[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i14p11465-d1201388.html
   My bibliography  Save this article

Estimation of the Extent of the Vulnerability of Agriculture to Climate Change Using Analytical and Deep-Learning Methods: A Case Study in Jammu, Kashmir, and Ladakh

Author

Listed:
  • Irtiqa Malik

    (School of Agricultural Economics and Horti-Business Management, SKUAST-K, Shalimar 190025, India)

  • Muneeb Ahmed

    (Bharti School of Telecom Technology, Department of Computer Science and Engineering, Indian Institute of Technology Delhi, New Delhi 110016, India)

  • Yonis Gulzar

    (Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

  • Sajad Hassan Baba

    (School of Agricultural Economics and Horti-Business Management, SKUAST-K, Shalimar 190025, India)

  • Mohammad Shuaib Mir

    (Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

  • Arjumand Bano Soomro

    (Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa 31982, Saudi Arabia
    Department of Software Engineering, Faculty of Engineering and Technology, University of Sindh, Jamshoro 76080, Pakistan)

  • Abid Sultan

    (School of Agricultural Economics and Horti-Business Management, SKUAST-K, Shalimar 190025, India)

  • Osman Elwasila

    (Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

Abstract
Climate stress poses a threat to the agricultural sector, which is vital for both the economy and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability is crucial. This study proposes a framework to estimate the impact climate stress on agriculture in terms of three objectives: assessing the regional vulnerability (exposure, sensitivity, and adaptive capacity), analysing the climate variability, and measuring agricultural performance under climatic stress. The vulnerability of twenty-two sub-regions in Jammu, Kashmir, and Ladakh is assessed using indicators to determine the collective susceptibility of the agricultural framework to climate change. An index-based approach with min–max normalization is employed, ranking the districts based on their relative performances across vulnerability indicators. This work assesses the impact of socio-economic and climatic indicators on the performance of agricultural growth using the benchmark Ricardian approach. The parameters of the agricultural growth function are estimated using a linear combination of socio-economic and exposure variables. Lastly, the forecasted trends of climatic variables are examined using a long short-term memory (LSTM)-based recurrent neural network, providing an annual estimate of climate variability. The results indicate a negative impact of annual minimum temperature and decreasing land holdings on agricultural GDP, while cropping intensity, rural literacy, and credit facilities have positive effects. Budgam, Ganderbal, and Bandipora districts exhibit higher vulnerability due to factors such as low literacy rates, high population density, and extensive rice cultivation. Conversely, Kargil, Rajouri, and Poonch districts show lower vulnerability due to the low population density and lower level of institutional development. We observe an increasing trend of minimum temperature across the region. The proposed LSTM synthesizes a predictive estimate across five essential climate variables with an average overall root mean squared error (RMSE) of 0.91, outperforming the benchmark ARIMA and exponential-smoothing models by 32–48%. These findings can guide policymakers and stakeholders in developing strategies to mitigate climate stress on agriculture and enhance resilience.

Suggested Citation

  • Irtiqa Malik & Muneeb Ahmed & Yonis Gulzar & Sajad Hassan Baba & Mohammad Shuaib Mir & Arjumand Bano Soomro & Abid Sultan & Osman Elwasila, 2023. "Estimation of the Extent of the Vulnerability of Agriculture to Climate Change Using Analytical and Deep-Learning Methods: A Case Study in Jammu, Kashmir, and Ladakh," Sustainability, MDPI, vol. 15(14), pages 1-25, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11465-:d:1201388
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/14/11465/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/14/11465/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Idris A. Adediran & Kazeem O. Isah & Ahamuefula E. Ogbonna & Sheriff K. Badmus, 2023. "A Global Analysis of the Macroeconomic Effects of Climate Change," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 4(1), pages 1-6.
    2. Sonam Aggarwal & Sheifali Gupta & Deepali Gupta & Yonis Gulzar & Sapna Juneja & Ali A. Alwan & Ali Nauman, 2023. "An Artificial Intelligence-Based Stacked Ensemble Approach for Prediction of Protein Subcellular Localization in Confocal Microscopy Images," Sustainability, MDPI, vol. 15(2), pages 1-20, January.
    3. Karen O'Brien & Siri Eriksen & Lynn P. Nygaard & Ane Schjolden, 2007. "Why different interpretations of vulnerability matter in climate change discourses," Climate Policy, Taylor & Francis Journals, vol. 7(1), pages 73-88, January.
    4. John Quiggin, 2010. "Agriculture and global climate stabilization: a public good analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 41(s1), pages 121-132, November.
    5. Gurdeep Singh Malhi & Manpreet Kaur & Prashant Kaushik, 2021. "Impact of Climate Change on Agriculture and Its Mitigation Strategies: A Review," Sustainability, MDPI, vol. 13(3), pages 1-21, January.
    6. Mendelsohn, Robert & Nordhaus, William D & Shaw, Daigee, 1994. "The Impact of Global Warming on Agriculture: A Ricardian Analysis," American Economic Review, American Economic Association, vol. 84(4), pages 753-771, September.
    7. Md. Abdur Rashid Sarker & Khorshed Alam & Jeff Gow, 2014. "Assessing the effects of climate change on rice yields: An econometric investigation using Bangladeshi panel data," Economic Analysis and Policy, Elsevier, vol. 44(4), pages 405-416.
    8. N. W. Arnell & J. A. Lowe & A. J. Challinor & T. J. Osborn, 2019. "Global and regional impacts of climate change at different levels of global temperature increase," Climatic Change, Springer, vol. 155(3), pages 377-391, August.
    9. Bashar Igried & Shadi AlZu’bi & Darah Aqel & Ala Mughaid & Iyad Ghaith & Laith Abualigah, 2023. "An Intelligent and Precise Agriculture Model in Sustainable Cities Based on Visualized Symptoms," Agriculture, MDPI, vol. 13(4), pages 1-20, April.
    10. Khadijeh Alibabaei & Pedro D. Gaspar & Tânia M. Lima, 2021. "Crop Yield Estimation Using Deep Learning Based on Climate Big Data and Irrigation Scheduling," Energies, MDPI, vol. 14(11), pages 1-21, May.
    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. Julian Andres Castillo Grisales & Yony Fernando Ceballos & Lina María Bastidas-Orrego & Natalia Isabel Jaramillo Gómez & Elizabeth Chaparro Cañola, 2024. "Development of an Agent-Based Model to Evaluate Rural Public Policies in Medellín, Colombia," Sustainability, MDPI, vol. 16(18), pages 1-19, September.

    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. Ding, Yugang & Xu, Jiangmin, 2023. "Global vulnerability of agricultural commodities to climate risk: Evidence from satellite data," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 669-687.
    2. Jeonghyun Kim & Hojeong Park & Jong Ahn Chun & Sanai Li, 2018. "Adaptation Strategies under Climate Change for Sustainable Agricultural Productivity in Cambodia," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
    3. Hossain, Mohammad Shakhawat & Arshad, Muhammad & Qian, Lu & Zhao, Minjuan & Mehmood, Yasir & Kächele, Harald, 2019. "Economic impact of climate change on crop farming in Bangladesh: An application of Ricardian method," Ecological Economics, Elsevier, vol. 164(C), pages 1-1.
    4. Boon Teck Tan & Pei Shan Fam & R. B. Radin Firdaus & Mou Leong Tan & Mahinda Senevi Gunaratne, 2021. "Impact of Climate Change on Rice Yield in Malaysia: A Panel Data Analysis," Agriculture, MDPI, vol. 11(6), pages 1-17, June.
    5. Swatantra Kumar Dubey & JungJin Kim & Syewoon Hwang & Younggu Her & Hanseok Jeong, 2023. "Variability of Extreme Events in Coastal and Inland Areas of South Korea during 1961–2020," Sustainability, MDPI, vol. 15(16), pages 1-17, August.
    6. M. MEHEDI HASAN & Md. ABDUR RASHID SARKER & JEFF GOW, 2016. "Assessment Of Climate Change Impacts On Aman And Boro Rice Yields In Bangladesh," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 7(03), pages 1-21, August.
    7. Raju Guntukula & Phanindra Goyari, 2020. "Climate Change Effects on the Crop Yield and Its Variability in Telangana, India," Studies in Microeconomics, , vol. 8(1), pages 119-148, June.
    8. Senni, Chiara Colesanti & von Jagow, Adrian, 2023. "Water risks for hydroelectricity generation," LSE Research Online Documents on Economics 119256, London School of Economics and Political Science, LSE Library.
    9. Mahboobe Ghobadi & Mahdi Gheysari & Mohammad Shayannejad & Hamze Dokoohaki, 2023. "Analyzing the Effects of Planting Date on the Uncertainty of CERES-Maize and Its Potential to Reduce Yield Gap in Arid and Mediterranean Climates," Agriculture, MDPI, vol. 13(8), pages 1-17, July.
    10. Alejandro Lopez-Feldman, 2013. "Climate change, agriculture, and poverty: A household level analysis for rural Mexico," Economics Bulletin, AccessEcon, vol. 33(2), pages 1126-1139.
    11. Tenzing, Janna & Conway, Declan, 2023. "Does the geographical footprint of Ethiopia’s flagship social protection programme align with climatic and conflict risks?," LSE Research Online Documents on Economics 120563, London School of Economics and Political Science, LSE Library.
    12. Busby, Joshua & Smith, Todd G. & Krishnan, Nisha & Wight, Charles & Vallejo-Gutierrez, Santiago, 2018. "In harm's way: Climate security vulnerability in Asia," World Development, Elsevier, vol. 112(C), pages 88-118.
    13. Yifeng Xie & Haitao Wu & Ruikuan Yao, 2023. "The Impact of Climate Change on the Urban–Rural Income Gap in China," Agriculture, MDPI, vol. 13(9), pages 1-17, August.
    14. Dadakas, Dimitrios & Jakus, Paul M., 1999. "El Nino/Southern Oscillation Effects On Farmland Values In The United States," 1999 Annual meeting, August 8-11, Nashville, TN 21572, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    15. Reinhard Mechler & Stefan Hochrainer & Asbjørn Aaheim & Håkon Salen & Anita Wreford, 2010. "Modelling economic impacts and adaptation to extreme events: Insights from European case studies," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 15(7), pages 737-762, October.
    16. Islam, Asif & Hyland, Marie, 2019. "The drivers and impacts of water infrastructure reliability – a global analysis of manufacturing firms," Ecological Economics, Elsevier, vol. 163(C), pages 143-157.
    17. Rouhi Rad, Mani & Haacker, Erin M.K. & Sharda, Vaishali & Nozari, Soheil & Xiang, Zaichen & Araya, A. & Uddameri, Venkatesh & Suter, Jordan F. & Gowda, Prasanna, 2020. "MOD$$AT: A hydro-economic modeling framework for aquifer management in irrigated agricultural regions," Agricultural Water Management, Elsevier, vol. 238(C).
    18. Ross McKitrick, 2001. "Mitigation versus compensation in global warming policy," Economics Bulletin, AccessEcon, vol. 17(2), pages 1-6.
    19. William D. Nordhaus & Robert Mendelsohn, 1999. "The Impact of Global Warming on Agriculture: A Ricardian Analysis: Reply," American Economic Review, American Economic Association, vol. 89(4), pages 1046-1048, September.
    20. Sassi, Maria & Cardaci, Alberto, 2013. "Impact of rainfall pattern on cereal market and food security in Sudan: Stochastic approach and CGE model," Food Policy, Elsevier, vol. 43(C), pages 321-331.

    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:15:y:2023:i:14:p:11465-:d:1201388. 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.