@article{lu_sun_mcnulty_amatya_2005, title={A comparison of six potential evapotranspiration methods for regional use in the southeastern United States}, volume={41}, ISSN={["1752-1688"]}, DOI={10.1111/j.1752-1688.2005.tb03759.x}, abstractNote={ABSTRACT: Potential evapotranspiration (PET) is an important index of hydrologic budgets at different spatial scales and is a critical variable for understanding regional biological processes. It is often an important variable in estimating actual evapotranspiration (AET) in rainfall‐runoff and ecosystem modeling. However, PET is defined in different ways in the literature and quantitative estimation of PET with existing mathematical formulas produces inconsistent results. The objectives of this study are to contrast six commonly used PET methods and quantify the long term annual PET across a physiographic gradient of 36 forested watersheds in the southeastern United States. Three temperature based (Thornthwaite, Hamon, and Hargreaves‐Samani) and three radiation based (Turc, Makkink, and Priestley‐Taylor) PET methods are compared. Long term water balances (precipitation, streamflow, and AET) for 36 forest dominated watersheds from 0.25 to 8213 km2 in size were estimated using associated hydrometeorological and land use databases. The study found that PET values calculated from the six methods were highly correlated (Pearson Correlation Coefficient 0.85 to 1.00). Multivariate statistical tests, however, showed that PET values from different methods were significantly different from each other. Greater differences were found among the temperature based PET methods than radiation based PET methods. In general, the Priestley‐Taylor, Turc, and Hamon methods performed better than the other PET methods. Based on the criteria of availability of input data and correlations with AET values, the Priestley‐Taylor, Turc, and Hamon methods are recommended for regional applications in the southeastern United States.}, number={3}, journal={JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION}, author={Lu, JB and Sun, G and McNulty, SG and Amatya, DM}, year={2005}, month={Jun}, pages={621–633} }
 @article{sun_mcnulty_lu_amatya_liang_kolka_2005, title={Regional annual water yield from forest lands and its response to potential deforestation across the southeastern United States}, volume={308}, ISSN={["0022-1694"]}, DOI={10.1016/j.jhydrol.2004.11.021}, abstractNote={Regional water yield at a meso-scale can be estimated as the difference between precipitation input and evapotranspiration output. Forest water yield from the southeastern US varies greatly both in space and time. Because of the hot climate and high evapotranspiration, less than half of the annual precipitation that falls on forest lands is available for stream flow in this water-rich region. Water yield is highest in the mountainous regions that receive the highest precipitation and have the lowest air temperature, and the lowest in the coastal regions that are dominated by wetlands receiving moderate rainfall but high evapotranspiration. Water resource management for both floods and droughts demands an accurate estimation of water yield from forests. Projected climate and land use changes further increase the variability of water yield in the region. The objectives of this study were to (1) develop a simple annual water yield modeling procedure by testing and calibrating a generalized global evapotranspiration model, (2) to apply the validated model to estimate regional forest water yield and to predict potential water yield response to forest removal. Hydrologic databases at a watershed-scale and a regional-scale were developed for model development, calibration, and validation. We applied the water yield model to the southern region by integrating land cover and high resolution climate databases by using a Geographic Information System (GIS). The model developed in this paper can be used to examine the spatial and temporal variability for water yield and predict the effects of climate and land cover changes at the regional scale.}, number={1-4}, journal={JOURNAL OF HYDROLOGY}, author={Sun, G and McNulty, SG and Lu, J and Amatya, DM and Liang, Y and Kolka, RK}, year={2005}, month={Jul}, pages={258–268} }
 @article{lu_sun_mcnulty_amatya_2003, title={Modeling actual evapotranspiration from forested watersheds across the Southeastern United States}, volume={39}, DOI={10.1111/j.1752-1688.2003.tb04413.x}, abstractNote={ABSTRACT:  About 50 to 80 percent of precipitation in the southeastern United States returns to the atmosphere by evapotranspiration. As evapotranspiration is a major component in the forest water balances, accurately quantifying it is critical to predicting the effects of forest management and global change on water, sediment, and nutrient yield from forested watersheds. However, direct measurement of forest evapotranspiration on a large basin or a regional scale is not possible. The objectives of this study were to develop an empirical model to estimate long‐term annual actual evapotranspiration (ART) for forested watersheds and to quantify spatial AET patterns across the southeast. A geographic information system (GIS) database including land cover, daily streamflow, and climate was developed using long term experimental and monitoring data from 39 forested watersheds across the region. Using the stepwise selection method implemented in a statistical modeling package, a long term annual AET model was constructed. The final multivariate linear model includes four independent variables—annual precipitation, watershed latitude, watershed elevation, and percentage of forest coverage. The model has an adjusted R2 of 0.794 and is sufficient to predict long term annual ART for forested watersheds across the southeastern United States. The model developed by this study may be used to examine the spatial variability of water availability, estimate annual water loss from mesoscale watersheds, and project potential water yield change due to forest cover change.}, number={4}, journal={Journal of the American Water Resources Association}, author={Lu, J. B. and Sun, G. and McNulty, S. G. and Amatya, D. M.}, year={2003}, pages={887–896} }