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A market-based mechanism for long-term groundwater management using remotely sensed data.
Safari, Safoura; Sharghi, Soroush; Kerachian, Reza; Noory, Hamideh.
Afiliação
  • Safari S; School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran. Electronic address: safoura.safari@ut.ac.ir.
  • Sharghi S; School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran. Electronic address: sharghi@ut.ac.ir.
  • Kerachian R; School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran. Electronic address: kerachian@ut.ac.ir.
  • Noory H; Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. Electronic address: hnoory@ut.ac.ir.
J Environ Manage ; 332: 117409, 2023 Apr 15.
Article em En | MEDLINE | ID: mdl-36746043
ABSTRACT
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.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Assunto principal: Água Subterrânea Tipo de estudo: Prognostic_studies Idioma: En Revista: J Environ Manage Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Assunto principal: Água Subterrânea Tipo de estudo: Prognostic_studies Idioma: En Revista: J Environ Manage Ano de publicação: 2023 Tipo de documento: Article