4.7 Article

Optimal control solutions to sodic soil reclamation

Journal

ADVANCES IN WATER RESOURCES
Volume 91, Issue -, Pages 37-45

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.advwatres.2016.02.014

Keywords

Sodicity; Reclamation; Salinity; Optimal control; Irrigation; Rehabilitation; Amelioration

Funding

  1. BARD, United States-Israel Binational Agricultural Research and Development Fund
  2. Vaadia-BARD Postdoctoral Fellowship Award [FI-517-14]
  3. NSF [CBET 1033467, EAR 1331846, EAR 1316258, FESD 1338694]
  4. US DOE through the Office of Biological and Environmental Research, Terrestrial Carbon Processes program [de-sc0006967]
  5. Agriculture and Food Research Initiative from USDA National Institute of Food and Agriculture [2011-67003-30222]
  6. USDA Agricultural Research Service [58-6408-3-027]
  7. Directorate For Geosciences
  8. Division Of Earth Sciences [1338694, 1331846] Funding Source: National Science Foundation
  9. NIFA [2011-67003-30222, 579719] Funding Source: Federal RePORTER

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We study the reclamation process of a sodic soil by irrigation with water amended with calcium cations. In order to explore the entire range of time-dependent strategies, this task is framed as an optimal control problem, where the amendment rate is the control and the total rehabilitation time is the quantity to be minimized. We use a minimalist model of vertically averaged soil salinity and sodicity, in which the main feedback controlling the dynamics is the nonlinear coupling of soil water and exchange complex, given by the Gapon equation. We show that the optimal solution is a bang-bang control strategy, where the amendment rate is discontinuously switched along the process from a maximum value to zero. The solution enables a reduction in remediation time of about 50%, compared with the continuous use of good-quality irrigation water. Because of its general structure, the bang-bang solution is also shown to work for the reclamation of other soil conditions, such as saline-sodic soils. The novelty in our modeling approach is the capability of searching the entire strategy space for optimal time-dependent protocols. The optimal solutions found for the minimalist model can be then fine-tuned by experiments and numerical simulations, applicable to realistic conditions that include spatial variability and heterogeneities. (C) 2016 Elsevier Ltd. All rights reserved.

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