WIT Webinar: Fast and Accurate Estimation of Evapotranspiration for Smart Agriculture.

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Speaker: Weiyu Li,

PhD Candidate, Energy Science and Engineering, Stanford University.

Time: 10:00am - 11:00am PKT

Date: June 14, 2023

Moderator: Dr. Jawairia Ashfaq Ahmad, WIT

Details and registration: MLSH - Seminar Series 2022-23 | Center of Water Informatics and Technology (lums.edu.pk)

 

Abstract: The ability to quantify evapotranspiration (ET) is crucial for smart agriculture and sustainable groundwater management. Efficient ET estimation strategies often rely on the vertical-flow assumption to assimilate data from soil-moisture sensors. While adequate in some large-scale applications, this assumption fails when the horizontal component of the local flow velocity is not negligible due to, for example, soil heterogeneity or drip irrigation. We present novel implementations of the ensemble Kalman filter (EnKF) and the maximum likelihood estimation (MLE), which enable us to infer spatially varying ET rates and root water uptake profiles from soil-moisture measurements. While the standard versions of EnKF and MLE update the predicted soil moisture prior to computing ET, ours treat the ET sink term in Richards' equation as an updatable observable. We test the prediction accuracy and computational efficiency of our methods in a setting representative of drip irrigation. Our strategies accurately estimate the total ET rates and root-uptake profiles and do so up to two-orders of magnitude faster than the standard EnKF.

About the Speaker:

Weiyu Li has received her PhD in Energy Science and Engineering from Stanford University. Her research focuses on data-assimilation and parameter estimation in environmental applications, aiming to provide science-based estimation of evapotranspiration from soil moisture measurements and the quantification of uncertainty inherent in such estimators. Her other research interests include modeling and simulation of electrochemical transport in batteries and biomedical modeling. Prior to her doctoral studies, Weiyu Li obtained her M.Sc. degree in Mechanical and Aerospace Engineering from Princeton University. Weiyu Li is the recipient of the Siebel Scholars Award in Energy Science, class of 2023. Furthermore, she has received prestigious awards, including the Henry J. Ramey Fellowship Award for outstanding research in the Department of Energy Science and Engineering at Stanford University, as well as the Princeton University Fellowship in Natural Sciences and Engineering.

For details or queries, please contact Soban Hameed Saigol at soban.hameed@lums.edu.pk or 0332 4495057

Add to Calendar 2023-06-14 10:00:00 2023-06-14 11:00:00 WIT Webinar: Fast and Accurate Estimation of Evapotranspiration for Smart Agriculture. Speaker: Weiyu Li,PhD Candidate, Energy Science and Engineering, Stanford University.Time: 10:00am - 11:00am PKTDate: June 14, 2023Moderator: Dr. Jawairia Ashfaq Ahmad, WITDetails and registration: MLSH - Seminar Series 2022-23 | Center of Water Informatics and Technology (lums.edu.pk) Abstract: The ability to quantify evapotranspiration (ET) is crucial for smart agriculture and sustainable groundwater management. Efficient ET estimation strategies often rely on the vertical-flow assumption to assimilate data from soil-moisture sensors. While adequate in some large-scale applications, this assumption fails when the horizontal component of the local flow velocity is not negligible due to, for example, soil heterogeneity or drip irrigation. We present novel implementations of the ensemble Kalman filter (EnKF) and the maximum likelihood estimation (MLE), which enable us to infer spatially varying ET rates and root water uptake profiles from soil-moisture measurements. While the standard versions of EnKF and MLE update the predicted soil moisture prior to computing ET, ours treat the ET sink term in Richards' equation as an updatable observable. We test the prediction accuracy and computational efficiency of our methods in a setting representative of drip irrigation. Our strategies accurately estimate the total ET rates and root-uptake profiles and do so up to two-orders of magnitude faster than the standard EnKF.About the Speaker:Weiyu Li has received her PhD in Energy Science and Engineering from Stanford University. Her research focuses on data-assimilation and parameter estimation in environmental applications, aiming to provide science-based estimation of evapotranspiration from soil moisture measurements and the quantification of uncertainty inherent in such estimators. Her other research interests include modeling and simulation of electrochemical transport in batteries and biomedical modeling. Prior to her doctoral studies, Weiyu Li obtained her M.Sc. degree in Mechanical and Aerospace Engineering from Princeton University. Weiyu Li is the recipient of the Siebel Scholars Award in Energy Science, class of 2023. Furthermore, she has received prestigious awards, including the Henry J. Ramey Fellowship Award for outstanding research in the Department of Energy Science and Engineering at Stanford University, as well as the Princeton University Fellowship in Natural Sciences and Engineering.For details or queries, please contact Soban Hameed Saigol at soban.hameed@lums.edu.pk or 0332 4495057 LUMS Drupal 8 adil.sarwar@lums.edu.pk Asia/Karachi public

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