TITLE:
Application of LiDAR Data for Hydrologic Assessments of Low-Gradient Coastal Watershed Drainage Characteristics
AUTHORS:
Devendra Amatya, Carl Trettin, Sudhanshu Panda, Herbert Ssegane
KEYWORDS:
Santee Experimental Forest; Digital Elevation Models (DEM); Drainage Area; Drainage Network; Low-Gradient Coastal Plain (LCP)
JOURNAL NAME:
Journal of Geographic Information System,
Vol.5 No.2,
April
25,
2013
ABSTRACT: Documenting the recovery of hydrologic functions following perturbations of a landscape/watershed is important to address issues associated with land use change and ecosystem restoration. High resolution LiDAR data for the USDAForestServiceSanteeExperimentalForestin coastalSouth Carolina,USAwas used to delineate the remnant historical water management structures within the watersheds supporting bottomland hardwood forests that are typical of the re- gion. Hydrologic functions were altered during the early1700’s agricultural use period for rice cultivation, with changes to detention storage, impoundments, and runoff routing. Since late1800’s, the land was left to revert to forests, without direct intervention. The resultant bottomlands, while typical in terms of vegetative structure and composition, still have altered hydrologic pathways and functions due to the historical land use. Furthermore, an accurate estimate of the watershed drainage area (DA) contributing to stream flow is critical for reliable estimates of peak flow rate, runoff depth and coefficient, as well as water and chemical balance. Peak flow rate, a parameter widely used in design of channels and cross drainage structures, is calculated as a function of the DA and other parameters. However, in contrast with the upland watersheds, currently available topographic maps and digital elevation models (DEMs) used to estimate the DA are not adequate for flat, low-gradient Coastal Plain (LCP) landscape. In this paper we explore a case study of a 3rd order watershed (equivalent to 14-digit hydrologic unit code (HUC)) at headwaters of east branch of Cooper River draining to Charleston Harbor, SC to assess the drainage area and corresponding mean annual runoff coefficient based on various DEMs including LiDAR data. These analyses demonstrate a need for application of LiDAR-based DEMs together with field verification to improve the basis for assessments of hydrology, watershed drainage characteristics, and modeling in the LCP.