Aerodynamic canopy height (ha) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface‐atmosphere coupling. However, methods to estimate ha from data are limited. This synthesis evaluates the applicability and robustness of the calculation of ha from eddy covariance momentum‐flux data. At 69 forest sites, annual ha robustly predicted site‐to‐site and year‐to‐year differences in canopy heights (R2 = 0.88, 111 site‐years). At 23 cropland/grassland sites, weekly ha successfully captured the dynamics of vegetation canopies over growing seasons (R2 > 0.70 in 74 site‐years). Our results demonstrate the potential of flux‐derived ha determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large‐scale and time‐varying ha derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure.

Coastal ecosystems are vulnerable to climate change and have been identified as sources of uncertainty in the global carbon budget. Here we introduce a recently established mesonet of eddy covariance towers in South Carolina and describe the sensor arrays and data workflow used to produce three site-years of flux observations in coastal ecosystems. The tower sites represent tidal salt marsh (US-HB1), mature longleaf pine forest (US-HB2), and longleaf pine restoration (replanted clearcut; US-HB3). Coastal ecosystems remain less represented in climate studies despite their potential to sequester large amounts of carbon. Our goal in publishing this open access dataset is to contribute observations in understudied coastal ecosystems to facilitate synthesis and modeling analyses that advance carbon cycle science.

This paper examines data from 18 USGS gauges in the lower Pee Dee Basin in an effort to explain the behavior of the flooding following Hurricane Florence (2018) in Georgetown County, South Carolina. Despite record or near-record flooding in all the tributaries to the Winyah Bay estuary, water levels near the city of Georgetown were well below predicted heights. Floodplain storage in the lower Great Pee Dee, Lynches, and Little Pee Dee River valleys stored over 1.2 million acre-feet of floodwaters, delaying peak stage near Bucksport for five days and reducing peak flow into the Winyah Bay tidal river/estuary system by nearly 50%. An unknown amount of flow from the Winyah Bay tidal river/estuary system flowed through the Atlantic Intracoastal Water Way to Little River rather than through Winyah Bay. The resulting freshwater flow to Winyah Bay only moved the point of tidal stagnation (where upstream tidal flow balances downstream freshwater flow) to near Georgetown. Since the city of Georgetown was near the point of stagnation, water level there was driven by ocean tidal height rather than river flood stage. The lack of discharge data from the tidal rivers in Georgetown County prevents evaluation of the importance of each of these factors and will limit efforts to make quantitative predictions of future flooding in the county.

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Over past years, extreme tropical storm events along the North and South Carolina coasts—and subsequent river flooding—have warranted the need for a better understanding of the hydrologic response to these events to protect life, property, businesses, and natural and cultural resources. Our focus in this study is the Pee Dee and Waccamaw River systems, which ultimately flow into Winyah Bay near Georgetown, South Carolina. River flows, coupled with the tidal nature of these freshwater systems, are complex and difficult to predict. The objective of the work is to analyze publicly available data from gauging stations along those river system as measured during Hurricanes Matthew and Florence and Tropical Storm Bertha—three uniquely different storm systems that produced varying rainfall depth, duration, and intensity across the Pee Dee Basin. The most important factor in tidal river analysis is the location of the stagnation point , where downstream river flow exactly balances upstream tidal flow. River flow only controls water level upstream of a tidal stagnation point, while ocean tide controls the water level downstream of a tidal stagnation point. An analysis of major flooding following Hurricanes Matthew, Florence, and Tropical Storm Bertha was used to determine the river flows associated with tidal stagnation at each stream gauge active during these storms. A major limitation of the analysis was a lack of flow data for the tidal channels in Georgetown County, which resulted in uncertainty in the flow associated with stagnation and uncertainty in the role played by each of the creeks that connect the Pee Dee and Waccamaw Rivers. Ignorance of the roles of these creeks most limited understanding of the relative importance of Pee Dee and Waccamaw flow to cause stagnation near Pawleys Island and Hagley gauges on the Waccamaw River and the Socastee gauge on the Atlantic Intracoastal Waterway.

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