IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i10p5652-d557050.html
   My bibliography  Save this article

Analysis of the Effects of Local Regulations on the Preservation of Water Resources Using the CA-Markov Model

Author

Listed:
  • Chul-Min Song

    (Department of Policy for Watershed Management, The Policy Council for Paldang Watershed, Yangpyeong 12585, Korea)

Abstract

The analysis of the local regulation effects is required for sustainable and effective land utilization because land use/land cover (LULC) changes are not only determined by human activity but are also affected by national policy and regulation; however, previous studies for land use/land cover (LULC) have mainly been conducted on the LULC changes using past experience. This study, therefore, analyzed the effects of local regulations aimed at preserving the water quality in South Korea. To this end, changes in LULC were simulated using the CA-Markov model under conditions in which two local regulations, the special countermeasure area (SCA) and total maximum daily load (TMDL), were not applied and examined the differences between the simulated LULC and the actual LULC as of 2018. In addition, the differences in the generation of pollutant loads were driven for Biochemical Oxygen Demand (BOD), Total Nitrogen (TN), and Total Phosphorus (TP) using pollutant unit-load. As a result, without SCA, the agricultural area increased by 379.0 km 2 , the urban area decreased by 101.8 km 2 , and the meadow area decreased by 176.0 km 2 . In addition, without TMDL, the urban area increased by 169.2 km 2 and the meadow area decreased to 158.8 km 2 .Differences in BOD, TN, and TP pollution loads without SCA applications were shown to decrease to 22,710.5 kg·km −2 day −1 , 1133.9 kg·km −2 day −1 , and 429.8 kg·km −2 day −1 , respectively, while BOD, TN, and TP pollution loads without TMDL applications decreased to 14,435.7 kg·km −2 day −1 , 2543.6 kg·km −2 day −1 , and 368.2 kg·km −2 day −1 , respectively. As such, this study presents a methodology for analyzing the effects of local regulations using the CA-Markov model, which can intuitively and efficiently examine the effects of regulations by predicting LULC changes.

Suggested Citation

  • Chul-Min Song, 2021. "Analysis of the Effects of Local Regulations on the Preservation of Water Resources Using the CA-Markov Model," Sustainability, MDPI, vol. 13(10), pages 1-22, May.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5652-:d:557050
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/10/5652/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/10/5652/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rahel Hamad & Heiko Balzter & Kamal Kolo, 2018. "Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios," Sustainability, MDPI, vol. 10(10), pages 1-23, September.
    2. Man Li, 2019. "The effect of land use regulations on farmland protection and non‐agricultural land conversions in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(3), pages 643-667, July.
    3. Cheechouyang Faichia & Zhijun Tong & Jiquan Zhang & Xingpeng Liu & Emmanuel Kazuva & Kashif Ullah & Bazel Al-Shaibah, 2020. "Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
    4. Yaobin Liu & Lu Dai & Huanhuan Xiong, 2015. "Simulation of urban expansion patterns by integrating auto-logistic regression, Markov chain and cellular automata models," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 58(6), pages 1113-1136, June.
    5. Sarah Hasan & Wenzhong Shi & Xiaolin Zhu & Sawaid Abbas & Hafiz Usman Ahmed Khan, 2020. "Future Simulation of Land Use Changes in Rapidly Urbanizing South China Based on Land Change Modeler and Remote Sensing Data," Sustainability, MDPI, vol. 12(11), pages 1-24, May.
    Full references (including those not matched with items on IDEAS)

    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. Sri Murniani Angelina Letsoin & David Herak & Fajar Rahmawan & Ratna Chrismiari Purwestri, 2020. "Land Cover Changes from 1990 to 2019 in Papua, Indonesia: Results of the Remote Sensing Imagery," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    2. Milad Asadi & Amir Oshnooei-Nooshabadi & Samira-Sadat Saleh & Fattaneh Habibnezhad & Sonia Sarafraz-Asbagh & John Lodewijk Van Genderen, 2022. "Urban Sprawl Simulation Mapping of Urmia (Iran) by Comparison of Cellular Automata–Markov Chain and Artificial Neural Network (ANN) Modeling Approach," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    3. Raoof Mostafazadeh & Hossein Talebi Khiavi, 2024. "Landscape change assessment and its prediction in a mountainous gradient with diverse land-uses," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(2), pages 3911-3941, February.
    4. Changqing Sun & Yulong Bao & Battsengel Vandansambuu & Yuhai Bao, 2022. "Simulation and Prediction of Land Use/Cover Changes Based on CLUE-S and CA-Markov Models: A Case Study of a Typical Pastoral Area in Mongolia," Sustainability, MDPI, vol. 14(23), pages 1-21, November.
    5. Cláudia M. Viana & Jorge Rocha, 2020. "Evaluating Dominant Land Use/Land Cover Changes and Predicting Future Scenario in a Rural Region Using a Memoryless Stochastic Method," Sustainability, MDPI, vol. 12(10), pages 1-28, May.
    6. Yongjiu Feng & Jiafeng Wang & Xiaohua Tong & Yang Liu & Zhenkun Lei & Chen Gao & Shurui Chen, 2018. "The Effect of Observation Scale on Urban Growth Simulation Using Particle Swarm Optimization-Based CA Models," Sustainability, MDPI, vol. 10(11), pages 1-20, November.
    7. Luoman Pu & Jiuchun Yang & Lingxue Yu & Changsheng Xiong & Fengqin Yan & Yubo Zhang & Shuwen Zhang, 2021. "Simulating Land-Use Changes and Predicting Maize Potential Yields in Northeast China for 2050," IJERPH, MDPI, vol. 18(3), pages 1-21, January.
    8. Hui Wei & Changhe Lu & Yaqun Liu, 2021. "Farmland Changes and Their Ecological Impact in the Huangshui River Basin," Land, MDPI, vol. 10(10), pages 1-15, October.
    9. Sandip Giri & Sourav Samanta & Partho Protim Mondal & Oindrila Basu & Samiran Khorat & Abhra Chanda & Sugata Hazra, 2022. "A geospatial assessment of growth pattern of aquaculture in the Indian Sundarbans Biosphere Reserve," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 4203-4225, March.
    10. Nij Tontisirin & Sutee Anantsuksomsri, 2021. "Economic Development Policies and Land Use Changes in Thailand: From the Eastern Seaboard to the Eastern Economic Corridor," Sustainability, MDPI, vol. 13(11), pages 1-20, May.
    11. Yangcheng Hu & Yi Liu & Changyan Li, 2022. "Multi-Scenario Simulation of Land Use Change and Ecosystem Service Value in the Middle Reaches of Yangtze River Urban Agglomeration," Sustainability, MDPI, vol. 14(23), pages 1-19, November.
    12. Carlos Manjarrez-Domínguez & Mario Iván Uc-Campos & Mario Edgar Esparza-Vela & María del Rosario Baray-Guerrero & Omar Giner-Chávez & Eduardo Santellano-Estrada, 2023. "Geospatial-Temporal Dynamics of Land Use in the Juárez Valley: Urbanization and Displacement of Agriculture," Sustainability, MDPI, vol. 15(11), pages 1-20, May.
    13. Liu, Zhengjia, 2025. "Rural land sustainability development planning and use by considering land multifunction values: A case study of analysis and simulation," Land Use Policy, Elsevier, vol. 150(C).
    14. Jie Liu & Lang Zhang & Qingping Zhang, 2019. "The Development Simulation of Urban Green Space System Layout Based on the Land Use Scenario: A Case Study of Xuchang City, China," Sustainability, MDPI, vol. 12(1), pages 1-19, December.
    15. Shravankumar Shivappa Masalvad & Chidanand Patil & Akkaram Pravalika & Basavaraj Katageri & Purandara Bekal & Prashant Patil & Nagraj Hegde & Uttam Kumar Sahoo & Praveen Kumar Sakare, 2024. "Application of geospatial technology for the land use/land cover change assessment and future change predictions using CA Markov chain model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(10), pages 24817-24842, October.
    16. Jinling Zhang & Ying Hou & Yifan Dong & Cun Wang & Weiping Chen, 2022. "Land Use Change Simulation in Rapid Urbanizing Regions: A Case Study of Wuhan Urban Areas," IJERPH, MDPI, vol. 19(14), pages 1-19, July.
    17. Motuma Shiferaw Regasa & Michael Nones, 2022. "Past and Future Land Use/Land Cover Changes in the Ethiopian Fincha Sub-Basin," Land, MDPI, vol. 11(8), pages 1-20, August.
    18. Jing Liu & Chunchun Hu & Xionghua Kang & Fei Chen, 2023. "A Loosely Coupled Model for Simulating and Predicting Land Use Changes," Land, MDPI, vol. 12(1), pages 1-19, January.
    19. Cheechouyang Faichia & Zhijun Tong & Jiquan Zhang & Xingpeng Liu & Emmanuel Kazuva & Kashif Ullah & Bazel Al-Shaibah, 2020. "Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
    20. Abdurrahim Aydın & Remzi Eker, 2022. "Future land use/land cover scenarios considering natural hazards using Dyna-CLUE in Uzungöl Nature Conservation Area (Trabzon-NE Türkiye)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 2683-2707, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jsusta:v:13:y:2021:i:10:p:5652-:d:557050. 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.