Soil moisture drydown patterns encode signatures of plant water use. Previous characterizations of the drydown patterns assume a static linear relationship between water-limited transpiration and available moisture. However, ecohydrological studies show that plants exhibit a spectrum of responses to water availability, suggesting that soil moisture loss functions may be nonlinear. To represent these dynamics, we introduce a nonlinearity parameter to the loss function. Our analysis shows that the nonlinear loss model improves the characterization of the satellite-observed soil moisture drydowns. Globally, functional responses of drydowns are dominated by convex nonlinearity, showing greater declines in water use in dry soils than the linear loss function predicts. We find distinct degrees of nonlinearity among different vegetation types; areas with non-woody vegetation more frequently exhibit a concave nonlinearity, the signature of aggressive water-use strategies. We propose the nonlinear loss function as continuous and dynamic representations of plant water-use strategies under changing water availability.

We evaluate the effect of surface wind stress on drone-based thermal surface water velocity measurements of tidal flow in an estuary relative to in-channel flow velocity measurements. Drones are a useful platform for capturing imagery of surface flows, with the ability to support many cameras and sensors. Drone-mounted thermal infrared microbolometer cameras can retrieve subtle temperature patterns that naturally occur in many surface flows. These thermal patterns are used as signals for pattern-tracking algorithms to produce distributed measurements of velocity across the observed water surface. The effect of wind on remote surface velocity measurements is relatively unstudied, and herein we present results demonstrating the impact of wind on surface velocity measurements. This study demonstrates the feasibility of drone-based thermal velocimetry in an estuarine channel, while collecting water velocities with an acoustic current profiler deployed on the channel bottom within the microbolometer’s field of view. Drone flights were conducted at Carpinteria Salt Marsh Reserve (California, USA). Wind speed and direction significantly increased the deviation of drone-based surface velocimetry measurements relative to in-channel current profiler measured velocities. Drone-based velocity measurements deviated more from in-channel near-surface measurements when the parallel wind stress direction was opposite the tidal flow, while drone-based velocities were in closer agreement with in-channel velocities when the parallel wind stress and tidal flow directions were the same. This experiment demonstrates the feasibility of drone-based thermal surface velocity measurements in an intertidal setting, while documenting the limitations of surface-based inferences of at-depth flows due to wind stress.