Testing DRAINMOD-FOREST for predicting evapotranspiration in a mid-rotation pine plantation

Abstract

a b s t r a c tEvapotranspiration (ET) is a key component of the hydrologic cycle in terrestrial ecosystems and accurate description of ET processes is essential for developing reliable ecohydrological models. This study investigated the accuracy of ET prediction by the DRAINMOD-FOREST after its calibration/validation for predicting commonly measured hydrological variables. The model was tested by conducting an eight year simulation of drainage and shallow groundwater dynamics in a managed mid-rotation loblolly pine (Pinus taeda L.) plantation located in the coastal plain of North Carolina, USA. Modeled daily ET rates were compared to those measured in the field using the eddy covariance technique. In addition, the wavelet transform and coherence analysis were used to compare ET predictions and measurements on the time-frequency domain. Results showed that DRAINMOD-FOREST accurately predicted annual and monthly ET after a successful calibration and validation using measured drainage rates and water table depth. The model under predicted ET on an annual basis by 2%, while the Nash-Sutcliffe coefficient of model predictions on a monthly basis was 0.78. Results from wavelet transform and coherence analysis demonstrated that the model reasonably captured the high power spectra of ET at an annual scale with significantly high model-data coherency. These results suggested that the calibrated DRAINMOD-FOREST collectively captured key factors and mechanisms controlling ET dynamics in the drained pine plantation. However, the global power spectrum revealed that the model over predicted the power spectrum of ET at an annual scale, suggesting the model may have under predicted canopy conductance during nongrowing seasons. In addition, this study also suggested that DRAINMOD-FOREST did not properly capture the seasonal dynamics of ET under extreme drought conditions with deeper water table depths. These results suggested further refinement to parameters, particularly vegetation related, and structures of DRAINMOD-FOREST to achieve better agreement between ET predictions and measurements in the time-frequency domain.Published by Elsevier B.V.

Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States

“…These wetlands were selected with the following considerations. AR (Miao, 2013) and LP Sun et al, 2010;Tian et al, 2015) are located in the lower coastal plain area of North Carolina within 100 km of one another, representing lower coastal plain forested wetlands with a similar climate and topography but different management conditions. AR is a natural coastal bottomland hardwood wetland with no tidal influence , while wetland LP is intensively managed by the forest industry for timber production (Manoli et al, 2016;Noormets et al, 2010; al., 2010).…”

“…To be consistent and reduce uncertainty of PET estimates, 1.2 was used for all five wetlands in this study. Artificially managed lower coastal plain forested wetland Sun et al (2010), Tian et al (2012Tian et al ( , 2015, Diggs (2004) Pyzoha et al (2008), Sun et al (2006) …”

“…Compared to a lumped (e.g., DRAINMOD-FOREST, Tian et al, 2015) or distributed parameter model (e.g., MIKE SHE, Lu et al, 2009), the empirical hydrological models developed in this study are simple. However, according to the model performance and results analysis in this study ( Overall, the empirical models developed from this study performed well at the site level, and can be incorporated into landscape and larger-scale biogeochemical models.…”

Response to Anonymous Referee #1

“…These wetlands were selected with the following considerations. AR (Miao, 2013) and LP Sun et al, 2010;Tian et al, 2015) are located in the lower coastal plain area of North Carolina within 62 miles of one another, representing lower coastal plain forested wetlands with similar climate and topography, but different management conditions. AR is a natural coastal bottomland hardwoods wetland with no tidal influence 95 , while wetland LP is intensively managed by the forest industry for timber production (Manoli et al, 2016;Noormets et al, 2010;Sun et al, 2010).…”

Forest Management Challenges for Sustaining Water Resources in the Anthropocene

“…Sophisticated simulation models have been widely used in forest ecohydrological research and watershed management since the 1990s when personal computers became available [41][42][43][44]. However, the ability to predict the impacts of extreme events presents considerable challenges to existing models [45].…”