This year, Elham Rouholahnejad Freund published a paper on how spatial heterogeneity and lateral moisture redistribution affect average evapotranspiration rates. We decided to ask her a couple of questions.
Q: Where are you from, where are you based, and what are your research interests?
I grew up in Iran, Isfahan and moved to Switzerland in 2009 to do a PhD at ETH Zurich. I am a Civil Engineer by background and studied Environmental Engineering and Environmental Science in my Master and PhD program. I finished my PhD at ETH Zurich in 2014 and did a postdoc at the department of Environmental Systems Science at ETH. I had been awarded a 2-year mobility grant by Swiss National Science Foundation (SNSF) to pursue my research in groundwater- soil moisture- atmosphere interactions. I am currently in Gent University and will move to Princeton for the second half of my scholarship.
My research focuses on interactions between water in the lithosphere and the overlying atmosphere, through which evapotranspiration processes balance latent and sensible heat fluxes and hence control the near-surface air temperature. These land–atmosphere feedbacks have implications for extreme events such as droughts and heatwaves. Our understanding of the amount of water on the surface of the planet Earth, the water that is stored underground and in the air, their interaction with atmosphere, and their evolution under expected climate change remains limited and our estimates of these processes’ rates often involve large uncertainties. I have focused much of my work on understanding distribution of water at continental and global scales, its evolution in a changing climate, its flow mechanics in a heterogeneous landscape, and its interaction with the atmosphere through evapotranspiration processes.
Q: What is the take home message of your paper?
Our analysis reveals that large-scale Earth System Models (ESMs) that overlook heterogeneity and lateral transfer of water encounter biases in their evapotranspiration estimates. We use a conceptual approach to show in any non-linear relationship, function of averages is not equal to average of functions (Fig. 1). We back up this claim with mathematical proof and demonstrate that averaging over spatial or temporal scales results in overestimation bias. We show that averaging over heterogeneous precipitation and potential evapotranspiration leads to overestimation in evapotranspiration estimates. We use the same analogy to demonstrate that lateral transfer within and between model columns alters the average evapotranspiration (Fig 2.).
Q: You state that your work can guide exploring the effects of spatial averaging and lateral transport in more detailed modeling. Are you planning to look into this?
In this paper we conceptually and mathematically showed that lateral transfer and heterogeneity matter in land-atmospheric feedbacks. The obvious next step is to include these processes in Erath System Models. However, the task is not straightforward and is an active field of research. There are many research groups around the world studying how to optimally include lateral transfer and heterogeneity in ESMs to minimize high computational cost. One possibility is to identify where around the globe these processes are most important and mask them for further detail work. Besides, assimilating global satellite observations (e.g. GRACE) will further constrain the land surface models. Both mentioned approaches are undergoing.
Q: The effects of spatial averaging are probably relevant for many other aspects of hydrology. Is there any opportunity to use your approach to understanding the effects on other processes (e.g. infiltration, runoff generation, etc)?
The averaging bias concept is general and expandable to any convex (or concave) function. In any nonlinear process (e.g. discharge-storage relation), averaging over spatial and potentially temporal scale leads to a bias. The resulting heterogeneity bias depends on how strongly curved the function is and how widely its input are scattered.
Q: You decided to use “simple thought experiments” instead of “detailed modeling”. Is this an approach you’d like to see more often in hydrology?
Hydrology is an inexact science. Given the heterogeneity that involves the Earth’s surface and subsurface, the chances that we could capture the physics of all the processes involved is slim. Even if all the processes are represented adequately, the data that could be collected at the scale that these processes are happening are limited. All the so-called physically based and distributed models are simplified models of reality and to some extent lumped. The detailed models are useful tools for scenario testing and running experiments but would not necessarily eliminate the need for using conceptual models.
[END] – Interviewed by Wouter Berghuijs
This interview is part of the new YHS Research “Hylights” series to showcase interesting and outstanding work by early career scientists. Selection criteria are not set in stone, but reasons to select work can include e.g. novelty and relevance of findings, fun of reading, unique collaborations, media coverage and generated controversy. Selected work will be provided with a short layman summary, and a short written or video interview with the (first) author(s). Tips can be sent to young firstname.lastname@example.org or email@example.com.
Reference to paper: Rouholahnejad Freund, E. and Kirchner, J. W.: A Budyko framework for estimating how spatial heterogeneity and lateral moisture redistribution affect average evapotranspiration rates as seen from the atmosphere, Hydrol. Earth Syst. Sci., 21, 217-233, doi:10.5194/hess-21-217-2017, 2017.