacting with complex upper-level trough.Greatest 24-h rainfall on St. Croix. Damage, $6 million.
29 Aug.-5 Sept. Hurricane David—maximum wind speed 54 mi/h on St. Croix;1979 rainfall 15 in. in 3 days. Tropical storm Frederic—maximum
wind speed 50 mi/h; maximum 24-h rainfall, 20 in. in AnnasHope, St. Croix. Damage (both storms), $14 million.
18 Apr. 1983 Most intense rainfall (3.4 in./h) of record on St. John. Deaths, 1;damage, $12.5 million.
17-18 Sept. 1989 Hurricane Hugo (category 4—sustained winds of 225 kph)
Source: National Water Summary 1988-89—Floods and Droughts: U.S. Virgin Islands.
model (DTM). Until now the application of erosion models has dealt mainly with basin-wide averages, Flacke et al. (1990) being the exception, which reduce sensitivity withinthe basin and make it almost impossible to focus on potentially risky properties. Themodel developed here, which is embedded in a geographic information system (GIS),maps hierarchically, at a resolution approaching the property level, polygons of land withgreat potential for erosion. Properties with a high risk of erosion can be identified andregulated to reduce risk of environmental degradation.
We map those areas currently not regulated or protected by the CZM plan or theNational Park, which have a high potential for soil erosion to threaten the coastal zone.We also identify more resilient areas that can be maintained with current developmentstrategies. The method allows for direct application to other island ecosystems and/orwatersheds faced with similar development pressures.
The application of the RUSLE determines what property on the island has the greatestpotential for sheet and rill erosion. Although the universal soil loss equation is contro-versial because it often over- or underpredicts the amount of soil actually eroded, for ourimplementation it is a reasonable tool to determine relative areas of erosion.
The Universal Soil Loss Equation (USLE)
The universal soil loss equation (USLE) is a powerful tool developed for soil conserva-tionists (Wischmeier & Smith, 1978) and widely applied in conservation planning activ-
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Detecting Potential Erosion Threats 241
ities (Rennard & Ferreira, 1993). The use of the model has spread from conservationistsstudying cropland and rangeland to planners studying recreation sites, highway construc-tion, and urban land use (Rennard et al., 1991). The USLE contains parameters that arerecognized as universally affecting erosion (Wischmeier, 1976). It estimates annual soilloss by sheet and rill erosion but does not provide information on sediment characteristicsand deposition. The model is empirically based and does not contain fundamental hy-drologic and erosion processes. Although there may be significant differences betweenestimates and observed data, the USLE is adequate in representing erosion potential andremains the most powerful and widely used estimator for first-order effects of sheet andrill erosion (Rennard et al, 1991).
The Revised Universal Soil Loss Equation (RUSLE)
The RUSLE builds upon the USLE and produces a model where the same factors aregenerated but with new equations. These new equations are based on analysis of data notpreviously used in the USLE and theory describing hydrologic and erosion processes(Rennard et al., 1991). The fundamental equation remains the same:
A = RKLSCP
where/4 = computed annual soil lossR — rainfall-runoff erosivity factorK = a soil erodibility factor
LS = a topographic factor combining slope length, L,and land surface slope angle, S
C = land cover and managementP = erosion-control practice for crops
Figure 2. Single-family residential development perched above the protected CZM area.
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The main differences in the two models are well documented by Rennard et al.(1991). For the island of St. John, where the slopes are very steep, the LS factor dominatesthe equation and Rennard et al. (1991) suggest that any difference between the two modelsunder these conditions would be noticed in a reduced estimate in the computed soil lossof the RUSLE.
Estimating the Factors for St. John, USVI
R Factor. The St. John climate is tropical maritime, with dominant easterly winds andrain-producing systems approaching from the east in summer and the northwest in winter(U.S. Geological Survey, 1991). The mean annual precipitation is approximately 114 cmand peaks in September to November and again in April and May. The estimated R factorfrom the isoerodent map (U. S. Soil Conservation Service, 1975) of the region is a constantR = 350.
K Factor. The K factor, an indicator of inherent soil erodibility, was calculated using theUSLE erodibility nomograph (Dunne & Leopold, 1978, p. 527) and the USVI Soil Survey(Rivera et al., 1970). Although modifications that account for seasonable variability weremade to the K factor in the development of the RUSLE (Rennard & Ferreira, 1993), inthis St. John study, seasonal variability is minimal and no modifications to K werenecessary.
LS Factor. The LS factor, which involves both slope length and steepness, was calculatedusing output from a digital terrain model of the island combined with a simplified methodof LS estimation derived by Moore and Wilson (1992).
The sediment transport equation used to derive the LS factor follows:
LS = ' A'22.13/ 10.0896
where As = slope length
m = slope length exponentP = land surface slope anglen = slope angle exponent
This equation produces the best fit between the RUSLE-LS and the dimensionless sedi-ment transport capacity derived from the Water Erosion Prediction Project (WEPP) theory(Laflen et al., 1991) when the area and slope exponents (m and n) are 0.6 and 1.3,respectively (Moore & Wilson, 1992, p. 427). We use these values in our model.
The land surface slope angle S is generated from a digital terrain model. The digitalsurface model, a Delaunay triangulation {DT) (Peucker et al., 1978; Okabe et al., 1992),is built based on the 1:24,000 U.S. Geological Survey (USGS) hypsography series ob-tained in digital form from the USGS. This method ensures a high spatial resolution ofsoil loss prediction similar to that of Flacke et al. (1990). The method introduced herediffers from that of Flacke et al. (1990) in that it addresses basin boundary issues in itscalculation of the soil loss for watersheds and then integrates many hydrologic basins tocalculate S for the entire island. The island is divided into 55 basins which were interpretedfrom the published USGS 7.5' quadrangle maps and digitized. The arcs defining the basin
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Detecting Potential Erosion Threats 243
edges are densified with sample points and used as break lines to eliminate any cross-basin interpolation of the surface. This ensures that the edges of the basins are definedby an edge in the DT.
Building a surface model from hypsography can lead to extreme irregular triangulatedfacets generated as a result of the nature of the DT (Okabe et al., 1992) and the originalspatial sampling pattern. Flacke et al. (1990) developed this model for level terrain anddid not encounter this problem in their sample and thus do not address the problem. Theprobability of encountering these extremely irregular triangles in the St. John data setwith its complex terrain is very high. To address this we construct a sample surface ofDelaunay triangles generated from combining a regular triangular lattice with the densifiedbasin edges and draped on the surface model to assign slope angle (3 and aspect a to eachtriangle or DT facet. Figure 3 illustrates the DT generated from combining the regulartriangulated sampling lattice with the densified basin edges of two basins from the St.John data set.
To calculate the longest slope length A, of each DT facet, we use the known aspecta, which is determined from the three points that construct each DT facet. Given the DTfacet in Figure 4, we first calculate the equation of a line passing through the first pointP(xf, y,) with aspect a:
y, = ox, + b
We calculate the equation of the opposite edge in the triangle to point P,:
1 = M-U' + v
Basin b1 and b2
500 m
Figure 3. The DT generated from combining the regular triangulated sampling lattice with thedensified basin edges of two basins from the St. John data set.
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/
•V''
= a • x, + b
/ P(x2,y2)
Figure 4. A DT facet where the L factor is calculated.
where Ay = (y, - y2)Ax = (x, - x2)
We calculate the intersection of these two lines:
/ = ax" + b"
(b' - b)where x =
a - (Ay/Ax)
If the intersection falls within the segment delineated by the second two points, P{x2, y2)and P(x3, y}), As is solved and the L factor is calculated.
C Factor. The estimated C factor was calculated using land cover from Woodbury andWeaver (1987), field survey and photographs, and the cropping management factors tablefrom the U.S. Soil Conservation Service (SCS) in Dunne and Leopold (1978, p. 529).
Rennard and Ferreira (1993) suggest the equation
C = PLU CC SC SR SM
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Detecting Potential Erosion Threats 245
where PLU = prior land useCC = canopySC = surface coverSR = surface roughnessSM = soil moisture (used in the Pacific Northwest)
as a revised calculation for the C factor. However, on the Island of St. John, only CCand SC subfactors could be measured. Not enough detailed historic information.is knownabout prior land use (PLU), except for the fact that most of the island was planted insugar cane during the colonial plantation years. Both PLU and surface roughness (SR)are calculated from the amount of biomass that accumulates in the soil. 'Mount (1995)suggests that the amount of biomass does not vary much throughout the island and that itis reasonable to consider PLU and SR as constants here. Mount et al. (1994) concludedthat additional sampling, specifically in physiographic units, is needed for greater accu-racy. The soil moisture subfactor (SM) is specific to the Pacific Northwest and does notapply here.
P Factor. The erosion-control practice factor P is a constant value 1, as there are currentlyno crops on the island.
The erosion estimation for all land on the island is calculated at near acre resolutionfor this landscape planning exercise in this extremely complex topographic environment.The Delaunay triangulated sample surface becomes the map template from which allresults are calculated. The sequence of steps in calculating this potential land erosionmodel are documented in Table 2.
ResultsSoil loss must be estimated with high resolution because of the complexity of the terrainon St. John and to fulfill the objective of building a spatially sensitive soil erosion modelwhich can map variation in potential soil loss within a basin. A surface model, illustratedin Figure 5, is generated for the complex topography of St. John from the 1:24000 USGShypsography data. This model serves as the base from which slope, aspect, and eventuallythe LS factor is calculated for the DT sampling surface generated from a regular triangularlattice and the densified basin edges.
The K factor, which represents the soil erodibility, is mapped in Figure 6. Althoughthe original spatial mapping units from the SCS Soil Series are quite complex, the islandis dominated by Cramer and Isaac soil groups, which comprise approximately 86% of theisland. When the K factor is calculated and classified, these soil mapping units dissolvetogether and form a relatively simple map.
The C factor results are mapped in Figure 7. Unlike the soils where.several classesresulted in the same K factor, each of the vegetation classes delineated from the landcover from Woodbury and Weaver (1987), field survey, and photographs produces aunique C factor.
Both K and C factors are assigned to each individual Delaunay triangle in the samplingsurface through the use of polygon overlay. The remaining factors, R and P, which areconstant throughout the island, are incorporated when the RUSLE model is applied toeach DT facet in the sample surface.
The estimated computed soil loss value A (in tonnes per acre per year) is calculatedand presented in Table 3, where five classes report the total area and percent of the island
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Table 2Processing steps in applying the potential land erosion risk model
Processing the RUSLE
• A digital terrain or surface model is built from elevation data.• The Delaunay triangulated sampling surface is calculated and draped on the surface
model.• The LS factor is calculated for each DT facet in the triangulated sampling surface.• The soil series are digitized as polygons from the USVI Soil Survey.• The K factor is estimated for each polygon.• The vegetation are digitized as polygons from the vegetation map of forest types
produced by Woodbury and Weaver (1987).• The C factor is estimated for each polygon.• The R factor is estimated as a constant (/? = 350), the isoerodent map of the U.S.
Soil Conservation Service (1975).• The P factor is estimated as a constant (P = 1), as there are no crops on the island.• The digitized maps are all overlaid to produce a map with all the factors defined for
each DT facet in the triangulated sampling surface.• The computed annual soil loss A (in tonnes per acre per year) is calculated for each
DT facet.
Processing lands at greatest risk of erosion
• The computed annual soil loss map is overlaid with a map delineating the protectedlands of the CZM and National Park to produce a potential erosion risk map, whichdelineates those areas at risk of potential erosion that are not protected by anyregulatory mechanism.
Digital Terrain Model
Z factor: 2.0
Figure 5. A digital terrain model of the complex topography of St. John.
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Detecting Potential Erosion Threats 247
K factor
[171 0.0-0.07I 1 0.07-0.10
0.10-0.13
0.13-0.16
0.16-1.0
2 Km
Figure 6. The K factor, which represents the soil erodibility.
within each class. The erosivity index R value for the USVI region adds considerably tothe large estimated values for A on St. John. However, the estimates of A are not out ofsync with estimates in other regions of the country with similar LS conditions. Forexample, if we moved the island of St. John to California, it would undergo a significantreduction in the erosivity index R and would produce estimates of A similar to those foundin California.3 The estimated values of A, if St. John were located in California, wouldbe approximately 20% of those currently reported for St. John in this study.
Figure 8 is a map of the estimated soil loss classes reported in Table 3. The distri-bution across classes is relatively even, and visual inspection reveals that there is highpotential for erosion along the coastline. The areas with lower estimated erosion potentialare located toward the middle of the island. The model has produced a detailed map ofpotential soil loss, where units are delinated near acre-level resolution.
Figure 9 is a map of the potential erosion risk for lands not protected by the CZMplan and the National Parks Service. It maps potentially erodable lands, as well as resilientareas, where erosion is unlikely even in the light of current development strategies. Asignificant portion of these unprotected lands, 1,398 acres out of 2,831 acres, possess apotential threat to the environment in the coastal zone. Table 4 presents the amount ofarea within each potential erosion class. Over 50% of the land in these relatively unreg-ulated zones are in the lower estimated soil loss classes. Most of this low-erosion-potentialland is located in a contiguous area on the west end of the island near the village of CruzBay.
Although some of the high-erosion-potential areas are perched above the costal zonenear the ocean and adjoining the settlement of Cruz Bay, must of this erodable land is
The largest estimates for California, approximately 90 tonnes/acre/year, were obtained fromRob Griffith, regional soil scientist, at the USFS office in San Francisco.
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248 J. Radke
C factor
CJ 0.0-0.5fZl 0.15-o
0.20-0.250.25-0 JO
0.30-1.0
0 2 Km
Figure 7. The C factor, which represents land cover and management.
located near the geographic center of the island and away from current developmentpressure. This land is considered by locals to be some of the most scenic on the island,and as improvements to infrastructure continue, the pressure to develop these lands willincrease. Over 1,000 acres are mapped in the highest two classes of estimated soil loss.
The GIS/RUSLE mapped results presented here clearly illustrate the portions of theunregulated upland that are not immediately at high risk, as well as the portions of theupland which have high erosion potential. These results provide the valuable landscapeand soil information necessary for planners and decision makers to formulate policies thatcan better mitigate against future erosion and damage in the coastal zone.
Erosion, A(tonnes/acre/year)"
0-50*50-100
100-150150-200>200
Table 3Estimated yearly erosion on St. John
Area(acres)
3,062.192,346.171,831.281,552.743,513.11
12,305.49
Area(% of island)
24.8819.0714.8812.6229.55
100.00
"Calculated using RUSLE, where A = computed annual soil loss.*0-50 tonnes/acre/year include areas covered by rock, open water, swamps, and tidal flats.
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Detecting Potential Erosion Threats 249
Soil Loss (tonnes/acre/year)
• 50-100100 -150
150-200>200
2 Km
Figure 8. Estimated soil loss for the entire island.
Discussion
In order to assess and predict the risk of potential soil erosion, the natural as well asregulated environment must be delineated and assessed. The method developed in thisstudy uses preexisting conditions to model and infer the potentially hazardous state ofcurrent land use. The results, mapped in Figure 9, indicate that lands with extremely highpotential for erosion exist in the areas above the protected region defined by the CZMplan.
Table 4Estimated yearly erosion—unprotected region
Erosion, A(tonnes/acre/year)"
Area(acres)
Area(% unprotected area)
0-50*50-100
100-150150-200> 2 0 0
903.02530.03383.52305.44709.28
2,831.29
31.8918.7213.5510.7925.05
100.00
"Calculated using RUSLE, where A = computed annual soil loss."0-50 tonnes/acre/year include areas covered by rock, open water, swamps, and tidal flats.
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250 J. Radke
Soil Loss (tonnes/acre/year)
. • 0-50n 50-100
100-150
150-200>200
0 2 Km
Figure 9. Estimated soil loss for the unprotected upland areas.
The results of this study appear promising. The spatial sensitivity established by theapplication of the RUSLE to each Delaunay triangle in the sample surface provide theplanner and land use manager with a powerful tool to identify and classify lands ofpotential erosion. Where basin-wide averages in the past camouflaged specific lands atrisk and forced blanket regulatory controls, we can now identify, apply, and administersite-specific regulations.
As in all studies of this kind, sources of error and a certain degree of spatial uncer-tainty exist. The scale of the study was based on the USGS 7.5' quadrangle, and themaximum size of the Delaunay triangles in the sample surface was 0.9 acre, or a littleless than twice the size of the average lot developed as residential property in subdivisionson St. John. The spatial resolution of the study here appears adequate for the land useexample studied.
This study uses ancillary data (McHarg, 1969) collected and published by the federalgovernment (USGS, SCS) and other sources (Woodbury & Weaver, 1987). More sensi-tive and possibly accurate results can be generated if the subfactors in the model aredetermined on a more site-specific basis rather than being estimated from the current datasources. However, not all data are readily available and easily obtainable in planningstudies such as this (Campbell et al., 1992; McHarg et al., 1992). There is always errorassociated with incorporating ancillary data such as that needed to estimate the K and Cfactors. However, most studies, especially in poor island communities such as this, cannotafford the luxury of redoing a soil survey or remapping the land cover and must utilizeexisting ancillary data sources. The application here accommodates such data.
The method proposed in this study is most interested in a strategy for addressing theunregulated lands at risk of potential erosion. The objective is to identify those lands,map them, and classify them hierarchically from highest to lowest potential erosion.
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Detecting Potential Erosion Threats 251
Although the values of A estimated appear high when compared to dryer areas such asCalifornia, they may actually underpredict in St. John, as most erosion is amplified duringcatastrophic events such as hurricanes. This relative classification of erosion intensity andnot absolute estimates of soil loss is the key to directing planners and land use managersto a strategy of regulation and protection without having to issue a moratorium ondevelopment.
Conclusions
This research developed a method for soil erosion mitigation for estuarine managementfor St. John, USVI. Based on potential soil erosion analysis of the 55 basins of St. John,the model serves as a quantitative tool for environmental planners and decision makersassessing the potential side effects of development on small, subtropical Caribbean is-lands. The method, which is embedded in a geographic information system, includespotential soil erosion, existing land cover, and potential unregulated development sites asinput criteria for the analysis. The method integrates a revised universal soil loss equation(RUSLE) and modifies the generation of the LS factor through the use of a digital terrainmodel (DTM) which sensitizes the within-basin potential erosion sites. It serves to identifyexisting threatened lands, as well as the more resilient areas that can be maintained in thelight of appropriate development strategies. It is also designed to have direct applicationto other similar areas in the Caribbean and abroad that are facing similar developmentpressures.
The results indicate a need to rethink the application of CZM plans on small islands.The results of applying the method on St. John indicates that Towle's (1985, p. 665)original assertion, that the entire island is coastal zone and that the direct application ofmainland CZM plans to small islands results in large amounts of land at risk, is true. Thepotential for destruction of lands and coral reef is very real in St. John, even though theisland at first glance appears quite safe due to the vast amount of St. John under NationalPark Service care. Its neighbors, St. Thomas and St. Croix, share many similarities, andit is reasonable to assume that they likely face great potential for the same type ofdestruction and loss. The destruction of the coral reefs, the USVI's most cherished asset,would destroy the local economy.
Poor land use practices serve to degrade the environment and enhance the destructivepotential of extreme weather conditions, such as those experienced during hurricanes.Mechanisms that provide better and more effective land use control can be credited witheasing the impact of such events and are effective tools in catastrophe planning. Thesemechanisms often appear as legislation or regulations applied to a designated or controlledregion, such as that delineated by a CZM plan or national park. They may also materializeas predictive models, like the multivariate one developed here, where landscape condi-tions dictate the prescribed land use control required. For the island of St. John they serveas an effective tool for land use control in areas that are essentially unregulated. Plannerscan now apply these multivariate models to the landscape, discover what land is poten-tially at risk from erosion, and apply development prescriptions at the permitting levelthat are better suited to individual parcels of land, rather than applying blanket legislationin a coastal region. Such predictive models are the first step in generating a new dynamicparadigm for land use planning.
It is easy to apply blanket restrictions to the land such that all development is subjectto the same constraints. However, not all land has the same opportunities and thereforeshould not be managed by the same constraints. This stifles development and is not a
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252 J. Radke
wise growth management practice. The method developed here provides an effectivemeans for assessing the variability in land and its potential impact on surrounding lands,in this instance, the coastal zone. Until now, erosion models have lacked spatial sensitiv-ity, which often diluted their predictive power over an entire basin. In contrast, the modeldeveloped here produces an almost parcel-level predictive tool which refines the appli-cation of regulatory mechanisms for land use control, especially in heterogeneous land-scape like that found in the unregulated regions of St. John. Embedding such models inGIS provides the planner with the necessary tools to apply individual prescriptions toparcels, using as a guide, maps establishing the hierarchy of potential risk of erosion.These GIS-based models provide new opportunity and insight for defining, delineating,and managing the coastal zone itself.
Finally, it is reasonable to assume that if development continues to take place onlands with little or no regulation of development, much of the coastal zone would bedestroyed. If no regulation is established to ensure that natural vegetation is secure andprotected, or some mitigation schema is in place, during the next catastrophic event, suchas a hurricane,4 soil will erode from these regions and cause havoc. It has been shownthat natural landscapes on this island, and in steep slopes where erosion has its greatestpotential, have stayed intact through hurricanes such as Hugo (Reilly, 1991). It is likelythat sound land use practices could accommodate both growth and environmental protec-tion in the potentially high-risk areas if strict regulations were in place and enforced.However, without the knowledge of where these high-risk lands are, and with no regu-latory mechanism in place, hurricanes, like Hugo, will continue to devastate these islandsand their coastal zones.
ReferencesCampbell, J. C., J. D. Radke, J. T. Gless, and R. Wirtshafter. 1992. An application of linear
programming and geographic information systems: cropland allocation in Antigua. Environ-ment and Planning A, 24: 535-549.
Case, R., and M. Mayfield. 1990. Annual summaries. Atlantic hurricane season of 1989. NOAA—National Weather Service.
Cendrero, A. 1989. Land-use problems, planning and management in the coastal zone: An intro-duction. Ocean and Shoreline Management 12: 367-381.
CF2M Hill, Inc. 1979. A sediment reduction program. Report to Department of Conservation andCultural Affairs, Government of the Virgin Islands, St. Thomas, Virgin Islands.
Cicin-Sain, B. 1993. Sustainable development and integrated coastal management. Ocean andCoastal Management 21: 11-43.
Dunne, T., and L. B. Leopold. 1978. Water in environmental planning. San Francisco: W. H.Freeman.
El-Swaify, S. A. 1990. Research needs and applications to reduce erosion and sedimentation in thetropics. Research needs and applications to reduce erosion and sedimentation in tropicalsteeplands, Proc. of the Fiji Symp., IAHS-AISH Publ. 192, pp. 3-13.
Ewel, J. J., and J. L. Whitmore. 1973. The ecological life zones of Puerto Rico and the VirginIslands. Forest Service Res. Paper, Inst. of Tropical Forestry 18. Rio Piedras, Puerto Rico:U.S. Department of Agriculture.
Flacke, W., K. Auerswald, and L. Neufang. 1990. Combining a modified universal soil lossequation with a digital terrain model for computing high resolution maps of soil loss resultingfrom rain wash. CATENA 17: 383-397.
4After this article had been submitted for review. Hurricane Marilyn devastated the USVI on15 September 1995.
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orni
a, B
erke
ley]
at 1
1:27
23
Oct
ober
201
2
Detecting Potential Erosion Threats 253
Gilliard-Payne, B. 1988. Striking the balance on business development, recreation, conservation.Special Paper. St. Thomas, USVI: UVI-Caribbean Research Institute.
Glyrin, P. W. 1973. Aspects of the ecology of coral reefs in the western Atlantic region. In 0 . A.Jones and E. Endean (eds.), Biology and geology of coral reefs, Vol. 1, pp. 271-324. Londonand New York: Academic Press.
Goudie, A. 1993. Human influence in geomorphology. Geomorphology 7: 37-59.Griffith, M. D., and J. Ashe. 1993. Sustainable development of coastal and marine areas in small
island developing states: A basis for integrated coastal management. Ocean and CoastalManagement 21: 269-284.
Hubbard, D. K. 1987. A general review of sedimentation as it relates to environmental stress inthe Virgin Islands Biosphere Reserve and the eastern Caribbean in general. Biosphere ReserveRes. Report 20, VIRMC/NPS.
Johannes, R. E. 1978. Coral reefs: Research methods. In D. R. Stoddart and R. E. Johnson (eds.),Monographs on oceanographic methodology 5, Paris: UNESCO.
Laflen, J. M., L. J. Lane, and G. R. Foster. 1991. A new generation of erosion predictiontechnology. J. Soil Water Conservation 46: 34-38.
McHarg, I., J. D. Radke, J. Berger, and K. Wallace. 1992. A database prototype for a nationalecological inventory (Federal Grant X003527-01-0). Washington, DC: U.S. EnvironmentalProtection Agency.
McHarg, I. 1969. Design with Nature. New York: Doubleday.Milliman, J. D. 1973. Caribbean coral reefs. In O. A. Jones and R. Endean (eds.), Biology and
geology of coral reefs, 1: Geology 1, pp. 1-50. New York: Academic Press.Moore, I. D., and J. P. Wilson. 1992. Length-slope factors for the revised universal soil loss
equation: simplified method of estimation. J. Soil Water Conservation 47(5): 423-428.Mount, H. R. 1995. Personal communication. (Henry R. Mount is a Soil Scientist at the Soil
Survey Quality Assurance Staff, SCS, Lincoln, NE.)Mount, H. R., W. C. Lynn, R. J. Engel, and R. Vick. 1994. Organic carbon in the soils of St.
John Island, United States Virgin Islands, Soil Survey Horizons 35(2): 29-36.NOAA, 1981. Final environmental impact statement of the proposed coastal management program
for the State of Florida. Office of Coastal Zone Management, NOAA, Department of Com-merce, and Florida Office of Coastal Management, Department of Environmental Regulation.
NOAA. No date. Coastal zone management map, St. John, USVI. Department of Planning andNatural Resources, Coastal Zone Management Program.
Okabe, A., B. Boots, and K. Sugihara. 1992. Spatial tessellations: Concepts and applications ofVoronoi diagrams. New York: John Wiley.
Peucker, T. K., R. J. Fowler, J. J. Little, and D. Mark. 1978. The triangulated irregular network,Proc. of the Digital Terrain Models Symp., American Society of Photogrammetry, St. Louis,Mo., pp. 516-540.
Reilly, A. E. 1991. The effects of Hurricane Hugo in three tropical forests in the U.S. VirginIslands. Biotropica 23(4a): 414-419.
Reilly, A. E., J. E. Earhart, and G. T. Prance. 1990. Three sub-tropical secondary forests in theU.S. Virgin Islands: A comparative quantitative ecological inventory. Adv. Econ. Bot. 8: 189-198.
Rennard, K. G., and V. A. Ferreira. 1993. RUSLE model description and database sensitivity.J. Environ. Qual. 22: 458-466.
Rennard, K. G., G. R. Foster, A. W. Glenn, and J. P. Porter. 1991. RUSLE: Revised universalsoil loss equation. J. Soil Water Conservation 46: 30-33.
Richards, K. 1992. Personal communication. (Keith Richards is the Director of the Department ofPlanning and Natural Resources within the Division of Comprehensive and Coastal Zone.)
Rivera, L. H., W. D. Frederick, C. Ferris, E. H. Jensen, L. Davis, C. D. Palmer, L. F. Jackson,and W. E. McKenzie. 1970. Soil survey—Virgin Islands of the United States. San Juan,Puerto Rico: USDA Soil Conservation Service.
Rivera, L. H., W. E. McKenzie, and H. H. Williamson. 1966. Soils and their interpretations for
Dow
nloa
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by [
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vers
ity o
f C
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erke
ley]
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1:27
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201
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254 J.Radke
various uses: St. Thomas, St. John, Virgin Islands. San Juan, Puerto Rico: USDA SoilConservation Service.
Sheng, T. C. 1990. Runoff plots and erosion phenomena on tropical steeplands. Research needsand applications to reduce erosion and sedimentation in tropical steeplands, Proc. of the FijiSymp., IAHS-AISH Publ. 192, pp. 154-161.
Teytaud, R. 1988. Environmental factors and potential natural vegetation in St. John, U.S. VirginIslands. Island Resources Foundation. Report to National Parks Service.
Thia-Eng, C. 1993. Essential elements of integrated coastal zone management. Ocean and CoastalManagement 21: 81-108.
Towle, E. L. 1985. The island microcosm. In J. R. Clark (ed.) Coastal resources management:Development case studies. Renewable Resources Information Series Coastal ManagementPublication No. 3, pp. 591-738. Washington, DC: National Parks Service.
U.S. Geological Survey. 1991. National water summary 1988-89—Floods and droughts: U.S.Virgin Islands. U.S. Geological Survey Water Supply Paper 2375.
U.S. Soil Conservation Service. 1975. Procedure for computing sheet and rill erosion on projectareas, Tech. Release No. 51, Washington, DC.
Verstappen, H. Th. 1988. Old and new observations on coastal changes of Jakarta Bay: An exampleof trends in urban stress on coastal environments. J. Coastal Res. 4(4): 573-588.
White, S. M. 1990. The influence of tropical cyclones as soil eroding and sediment transportingevents. An example from the Philippines. Research needs and applications to reduce erosionand sedimentation in tropical steeplands, Proc. of the Fiji Symp., IAHS-AISH Publ. 192,pp. 259-269.
Williams, S. L. 1988. Assessment of anchor damage and carrying capacity of seagrass beds inFrancis and Maho Bays for green sea turtles. Biosphere Reserve Res. Rep. No. 25, VIRMC/NPS.
Wischmeier, W. H. 1976. Use and misuse of the universal soil loss equations. J. Soil WaterConserv. 31: 5-9.
Woodbury, R. O., and P. L. Weaver. 1987. The vegetation of St. John and Hassel Island. U.S.V.I.A report to the U.S. National Park.
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