We are delighted to share that Ms. Safoura Safari has been accepted to the Department of Civil and Environmental Engineering and will be joining us in summer 2023. Safoura holds a B.Sc. in Civil Engineering from the Isfahan University of Technology and a M.Sc. in Civil Engineering - Water Resources Engineering and Management from the University of Tehran, both in Iran. Her masters thesis integrated physical modeling and socio-economic tools to model and optimize a groundwater market to address water scarcity and subsidence, and this work has been recently published in the Journal of Environmental Management 1. We are delighted to welcome her to Rice!

Safari, S., Sharghi, S., Kerachian, R. & Noory, H. A Market-Based Mechanism for Long-Term Groundwater Management Using Remotely Sensed Data. Journal of Environmental Management 117409 (2023).
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Groundwater markets improve the agricultural economy by transferring water entitlements from low-efficient users to high-efficient ones to maximize productivity. Aiming at developing an efficient groundwater market, the environmental effects of the market mechanism should be assessed, and a reliable method for monitoring water consumption needs to be employed. Toward this end, this paper proposes three annual smart groundwater market mechanisms to maximize water net benefits, minimize groundwater withdrawal, and precisely measure water consumption in agricultural fields. To guarantee the aquifer’s safe yield in each mechanism, a groundwater simulation model (i.e., Groundwater Modeling System (GMS)) is used to control groundwater table drawdown at the end of the planning horizon. In addition, the fields’ evapotranspiration (ET) is estimated using Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapo Transpiration at high Resolution with Internalized Calibration (METRIC) algorithm to measure the net groundwater consumption during the market. In this regard, we evaluated the algorithms’ performances using observed data from a local lysimeter. They are applied to the Nough plain in Iran to assess the effectiveness of the proposed market framework. The findings illustrate their efficiency in recovering approximately 80% (23.33 million cubic meters (MCM)) of groundwater loss due to overexploitation in the study area and increasing the users’ annual benefits by 10.6% compared to the non-market condition. In addition, results imply that the METRIC model approximates daily crop ET with a higher accuracy level than the SEBAL model with RMSE, MAE, and Percentage Error of 0.37 mm/day, 0.32 mm/day, and 14.92%, respectively. This research revealed that the proposed market framework is a powerful tool for reallocating water entitlements and increasing water productivity in arid and semi-arid regions.

  title = {A Market-Based Mechanism for Long-Term Groundwater Management Using Remotely Sensed Data},
  author = {Safari, Safoura and Sharghi, Soroush and Kerachian, Reza and Noory, Hamideh},
  date = {2023-04-15},
  journaltitle = {Journal of Environmental Management},
  shortjournal = {Journal of Environmental Management},
  volume = {332},
  pages = {117409},
  issn = {0301-4797},
  doi = {10.1016/j.jenvman.2023.117409},
  url = {https://www.sciencedirect.com/science/article/pii/S0301479723001974},
  urldate = {2023-02-09}