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Canopy Rainfall Interception Measured over Ten Years in a Coastal Plain Loblolly Pine (Pinus taeda L.) Plantation
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: Transactions of the ASABE. 59(2): 601-610. (doi: 10.13031/trans.59.11101) @2016
Authors: Michael J. Gavazzi, Ge Sun, Steven G. McNulty, Emrys A. Treasure, Maxwell G. Wightman
Keywords: Canopy interception, Evapotranspiration, Loblolly pine, Pinus taeda, Throughfall.
Abstract. The area of planted pine in the southern U.S. is predicted to increase by over 70% by 2060, potentially altering the natural hydrologic cycle and water balance at multiple scales. To better account for potential shifts in water yield, land managers and resource planners must accurately quantify water budgets from the stand to the regional scale. The amount of precipitation as rainfall intercepted by forest canopies is an important component of evapotranspiration in forested ecosystems, yet there is little information about intra- and inter-annual canopy interception variability in southern pine plantations. To address this knowledge gap, canopy rainfall interception was measured between 2005 and 2014 in a North Carolina coastal plain loblolly pine ( L.) plantation to quantify the range of annual and seasonal variability in interception rates (IRs) as influenced by stand thinning and natural variation in rainfall rates and intensities. Over the study period, biweekly measured canopy IRs averaged 19% across all years, with a range of 14% to 23%. However, at the annual scale, IRs averaged 12% and ranged from 2% to 17%. Thinning resulted in a 5% decrease in rainfall interception, but IRs quickly returned to pre-thin levels. Across years, the amount of annual rainfall intercepted by the canopy averaged 15% of total evapotranspiration, with a range of 2% to 24%. The decade-long data indicate that inter-annual variability of canopy interception is higher than reported in short-term studies. Local and regional hydrological models must describe the variability of canopy interception to accurately predict the hydrologic impacts of forest management and climate change.
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