Storm water damage risk assessment along the South Carolina Heritage Trail

This study was conducted to better predict and assess damage to high-value small-spatial scale landscapes from storm water. Storm water damage in the form of rill formation across the South Carolina Botanic Gardens (SCBG) Natural Heritage Garden Trail has been modelled as a function of contributing area using D8 and D-infinity flow direction algorithms on a preprocessed LiDAR-derived elevation raster. D8 and D-infinity algorithms were also applied over a set of stochastic Monte Carlo simulations (n=1,000) representing elevation error. The contributing area was calculated using each of the four methods for each 5'x5' cell along the trail. The output was then filtered using a moving kernel calculating a value for each cell according to the maximum value within specified radii of neighboring cells. Observed storm water damage along the trail was geo-referenced as a validation dataset for the model. The receiver operating characteristic (ROC) curves of the three contributing area estimates filtered at various filter radii were graphed by comparison with geo-referenced rills. Results indicate that high resolution LiDAR elevation data can be used to localize storm water damage risks. The D-8 and D-infinity algorithms performed equivalently, and the Monte Carlo procedure improved the performance of both. These models should prove effective in predicting and preventing damage in high-value public landscapes.