Long‐term hydro‐meteorology and water quality data from low‐gradient catchments of varying scales on the Santee experimental Forest, South Carolina

Abstract

AbstractThe forest landscape of the Southeastern Atlantic coastal plain of the United States is experiencing increased threats from extreme precipitation events, tropical storms, flooding, droughts, and growing urbanization impacting on vegetation, road infrastructure, water extraction and other related ecosystem processes (e.g., storm runoff, nutrient and carbon cycling) and functions (e.g., flood protection, aquatic habitat). We describe ongoing hydro‐meteorologic monitoring on two first—(1.6 km2 each), the second—(5 km2), and the third—(52.5 km2) order catchments. The catchments are located on the Santee Experimental Forest at the headwaters of the Cooper River that drains into Charleston Harbour, South Carolina. Monitoring started in 1946, with a gap between 1982 and 1989, includes precipitation, weather, streamflow, water table, and water quality (anions, cations, and physical parameters) at varying temporal scales. The catchments are forest ecosystems dominated by loblolly (Pinus taeda) and longleaf pine (Pinus palustris) (LLP) mixed hardwood stands on the uplands and bottomland hardwoods on well‐drained to poorly‐drained soils characteristic of the low‐gradient Atlantic Coastal Plain. These data support multiple field and modelling studies, ranging from water and carbon budgets to hydrologic and biogeochemical processes to effects of microtopography and extreme climate on hydrology and water quality of these coastal catchments withstands regenerated since Hurricane Hugo (1989). One significant finding from the long‐term data was a reversal of the pre‐Hugo flow pattern between the paired watersheds 3 years after Hugo. This reversal persisted for 10 years and was attributed to change in forest vegetation due to hurricane damage to older pine and larger hardwood stands followed by delayed regeneration before full forest recovery. These publicly available data serve as a reference within a rapidly developing landscape and also for addressing potential impacts of extreme climate and forest disturbance on ecohydrology, biogeochemistry, habitat, water supply and infrastructure using validated models and tools.