Research article

Optimal boundary control of a vegetation–water model with cross-diffusion

  • Published: 22 September 2026
  • To address vegetation degradation in arid and semi-arid ecosystems, existing vegetation–water models neglect the directional transport of soil water induced by root uptake (cross-diffusion) and human regulation at boundaries. This paper formulates a vegetation–water reaction–diffusion model incorporating a cross-diffusion term and a Robin-type boundary condition. First, the existence and uniqueness of weak solutions are proved with a priori estimates. Second, under bilateral pointwise constraints and an integral constraint on the cumulative boundary-regulation effort, the existence of an optimal boundary control is established via a penalty method. The adjoint system is derived using the Lagrange multiplier method, yielding first-order necessary and second-order sufficient optimality conditions, and the twice continuous Fréchet differentiability of the control-to-state mapping is demonstrated. Numerical simulations verify the effectiveness of the proposed control strategy. The framework provides theoretical support for ecological restoration in water-limited regions.

    Citation: Jiali Chai, Qimin Zhang, Panrun Li. Optimal boundary control of a vegetation–water model with cross-diffusion[J]. Electronic Research Archive, 2026, 34(11): 8026-8068. doi: 10.3934/era.2026343

    Related Papers:

  • To address vegetation degradation in arid and semi-arid ecosystems, existing vegetation–water models neglect the directional transport of soil water induced by root uptake (cross-diffusion) and human regulation at boundaries. This paper formulates a vegetation–water reaction–diffusion model incorporating a cross-diffusion term and a Robin-type boundary condition. First, the existence and uniqueness of weak solutions are proved with a priori estimates. Second, under bilateral pointwise constraints and an integral constraint on the cumulative boundary-regulation effort, the existence of an optimal boundary control is established via a penalty method. The adjoint system is derived using the Lagrange multiplier method, yielding first-order necessary and second-order sufficient optimality conditions, and the twice continuous Fréchet differentiability of the control-to-state mapping is demonstrated. Numerical simulations verify the effectiveness of the proposed control strategy. The framework provides theoretical support for ecological restoration in water-limited regions.



    加载中


    [1] S. Kefi, M. Rietkerk, C. L. Alados, Y. Pueyo, V. P. Papanastasis, A. ElAich, et al., Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems, Nature, 449 (2007), 213–217. https://doi.org/10.1038/nature06111 doi: 10.1038/nature06111
    [2] M. Rietkerk, R. Bastiaansen, S. Banerjee, J. van de Koppel, M. Baudena, A. Doelman, Evasion of tipping in complex systems through spatial pattern formation, Science, 374 (2021), eabj0359. https://doi.org/10.1126/science.abj0359 doi: 10.1126/science.abj0359
    [3] M. Scheffer, J. Bascompte, W. A. Brock, V. Brovkin, S. R. Carpenter, V. Dakos, et al., Early-warning signals for critical transitions, Nature, 461 (2009), 53–59. https://doi.org/10.1038/nature08227 doi: 10.1038/nature08227
    [4] C. A. Klausmeier, Regular and irregular patterns in semi-arid vegetation, Science, 284 (1999), 1826–1828. https://doi.org/10.1126/science.284.5421.1826 doi: 10.1126/science.284.5421.1826
    [5] T. M. Scanlon, K. K. Caylor, S. A. Levin, I. Rodriguez-Iturbe, Positive feedbacks promote power-law clustering of Kalahari vegetation, Nature, 449 (2007), 209–212. https://doi.org/10.1038/nature06060 doi: 10.1038/nature06060
    [6] E. Gilad, J. von Hardenberg, A. Provenzale, M. Shachak, E. Meron, A mathematical model of plants as ecosystem engineers, J. Theor. Biol., 244 (2007), 680–691. https://doi.org/10.1016/j.jtbi.2006.08.006 doi: 10.1016/j.jtbi.2006.08.006
    [7] G. Grifò, Vegetation patterns in the hyperbolic Klausmeier model with secondary seed dispersal, Mathematics, 11 (2023), 1084. https://doi.org/10.3390/math11051084 doi: 10.3390/math11051084
    [8] G. Consolo, G. Grifò, Turing vegetation patterns in flat arid environments with finite soil carrying capacity, Ric. Mat., 74 (2025), 235–247. https://doi.org/10.1007/s11587-023-00783-z doi: 10.1007/s11587-023-00783-z
    [9] G. Consolo, G. Grifò, Eckhaus instability of stationary patterns in hyperbolic reaction–diffusion models on large finite domains, Partial Differ. Equations Appl., 3 (2022), 57. https://doi.org/10.1007/s42985-022-00193-0 doi: 10.1007/s42985-022-00193-0
    [10] G. Grifò, C. Currò, G. Valenti, Travelling waves in dryland ecology: Continuous and discontinuous connections in a hyperbolic vegetation model, Nonlinear Dyn., 113 (2025), 15295–15319. https://doi.org/10.1007/s11071-025-10925-7 doi: 10.1007/s11071-025-10925-7
    [11] G. Grifò, A. Iuorio, F. Veerman, Far-from-equilibrium traveling pulses in sloped semiarid environments driven by autotoxicity effects, SIAM J. Appl. Math., 85 (2025), 188–209. https://doi.org/10.1137/24M1669499 doi: 10.1137/24M1669499
    [12] G. Consolo, C. Currò, G. Grifò, G. Valenti, Vegetation pattern formation and transition in dryland ecosystems with finite soil resources and inertia, Physica D, 476 (2025), 134601. https://doi.org/10.1016/j.physd.2025.134601 doi: 10.1016/j.physd.2025.134601
    [13] F. Li, R. Yang, L. Liu, Synergistic effects of feedback regulation and vegetation internal competition on vegetation patterns in semi-arid environments, Chaos Solitons Fractals, 199 (2025), 116912. https://doi.org/10.1016/j.chaos.2025.116912 doi: 10.1016/j.chaos.2025.116912
    [14] Y. Zhang, M. Zhang, E. Buhe, J. H. He, K. A. Gepreel, Effects of local grazing and cross-diffusion on vegetation-water systems and modeling for desertification prevention, Appl. Math. Model., 151 (2026), 116502. https://doi.org/10.1016/j.apm.2025.116502 doi: 10.1016/j.apm.2025.116502
    [15] G. Guo, Q. Qin, H. Cao, Y. Jia, D. Pang, Pattern formation of a spatial vegetation system with cross-diffusion and nonlocal delay, Chaos Solitons Fractals, 181 (2024), 114622. https://doi.org/10.1016/j.chaos.2024.114622 doi: 10.1016/j.chaos.2024.114622
    [16] G. Guo, S. Zhao, D. Pang, Y. Su, Stability and cross-diffusion-driven instability for a water-vegetation model with the infiltration feedback effect, Z. Angew. Math. Phys., 75 (2024), 33. https://doi.org/10.1007/s00033-023-02167-7 doi: 10.1007/s00033-023-02167-7
    [17] R. Griesse, S. Volkwein, A primal-dual active set strategy for optimal boundary control of a nonlinear reaction-diffusion system, SIAM J. Control Optim., 44 (2005), 467–494. https://doi.org/10.1137/S0363012903438696 doi: 10.1137/S0363012903438696
    [18] J. Jiang, Z. Tan, J. Zhou, Optimal boundary control of viscoelastic fluids equations, J. Math. Phys., 67 (2026), 031501. https://doi.org/10.1063/5.0311050 doi: 10.1063/5.0311050
    [19] C. Duarte-Leiva, Y. R. Linares, S. Lorca, E. Mallea-Zepeda, Optimal control problem related to the non-stationary Boussinesq system with Navier-slip boundary conditions, Math. Control Relat. Fields, (2026), In press. https://doi.org/10.3934/mcrf.2026014
    [20] J. K. Kazaku, M. M. Kahilu, J. K. K. Kasongo, D. Dochain, Dynamical analysis and observer-based boundary optimal control of a counterflow heat exchanger, IMA J. Math. Control Inf., 43 (2026), dnag006. https://doi.org/10.1093/imamci/dnag006 doi: 10.1093/imamci/dnag006
    [21] P. Schäfer Aguilar, S. Ulbrich, Convergence of numerical adjoint schemes arising from optimal boundary control problems of hyperbolic conservation laws, SIAM J. Control Optim., 64 (2026), 335–362. https://doi.org/10.1137/23M1560975 doi: 10.1137/23M1560975
    [22] P. Colli, J. Sprekels, Second-order optimality conditions for the sparse optimal control of nonviscous Cahn–Hilliard systems, ESAIM Control Optim. Calc. Var., 32 (2026), 8. https://doi.org/10.1051/cocv/2025096 doi: 10.1051/cocv/2025096
    [23] G. Q. Sun, L. F. Hou, L. Li, Z. Jin, H. Wang, Spatial dynamics of a vegetation model with uptake-diffusion feedback in an arid environment, J. Math. Biol., 85 (2022), 50. https://doi.org/10.1007/s00285-022-01825-0 doi: 10.1007/s00285-022-01825-0
    [24] M. M. Caldwell, T. E. Dawson, J. H. Richards, Hydraulic lift: Consequences of water efflux from the roots of plants, Oecologia, 113 (1998), 151–161. https://doi.org/10.1007/s004420050363 doi: 10.1007/s004420050363
    [25] I. Prieto, C. Armas, F. I. Pugnaire, Water release through plant roots: New insights into its consequences at the plant and ecosystem level, New Phytol., 193 (2012), 830–841. https://doi.org/10.1111/j.1469-8137.2011.04039.x doi: 10.1111/j.1469-8137.2011.04039.x
    [26] R. B. Neumann, Z. G. Cardon, The magnitude of hydraulic redistribution by plant roots: A review and synthesis of empirical and modeling studies, New Phytol., 194 (2012), 337–352. https://doi.org/10.1111/j.1469-8137.2012.04088.x doi: 10.1111/j.1469-8137.2012.04088.x
    [27] A. R. Kacimov, Yu. V. Obnosov, Modelling of 2-D seepage from aquifer towards stream via clogged bed: The Toth–Trefftz legacy conjugated, Adv. Water Resour., 131 (2019), 103372. https://doi.org/10.1016/j.advwatres.2019.07.002 doi: 10.1016/j.advwatres.2019.07.002
    [28] R. Sarmah, I. Sonkar, S. R. Chavan, Analytical solutions for predicting seepage in a layered ditch drainage system under Dirichlet and lagging Robin boundary conditions, Hydrol. Sci. J., 67 (2022), 1917–1940. https://doi.org/10.1080/02626667.2022.2101891 doi: 10.1080/02626667.2022.2101891
    [29] M. Chen, Z. Hu, Q. Zheng, H. M. Srivastava, Dynamics analysis of a spatiotemporal SI model, Alex. Eng. J., 74 (2023), 705–714. https://doi.org/10.1016/j.aej.2023.05.044 doi: 10.1016/j.aej.2023.05.044
    [30] Q. Liu, H. Xiang, M. Zhou, Optimal control strategies for an ecological model including infection and competition, J. Franklin Inst., 359 (2022), 3444–3465. https://doi.org/10.1016/j.jfranklin.2022.03.022 doi: 10.1016/j.jfranklin.2022.03.022
    [31] H. Xiang, B. Liu, Z. Fang, Optimal control strategies for a new ecosystem governed by reaction-diffusion equations, J. Math. Anal. Appl., 467 (2018), 270–291. https://doi.org/10.1016/j.jmaa.2018.07.001 doi: 10.1016/j.jmaa.2018.07.001
    [32] H. L. Zhang, Z. Y. Li, Investigating the impact of fractional parameters on stability and bifurcation in the time-fractional Swift–Hohenberg model, Int. J. Bifurcation Chaos, 36 (2026), 2650185. https://doi.org/10.1142/S0218127426501853 doi: 10.1142/S0218127426501853
    [33] H. L. Zhang, X. Y. Li, Z. Y. Li, Analysis and simulation of the effect of fractional parameters on dynamic behavior for a fractional-in-time three-species reaction-diffusion model, Networks Heterogen. Media, 21 (2026), 426–445. https://doi.org/10.3934/nhm.2026020 doi: 10.3934/nhm.2026020
  • Reader Comments
  • © 2026 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(227) PDF downloads(19) Cited by(0)

Article outline

Figures and Tables

Figures(8)  /  Tables(4)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog