In this presentation we demonstrate the use of NASA's new Soil Moisture Active Passive passive microwave observations, in situ precipitation data and a simple water balance model to directly estimate evaporation. Similar as done by Brocca et al. (2013) quantitative estimates of evaporation are obtained from soil moisture data directly, by solving the water balance equation for evaporation and estimating drainage using conditional sampling of soil moisture (Salvucci, 2001). Evaporation estimates are compared to in situ measurements from lysimeters and eddy covariance stations over three different locations.
This approach enables the investigation of dynamics in evaporation after rainfall events. The timing of the transition between the different stages of evaporation is assessed, more precisely the transition from stage 1 to stage 2 evaporation: The first stage is the energy limited stage, where the evaporation equals the atmospheric demand and no water stress exists. Stage two is the falling rate stage, where evaporation is limited by soil moisture diffusion in the soil. With the start of stage 2 evaporation decreases due to soil moisture deficits. When these conditions persist, this leads to an increase in sensible heat flux and subsequently air temperatures, water stress in plants and can over time lead to droughts and heat waves.
By estimating the duration of stage 1 and stage 2 evaporation during continuous drying events in an inter-storm period for a certain location, feedbacks between evaporation and the extreme conditions of droughts and heat waves can be investigated. The number of days where stage 2 evaporation occurs in 2015 is compared to earlier years. It is expected that, in areas which were affected by heat waves and droughts, more days with stage 2 evaporation occur. In addition, the evaporation is compared to air temperature to assess the interaction between evaporation and temperature. The results of this study help understand the links between the water, energy and carbon cycle. Furthermore, it can provide additional information for risk management in predicting droughts. When applied to a smaller scale of 500 m to 3 km, using e.g. soil moisture data from SMAP radar or Sentinel-1, it can provide crucial information in preventing agricultural losses.
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Miralles, D.G., Teuling, A.J., van Heerwaarden, C.C., Vilà-Guerau de Arellano, J., 2014. Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nat. Geosci. 7, 345–349. doi:10.1038/ngeo2141 Salvucci, G.D., 2001. Estimating the moisture dependence of root zone water loss using conditionally averaged precipitation. Water Resour. Res. 37, 1357–1365. doi:10.1029/2000WR900336
Seneviratne, S.I., Lehner, I., Gurtz, J., Teuling, A.J., Lang, H., Moser, U., Grebner, D., Menzel, L., Schroff, K., Vitvar, T., Zappa, M., 2012. Swiss prealpine Rietholzbach research catchment and lysimeter: 32 year time series and 2003 drought event. Water Resour. Res. 48, W06526. doi:10.1029/2011WR011749
Teuling, A.J., Van Loon, A.F., Seneviratne, S.I., Lehner, I., Aubinet, M., Heinesch, B., Bernhofer, C., Grünwald, T., Prasse, H., Spank, U., 2013. Evapotranspiration amplifies European summer drought. Geophys. Res. Lett. 40, 2071–2075. doi:10.1002/grl.50495