IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i24p13411-d706643.html
   My bibliography  Save this article

Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty

Author

Listed:
  • Yao Lu

    (College of Marxism, Hubei University, Wuhan 430062, China)

  • Min Zhou

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430030, China)

  • Guoliang Ou

    (School of Construction and Environmental Engineering, Shenzhen Polytechnic, Shenzhen 518055, China)

  • Zuo Zhang

    (School of Public Administration, Central China Normal University, Wuhan 430079, China)

  • Li He

    (School of Urban Construction, Yangtze University, Jingzhou 434023, China)

  • Yuxiang Ma

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430030, China)

  • Chaonan Ma

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430030, China)

  • Jiating Tu

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430030, China)

  • Siqi Li

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430030, China)

Abstract

Land-use allocation models can effectively support sustainable land use. A large number of studies solve the problems of land-use planning by constructing models, such as mathematical models and spatial analysis models. However, these models fail to fully and comprehensively consider three uncertain factors of land-use systems: randomness, interval and fuzziness. 33Therefore, through the study of the watershed land-use system, this paper develops a land-use allocation model considering the regional land–society–economy–environment system under uncertain conditions. On the basis of this model, an interval fuzzy two-stage random land-use allocation model (IFTSP-LUAM) combining social, economic and ecological factors is proposed to provide sustainable development strategies at the basin level. In addition, the proposed IFTSP-LUAM takes into account the above three uncertainties and multistage, multiobjective, dynamic, systematic and complex characteristics of typical land-use planning systems. The results showed that the model considers more socioeconomic and ecological factors and can effectively reflect the quantitative relationship between the increase in economic benefits and the decrease in environmental costs of a land-use system. The model was applied to land-use planning of Nansihu River Basin in Shandong Province. The results provided a series of suitable land-use patterns and environmental emission scenarios under uncertain conditions, which can help the watershed environmental protection bureau and watershed land-use decision-makers to formulate appropriate land-use policies, so as to balance social and economic development and ecological protection. The simulation results can provide support for an in-depth analysis of land-use patterns and the trade-off between economic development and ecological environment protection.

Suggested Citation

  • Yao Lu & Min Zhou & Guoliang Ou & Zuo Zhang & Li He & Yuxiang Ma & Chaonan Ma & Jiating Tu & Siqi Li, 2021. "Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty," IJERPH, MDPI, vol. 18(24), pages 1-19, December.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:24:p:13411-:d:706643
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/24/13411/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/24/13411/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. d’Amato, Maurizio & Zrobek, Sabina & Renigier Bilozor, Malgorzata & Walacik, Marek & Mercadante, Giuseppe, 2019. "Valuing the effect of the change of zoning on underdeveloped land using fuzzy real option approach," Land Use Policy, Elsevier, vol. 86(C), pages 365-374.
    2. Sante, Ines & Crecente, Rafael, 2007. "LUSE, a decision support system for exploration of rural land use allocation: Application to the Terra Cha district of Galicia (N.W. Spain)," Agricultural Systems, Elsevier, vol. 94(2), pages 341-356, May.
    3. Chakir, Raja & Le Gallo, Julie, 2013. "Predicting land use allocation in France: A spatial panel data analysis," Ecological Economics, Elsevier, vol. 92(C), pages 114-125.
    4. Jeroen Aerts & Marjan Van Herwijnen & Ron Janssen & Theodor Stewart, 2005. "Evaluating Spatial Design Techniques for Solving Land-use Allocation Problems," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 48(1), pages 121-142.
    5. Dai, Z.Y. & Li, Y.P., 2013. "A multistage irrigation water allocation model for agricultural land-use planning under uncertainty," Agricultural Water Management, Elsevier, vol. 129(C), pages 69-79.
    6. Peltonen-Sainio, Pirjo & Jauhiainen, Lauri & Laurila, Heikki & Sorvali, Jaana & Honkavaara, Eija & Wittke, Samantha & Karjalainen, Mika & Puttonen, Eetu, 2019. "Land use optimization tool for sustainable intensification of high-latitude agricultural systems," Land Use Policy, Elsevier, vol. 88(C).
    7. Sharawi, Huda Abdelwahab, 2006. "Optimal land-use allocation in central Sudan," Forest Policy and Economics, Elsevier, vol. 8(1), pages 10-21, January.
    8. Shirmohammadi, Bagher & Malekian, Arash & Salajegheh, Ali & Taheri, Bahram & Azarnivand, Hossein & Malek, Ziga & Verburg, Peter H., 2020. "Scenario analysis for integrated water resources management under future land use change in the Urmia Lake region, Iran," Land Use Policy, Elsevier, vol. 90(C).
    9. Kertész, Ádám & Nagy, Loránd Attila & Balázs, Boglárka, 2019. "Effect of land use change on ecosystem services in Lake Balaton Catchment," Land Use Policy, Elsevier, vol. 80(C), pages 430-438.
    10. Liu, Xiaoping & Ou, Jinpei & Li, Xia & Ai, Bin, 2013. "Combining system dynamics and hybrid particle swarm optimization for land use allocation," Ecological Modelling, Elsevier, vol. 257(C), pages 11-24.
    11. Guldmann, Jean-Michel, 1979. "Urban land use allocation and environmental pollution control: An intertemporal optimization approach," Socio-Economic Planning Sciences, Elsevier, vol. 13(2), pages 71-86.
    12. John F. McDonald, 2001. "Cost‐Benefit Analysis of Local Land Use Allocation Decisions," Journal of Regional Science, Wiley Blackwell, vol. 41(2), pages 277-299, May.
    13. Daniel Caparros‐Midwood & Stuart Barr & Richard Dawson, 2017. "Spatial Optimization of Future Urban Development with Regards to Climate Risk and Sustainability Objectives," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2164-2181, November.
    14. Robert G. Cromley & Dean M. Hanink, 1999. "Coupling land use allocation models with raster GIS," Journal of Geographical Systems, Springer, vol. 1(2), pages 137-153, July.
    15. Yanis Elalamy & Luc Doyen & Lauriane Mouysset, 2019. "Contribution of the land use allocation model for agroecosystems: The case of Torrecchia Vecchia," Post-Print hal-03143304, HAL.
    16. Wang, Szu-Hua & Huang, Shu-Li & Budd, William W., 2012. "Integrated ecosystem model for simulating land use allocation," Ecological Modelling, Elsevier, vol. 227(C), pages 46-55.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bunga Ludmila Rendrarpoetri & Ernan Rustiadi & Akhmad Fauzi & Andrea Emma Pravitasari, 2024. "Sustainability Assessment of the Upstream Bengawan Solo Watershed in Wonogiri Regency, Central Java Province, Indonesia," Sustainability, MDPI, vol. 16(5), pages 1-29, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bingkui Qiu & Shasha Lu & Min Zhou & Lu Zhang & Yu Deng & Ci Song & Zuo Zhang, 2015. "A Hybrid Inexact Optimization Method for Land-Use Allocation in Association with Environmental/Ecological Requirements at a Watershed Level," Sustainability, MDPI, vol. 7(4), pages 1-25, April.
    2. Min Zhou & Shukui Tan & Lizao Tao & Xiangbo Zhu & Ghulam Akhmat, 2015. "An interval fuzzy land-use allocation model (IFLAM) for Beijing in association with environmental and ecological consideration under uncertainty," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(6), pages 2269-2290, November.
    3. Zuo Zhang & Min Zhou & Guoliang Ou & Shukui Tan & Yan Song & Lu Zhang & Xin Nie, 2019. "Land Suitability Evaluation and an Interval Stochastic Fuzzy Programming-Based Optimization Model for Land-Use Planning and Environmental Policy Analysis," IJERPH, MDPI, vol. 16(21), pages 1-23, October.
    4. Shukui Tan & Lu Zhang & Min Zhou & Yanan Li & Siliang Wang & Bing Kuang & Xiang Luo, 2017. "A hybrid mathematical model for urban land-use planning in association with environmental–ecological consideration under uncertainty," Environment and Planning B, , vol. 44(1), pages 54-79, January.
    5. Sajith, Gouri & Srinivas, Rallapalli & Golberg, Alexander & Magner, Joe, 2022. "Bio-inspired and artificial intelligence enabled hydro-economic model for diversified agricultural management," Agricultural Water Management, Elsevier, vol. 269(C).
    6. Chenhao Zhu & Jonah Susskind & Mario Giampieri & Hazel Backus O’Neil & Alan M. Berger, 2023. "Optimizing Sustainable Suburban Expansion with Autonomous Mobility through a Parametric Design Framework," Land, MDPI, vol. 12(9), pages 1-31, September.
    7. Xiaoyu Chen & Qingming Zhan & Yuli Fan, 2023. "Classification and Evaluation Methods for Optimization of Land Use Efficiency at Village Level," Land, MDPI, vol. 12(3), pages 1-16, March.
    8. Zhang, Jianjun & Fu, Meichen & Zhang, Zhongya & Tao, Jin & Fu, Wei, 2014. "A trade-off approach of optimal land allocation between socio-economic development and ecological stability," Ecological Modelling, Elsevier, vol. 272(C), pages 175-187.
    9. Jin, Wanfu & Zhou, Chunshan & Zhang, Guojun, 2020. "Characteristics of state-owned construction land supply in Chinese cities by development stage and industry," Land Use Policy, Elsevier, vol. 96(C).
    10. Xia Xu & Mengxi Guan & Honglei Jiang & Lingfei Wang, 2019. "Dynamic Simulation of Land Use Change of the Upper and Middle Streams of the Luan River, Northern China," Sustainability, MDPI, vol. 11(18), pages 1-15, September.
    11. Yaolin Liu & Jinjin Peng & Limin Jiao & Yanfang Liu, 2016. "PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-21, June.
    12. Nana, Tian & Lu, Fadian, 2013. "Adaptive management decision of agroforestry under timber price risk," Journal of Forest Economics, Elsevier, vol. 19(2), pages 162-173.
    13. Chih-Hao Wang & Na Chen, 2021. "A multi-objective optimization approach to balancing economic efficiency and equity in accessibility to multi-use paths," Transportation, Springer, vol. 48(4), pages 1967-1986, August.
    14. Guadalupe Azuara García & Efrén Palacios Rosas & Alfonso García-Ferrer & Pilar Montesinos Barrios, 2017. "Multi-Objective Spatial Optimization: Sustainable Land Use Allocation at Sub-Regional Scale," Sustainability, MDPI, vol. 9(6), pages 1-21, June.
    15. Parvez, Md Rezwanul & Ripplinger, David & Maduraperuma, Buddhika, 2015. "Modeling Land Use Pattern Change Analysis in the Northern Great Plains: A Novel Approach," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205868, Agricultural and Applied Economics Association.
    16. Gintautas Mozgeris & Daiva Juknelienė, 2021. "Modeling Future Land Use Development: A Lithuanian Case," Land, MDPI, vol. 10(4), pages 1-21, April.
    17. Pirjo Peltonen-Sainio & Lauri Jauhiainen, 2019. "Risk of Low Productivity is Dependent on Farm Characteristics: How to Turn Poor Performance into an Advantage," Sustainability, MDPI, vol. 11(19), pages 1-17, October.
    18. Kuschnig, Nikolas, 2021. "Bayesian Spatial Econometrics and the Need for Software," Department of Economics Working Paper Series 318, WU Vienna University of Economics and Business.
    19. Chi, Yuan & Liu, Dahai & Wang, Jing & Wang, Enkang, 2020. "Human negative, positive, and net influences on an estuarine area with intensive human activity based on land covers and ecological indices: An empirical study in Chongming Island, China," Land Use Policy, Elsevier, vol. 99(C).
    20. Chen, Shu & Shao, Dongguo & Tan, Xuezhi & Gu, Wenquan & Lei, Caixiu, 2017. "An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition," Agricultural Water Management, Elsevier, vol. 191(C), pages 98-112.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:24:p:13411-:d:706643. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.