S. BHALAI – Landslide susceptibility of Portland, Jamaica
Figure 4. Elaborate gabion works installed at Spring Hill, Buff Bay River valley. Landslide (background) had obliterated the road. The source area still having portions of the slipped mass is clearly visible. This structure is a combination of step-gabion baskets and mattress gabion baskets (partially seen at base of photograph). Note the large drainage pipe at the centre of the photo. Poor drainage is a major trigger of slope failures throughout Portland. Remediation measures such as this are quite costly [R. Green, Feb. 2007]
It is therefore necessary to be able to predict the landslide susceptibility, that is, the probability of the occurrence of potentially damaging landslides across the parish in order to reduce disaster-related costs and proactively save lives. Many techniques are currently available for predicting landslide susceptibility employing direct (landslide inventory approach) and indirect (heuristic, statistical and deterministic approaches) methods (Hansen, 1984; Soeters and van Westen, 1996). For Portland a combination of both methods was employed. The direct method involves surveyors indentifying and documenting past and present landslides, and making interpretations of the potential for failure. Indirect methods follow where landslide distribution obtained by the surveyor is analyzed statistically using factors that can cause landslides, such as, elevation, slope gradient, slope aspect, lithology and geological faults, to determine weightings or the respective role of each factor.
Bivariate statistical analysis, introduced by Brabb et al. (1972), is the approach of choice. The landslide distribution map is simply combined with individual maps of elevation, slope gradient, slope aspect, lithology and geological faults. This comparison shows numerically the correlation of landslides with the causative factors. This is further used to compute the weight or level of susceptibility (Susceptibility index) for each factor. This index is applied to the maps of each causative factor as a weighting value, and these spatial coverages are simply combined to generate the final model.
Figure 5. Fig. 5. Landslide at Friday, south of Ginger House, Rio Grande valley. Landslide (centre) has reduced the road to narrow single lane. The landslide is very active, continually retreating over the last 10 years. It continues to fail as the unstable colluvial material slips from the steep slope above in the zone of unstable material delineated by secondary shrubbery. Colluvium consists of debris of volcanic rock and limestone originating from across the river (behind photographer). Note that the colluvium overlies the shale which shows distinct bedding in the river bank (lower left-hand corner). Beds dip towards the river encouraging planar failure in the colluvium. This particular landslide has made several news reports as the locality is hazardous to road users. The latest was 2009 when a vehicle toppled over and became lodged just below the roadway. [S. Bhalai, June 2009]
This final model is classified into zones of increasing landslide susceptibility. Guidelines defining each susceptibility zones are created to support the model and increase its usefulness to planners, engineers, developers and citizens who may have an interest in understanding the landslide propensity of the parish.
2. PHYSIOGRAPHY AND GEOLOGY
The parish of Portland covers 814.5 km2, or approximately 7% of the area of Jamaica, and includes the northern flank of the Blue Mountains. The parish is dominantly mountainous with low hills on the northern edge and the steeper, higher slopes of the Blue Mountains on the southern extent (Figure 6). Blue Mountain Peak, the highest peak in the range, culminates at 2256 metres above sea level. There are also the John Crow Mountains, a low cuesta in the east. Surficial drainage is dominant in Portland; the parish hosts five watersheds having large rivers, such as, the Rio Grande, Buff Bay, Swift, and Spanish Rivers. These are rarely dry, because their headwaters are constantly fed by rainfall in the mountains.