Technical Note: A comparison of model and empirical measures of catchment-scale effective energy and mass transfer
- 1Department of Soil, Water and Environmental Science, University of Arizona, Tucson, AZ, USA
- 2Department of Hydrology and Water Resources, University of Arizona, Tucson, AZ, USA
Abstract. Recent work suggests that a coupled effective energy and mass transfer (EEMT) term, which includes the energy associated with effective precipitation and primary production, may serve as a robust prediction parameter of critical zone structure and function. However, the models used to estimate EEMT have been solely based on long-term climatological data with little validation using direct empirical measures of energy, water, and carbon balances. Here we compare catchment-scale EEMT estimates generated using two distinct approaches: (1) EEMT modeled using the established methodology based on estimates of monthly effective precipitation and net primary production derived from climatological data, and (2) empirical catchment-scale EEMT estimated using data from 86 catchments of the Model Parameter Estimation Experiment (MOPEX) and MOD17A3 annual net primary production (NPP) product derived from Moderate Resolution Imaging Spectroradiometer (MODIS). Results indicated positive and significant linear correspondence (R2 = 0.75; P < 0.001) between model and empirical measures with an average root mean square error (RMSE) of 4.86 MJ m−2 yr−1. Modeled EEMT values were consistently greater than empirical measures of EEMT. Empirical catchment estimates of the energy associated with effective precipitation (EPPT) were calculated using a mass balance approach that accounts for water losses to quick surface runoff not accounted for in the climatologically modeled EPPT. Similarly, local controls on primary production such as solar radiation and nutrient limitation were not explicitly included in the climatologically based estimates of energy associated with primary production (EBIO), whereas these were captured in the remotely sensed MODIS NPP data. These differences likely explain the greater estimate of modeled EEMT relative to the empirical measures. There was significant positive correlation between catchment aridity and the fraction of EEMT partitioned into EBIO (FBIO), with an increase in FBIO as a fraction of the total as aridity increases and percentage of catchment woody plant cover decreases. In summary, the data indicated strong correspondence between model and empirical measures of EEMT with limited bias that agree well with other empirical measures of catchment energy and water partitioning and plant cover.