Evapotranspiration from drained wetlands with different hydrologic regimes: Drivers, modeling, and storage functions

- Drainage reduces evapotranspiration (ET) from wetlands in the sub-tropics.
- ET from a heavily-drained wetland was 34% less than a more functional wetland.
- Main environmental drivers affecting wetland ET were inundation and net radiation.
- Generic models (R2 = 0.76-0.84) can predict ET under variable hydrologic regimes.
- Integrated with watershed models, wetland restoration effects on ET can be predicted.

SummaryWe tested whether the current understanding of insignificant effect of drainage on evapotranspiration (ET) in the temperate region wetlands applies to those in the subtropics. Hydro-climatic drivers causing the changes in drained wetlands were identified and used to develop a generic model to predict wetland ET. Eddy covariance (EC)-based ET measurements were made for two years at two differently drained but close by wetlands, a heavily drained wetland (SW) (97% reduced surface storage) and a more functional wetland (DW) (42% reduced storage). Annual ET for more intensively drained SW was 836 mm, 34% less than DW (1271 mm) and the difference was significant (p = 0.001). This difference was mainly due to drainage driven differences in inundation and associated effects on net radiation (Rn) and local relative humidity. Two generic daily ET models, a regression model (MSE = 0.44 mm2, R2 = 0.80) and a machine learning-based Relevance Vector Machine (RVM) model (MSE = 0.36 mm2, R2 = 0.84), were developed with the latter being more robust. The RVM model can predict changes in ET for different restoration scenarios; a 1.1 m rise in drainage level showed 7% increase ET (18 mm) at SW while the increase at DW was negligible. The additional ET, 28% of surface flow, can enhance water storage, flood protection, and climate mitigation services at SW compared to DW. More intensely drained wetlands at higher elevation should be targeted for restoration for enhanced storage through increased ET. The models developed can predict changes in ET for improved evaluation of basin-scale effects of restoration programs and climate change scenarios.